('featured_article',0,74,675,'en',0,'<p>Artificial Intelligence for All, Responsibly</p><p>As we look towards the turn of another year, it is a time of introspection for many organizations. Annual forecasting, budgeting, and planning efforts are likely in progress by now, often bringing increased stress and anxiety to the C-Suite and the managers that report to them. Everyone is asked to predict the future based on entirely insufficient information. No one knows what will happen, so there are usually no alternatives to good old-fashioned guessing. Sure, you can build a spreadsheet, do elaborate calculations, and ultimately convince yourself that your forecasts are spot-on. Still, overwhelming research shows human judgement is prone to error (bias and noise). So, how do you make the best guesses you can? What tools and technologies can help you guess better?</p><p>Enter Artificial Intelligence (AI). The availability of virtually unlimited and relatively inexpensive compute and storage capabilities in the cloud today, along with advances in both the capabilities and usability of AI software, offer unprecedented opportunities to ‘crunch the numbers in new and different ways. We are now well past the point where computers are more effective than people at many data-based tasks, including searching, extrapolating, interpolating, predicting, and even winning strategy and video games. In other words, computers have gotten much better at guessing and making judgements than we are!</p><p>In the not-too-distant past, designing, building, testing, and delivering working solutions based on artificial intelligence and machine learning (AI/ML) was complicated and expensive. Fortunately, state-of-the-art. AI/ML technology has been evolving rapidly over the last few years, and several major vendors now offer powerful tools and capabilities at price points that are reasonable for nearly all organizations. In fact, according to Deloitte’s State of AI in the Enterprise survey for the 2022 edition, 94% of the 2600+ business leaders surveyed agree that AI is critical to success over the next five years. A recent Accenture survey of over 1,600 C-suite executives and data-science leaders from the world’s largest organizations found that nearly 75% of companies have integrated AI into their business strategies and reworked their cloud plans to achieve AI success. While adoption does remain somewhat higher in the enterprise space, a recent report from McKinsey showed that 56% of all respondents report AI adoption in at least one function.</p><p>Microsoft is one of the leaders in data science and management and has invested heavily for years in expanding AI/ML capabilities across many of its products and platforms. The Microsoft Azure cloud offers various services and tools that make it relatively easy to create robust AI/ML solutions for many scenarios. Microsoft has taken the integration of these technologies with core products to a new level with the recent introduction of Syntex, which brings ‘Content AI’ into SharePoint. It enables productivity-boosting functionality, including automatic document recognition, classification, summarization, translation, automated content generation, automated document assembly, AI-powered search, and active dynamic security/compliance/resilience.</p><p>In addition to AI-based content processing, there are a lot of other potentially compelling scenarios for many types of organizations, regardless of size, industry, business type, etc. Some of the most common examples of successful AI/ML outcomes include the following:</p><ul><li><strong>General decision support</strong> – Predict likely effects of various options</li><li><strong>Interpreting unstructured content</strong> – Search, identification, organization, reuse</li><li><strong>Automated document classification</strong> – Assign content types, security levels, etc.</li><li><strong>Auditing, compliance, eDiscovery</strong> – Understand what you have, where it is, how it is used</li><li><strong>Resume analysis</strong> – Interpret and rate candidates based on machine learning</li><li><strong>Anomaly detection</strong> – Identify outliers, unexpected results, and process bottlenecks</li><li><strong>Customer churn reduction</strong> – Identify at-risk customers in time to take corrective action</li><li><strong>Support process optimization</strong> – Analyze support tickets, response/resolution times, issue types</li><li><strong>Language processing</strong> – Interpret and translate between languages, natural language queries</li><li><strong>Image recognition and classification</strong> – Identify and tag pictures and graphics</li><li><strong>Audio and video transcription</strong> – Turn sounds and images into text</li><li><strong>Content generation</strong> – Create content and media based on similar existing items, text-to-speech</li></ul><p>However, all the “magic” that AI might seem to promise has a critical caveat. Along with the exciting possibilities that AI/ML offers, it is essential not to lose sight of the potential risks that can arise if care is not taken in implementing solutions. Artificial Intelligence can deliver substantial benefits to organizations that successfully leverage its power. But, if executed without attention to ethical, legal, and other people-centric and societal considerations, AI could also cause significant or even calamitous damage to a company’s reputation and prospects.</p><p>To ensure maximum value while minimizing the corresponding risks, it is helpful to have a ‘frame of reference to assess AI technologies. In that spirit, Deloitte has developed a valuable paradigm for evaluating AI-based solutions. The six dimensions in the Trustworthy AI™ framework are:</p><ul><li><strong>Fair and impartial</strong> – Help participants understand how their data can be used and how AI systems make decisions. Algorithms, attributes, and correlations are open to inspection.</li><li><strong>Transparent and explainable</strong> – Assess whether AI systems include internal and external checks to help enable equitable application across all participants.</li><li><strong>Responsible and accountable</strong> – Put an organizational structure and policies in place that can help determine who is responsible for the output of AI system decisions.</li><li><strong>Robust and reliable</strong> – Confirm that AI systems can learn from humans and other systems and produce consistent and reliable results.</li><li><strong>Respectful of privacy</strong> – Respect data privacy and avoid using AI to leverage customer data beyond its intended and stated use. Allow customers to opt in and out of sharing their data.</li><li><strong>Safe and secure</strong> – Protect AI systems from potential risks (including cyber threats) that may cause physical and digital harm.</li></ul><p>Whether your business is a Fortune 500 firm or a small organization with limited resources, there are almost certainly one or more areas where Artificial Intelligence / Machine Learning solutions could significantly impact the bottom line. Of course, given some recent survey results, you can be sure that other organizations in your space are also exploring the big, beautiful, and slightly scary world of AI/ML. Don’t be too late for the party but be careful on your way there!</p><p><strong>DISCLAIMER</strong></p><p>Copyright ©2022 by DivIHN Integration Inc.| <a href=\"mailto:kannan@divihn.com\">yoursuccess@divihn.com.</a></p><p><em>The creator of the document reserves all rights. Publication Date: November 2022. DivIHN Integration Inc. reserves the right to change the contents of this article, the features or the scope without the obligation to notify anyone of such changes. The content has been adapted using secondary research from various data points via “Google Search”. Infographics and Images used in the document are the property of the respective owners and have been used for indicative purposes only. The author reserves the right to authorize and use the Intellectual Property contained in the document.</em></p>','','full_html'),('blog',0,76,200,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>In 1996 and 1997, reigning world chess champion Garry Kasparov played two six-game matches against an IBM computer called Deep Blue. Kasparov won the first match. Deep Blue was victorious in the second match, marking the first time that a computer had defeated a reigning world champion. Today, any of us could buy an inexpensive chess program for our laptop computer which would consistently outplay Deep Blue. In 1997 however, Deep Blue’s victory was a milestone in the development of artificial intelligence (AI). There was much speculation at the time about the future of AI and about the similarities of computing machines and the human mind. Yale University professor David Gelernter urged restraint.</p><p>“The idea that Deep Blue has a mind is absurd. How can an object that wants nothing, fears nothing, enjoys nothing, needs nothing, and cares about nothing have a mind? It can win at chess, but not because it wants to. It isn’t happy when it wins or sad when it loses. What are its [post]-match plans if it beats Kasparov? Is it hoping to take Deep Pink out for a night on the town?” (Gelernter, 1997)</p><p>Ask ten people to define “artificial intelligence” and you will get ten different answers. This is, in some ways, beneficial ambiguity. Firm definitions can be needlessly constraining to those whose role it is to innovate. According to Stone et al at Stanford University, “the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace.” (Stanford, 2016). Nevertheless, to talk about a thing intelligently, it is worth a paragraph or two to define it as it is used in the present discussion. The word “artificial” is relatively easy to define. We use it to refer to things that do not occur naturally, things that are created by humans. The word “intelligence” is a bit more difficult. Philosophers, psychologists, anthropologists, and even theologians offer a variety of definitions. For the purposes of this article series, we will start with a definition which focuses on problem-solving. Psychologist Howard Gardner wrote, “Intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings” (Gardner, 1983).</p><p>Thus, artificial intelligence or AI, as we shall use it here, is a machine capability, which does not occur naturally, to solve problems or create something of value. We call this the realm of narrow AI, where an intelligent apparatus is created to solve a particular kind of problem or create a particular type of valuable thing. General AI, which theoretically includes non-trivial foresight, independent problem identification, and problem prioritization based on something like a human value system, or human-like hopes and dreams does not yet exist. In Gelernter’s view, “the gap between the human and the [electronic] surrogate is permanent… Machines will continue to make life easier, healthier, richer, and more puzzling. And humans will continue to care, ultimately, about the same things they always have: about themselves, about one another, and many of them, about God.” (Gelernter, 1976)</p><p>In the next installment, we will consider, “What does AI offer humankind?”</p><p>Notes and references:</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstream Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Gelernter, D., 1997, How Hard Is Chess? TIME, (May 19, 1997)</p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,76,243,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>In 1996 and 1997, reigning world chess champion Garry Kasparov played two six-game matches against an IBM computer called Deep Blue. Kasparov won the first match. Deep Blue was victorious in the second match, marking the first time that a computer had defeated a reigning world champion. Today, any of us could buy an inexpensive chess program for our laptop computer which would consistently outplay Deep Blue. In 1997 however, Deep Blue’s victory was a milestone in the development of artificial intelligence (AI). There was much speculation at the time about the future of AI and about the similarities of computing machines and the human mind. Yale University professor David Gelernter urged restraint.</p><p>“The idea that Deep Blue has a mind is absurd. How can an object that wants nothing, fears nothing, enjoys nothing, needs nothing, and cares about nothing have a mind? It can win at chess, but not because it wants to. It isn’t happy when it wins or sad when it loses. What are its [post]-match plans if it beats Kasparov? Is it hoping to take Deep Pink out for a night on the town?” (Gelernter, 1997)</p><p>Ask ten people to define “artificial intelligence” and you will get ten different answers. This is, in some ways, beneficial ambiguity. Firm definitions can be needlessly constraining to those whose role it is to innovate. According to Stone et al at Stanford University, “the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace.” (Stanford, 2016). Nevertheless, to talk about a thing intelligently, it is worth a paragraph or two to define it as it is used in the present discussion. The word “artificial” is relatively easy to define. We use it to refer to things that do not occur naturally, things that are created by humans. The word “intelligence” is a bit more difficult. Philosophers, psychologists, anthropologists, and even theologians offer a variety of definitions. For the purposes of this article series, we will start with a definition which focuses on problem-solving. Psychologist Howard Gardner wrote, “Intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings” (Gardner, 1983).</p><p>Thus, artificial intelligence or AI, as we shall use it here, is a machine capability, which does not occur naturally, to solve problems or create something of value. We call this the realm of narrow AI, where an intelligent apparatus is created to solve a particular kind of problem or create a particular type of valuable thing. General AI, which theoretically includes non-trivial foresight, independent problem identification, and problem prioritization based on something like a human value system, or human-like hopes and dreams does not yet exist. In Gelernter’s view, “the gap between the human and the [electronic] surrogate is permanent… Machines will continue to make life easier, healthier, richer, and more puzzling. And humans will continue to care, ultimately, about the same things they always have: about themselves, about one another, and many of them, about God.” (Gelernter, 1976)</p><p>In the next installment, we will consider, “What does AI offer humankind?”</p><p>Notes and references:</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstream Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Gelernter, D., 1997, How Hard Is Chess? TIME, (May 19, 1997)</p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,76,476,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>In 1996 and 1997, reigning world chess champion Garry Kasparov played two six-game matches against an IBM computer called Deep Blue. Kasparov won the first match. Deep Blue was victorious in the second match, marking the first time that a computer had defeated a reigning world champion. Today, any of us could buy an inexpensive chess program for our laptop computer which would consistently outplay Deep Blue. In 1997 however, Deep Blue’s victory was a milestone in the development of artificial intelligence (AI). There was much speculation at the time about the future of AI and about the similarities of computing machines and the human mind. Yale University professor David Gelernter urged restraint.</p><p>“The idea that Deep Blue has a mind is absurd. How can an object that wants nothing, fears nothing, enjoys nothing, needs nothing, and cares about nothing have a mind? It can win at chess, but not because it wants to. It isn’t happy when it wins or sad when it loses. What are its [post]-match plans if it beats Kasparov? Is it hoping to take Deep Pink out for a night on the town?” (Gelernter, 1997)</p><p>Ask ten people to define “artificial intelligence” and you will get ten different answers. This is, in some ways, beneficial ambiguity. Firm definitions can be needlessly constraining to those whose role it is to innovate. According to Stone et al at Stanford University, “the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace.” (Stanford, 2016). Nevertheless, to talk about a thing intelligently, it is worth a paragraph or two to define it as it is used in the present discussion. The word “artificial” is relatively easy to define. We use it to refer to things that do not occur naturally, things that are created by humans. The word “intelligence” is a bit more difficult. Philosophers, psychologists, anthropologists, and even theologians offer a variety of definitions. For the purposes of this article series, we will start with a definition which focuses on problem-solving. Psychologist Howard Gardner wrote, “Intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings” (Gardner, 1983).</p><p>Thus, artificial intelligence or AI, as we shall use it here, is a machine capability, which does not occur naturally, to solve problems or create something of value. We call this the realm of narrow AI, where an intelligent apparatus is created to solve a particular kind of problem or create a particular type of valuable thing. General AI, which theoretically includes non-trivial foresight, independent problem identification, and problem prioritization based on something like a human value system, or human-like hopes and dreams does not yet exist. In Gelernter’s view, “the gap between the human and the [electronic] surrogate is permanent… Machines will continue to make life easier, healthier, richer, and more puzzling. And humans will continue to care, ultimately, about the same things they always have: about themselves, about one another, and many of them, about God.” (Gelernter, 1976)</p><p>In the next installment, we will consider, “What does AI offer humankind?”</p><p>Notes and references:</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstream Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Gelernter, D., 1997, How Hard Is Chess? TIME, (May 19, 1997)</p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,76,556,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>In 1996 and 1997, reigning world chess champion Garry Kasparov played two six-game matches against an IBM computer called Deep Blue. Kasparov won the first match. Deep Blue was victorious in the second match, marking the first time that a computer had defeated a reigning world champion. Today, any of us could buy an inexpensive chess program for our laptop computer which would consistently outplay Deep Blue. In 1997 however, Deep Blue’s victory was a milestone in the development of artificial intelligence (AI). There was much speculation at the time about the future of AI and about the similarities of computing machines and the human mind. Yale University professor David Gelernter urged restraint.</p><p>“The idea that Deep Blue has a mind is absurd. How can an object that wants nothing, fears nothing, enjoys nothing, needs nothing, and cares about nothing have a mind? It can win at chess, but not because it wants to. It isn’t happy when it wins or sad when it loses. What are its [post]-match plans if it beats Kasparov? Is it hoping to take Deep Pink out for a night on the town?” (Gelernter, 1997)</p><p>Ask ten people to define “artificial intelligence” and you will get ten different answers. This is, in some ways, beneficial ambiguity. Firm definitions can be needlessly constraining to those whose role it is to innovate. According to Stone et al at Stanford University, “the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace.” (Stanford, 2016). Nevertheless, to talk about a thing intelligently, it is worth a paragraph or two to define it as it is used in the present discussion. The word “artificial” is relatively easy to define. We use it to refer to things that do not occur naturally, things that are created by humans. The word “intelligence” is a bit more difficult. Philosophers, psychologists, anthropologists, and even theologians offer a variety of definitions. For the purposes of this article series, we will start with a definition which focuses on problem-solving. Psychologist Howard Gardner wrote, “Intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings” (Gardner, 1983).</p><p>Thus, artificial intelligence or AI, as we shall use it here, is a machine capability, which does not occur naturally, to solve problems or create something of value. We call this the realm of narrow AI, where an intelligent apparatus is created to solve a particular kind of problem or create a particular type of valuable thing. General AI, which theoretically includes non-trivial foresight, independent problem identification, and problem prioritization based on something like a human value system, or human-like hopes and dreams does not yet exist. In Gelernter’s view, “the gap between the human and the [electronic] surrogate is permanent… Machines will continue to make life easier, healthier, richer, and more puzzling. And humans will continue to care, ultimately, about the same things they always have: about themselves, about one another, and many of them, about God.” (Gelernter, 1976)</p><p>In the next installment, we will consider, “What does AI offer humankind?”</p><p>Notes and references:</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstream Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Gelernter, D., 1997, How Hard Is Chess? TIME, (May 19, 1997)</p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,76,631,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>In 1996 and 1997, reigning world chess champion Garry Kasparov played two six-game matches against an IBM computer called Deep Blue. Kasparov won the first match. Deep Blue was victorious in the second match, marking the first time that a computer had defeated a reigning world champion. Today, any of us could buy an inexpensive chess program for our laptop computer which would consistently outplay Deep Blue. In 1997 however, Deep Blue’s victory was a milestone in the development of artificial intelligence (AI). There was much speculation at the time about the future of AI and about the similarities of computing machines and the human mind. Yale University professor David Gelernter urged restraint.</p><p>“The idea that Deep Blue has a mind is absurd. How can an object that wants nothing, fears nothing, enjoys nothing, needs nothing, and cares about nothing have a mind? It can win at chess, but not because it wants to. It isn’t happy when it wins or sad when it loses. What are its [post]-match plans if it beats Kasparov? Is it hoping to take Deep Pink out for a night on the town?” (Gelernter, 1997)</p><p>Ask ten people to define “artificial intelligence” and you will get ten different answers. This is, in some ways, beneficial ambiguity. Firm definitions can be needlessly constraining to those whose role it is to innovate. According to Stone et al at Stanford University, “the lack of a precise, universally accepted definition of AI probably has helped the field to grow, blossom, and advance at an ever-accelerating pace.” (Stanford, 2016). Nevertheless, to talk about a thing intelligently, it is worth a paragraph or two to define it as it is used in the present discussion. The word “artificial” is relatively easy to define. We use it to refer to things that do not occur naturally, things that are created by humans. The word “intelligence” is a bit more difficult. Philosophers, psychologists, anthropologists, and even theologians offer a variety of definitions. For the purposes of this article series, we will start with a definition which focuses on problem-solving. Psychologist Howard Gardner wrote, “Intelligence is the ability to solve problems, or to create products, that are valued within one or more cultural settings” (Gardner, 1983).</p><p>Thus, artificial intelligence or AI, as we shall use it here, is a machine capability, which does not occur naturally, to solve problems or create something of value. We call this the realm of narrow AI, where an intelligent apparatus is created to solve a particular kind of problem or create a particular type of valuable thing. General AI, which theoretically includes non-trivial foresight, independent problem identification, and problem prioritization based on something like a human value system, or human-like hopes and dreams does not yet exist. In Gelernter’s view, “the gap between the human and the [electronic] surrogate is permanent… Machines will continue to make life easier, healthier, richer, and more puzzling. And humans will continue to care, ultimately, about the same things they always have: about themselves, about one another, and many of them, about God.” (Gelernter, 1976)</p><p>In the next installment, we will consider, “What does AI offer humankind?”</p><p>Notes and references:</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstream Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Gelernter, D., 1997, How Hard Is Chess? TIME, (May 19, 1997)</p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,201,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,202,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,242,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,477,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,557,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,77,632,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Information technology in general and AI in particular serve as assistants to humankind in problem-solving and value creation. Humans can articulate problems and propose solutions beyond their capacity to effectively execute the solution. That is, some solutions require computational capacity that exceeds human capacity in scale, complexity, or both.</p><p>It is important to distinguish between scale and complexity. Humans are more than capable of adding a column of numbers. Machines are better at scale, making short work of calculating totals and averages of thousands or millions of values. Humans are still better than AI at certain kinds of complex tasks when those tasks are performed on a small scale.</p><p>Amazon’s Alexa, Apple’s Siri, and Google’s Assistant use a special kind of AI, Natural Language Processing (NLP), to recognize spoken commands and questions, and to provide synthetic replies. As complex as these tasks might be, they are not as complex as human conversation which considers not only words and grammar, but tone, and non-verbal and paraverbal cues. Human conversations take place in multiple simultaneous contexts. Words and grammar mean different things in different conversations. Thus far, NLP allows machines to process language. It does not yet enable them to converse as humans do, bringing feelings, perceptions, and imagination into the exchange of information. On the other hand, humans can converse with only a limited number of other humans at once at a limited pace. On the other hand, a machine’s ability to tirelessly process long streams of natural language, even more than one at a time, is limited only by the technical architecture of the hardware and software on which it is realized.</p><p>Figure 1 positions some illustrative problem on axes of scale and complexity. The promise of AI is in the high-complexity, low-scale and high-complexity, high-scale quadrants.</p><p><img src=\"/sites/default/files/inline-images/scale-and-complexity-1.jpg\" data-entity-uuid=\"811a7876-8da6-4989-8474-f27eaee5dfc1\" data-entity-type=\"file\" width=\"500\" height=\"445\"></p><p>This is what makes widespread applications of AI possible – exponential increases in ubiquitous computing capacity. Computers which filled entire rooms in the 1960s were capable of little more than arithmetic at scale. Today, billions of mobile phones contain the computing capacity required to perform the complex tasks which we refer to as Artificial Intelligence. Except where human “wiring” remains the better tool for some kinds of problem-solving, machines can outperform humans in both scale and complexity. This may seem obvious, but it is exactly the point of all technology. The first sharpened stone was a better cutting instrument than human fingernails. This is what we humans do. We are toolmakers. We create things that allow us to solve problems and create value better, faster, and more reliably than we can with our innate capacities. AI is just a new tool. It may be an exceptionally interesting tool because, more than a sharpened stone, we see a bit of ourselves reflected in it.</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/\">https://www.wcsaglobal.org/volume-1-issue-2-2020</a></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,78,203,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table>','','full_html'),('blog',0,78,204,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table><p>With access to exponentially more powerful computing capabilities and the capacity to cost-effectively generate and store vast amounts of data many organizations are just trying to make sense of the ever-increasing waves of transactional data created by operational activity. Even so, the goal posts keep moving. Organizations must do more than simply keep up with volume. They must find differentiating and innovative ways to extract value from the data, to intelligently steer the enterprise, one operational process at a time, through Systems of Intelligence.</p><p>Systems of Intelligence is a fourth layer not explicitly anticipated in the 2012 Gartner report in the sense that it offers the potential of something beyond what we traditionally call innovation. In Gartner’s Pace Layers, we think of innovation as something humans do, enabled by technology. The human has a hypothesis about the market or a particular kind of stakeholder. A System of Innovation, relying on machine learning still depends on a hypothesis formed by a human, but it offers the promise of validating or invalidating many hypotheses, quickly, throughout a complex enterprise.</p><p>Data warehouse analytics was once called innovative. Today, the ability to process massive amounts of data and produce meaningful insights are a mature technology – mature enough to be called “traditional”. These technologies can create significant stakeholder value, but they suffer from a fundamental limitation. They are all backward facing. Industry research analyst David Floyer said this, “Traditional Data Warehouse Analytics empower the few to steer the ship by analyzing its wake.” (Floyer, 2015) Traditional analytics most often deliver value as hindsight. Predictive analytics attempt to add value as foresight. But the accuracy of predictions can be diminished by age of the data. Analyses are often based on data which is days or weeks old. Results are published in reports and dashboard to managers and executives who then decide what to share. In contrast, the vision for Systems of Intelligence is real-time, or near real-time analyses, recommendations, and decisions, in the hands of the information producer and consumer. The idea is, process as much data as possible, as quickly as possible, with the best available algorithms to steer the ship intelligently, collectively, and organically with a forward outlook.</p><p>Machine Learning often dominates discussions about AI in which the topic is novel problem solving and modeling and deriving insights from massive and complex data. In the potential for widespread enterprise adoption however, several kinds of AI have the potential to create stakeholder value, separately or in combination.</p><ul><li>Natural Language Processing</li><li>Image Recognition</li><li>Machine Learning based analysis and forecasting</li><li>Robotics</li></ul><p>This is not an exhaustive list, but these four kinds of AI are relatively easy to define empirically through well-known examples. Stanford’s One Hundred Year Study on Artificial Intelligence — <a href=\"https://ai100.stanford.edu/2016-report\">Artificial Intelligence and Life in 2030</a>— lists 11 applications of AI each of which are forms of narrow AI. Some of the most compelling applications, or use cases, employ more than one kind of AI. For reasons of space and simplicity, we will go only a little deeper into the found kinds of AI mentioned above.</p><p>Natural Language Processing (NLP) is the ability of a machine to process human communication in its natural form, written or audible, and generate human-understandable responses in a natural form. Apple’s Siri, Google’s Assistant, and Amazon Alexa are well known examples of the tech giants. Many other enterprises are today using some form of NLP. Airline reservation systems are a prominent example. In this case, the organization derives stakeholder value by providing customer service for routine matters at a lower cost than doing so with human agents.</p><p>Image Recognition appears in Google’s reverse image search at images.google.com. Instead of typing a search term and receiving images as result, a user can provide an image and the technology tells you what it probably is, where to read about it and a selection of visually similar images.</p><p>The photo in Figure 2 (taken by the author in February 2020) returned the primary result “Western Wall” even though the most visually prominent object is not the wall but the Dome of the Rock and other structures beyond the wall. A review of the visually similar images suggests an explanation. Many of the visually similar images were captured from the same direction but with a wider view. In them, the Western Wall is visible along with the Dome of the Rock. The images appear to have a relatively larger number of metadata tags which refer to the Western Wall rather than the Dome of the Rock. This reveals potential weakness of image recognition technologies. All AI must be “trained” in some way. That is, we give the machine examples and tell it how to recognize important things in the examples. In this instance of image recognition, users contribute images and add keywords or metadata about the image. Because many images in the training data containing the Dome of the Rock are tagged with keywords referring to the Western Wall, Google’s algorithm says this is a photo of the wall, even though the wall is not visible. This answer is in the right neighborhood, in more ways than one, but it is not correct. A human observer would say this is a photo of the Dome of the Rock, not of the Western Wall. As impressive as the technology has become, it is not able to overcome poor training or a bias in the training data. Because of errors like this, humans need to supervise the machine’s output, especially when that output is used to inform high-stakes decisions. With enough correction provided by human supervisors, the machine will learn more and produce increasingly accurate results.</p><p>&nbsp;</p><p><img src=\"/sites/default/files/inline-images/Jerusalem.jpg\" data-entity-uuid=\"ed988183-66fe-41f3-9cae-a39dba82e20c\" data-entity-type=\"file\" width=\"468\" height=\"312\"></p><p>Figure 2: The Dome of the Rock, Jerusalem (Source: the author)</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020. <a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p><strong>References</strong></p><p>AWS (Amazon Web Services), 2021, Machine Learing on AWS, June 7, 2021. <a href=\"https://aws.amazon.com/ai/machine-learning/\">https://aws.amazon.com/machine-learning</a></p><p>Deloitte. 2020. Industry 4.0, Deloitte Insights <a href=\"https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html\">https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Floyer D., 2015, Managing the Data Tsunami with Systems of Intelligence. Wikibon, Inc. October 10, 2015. <a href=\"https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence\">https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence</a></p><p>Gaughan D., 2012, Introducing the Pace Layered Application Strategy Special Report. Gartner Inc., February 3, 2012. <a href=\"https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report\">https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report</a></p><p>Hickey J., 2020, Using Machine Learning to “Nowcast” Precipitation in High Resolution. January 13, 2020. Google. <a href=\"https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html\">https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html</a></p><p>King S., 2020, Why COVID-19 Is Accelerating The Adoption Of AI And Research Tech. May 11, 2020. Forbes. <a href=\"https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140\">https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140</a></p><p>Microsoft, 2021, Microsoft Azure Cognitive Services, June 7, 2021. <a href=\"https://azure.microsoft.com/en-us/services/cognitive-services\">https://azure.microsoft.com/en-us/services/cognitive-services</a></p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,78,241,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table><p>With access to exponentially more powerful computing capabilities and the capacity to cost-effectively generate and store vast amounts of data many organizations are just trying to make sense of the ever-increasing waves of transactional data created by operational activity. Even so, the goal posts keep moving. Organizations must do more than simply keep up with volume. They must find differentiating and innovative ways to extract value from the data, to intelligently steer the enterprise, one operational process at a time, through Systems of Intelligence.</p><p>Systems of Intelligence is a fourth layer not explicitly anticipated in the 2012 Gartner report in the sense that it offers the potential of something beyond what we traditionally call innovation. In Gartner’s Pace Layers, we think of innovation as something humans do, enabled by technology. The human has a hypothesis about the market or a particular kind of stakeholder. A System of Innovation, relying on machine learning still depends on a hypothesis formed by a human, but it offers the promise of validating or invalidating many hypotheses, quickly, throughout a complex enterprise.</p><p>Data warehouse analytics was once called innovative. Today, the ability to process massive amounts of data and produce meaningful insights are a mature technology – mature enough to be called “traditional”. These technologies can create significant stakeholder value, but they suffer from a fundamental limitation. They are all backward facing. Industry research analyst David Floyer said this, “Traditional Data Warehouse Analytics empower the few to steer the ship by analyzing its wake.” (Floyer, 2015) Traditional analytics most often deliver value as hindsight. Predictive analytics attempt to add value as foresight. But the accuracy of predictions can be diminished by age of the data. Analyses are often based on data which is days or weeks old. Results are published in reports and dashboard to managers and executives who then decide what to share. In contrast, the vision for Systems of Intelligence is real-time, or near real-time analyses, recommendations, and decisions, in the hands of the information producer and consumer. The idea is, process as much data as possible, as quickly as possible, with the best available algorithms to steer the ship intelligently, collectively, and organically with a forward outlook.</p><p>Machine Learning often dominates discussions about AI in which the topic is novel problem solving and modeling and deriving insights from massive and complex data. In the potential for widespread enterprise adoption however, several kinds of AI have the potential to create stakeholder value, separately or in combination.</p><ul><li>Natural Language Processing</li><li>Image Recognition</li><li>Machine Learning based analysis and forecasting</li><li>Robotics</li></ul><p>This is not an exhaustive list, but these four kinds of AI are relatively easy to define empirically through well-known examples. Stanford’s One Hundred Year Study on Artificial Intelligence — <a href=\"https://ai100.stanford.edu/2016-report\">Artificial Intelligence and Life in 2030</a>— lists 11 applications of AI each of which are forms of narrow AI. Some of the most compelling applications, or use cases, employ more than one kind of AI. For reasons of space and simplicity, we will go only a little deeper into the found kinds of AI mentioned above.</p><p>Natural Language Processing (NLP) is the ability of a machine to process human communication in its natural form, written or audible, and generate human-understandable responses in a natural form. Apple’s Siri, Google’s Assistant, and Amazon Alexa are well known examples of the tech giants. Many other enterprises are today using some form of NLP. Airline reservation systems are a prominent example. In this case, the organization derives stakeholder value by providing customer service for routine matters at a lower cost than doing so with human agents.</p><p>Image Recognition appears in Google’s reverse image search at images.google.com. Instead of typing a search term and receiving images as result, a user can provide an image and the technology tells you what it probably is, where to read about it and a selection of visually similar images.</p><p>The photo in Figure 2 (taken by the author in February 2020) returned the primary result “Western Wall” even though the most visually prominent object is not the wall but the Dome of the Rock and other structures beyond the wall. A review of the visually similar images suggests an explanation. Many of the visually similar images were captured from the same direction but with a wider view. In them, the Western Wall is visible along with the Dome of the Rock. The images appear to have a relatively larger number of metadata tags which refer to the Western Wall rather than the Dome of the Rock. This reveals potential weakness of image recognition technologies. All AI must be “trained” in some way. That is, we give the machine examples and tell it how to recognize important things in the examples. In this instance of image recognition, users contribute images and add keywords or metadata about the image. Because many images in the training data containing the Dome of the Rock are tagged with keywords referring to the Western Wall, Google’s algorithm says this is a photo of the wall, even though the wall is not visible. This answer is in the right neighborhood, in more ways than one, but it is not correct. A human observer would say this is a photo of the Dome of the Rock, not of the Western Wall. As impressive as the technology has become, it is not able to overcome poor training or a bias in the training data. Because of errors like this, humans need to supervise the machine’s output, especially when that output is used to inform high-stakes decisions. With enough correction provided by human supervisors, the machine will learn more and produce increasingly accurate results.</p><p>&nbsp;</p><p><img src=\"/sites/default/files/inline-images/Jerusalem.jpg\" data-entity-uuid=\"ed988183-66fe-41f3-9cae-a39dba82e20c\" data-entity-type=\"file\" width=\"468\" height=\"312\"></p><p>Figure 2: The Dome of the Rock, Jerusalem (Source: the author)</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020. <a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p><strong>References</strong></p><p>AWS (Amazon Web Services), 2021, Machine Learing on AWS, June 7, 2021. <a href=\"https://aws.amazon.com/ai/machine-learning/\">https://aws.amazon.com/machine-learning</a></p><p>Deloitte. 2020. Industry 4.0, Deloitte Insights <a href=\"https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html\">https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Floyer D., 2015, Managing the Data Tsunami with Systems of Intelligence. Wikibon, Inc. October 10, 2015. <a href=\"https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence\">https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence</a></p><p>Gaughan D., 2012, Introducing the Pace Layered Application Strategy Special Report. Gartner Inc., February 3, 2012. <a href=\"https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report\">https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report</a></p><p>Hickey J., 2020, Using Machine Learning to “Nowcast” Precipitation in High Resolution. January 13, 2020. Google. <a href=\"https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html\">https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html</a></p><p>King S., 2020, Why COVID-19 Is Accelerating The Adoption Of AI And Research Tech. May 11, 2020. Forbes. <a href=\"https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140\">https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140</a></p><p>Microsoft, 2021, Microsoft Azure Cognitive Services, June 7, 2021. <a href=\"https://azure.microsoft.com/en-us/services/cognitive-services\">https://azure.microsoft.com/en-us/services/cognitive-services</a></p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,78,478,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table><p>With access to exponentially more powerful computing capabilities and the capacity to cost-effectively generate and store vast amounts of data many organizations are just trying to make sense of the ever-increasing waves of transactional data created by operational activity. Even so, the goal posts keep moving. Organizations must do more than simply keep up with volume. They must find differentiating and innovative ways to extract value from the data, to intelligently steer the enterprise, one operational process at a time, through Systems of Intelligence.</p><p>Systems of Intelligence is a fourth layer not explicitly anticipated in the 2012 Gartner report in the sense that it offers the potential of something beyond what we traditionally call innovation. In Gartner’s Pace Layers, we think of innovation as something humans do, enabled by technology. The human has a hypothesis about the market or a particular kind of stakeholder. A System of Innovation, relying on machine learning still depends on a hypothesis formed by a human, but it offers the promise of validating or invalidating many hypotheses, quickly, throughout a complex enterprise.</p><p>Data warehouse analytics was once called innovative. Today, the ability to process massive amounts of data and produce meaningful insights are a mature technology – mature enough to be called “traditional”. These technologies can create significant stakeholder value, but they suffer from a fundamental limitation. They are all backward facing. Industry research analyst David Floyer said this, “Traditional Data Warehouse Analytics empower the few to steer the ship by analyzing its wake.” (Floyer, 2015) Traditional analytics most often deliver value as hindsight. Predictive analytics attempt to add value as foresight. But the accuracy of predictions can be diminished by age of the data. Analyses are often based on data which is days or weeks old. Results are published in reports and dashboard to managers and executives who then decide what to share. In contrast, the vision for Systems of Intelligence is real-time, or near real-time analyses, recommendations, and decisions, in the hands of the information producer and consumer. The idea is, process as much data as possible, as quickly as possible, with the best available algorithms to steer the ship intelligently, collectively, and organically with a forward outlook.</p><p>Machine Learning often dominates discussions about AI in which the topic is novel problem solving and modeling and deriving insights from massive and complex data. In the potential for widespread enterprise adoption however, several kinds of AI have the potential to create stakeholder value, separately or in combination.</p><ul><li>Natural Language Processing</li><li>Image Recognition</li><li>Machine Learning based analysis and forecasting</li><li>Robotics</li></ul><p>This is not an exhaustive list, but these four kinds of AI are relatively easy to define empirically through well-known examples. Stanford’s One Hundred Year Study on Artificial Intelligence — <a href=\"https://ai100.stanford.edu/2016-report\">Artificial Intelligence and Life in 2030</a>— lists 11 applications of AI each of which are forms of narrow AI. Some of the most compelling applications, or use cases, employ more than one kind of AI. For reasons of space and simplicity, we will go only a little deeper into the found kinds of AI mentioned above.</p><p>Natural Language Processing (NLP) is the ability of a machine to process human communication in its natural form, written or audible, and generate human-understandable responses in a natural form. Apple’s Siri, Google’s Assistant, and Amazon Alexa are well known examples of the tech giants. Many other enterprises are today using some form of NLP. Airline reservation systems are a prominent example. In this case, the organization derives stakeholder value by providing customer service for routine matters at a lower cost than doing so with human agents.</p><p>Image Recognition appears in Google’s reverse image search at images.google.com. Instead of typing a search term and receiving images as result, a user can provide an image and the technology tells you what it probably is, where to read about it and a selection of visually similar images.</p><p>The photo in Figure 2 (taken by the author in February 2020) returned the primary result “Western Wall” even though the most visually prominent object is not the wall but the Dome of the Rock and other structures beyond the wall. A review of the visually similar images suggests an explanation. Many of the visually similar images were captured from the same direction but with a wider view. In them, the Western Wall is visible along with the Dome of the Rock. The images appear to have a relatively larger number of metadata tags which refer to the Western Wall rather than the Dome of the Rock. This reveals potential weakness of image recognition technologies. All AI must be “trained” in some way. That is, we give the machine examples and tell it how to recognize important things in the examples. In this instance of image recognition, users contribute images and add keywords or metadata about the image. Because many images in the training data containing the Dome of the Rock are tagged with keywords referring to the Western Wall, Google’s algorithm says this is a photo of the wall, even though the wall is not visible. This answer is in the right neighborhood, in more ways than one, but it is not correct. A human observer would say this is a photo of the Dome of the Rock, not of the Western Wall. As impressive as the technology has become, it is not able to overcome poor training or a bias in the training data. Because of errors like this, humans need to supervise the machine’s output, especially when that output is used to inform high-stakes decisions. With enough correction provided by human supervisors, the machine will learn more and produce increasingly accurate results.</p><p>&nbsp;</p><p><img src=\"/sites/default/files/inline-images/Jerusalem.jpg\" data-entity-uuid=\"ed988183-66fe-41f3-9cae-a39dba82e20c\" data-entity-type=\"file\" width=\"468\" height=\"312\"></p><p>Figure 2: The Dome of the Rock, Jerusalem (Source: the author)</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020. <a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p><strong>References</strong></p><p>AWS (Amazon Web Services), 2021, Machine Learing on AWS, June 7, 2021. <a href=\"https://aws.amazon.com/ai/machine-learning/\">https://aws.amazon.com/machine-learning</a></p><p>Deloitte. 2020. Industry 4.0, Deloitte Insights <a href=\"https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html\">https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Floyer D., 2015, Managing the Data Tsunami with Systems of Intelligence. Wikibon, Inc. October 10, 2015. <a href=\"https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence\">https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence</a></p><p>Gaughan D., 2012, Introducing the Pace Layered Application Strategy Special Report. Gartner Inc., February 3, 2012. <a href=\"https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report\">https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report</a></p><p>Hickey J., 2020, Using Machine Learning to “Nowcast” Precipitation in High Resolution. January 13, 2020. Google. <a href=\"https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html\">https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html</a></p><p>King S., 2020, Why COVID-19 Is Accelerating The Adoption Of AI And Research Tech. May 11, 2020. Forbes. <a href=\"https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140\">https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140</a></p><p>Microsoft, 2021, Microsoft Azure Cognitive Services, June 7, 2021. <a href=\"https://azure.microsoft.com/en-us/services/cognitive-services\">https://azure.microsoft.com/en-us/services/cognitive-services</a></p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,78,558,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table><p>With access to exponentially more powerful computing capabilities and the capacity to cost-effectively generate and store vast amounts of data many organizations are just trying to make sense of the ever-increasing waves of transactional data created by operational activity. Even so, the goal posts keep moving. Organizations must do more than simply keep up with volume. They must find differentiating and innovative ways to extract value from the data, to intelligently steer the enterprise, one operational process at a time, through Systems of Intelligence.</p><p>Systems of Intelligence is a fourth layer not explicitly anticipated in the 2012 Gartner report in the sense that it offers the potential of something beyond what we traditionally call innovation. In Gartner’s Pace Layers, we think of innovation as something humans do, enabled by technology. The human has a hypothesis about the market or a particular kind of stakeholder. A System of Innovation, relying on machine learning still depends on a hypothesis formed by a human, but it offers the promise of validating or invalidating many hypotheses, quickly, throughout a complex enterprise.</p><p>Data warehouse analytics was once called innovative. Today, the ability to process massive amounts of data and produce meaningful insights are a mature technology – mature enough to be called “traditional”. These technologies can create significant stakeholder value, but they suffer from a fundamental limitation. They are all backward facing. Industry research analyst David Floyer said this, “Traditional Data Warehouse Analytics empower the few to steer the ship by analyzing its wake.” (Floyer, 2015) Traditional analytics most often deliver value as hindsight. Predictive analytics attempt to add value as foresight. But the accuracy of predictions can be diminished by age of the data. Analyses are often based on data which is days or weeks old. Results are published in reports and dashboard to managers and executives who then decide what to share. In contrast, the vision for Systems of Intelligence is real-time, or near real-time analyses, recommendations, and decisions, in the hands of the information producer and consumer. The idea is, process as much data as possible, as quickly as possible, with the best available algorithms to steer the ship intelligently, collectively, and organically with a forward outlook.</p><p>Machine Learning often dominates discussions about AI in which the topic is novel problem solving and modeling and deriving insights from massive and complex data. In the potential for widespread enterprise adoption however, several kinds of AI have the potential to create stakeholder value, separately or in combination.</p><ul><li>Natural Language Processing</li><li>Image Recognition</li><li>Machine Learning based analysis and forecasting</li><li>Robotics</li></ul><p>This is not an exhaustive list, but these four kinds of AI are relatively easy to define empirically through well-known examples. Stanford’s One Hundred Year Study on Artificial Intelligence — <a href=\"https://ai100.stanford.edu/2016-report\">Artificial Intelligence and Life in 2030</a>— lists 11 applications of AI each of which are forms of narrow AI. Some of the most compelling applications, or use cases, employ more than one kind of AI. For reasons of space and simplicity, we will go only a little deeper into the found kinds of AI mentioned above.</p><p>Natural Language Processing (NLP) is the ability of a machine to process human communication in its natural form, written or audible, and generate human-understandable responses in a natural form. Apple’s Siri, Google’s Assistant, and Amazon Alexa are well known examples of the tech giants. Many other enterprises are today using some form of NLP. Airline reservation systems are a prominent example. In this case, the organization derives stakeholder value by providing customer service for routine matters at a lower cost than doing so with human agents.</p><p>Image Recognition appears in Google’s reverse image search at images.google.com. Instead of typing a search term and receiving images as result, a user can provide an image and the technology tells you what it probably is, where to read about it and a selection of visually similar images.</p><p>The photo in Figure 2 (taken by the author in February 2020) returned the primary result “Western Wall” even though the most visually prominent object is not the wall but the Dome of the Rock and other structures beyond the wall. A review of the visually similar images suggests an explanation. Many of the visually similar images were captured from the same direction but with a wider view. In them, the Western Wall is visible along with the Dome of the Rock. The images appear to have a relatively larger number of metadata tags which refer to the Western Wall rather than the Dome of the Rock. This reveals potential weakness of image recognition technologies. All AI must be “trained” in some way. That is, we give the machine examples and tell it how to recognize important things in the examples. In this instance of image recognition, users contribute images and add keywords or metadata about the image. Because many images in the training data containing the Dome of the Rock are tagged with keywords referring to the Western Wall, Google’s algorithm says this is a photo of the wall, even though the wall is not visible. This answer is in the right neighborhood, in more ways than one, but it is not correct. A human observer would say this is a photo of the Dome of the Rock, not of the Western Wall. As impressive as the technology has become, it is not able to overcome poor training or a bias in the training data. Because of errors like this, humans need to supervise the machine’s output, especially when that output is used to inform high-stakes decisions. With enough correction provided by human supervisors, the machine will learn more and produce increasingly accurate results.</p><p>&nbsp;</p><p><img src=\"/sites/default/files/inline-images/Jerusalem.jpg\" data-entity-uuid=\"ed988183-66fe-41f3-9cae-a39dba82e20c\" data-entity-type=\"file\" width=\"468\" height=\"312\"></p><p>Figure 2: The Dome of the Rock, Jerusalem (Source: the author)</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020. <a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p><strong>References</strong></p><p>AWS (Amazon Web Services), 2021, Machine Learing on AWS, June 7, 2021. <a href=\"https://aws.amazon.com/ai/machine-learning/\">https://aws.amazon.com/machine-learning</a></p><p>Deloitte. 2020. Industry 4.0, Deloitte Insights <a href=\"https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html\">https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Floyer D., 2015, Managing the Data Tsunami with Systems of Intelligence. Wikibon, Inc. October 10, 2015. <a href=\"https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence\">https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence</a></p><p>Gaughan D., 2012, Introducing the Pace Layered Application Strategy Special Report. Gartner Inc., February 3, 2012. <a href=\"https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report\">https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report</a></p><p>Hickey J., 2020, Using Machine Learning to “Nowcast” Precipitation in High Resolution. January 13, 2020. Google. <a href=\"https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html\">https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html</a></p><p>King S., 2020, Why COVID-19 Is Accelerating The Adoption Of AI And Research Tech. May 11, 2020. Forbes. <a href=\"https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140\">https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140</a></p><p>Microsoft, 2021, Microsoft Azure Cognitive Services, June 7, 2021. <a href=\"https://azure.microsoft.com/en-us/services/cognitive-services\">https://azure.microsoft.com/en-us/services/cognitive-services</a></p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('blog',0,78,633,'en',0,'<p>This article is one of a series on the subject of Artificial Intelligence in mainstream enterprise computing.</p><p>Leaders and managers of businesses, non-profit organizations, government agencies and others have something in common. They have organizational goals and organizational stakeholders. Whether those stakeholders are owners, customers, social service clients, or citizen constituents, the organizational goals must align in whole or in part with solving a problem or creating something of value for stakeholders. Ultimately, as AI becomes widely adopted, everyone stands to benefit. We are all consumers, citizens, and owners. We are all stakeholders.</p><p>Here again some definitions are necessary. By “enterprise systems”, we mean solutions built of software applications, data, and supporting technologies which enable an organization to achieve its distinct goals and create value for its stakeholders. But we also include in this definition of system, the humans who use the system, the humans who derive some benefit from it, and the policies and operating procedures which govern the use of the technical solution. By “mainstream”, we mean those solutions that are widely adopted or that have the potential for wide adoption yielding transformed operational processes across industry sectors.</p><ul><li>The field of artificial intelligence (AI) is finally yielding valuable smart devices and applications that do more than win games against human champions. According to a report from the Frederick S. Pardee Center for International Futures at the University of Denver, the products of AI are changing the competitive landscape in several industry sectors and are poised to upend operations in many business functions« (Kiron, 2017).</li></ul><p>It is tempting to omit computer games from this discussion. We might not think that they create real value for the stakeholders. But the consumers who pay for them clearly find value in them as a form of entertainment. Further, the broad genre of computer applications, games and simulations, which incorporate advanced AI technologies, create stakeholder value as training and development platforms. One need to look no further than commercial flight simulators which allow students and pilots of all levels of experience to train and learn without the risk of making inappropriate contact with the ground in a real aircraft with real people aboard.</p><p>For over half a century, enterprises of all kinds have adopted successive generations of information technology to create stakeholder value by increasing sales, reducing costs, producing widgets, or delivering services faster and more reliably. Organizations of all sizes today use a computer of some kind to house their Systems of Record – a system for the collection and management of transactional information, for operational needs and management reporting. Some organizations find ways to achieve competitive advantage through clever uses of Information Technology, often doing the same thing as their competitors, just doing it faster or cheaper. We can call this a System of Differentiation. A few companies change the marketplace through Systems of Innovation – innovative applications of Information Technology. A leading Information Technology research firm introduced this three-layer model in 2012, referring to it as “Pace Layered Application Strategy” (Gartner, 2012) because each layer promises to drive organizational change and accelerate value creation at a different pace.</p><p>The most well-known example of Systems of Innovation is an entire enterprise – Amazon.com. Beginning as an online bookseller, Amazon innovated so profoundly that they almost single-handedly killed brick and mortar bookstores. It is telling that they are not known as Amazon, Incorporated, or the Amazon Company. They are known by their Internet domain name. Today, their technology innovations have not only transformed how households and business acquire all manner of goods, their technology itself has become a market-disruptive service in the form of Amazon Web Services (AWS). Further, AWS, along with Microsoft Azure, IBM Watson, and others are now commoditizing elements of their AI infrastructure providing an unprecedented opportunity for enterprises which are not among the “tech giants’ to employ these technologies in their pursuit of stakeholder value.</p><p>Table 1 lists a sample of the AI services provided by AI that enterprises can integrate into their systems. According to Amazon, “you get instant access to fast, high quality AI tools based on the same technology used to power Amazon’s own businesses.” (AWS, 2021)</p><p><strong>Table 1: Sample AWS AI Services (source: AWS, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Amazon CodeGuru</td><td>Automate code reviews to improve software quality</td></tr><tr><td>Amazon Comprehend</td><td>Discover insights and relationships in text</td></tr><tr><td>Amazon Fraud Detector</td><td>Detect online fraud faster</td></tr><tr><td>Amazon Lex</td><td>Build voice and text chatbots</td></tr><tr><td>Amazon Polly</td><td>Turn text into lifelike speech</td></tr><tr><td>Amazon Recognition</td><td>Analyze image and video</td></tr><tr><td>Amazon Transcribe</td><td>Automatic speech recognition</td></tr></tbody></table><p>Table 2 lists some of Microsoft’s AI services provide under a product line called Azure Cognitive Services.</p><p><strong>Table 2: Sample Microsoft AI Services (Microsoft Azure Cognitive Services, 2021)</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Service Name</th><th>Service Description</th></tr></thead><tbody><tr><td>Content Moderator</td><td>Detect potentially offensive or unwanted content</td></tr><tr><td>Text Analytics</td><td>Detect sentiment, key phrases, and named entities</td></tr><tr><td>Translator</td><td>Detect and translate more than 60 supported languages</td></tr><tr><td>Speaker Recognition</td><td>Identify and verify the people speaking based on audio</td></tr><tr><td>Computer Vision</td><td>Analyze content images</td></tr><tr><td>Face</td><td>Detect and identify people and emotions in images</td></tr><tr><td>Video Indexer</td><td>Analyze the visual and audio channels of a video, and index its content</td></tr></tbody></table><p>With access to exponentially more powerful computing capabilities and the capacity to cost-effectively generate and store vast amounts of data many organizations are just trying to make sense of the ever-increasing waves of transactional data created by operational activity. Even so, the goal posts keep moving. Organizations must do more than simply keep up with volume. They must find differentiating and innovative ways to extract value from the data, to intelligently steer the enterprise, one operational process at a time, through Systems of Intelligence.</p><p>Systems of Intelligence is a fourth layer not explicitly anticipated in the 2012 Gartner report in the sense that it offers the potential of something beyond what we traditionally call innovation. In Gartner’s Pace Layers, we think of innovation as something humans do, enabled by technology. The human has a hypothesis about the market or a particular kind of stakeholder. A System of Innovation, relying on machine learning still depends on a hypothesis formed by a human, but it offers the promise of validating or invalidating many hypotheses, quickly, throughout a complex enterprise.</p><p>Data warehouse analytics was once called innovative. Today, the ability to process massive amounts of data and produce meaningful insights are a mature technology – mature enough to be called “traditional”. These technologies can create significant stakeholder value, but they suffer from a fundamental limitation. They are all backward facing. Industry research analyst David Floyer said this, “Traditional Data Warehouse Analytics empower the few to steer the ship by analyzing its wake.” (Floyer, 2015) Traditional analytics most often deliver value as hindsight. Predictive analytics attempt to add value as foresight. But the accuracy of predictions can be diminished by age of the data. Analyses are often based on data which is days or weeks old. Results are published in reports and dashboard to managers and executives who then decide what to share. In contrast, the vision for Systems of Intelligence is real-time, or near real-time analyses, recommendations, and decisions, in the hands of the information producer and consumer. The idea is, process as much data as possible, as quickly as possible, with the best available algorithms to steer the ship intelligently, collectively, and organically with a forward outlook.</p><p>Machine Learning often dominates discussions about AI in which the topic is novel problem solving and modeling and deriving insights from massive and complex data. In the potential for widespread enterprise adoption however, several kinds of AI have the potential to create stakeholder value, separately or in combination.</p><ul><li>Natural Language Processing</li><li>Image Recognition</li><li>Machine Learning based analysis and forecasting</li><li>Robotics</li></ul><p>This is not an exhaustive list, but these four kinds of AI are relatively easy to define empirically through well-known examples. Stanford’s One Hundred Year Study on Artificial Intelligence — <a href=\"https://ai100.stanford.edu/2016-report\">Artificial Intelligence and Life in 2030</a>— lists 11 applications of AI each of which are forms of narrow AI. Some of the most compelling applications, or use cases, employ more than one kind of AI. For reasons of space and simplicity, we will go only a little deeper into the found kinds of AI mentioned above.</p><p>Natural Language Processing (NLP) is the ability of a machine to process human communication in its natural form, written or audible, and generate human-understandable responses in a natural form. Apple’s Siri, Google’s Assistant, and Amazon Alexa are well known examples of the tech giants. Many other enterprises are today using some form of NLP. Airline reservation systems are a prominent example. In this case, the organization derives stakeholder value by providing customer service for routine matters at a lower cost than doing so with human agents.</p><p>Image Recognition appears in Google’s reverse image search at images.google.com. Instead of typing a search term and receiving images as result, a user can provide an image and the technology tells you what it probably is, where to read about it and a selection of visually similar images.</p><p>The photo in Figure 2 (taken by the author in February 2020) returned the primary result “Western Wall” even though the most visually prominent object is not the wall but the Dome of the Rock and other structures beyond the wall. A review of the visually similar images suggests an explanation. Many of the visually similar images were captured from the same direction but with a wider view. In them, the Western Wall is visible along with the Dome of the Rock. The images appear to have a relatively larger number of metadata tags which refer to the Western Wall rather than the Dome of the Rock. This reveals potential weakness of image recognition technologies. All AI must be “trained” in some way. That is, we give the machine examples and tell it how to recognize important things in the examples. In this instance of image recognition, users contribute images and add keywords or metadata about the image. Because many images in the training data containing the Dome of the Rock are tagged with keywords referring to the Western Wall, Google’s algorithm says this is a photo of the wall, even though the wall is not visible. This answer is in the right neighborhood, in more ways than one, but it is not correct. A human observer would say this is a photo of the Dome of the Rock, not of the Western Wall. As impressive as the technology has become, it is not able to overcome poor training or a bias in the training data. Because of errors like this, humans need to supervise the machine’s output, especially when that output is used to inform high-stakes decisions. With enough correction provided by human supervisors, the machine will learn more and produce increasingly accurate results.</p><p>&nbsp;</p><p><img src=\"/sites/default/files/inline-images/Jerusalem.jpg\" data-entity-uuid=\"ed988183-66fe-41f3-9cae-a39dba82e20c\" data-entity-type=\"file\" width=\"468\" height=\"312\"></p><p>Figure 2: The Dome of the Rock, Jerusalem (Source: the author)</p><p>Portions of this article originally appeared in the Journal of the World Complexity Science Academy Volume 1, Issue 2 as “Artificial Intelligence in Mainstrem Enterprise Applications”, Picirillo, D. 2020. <a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020\">https://www.wcsaglobal.org/volume-1-issue-2-2020/</a></p><p><strong>References</strong></p><p>AWS (Amazon Web Services), 2021, Machine Learing on AWS, June 7, 2021. <a href=\"https://aws.amazon.com/ai/machine-learning/\">https://aws.amazon.com/machine-learning</a></p><p>Deloitte. 2020. Industry 4.0, Deloitte Insights <a href=\"https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html\">https://www2.deloitte.com/us/en/insights/focus/industry-4-0.html</a></p><p>Gardner H., 1983, Frames of Mind: The Theory of Multiple Intelligences. New York, Fontana Press.</p><p>Floyer D., 2015, Managing the Data Tsunami with Systems of Intelligence. Wikibon, Inc. October 10, 2015. <a href=\"https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence\">https://wikibon.com/managing-the-data-tsunami-with-systems-of-intelligence</a></p><p>Gaughan D., 2012, Introducing the Pace Layered Application Strategy Special Report. Gartner Inc., February 3, 2012. <a href=\"https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report\">https://blogs.gartner.com/dennis-gaughan/2012/02/03/introducing-the-pace-layered-application-strategy-special-report</a></p><p>Hickey J., 2020, Using Machine Learning to “Nowcast” Precipitation in High Resolution. January 13, 2020. Google. <a href=\"https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html\">https://ai.googleblog.com/2020/01/using-machine-learning-to-nowcast.html</a></p><p>King S., 2020, Why COVID-19 Is Accelerating The Adoption Of AI And Research Tech. May 11, 2020. Forbes. <a href=\"https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140\">https://www.forbes.com/sites/steveking/2020/05/11/why-covid-19-is-accelerating-the-adoption-of-ai-and-research-tech/#2983b7162140</a></p><p>Microsoft, 2021, Microsoft Azure Cognitive Services, June 7, 2021. <a href=\"https://azure.microsoft.com/en-us/services/cognitive-services\">https://azure.microsoft.com/en-us/services/cognitive-services</a></p><p>Stone P., Brooks R., Brynjolfsson E., Calo R., Etzioni O., Hager G., Hirschberg J., Kalyanakrishnan S., Kamar E., Kraus S., Leyton-Brown K., Parkes D., Press W., Saxenian A., Shah J., Tambe M., and Teller A., 2016. Artificial Intelligence and Life in 2030. One Hundred Year Study on Artificial Intelligence: Report of the 2015-2016 Study Panel, Stanford University, Stanford, CA, September 2016.<a href=\"http://ai100.stanford.edu/2016-report\">http://ai100.stanford.edu/2016-report</a></p><p><strong>Posts in this series</strong></p><ol><li>AI In Mainstream Enterprise Applications</li><li>What does AI offer humankind?</li><li>What Does AI Offer Users Of Mainstream Enterprise Systems?</li></ol>','','full_html'),('featured_article',0,79,206,'en',0,'<p><strong>GRC Definition: -</strong></p><p>GRC is the capability, or integrated collection of capabilities, that enables an organization to reliably achieve objectives, address uncertainty and act with integrity, including the governance, assurance and management of performance, risk, and compliance.<a href=\"https://www.oceg.org/glossary/en/\">www.grcglossary.org</a></p><p><strong>What is GRC?</strong></p><p>In February of 2002, Mr Michael Rasmussen, considered by many to be the “father” of GRC, was the one who first proposed using the abbreviation GRC. A model and a framework for GRC were initially made available in 2003 by the Open Compliance and Ethics Group (OCEG). The acronym is now recognised in its official capacity, and it signifies the three terms “Governance,” “Risk,” and “Compliance.”</p><p>Every global business engages in good governance, risk management, and compliance practices (GRC), even though many people are unaware of the value and meaning of GRC. In an official or informal setting, OCEG has stated, “GRC is not a recently developed concept”.</p><p>Let’s begin by discussing this anecdote to comprehend the rationale behind Mr Rasmussen and OCEG’s decision to merge these three words into a single acronym that has gained widespread reputation over the years.</p><p>In 2001, Fortune magazine honoured “America’s Most Innovative Company” for the sixth year in a row as one of the most successful corporations in the United States. The dot-com era had just reached its zenith; consequently, most investors and regulators were accustomed to the new normal of unusually high share prices. This, in conjunction with the lax regulatory climate of the period, allowed the CEO to be “creative,” enabling him to conceal hazardous assets and losses through a scheme that also involved the chief financial officer, other executives, and even the company’s auditor.</p><p>Enron went bankrupt in December of 2001, resulting in a loss of $74 billion for shareholders, the loss of billions of dollars in pension benefits for its employees, the collapse of the audit firm Arthur Andersen, and the loss of all employees, business partners, and other financial and societal implications as a result of people and businesses losing their income. We now know that this was the largest corporate bankruptcy that had ever occurred in the history of the financial world.</p><p>Even though Mr Rasmussen had a broad vision for GRC version 1.0, the Sarbanes-Oxley Act of 2002 (SOX), adopted as a direct response to the Enron scandal, was the focus of every organisation in the financial sector at that time. GRC 1.0 became, in essence, the recipe for managing your firm in a manner that complies with the SOX internal control criteria.</p><p><strong>Components: -</strong></p><p>To understand the term more comprehensively, let’s understand each one of its components individually:&nbsp;</p><p><strong>Governance:</strong> Governance is a term that refers to a collection of guiding principles, policies, and procedures that determine how an organization works towards achieving its objectives. When it comes to implementation, it takes a top-down approach, which involves essential stakeholders such as board members, senior management, and other high-level executives. The ability to carry out its operations honestly and openly depends on the robustness of its governance structure.</p><p>The higher-ups are given the ability to make decisions while keeping an awareness of the risks involved, engaging with the various stakeholders, and obtaining greater visibility into potential problems and incidents. The data is an indispensable component of this equation. The processes of data visualization, internal auditing, reporting, and risk assessment are all facilitated by a GRC programmed, making accessing relevant metrics easier.</p><p><strong>Risk Management: </strong>Identifying, analyzing, and taking preventative measures against possible risks is referred to as “risk management.” Cybersecurity risk, legal risk, financial risk, operational risk, contractual risk, third-party risk, and the unpredictable risk of natural disasters and crises are examples of the many types of risk that can exist. Risk managers and risk management software must work together as part of a successful risk management programme to address potential dangers before they can cause any damage.</p><p>As an alternative to implementing a separate risk management programme, you can choose to incorporate risk management processes into your daily operations. This improves risk visibility, making accessing risk data more straightforward, prioritizing threats, and implementing remediation strategies.</p><p>An organization needs to strike a balance between its risk appetite and the amount of risk it is willing to take to accomplish its business goals while reducing the amount of risk it is exposed to. You can significantly increase the rate at which threats are responded to and incidents are resolved if you have open communication channels and a well-established hierarchy. You can protect your organization on multiple fronts when you add automated controls and plans for business continuity.</p><p><strong>Compliance:</strong> You, as a business, will have to act with integrity by following the statutory government regulations that are particular to your practice area. The penalties for violating these regulations range from a reprimand that amounts to little more than a slap on the wrist to significant monetary harm.</p><p>The rules themselves are subject to ongoing revision and adjustment. You don’t want to end up in the headlines for violating some environmental regulation, do you?</p><p>You can keep tabs on many regulations, industry standards, rules, and policies while using only a few resources available if you have a compliance programme that works effectively. Establish transparent workflows to facilitate the acceleration of compliance management and conduct internal audits at regular intervals to ensure that everything is operating as it should.</p><p><strong>The Importance of GRC: -</strong><br>&nbsp;</p><p>If you have an integrated plan of action, managing risks will be much less demanding, even as those risks become more complicated and maintaining compliance becomes costlier.</p><p>The lessons learned from the pandemic caused by COVID-19 show that flexibility in risk management and compliance programmes is hugely beneficial. As a result of disruptions in supply chains, businesses are increasingly turning to third-party logistics (3PL) providers to capitalize on the explosive growth of the retail eCommerce industry.</p><p>However, increasing the number of relationships with third parties increases risk and the obligations to comply with regulations. When it comes to governance, risk, and compliance (GRC), having a framework that is clearly defined makes it possible to incorporate additional responsibilities with relatively little friction.</p><p>Greater visibility into governance, risk, and compliance programmes provides the data necessary to recognize areas of vulnerability and overcome challenges. It provides you with sufficient room to capitalize on potentially beneficial chances while minimizing the likelihood of potentially harmful incidents. Your company can expand its operations with the appropriate GRC programme, which will also assist it in managing the risks and regulations associated with its expansion.&nbsp;</p><p>&nbsp;</p><img src=\"/sites/default/files/inline-images/GRC%20framework_1.png\" data-entity-uuid=\"e34ad557-cfdb-4262-8bdc-7b53ff55ffa3\" data-entity-type=\"file\" width=\"1200\" height=\"936\"><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Renowned Frameworks:</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Framework</th><th>Area of Implementation</th><th>Description</th></tr></thead><tbody><tr><td>COSO</td><td>Enterprise Risk Management</td><td>The COSO Framework sets up internal controls for corporate processes. COSO was founded because of Enron. These controls ensure the organization operates ethically, transparently, and according to industry standards.</td></tr><tr><td>HACCP</td><td>Food Safety</td><td>HACCP is a preventive approach to food safety from biological, chemical, and physical hazards in production processes that might make the finished product dangerous. It proposes ways to minimize these risks to a safe level.</td></tr><tr><td>FAIR</td><td>IT Risk, Information Security Risk Assessment</td><td>Factor Analysis of Information Risk (FAIR) is a taxonomy of risk variables and their interactions. It’s focused chiefly on estimating the frequency and magnitude of data loss.</td></tr><tr><td>ISO 27005</td><td>IT Risk, Information Security Risk Assessment</td><td>ISO 27005 supports ISO/IEC 27001’s general concepts and aids in risk-based information security implementation.</td></tr><tr><td>ISO 31000</td><td>Risk Management</td><td>Using ISO 31000 can help organizations achieve goals, identify opportunities and hazards, and allocate and manage resources for risk treatment.</td></tr><tr><td>The Basel Committee</td><td>Operational Risk in Banking And Finance</td><td>Operational risk is embedded in all banking products, activities, processes, and systems, and effective management is a cornerstone of a bank’s risk management programme.</td></tr></tbody></table><p><strong>Critical Drivers For Adoption: -</strong></p><ul><li><strong>Risk Landscape is becoming more complex</strong> – Today’s exposure to risk entails a greater degree of complication and potential harm than it did thirty or forty years ago. It is no longer possible to combat every threat with legacy programmes or restrict fallout to a particular industry without allowing it to spread to other business divisions. The Good Governance, Risk, and Compliance (GRC) framework functions as a checks and balances system that maintains all risks within acceptable parameters.</li><li><strong>Constantly evolving Regulatory Compliance</strong> – You can build tactics to track the modifications made in real time to regulations. The vast majority of GRC solutions can fully automate this process, eliminating the requirement for additional resources to be invested.</li><li><strong>Data Privacy and Protection</strong> – On the one hand, the General Data Protection Regulation (GDPR), the Consumer Cancellation and Portability Act (CCPA), and the Personal Information Protection and Electronic Documents Act (PIPL) have mandated that businesses strengthen their cybersecurity defences. On the other hand, in contrast to adopting a standalone programme, implementing an integrated security solution has become significantly more cost-effective and efficient.</li><li><strong>Third-Party Engagements</strong> – Due to shifting legislation and disturbances in the supply chain, relationships with third-party entities and suppliers have become significantly more complicated. GRC allows you to review and manage your connections with third parties so that they are in your best interests.</li><li><strong>Big Data &amp; Analytics</strong> – Having a foundation in GRC enables you to gain additional insights from risk data, which is especially helpful in light of recent advancements in big data analytics.</li></ul><p><strong>Essential Benefits of GRC: -</strong></p><p><img src=\"/sites/default/files/inline-images/GRC%20benefits.jpg\" data-entity-uuid=\"89073301-09d3-478e-9dc0-ea6e549e7dd6\" data-entity-type=\"file\" width=\"750\" height=\"411\"></p><ul><li><strong>Visibility</strong> – Thanks to GRC, which provides a unified framework for managing governance, risk, and compliance issues, you may find all your data in a single location. This, in turn, enables you to delve deeper into risk data and acquire contextual information on fundamental weaknesses. It is not enough to be aware of what is incorrect; GRC enables you to comprehend the modifications you need to implement into the three systems to forestall future problems. Gaining visibility into your organisation’s financial and operational health helps you to make real-time adjustments and benchmark key performance indicators (KPIs).</li><li><strong>Optimising Costs &amp; Resources</strong> – The potential to save time and money is the key benefit of implementing a GRC programme in your organisation. As a result of the unification of these three processes, you will no longer be required to allocate resources distinctly for each unit. In addition, if you opt to go with GRC software, you can automate day-to-day processes. This will allow your personnel to spend more time on billable activities, ultimately increasing your revenue. You can even integrate chatbots and natural language processing (NLP) to build rules for responding to and dealing with risk situations without involving a natural person if you combine artificial intelligence (AI) and machine learning (ML).</li><li><strong>Centralised Access To Risk Data</strong> – Maintain a record of every piece of information about risks in a single database. You can view the data remotely, allowing you to respond to risk situations more quickly. For safety and privacy reasons, you may choose who can access the risk data and what devices can access it.</li><li><strong>Process Unification</strong> - is one of the more understated benefits; you won’t notice it immediately, but it will pay dividends in the long run. A uniform process, taxonomy, and terminology are all things that can be established using GRC. Standardised methods simplify training new employees, evaluating and benchmarking performance, and ensuring that the platform continues to operate smoothly even when staff members leave or are replaced. Additionally, over time, it fosters a more risk-aware culture at work, ultimately reducing the number of risk-related occurrences. This increases the organisations’ ability to withstand risks and breaks down the functional and operational walls built up.</li><li><strong>Analytics</strong> - You are provided unrestricted access to the risk data, enabling you to go deeper into the information to unearth hidden insights that might have otherwise been missed owing to a lack of oversight. Additionally, integrated advanced analytics tools and reporting capabilities assist in analysing, sharing, and utilising risk information advantageous to the organisation and its customers.</li></ul><p><strong>How Does GRC Function?</strong></p><p>The following are the underlying principles that enable a successful implementation of a GRC framework.</p><p><strong>Key Stakeholder Management</strong> - Collaboration between departments that practise governance, risk management, and regulatory compliance is necessary for GRC, which necessitates cross-functional working relationships. The following are a few examples that illustrate this point:</p><ul><li>Senior Level Executives responsible for making strategic decisions after risk assessment.</li><li>Legal professionals who help in preparing and mitigating legal implications.</li><li>Financial experts responsible for statutory compliance.</li><li>The HR function manages critical and confidential information.</li><li>IT function taking care of cybersecurity and cybersecurity resilience.</li></ul><p><strong>GRC Framework</strong> - A GRC framework is a paradigm for managing an organisation\'s governance and compliance risks. It entails the process of defining the essential policies that can push the firm toward the goals that it has set for itself. You may take a proactive approach to managing risks, make well-informed decisions, and guarantee business continuity if you adopt a GRC framework. This enables you to take advantage of the many benefits of using such a framework.</p><p>Companies put in place GRC by adopting GRC frameworks, which include essential policies that align with the organisation’s strategic objectives. When formulating company policies, organising processes, and exercising governance over the business, key stakeholders base their work on a shared understanding derived from the GRC framework. Companies can use specialised software and other resources to coordinate and keep track of the progress made using the GRC framework.</p><p><strong>GRC Maturity</strong> - An organisation’s level of GRC maturity can be defined as the degree to which it has successfully integrated governance, risk assessment, and compliance. You have reached a high degree of GRC maturity when implementing a well-planned GRC strategy yields positive cost efficiency, productivity, and the efficacy of risk mitigation. On the other hand, a low level of GRC maturity is inefficient and causes business units to continue functioning in isolation.</p><p><strong>Implementing GRC Effectively: -</strong></p><p><br>To implement a GRC solution effectively, below are the tips to ensure a successful implementation</p><p><strong>Value Creation:</strong> It is essential to understand the actual benefit of GRC implementation. The start of a successful implementation starts by identifying the already existing multiple methods across different business segments. In addition, the process enables you to determine which procedures are successful and must be maintained in constructing a unified system.</p><p>Similarly, you can get rid of any data, technologies, or assets that aren\'t needed, are duplicates and hurt value while also having the ability to make the centralised process more difficult.</p><p>From this vantage point, you will be able to prioritise the assets of your company that bring in the highest revenue, and you will be able to direct your GRC strategy toward improving these assets.</p><p><strong>Creating A GRC Roadmap:</strong> To narrow the scope of your strategy, you will need a distinct goal that summarises the primary GRC functions performed by the framework. These results have to be the product of ongoing collaboration between all stakeholders to guarantee that they are by the requirements of each division. Your targeted results can be more easily achieved if you have a solid understanding of the potential benefits that could be gained from a successful GRC framework. Some pertinent benefits of a practical GRC framework are:</p><ul><li>Cohesive approach and better alignment of every department and business goals.</li><li>Ensures effective risk mitigation and management entailing financial, legal, strategic, operational, and cyber.</li><li>Well Informed and quick decision making.</li></ul><p><strong>GAP Analysis:</strong> Once you have identified all the details about your existing GRC processes, you need to zero in on the following</p><ol><li>Maturity of the processes.</li><li>Quality of Data.</li><li>Existing Gaps.</li></ol><p>The following are next steps are to record the following</p><ol><li>Any missing or duplicate data.</li><li>Any duplication or redundant processes.</li><li>Identify the scope for automating or removing manual workflows.</li></ol><p><strong>Managing Stakeholder Expectations:</strong> Your GRC implementation strategy\'s success needs to ensure that your entire organisation is on the same page, even though this is frequently neglected. Every department is involved in an effectively planned GRC project. All significant stakeholders must be allowed to express their thoughts and concerns about your plan. Organisational alignment can be achieved as shared below:</p><ul><li>Alignment of Executive Team With Critical Factors - The first stage in securing organisational common ground is to create a detailed plan that includes essential aspects of the project, such as the timetable and the budget. Before taking additional action, you must confirm that leadership agrees with your strategy. Then it would be best if you made any necessary adjustments before telling the rest of the organisation.</li><li>Moving Down From The Top - As soon as you have received executive approval, you will need to put change management practices into effect across all other business units. These processes need to be realistic and conveyed understandably.<br>For instance, it is reasonable to anticipate that the modifications you have suggested will be met with some level of opposition. Processes and procedures that have been in a department for a long time often need to be gradually phased out before they can be eliminated.</li></ul><p>It is to be ensured that each team receives consistent and informative updates if you want a seamless transition. These updates should inform all the leading stakeholders about the essential changes that have been made and how those changes will influence their roles. Make sure that any team member can easily share any concerns, suggestions, or other significant input that may be why it is required to adjust your approach. Create a process that is open and transparent.</p><p><strong>Create A Robust GRC Approach</strong> - Putting in the necessary foundation is necessary if you want to ensure that your GRC system is practical and adaptive. Because of the ever-evolving nature of cyber threats and vulnerabilities, the ever-changing landscape of cyber threats, and the severe repercussions of data breaches, these components are of the utmost importance in information technology governance and risk management (IT GRC).</p><p>Even more, emphasis needs to be paid to guaranteeing that the GRC methods employed by financial institutions and health organisations are flexible enough to accommodate the regular changes in regulatory requirements that their respective businesses are subject to.</p><p><strong>Invest In A GRC Software Solution Of Repute</strong> - Putting in place a GRC programme from the beginning necessitates the utilisation of many different moving elements, such as the consolidation of information silos, continual upgrades, and the utilisation of manual procedures such as spreadsheets. You can direct more of your implementation efforts to higher-level activities using a GRC platform because it can simplify many of these problematic areas.</p><p>When selecting a GRC tool for your firm, just as you would with any other third-party vendor, you need to complete your due diligence to ensure that the tool complies with all compliance rules and does not put your organisation in a position where it faces extreme security risks.</p><p>The appropriate GRC technology should result in a return on investment (ROI) that can be measured in terms of money and time saved. Some critical questions that need to be addressed are</p><ul><li>Does the software solution offer ease of use?</li><li>Does it have automated workflows?</li><li>Is it customisable and scalable?</li><li>Does the solution offer detailed task management and execution?</li><li>Does it support the integration of third-party applications?</li><li>Is it cost-effective from a TCO (Total Cost of Ownership) perspective?</li></ul><p><strong>Use Industry Prevalent and Accepted Standards</strong> - The capacity to align with the requirements of the entire business is one of the essential characteristics of a GRC strategy that is both successful and efficient. A baseline should be established as a point of reference, even if every department will have its own unique set of criteria. For example, you can adopt an industry standard such as NIST 800-53 or ISO 27001 to standardise your control architecture.</p><p><strong>Evaluate and Adjust Your GRC Strategy</strong> - Getting your new GRC programme up and running is not a \"set it and forget it\" kind of endeavour. After it has been implemented, you must ensure that your strategy can develop and adapt to your company\'s goals. Every group should maintain comprehensive and up-to-date records of their GRC requirements, highlighting any significant shifts in the situation, such as incorporating new tools.</p><p>This reporting can serve as a point of reference during the periodic meetings with stakeholders to ensure that the entirety of your organisation continues to follow the overall strategy. To ensure compliance management is being properly carried out, at least one annual audit must be performed. You should then prioritise the resolution of any compliance issues that have arisen.</p><p><strong>Concluding Remarks</strong> – Deploying a robust GRC framework is a tedious initiative. But If you partner with an expert partner like DivIHN Integration Inc., you do not have to worry about your ROI. To know more, please reach out to <a href=\"mailto:sgovilkar@divihn.com\">sgovilkar@divihn.com.</a></p>','','full_html'),('featured_article',0,79,260,'en',0,'<p><strong>GRC Definition: -</strong></p><p>GRC is the capability, or integrated collection of capabilities, that enables an organization to reliably achieve objectives, address uncertainty and act with integrity, including the governance, assurance and management of performance, risk, and compliance.<a href=\"https://www.oceg.org/glossary/en/\">www.grcglossary.org</a></p><p><strong>What is GRC?</strong></p><p>In February of 2002, Mr Michael Rasmussen, considered by many to be the “father” of GRC, was the one who first proposed using the abbreviation GRC. A model and a framework for GRC were initially made available in 2003 by the Open Compliance and Ethics Group (OCEG). The acronym is now recognised in its official capacity, and it signifies the three terms “Governance,” “Risk,” and “Compliance.”</p><p>Every global business engages in good governance, risk management, and compliance practices (GRC), even though many people are unaware of the value and meaning of GRC. In an official or informal setting, OCEG has stated, “GRC is not a recently developed concept”.</p><p>Let’s begin by discussing this anecdote to comprehend the rationale behind Mr Rasmussen and OCEG’s decision to merge these three words into a single acronym that has gained widespread reputation over the years.</p><p>In 2001, Fortune magazine honoured “America’s Most Innovative Company” for the sixth year in a row as one of the most successful corporations in the United States. The dot-com era had just reached its zenith; consequently, most investors and regulators were accustomed to the new normal of unusually high share prices. This, in conjunction with the lax regulatory climate of the period, allowed the CEO to be “creative,” enabling him to conceal hazardous assets and losses through a scheme that also involved the chief financial officer, other executives, and even the company’s auditor.</p><p>Enron went bankrupt in December of 2001, resulting in a loss of $74 billion for shareholders, the loss of billions of dollars in pension benefits for its employees, the collapse of the audit firm Arthur Andersen, and the loss of all employees, business partners, and other financial and societal implications as a result of people and businesses losing their income. We now know that this was the largest corporate bankruptcy that had ever occurred in the history of the financial world.</p><p>Even though Mr Rasmussen had a broad vision for GRC version 1.0, the Sarbanes-Oxley Act of 2002 (SOX), adopted as a direct response to the Enron scandal, was the focus of every organisation in the financial sector at that time. GRC 1.0 became, in essence, the recipe for managing your firm in a manner that complies with the SOX internal control criteria.</p><p><strong>Components: -</strong></p><p>To understand the term more comprehensively, let’s understand each one of its components individually:&nbsp;</p><p><strong>Governance:</strong> Governance is a term that refers to a collection of guiding principles, policies, and procedures that determine how an organization works towards achieving its objectives. When it comes to implementation, it takes a top-down approach, which involves essential stakeholders such as board members, senior management, and other high-level executives. The ability to carry out its operations honestly and openly depends on the robustness of its governance structure.</p><p>The higher-ups are given the ability to make decisions while keeping an awareness of the risks involved, engaging with the various stakeholders, and obtaining greater visibility into potential problems and incidents. The data is an indispensable component of this equation. The processes of data visualization, internal auditing, reporting, and risk assessment are all facilitated by a GRC programmed, making accessing relevant metrics easier.</p><p><strong>Risk Management: </strong>Identifying, analyzing, and taking preventative measures against possible risks is referred to as “risk management.” Cybersecurity risk, legal risk, financial risk, operational risk, contractual risk, third-party risk, and the unpredictable risk of natural disasters and crises are examples of the many types of risk that can exist. Risk managers and risk management software must work together as part of a successful risk management programme to address potential dangers before they can cause any damage.</p><p>As an alternative to implementing a separate risk management programme, you can choose to incorporate risk management processes into your daily operations. This improves risk visibility, making accessing risk data more straightforward, prioritizing threats, and implementing remediation strategies.</p><p>An organization needs to strike a balance between its risk appetite and the amount of risk it is willing to take to accomplish its business goals while reducing the amount of risk it is exposed to. You can significantly increase the rate at which threats are responded to and incidents are resolved if you have open communication channels and a well-established hierarchy. You can protect your organization on multiple fronts when you add automated controls and plans for business continuity.</p><p><strong>Compliance:</strong> You, as a business, will have to act with integrity by following the statutory government regulations that are particular to your practice area. The penalties for violating these regulations range from a reprimand that amounts to little more than a slap on the wrist to significant monetary harm.</p><p>The rules themselves are subject to ongoing revision and adjustment. You don’t want to end up in the headlines for violating some environmental regulation, do you?</p><p>You can keep tabs on many regulations, industry standards, rules, and policies while using only a few resources available if you have a compliance programme that works effectively. Establish transparent workflows to facilitate the acceleration of compliance management and conduct internal audits at regular intervals to ensure that everything is operating as it should.</p><p><strong>The Importance of GRC: -</strong><br>&nbsp;</p><p>If you have an integrated plan of action, managing risks will be much less demanding, even as those risks become more complicated and maintaining compliance becomes costlier.</p><p>The lessons learned from the pandemic caused by COVID-19 show that flexibility in risk management and compliance programmes is hugely beneficial. As a result of disruptions in supply chains, businesses are increasingly turning to third-party logistics (3PL) providers to capitalize on the explosive growth of the retail eCommerce industry.</p><p>However, increasing the number of relationships with third parties increases risk and the obligations to comply with regulations. When it comes to governance, risk, and compliance (GRC), having a framework that is clearly defined makes it possible to incorporate additional responsibilities with relatively little friction.</p><p>Greater visibility into governance, risk, and compliance programmes provides the data necessary to recognize areas of vulnerability and overcome challenges. It provides you with sufficient room to capitalize on potentially beneficial chances while minimizing the likelihood of potentially harmful incidents. Your company can expand its operations with the appropriate GRC programme, which will also assist it in managing the risks and regulations associated with its expansion.&nbsp;</p><p>&nbsp;</p><img src=\"/sites/default/files/inline-images/GRC%20framework_1.png\" data-entity-uuid=\"e34ad557-cfdb-4262-8bdc-7b53ff55ffa3\" data-entity-type=\"file\" width=\"1200\" height=\"936\"><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Renowned Frameworks:</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Framework</th><th>Area of Implementation</th><th>Description</th></tr></thead><tbody><tr><td>COSO</td><td>Enterprise Risk Management</td><td>The COSO Framework sets up internal controls for corporate processes. COSO was founded because of Enron. These controls ensure the organization operates ethically, transparently, and according to industry standards.</td></tr><tr><td>HACCP</td><td>Food Safety</td><td>HACCP is a preventive approach to food safety from biological, chemical, and physical hazards in production processes that might make the finished product dangerous. It proposes ways to minimize these risks to a safe level.</td></tr><tr><td>FAIR</td><td>IT Risk, Information Security Risk Assessment</td><td>Factor Analysis of Information Risk (FAIR) is a taxonomy of risk variables and their interactions. It’s focused chiefly on estimating the frequency and magnitude of data loss.</td></tr><tr><td>ISO 27005</td><td>IT Risk, Information Security Risk Assessment</td><td>ISO 27005 supports ISO/IEC 27001’s general concepts and aids in risk-based information security implementation.</td></tr><tr><td>ISO 31000</td><td>Risk Management</td><td>Using ISO 31000 can help organizations achieve goals, identify opportunities and hazards, and allocate and manage resources for risk treatment.</td></tr><tr><td>The Basel Committee</td><td>Operational Risk in Banking And Finance</td><td>Operational risk is embedded in all banking products, activities, processes, and systems, and effective management is a cornerstone of a bank’s risk management programme.</td></tr></tbody></table><p><strong>Critical Drivers For Adoption: -</strong></p><ul><li><strong>Risk Landscape is becoming more complex</strong> – Today’s exposure to risk entails a greater degree of complication and potential harm than it did thirty or forty years ago. It is no longer possible to combat every threat with legacy programmes or restrict fallout to a particular industry without allowing it to spread to other business divisions. The Good Governance, Risk, and Compliance (GRC) framework functions as a checks and balances system that maintains all risks within acceptable parameters.</li><li><strong>Constantly evolving Regulatory Compliance</strong> – You can build tactics to track the modifications made in real time to regulations. The vast majority of GRC solutions can fully automate this process, eliminating the requirement for additional resources to be invested.</li><li><strong>Data Privacy and Protection</strong> – On the one hand, the General Data Protection Regulation (GDPR), the Consumer Cancellation and Portability Act (CCPA), and the Personal Information Protection and Electronic Documents Act (PIPL) have mandated that businesses strengthen their cybersecurity defences. On the other hand, in contrast to adopting a standalone programme, implementing an integrated security solution has become significantly more cost-effective and efficient.</li><li><strong>Third-Party Engagements</strong> – Due to shifting legislation and disturbances in the supply chain, relationships with third-party entities and suppliers have become significantly more complicated. GRC allows you to review and manage your connections with third parties so that they are in your best interests.</li><li><strong>Big Data &amp; Analytics</strong> – Having a foundation in GRC enables you to gain additional insights from risk data, which is especially helpful in light of recent advancements in big data analytics.</li></ul><p><strong>Essential Benefits of GRC: -</strong></p><p><img src=\"/sites/default/files/inline-images/GRC%20benefits.jpg\" data-entity-uuid=\"89073301-09d3-478e-9dc0-ea6e549e7dd6\" data-entity-type=\"file\" width=\"750\" height=\"411\"></p><ul><li><strong>Visibility</strong> – Thanks to GRC, which provides a unified framework for managing governance, risk, and compliance issues, you may find all your data in a single location. This, in turn, enables you to delve deeper into risk data and acquire contextual information on fundamental weaknesses. It is not enough to be aware of what is incorrect; GRC enables you to comprehend the modifications you need to implement into the three systems to forestall future problems. Gaining visibility into your organisation’s financial and operational health helps you to make real-time adjustments and benchmark key performance indicators (KPIs).</li><li><strong>Optimising Costs &amp; Resources</strong> – The potential to save time and money is the key benefit of implementing a GRC programme in your organisation. As a result of the unification of these three processes, you will no longer be required to allocate resources distinctly for each unit. In addition, if you opt to go with GRC software, you can automate day-to-day processes. This will allow your personnel to spend more time on billable activities, ultimately increasing your revenue. You can even integrate chatbots and natural language processing (NLP) to build rules for responding to and dealing with risk situations without involving a natural person if you combine artificial intelligence (AI) and machine learning (ML).</li><li><strong>Centralised Access To Risk Data</strong> – Maintain a record of every piece of information about risks in a single database. You can view the data remotely, allowing you to respond to risk situations more quickly. For safety and privacy reasons, you may choose who can access the risk data and what devices can access it.</li><li><strong>Process Unification</strong> - is one of the more understated benefits; you won’t notice it immediately, but it will pay dividends in the long run. A uniform process, taxonomy, and terminology are all things that can be established using GRC. Standardised methods simplify training new employees, evaluating and benchmarking performance, and ensuring that the platform continues to operate smoothly even when staff members leave or are replaced. Additionally, over time, it fosters a more risk-aware culture at work, ultimately reducing the number of risk-related occurrences. This increases the organisations’ ability to withstand risks and breaks down the functional and operational walls built up.</li><li><strong>Analytics</strong> - You are provided unrestricted access to the risk data, enabling you to go deeper into the information to unearth hidden insights that might have otherwise been missed owing to a lack of oversight. Additionally, integrated advanced analytics tools and reporting capabilities assist in analysing, sharing, and utilising risk information advantageous to the organisation and its customers.</li></ul><p><strong>How Does GRC Function?</strong></p><p>The following are the underlying principles that enable a successful implementation of a GRC framework.</p><p><strong>Key Stakeholder Management</strong> - Collaboration between departments that practise governance, risk management, and regulatory compliance is necessary for GRC, which necessitates cross-functional working relationships. The following are a few examples that illustrate this point:</p><ul><li>Senior Level Executives responsible for making strategic decisions after risk assessment.</li><li>Legal professionals who help in preparing and mitigating legal implications.</li><li>Financial experts responsible for statutory compliance.</li><li>The HR function manages critical and confidential information.</li><li>IT function taking care of cybersecurity and cybersecurity resilience.</li></ul><p><strong>GRC Framework</strong> - A GRC framework is a paradigm for managing an organisation\'s governance and compliance risks. It entails the process of defining the essential policies that can push the firm toward the goals that it has set for itself. You may take a proactive approach to managing risks, make well-informed decisions, and guarantee business continuity if you adopt a GRC framework. This enables you to take advantage of the many benefits of using such a framework.</p><p>Companies put in place GRC by adopting GRC frameworks, which include essential policies that align with the organisation’s strategic objectives. When formulating company policies, organising processes, and exercising governance over the business, key stakeholders base their work on a shared understanding derived from the GRC framework. Companies can use specialised software and other resources to coordinate and keep track of the progress made using the GRC framework.</p><p><strong>GRC Maturity</strong> - An organisation’s level of GRC maturity can be defined as the degree to which it has successfully integrated governance, risk assessment, and compliance. You have reached a high degree of GRC maturity when implementing a well-planned GRC strategy yields positive cost efficiency, productivity, and the efficacy of risk mitigation. On the other hand, a low level of GRC maturity is inefficient and causes business units to continue functioning in isolation.</p><p><strong>Implementing GRC Effectively: -</strong></p><p><br>To implement a GRC solution effectively, below are the tips to ensure a successful implementation</p><p><strong>Value Creation:</strong> It is essential to understand the actual benefit of GRC implementation. The start of a successful implementation starts by identifying the already existing multiple methods across different business segments. In addition, the process enables you to determine which procedures are successful and must be maintained in constructing a unified system.</p><p>Similarly, you can get rid of any data, technologies, or assets that aren\'t needed, are duplicates and hurt value while also having the ability to make the centralised process more difficult.</p><p>From this vantage point, you will be able to prioritise the assets of your company that bring in the highest revenue, and you will be able to direct your GRC strategy toward improving these assets.</p><p><strong>Creating A GRC Roadmap:</strong> To narrow the scope of your strategy, you will need a distinct goal that summarises the primary GRC functions performed by the framework. These results have to be the product of ongoing collaboration between all stakeholders to guarantee that they are by the requirements of each division. Your targeted results can be more easily achieved if you have a solid understanding of the potential benefits that could be gained from a successful GRC framework. Some pertinent benefits of a practical GRC framework are:</p><ul><li>Cohesive approach and better alignment of every department and business goals.</li><li>Ensures effective risk mitigation and management entailing financial, legal, strategic, operational, and cyber.</li><li>Well Informed and quick decision making.</li></ul><p><strong>GAP Analysis:</strong> Once you have identified all the details about your existing GRC processes, you need to zero in on the following</p><ol><li>Maturity of the processes.</li><li>Quality of Data.</li><li>Existing Gaps.</li></ol><p>The following are next steps are to record the following</p><ol><li>Any missing or duplicate data.</li><li>Any duplication or redundant processes.</li><li>Identify the scope for automating or removing manual workflows.</li></ol><p><strong>Managing Stakeholder Expectations:</strong> Your GRC implementation strategy\'s success needs to ensure that your entire organisation is on the same page, even though this is frequently neglected. Every department is involved in an effectively planned GRC project. All significant stakeholders must be allowed to express their thoughts and concerns about your plan. Organisational alignment can be achieved as shared below:</p><ul><li>Alignment of Executive Team With Critical Factors - The first stage in securing organisational common ground is to create a detailed plan that includes essential aspects of the project, such as the timetable and the budget. Before taking additional action, you must confirm that leadership agrees with your strategy. Then it would be best if you made any necessary adjustments before telling the rest of the organisation.</li><li>Moving Down From The Top - As soon as you have received executive approval, you will need to put change management practices into effect across all other business units. These processes need to be realistic and conveyed understandably.<br>For instance, it is reasonable to anticipate that the modifications you have suggested will be met with some level of opposition. Processes and procedures that have been in a department for a long time often need to be gradually phased out before they can be eliminated.</li></ul><p>It is to be ensured that each team receives consistent and informative updates if you want a seamless transition. These updates should inform all the leading stakeholders about the essential changes that have been made and how those changes will influence their roles. Make sure that any team member can easily share any concerns, suggestions, or other significant input that may be why it is required to adjust your approach. Create a process that is open and transparent.</p><p><strong>Create A Robust GRC Approach</strong> - Putting in the necessary foundation is necessary if you want to ensure that your GRC system is practical and adaptive. Because of the ever-evolving nature of cyber threats and vulnerabilities, the ever-changing landscape of cyber threats, and the severe repercussions of data breaches, these components are of the utmost importance in information technology governance and risk management (IT GRC).</p><p>Even more, emphasis needs to be paid to guaranteeing that the GRC methods employed by financial institutions and health organisations are flexible enough to accommodate the regular changes in regulatory requirements that their respective businesses are subject to.</p><p><strong>Invest In A GRC Software Solution Of Repute</strong> - Putting in place a GRC programme from the beginning necessitates the utilisation of many different moving elements, such as the consolidation of information silos, continual upgrades, and the utilisation of manual procedures such as spreadsheets. You can direct more of your implementation efforts to higher-level activities using a GRC platform because it can simplify many of these problematic areas.</p><p>When selecting a GRC tool for your firm, just as you would with any other third-party vendor, you need to complete your due diligence to ensure that the tool complies with all compliance rules and does not put your organisation in a position where it faces extreme security risks.</p><p>The appropriate GRC technology should result in a return on investment (ROI) that can be measured in terms of money and time saved. Some critical questions that need to be addressed are</p><ul><li>Does the software solution offer ease of use?</li><li>Does it have automated workflows?</li><li>Is it customisable and scalable?</li><li>Does the solution offer detailed task management and execution?</li><li>Does it support the integration of third-party applications?</li><li>Is it cost-effective from a TCO (Total Cost of Ownership) perspective?</li></ul><p><strong>Use Industry Prevalent and Accepted Standards</strong> - The capacity to align with the requirements of the entire business is one of the essential characteristics of a GRC strategy that is both successful and efficient. A baseline should be established as a point of reference, even if every department will have its own unique set of criteria. For example, you can adopt an industry standard such as NIST 800-53 or ISO 27001 to standardise your control architecture.</p><p><strong>Evaluate and Adjust Your GRC Strategy</strong> - Getting your new GRC programme up and running is not a \"set it and forget it\" kind of endeavour. After it has been implemented, you must ensure that your strategy can develop and adapt to your company\'s goals. Every group should maintain comprehensive and up-to-date records of their GRC requirements, highlighting any significant shifts in the situation, such as incorporating new tools.</p><p>This reporting can serve as a point of reference during the periodic meetings with stakeholders to ensure that the entirety of your organisation continues to follow the overall strategy. To ensure compliance management is being properly carried out, at least one annual audit must be performed. You should then prioritise the resolution of any compliance issues that have arisen.</p><p><strong>Concluding Remarks</strong> – Deploying a robust GRC framework is a tedious initiative. But If you partner with an expert partner like DivIHN Integration Inc., you do not have to worry about your ROI. To know more, please reach out to <a href=\"mailto:sgovilkar@divihn.com\">sgovilkar@divihn.com.</a></p>','','full_html'),('featured_article',0,79,479,'en',0,'<p><strong>GRC Definition: -</strong></p><p>GRC is the capability, or integrated collection of capabilities, that enables an organization to reliably achieve objectives, address uncertainty and act with integrity, including the governance, assurance and management of performance, risk, and compliance.<a href=\"https://www.oceg.org/glossary/en/\">www.grcglossary.org</a></p><p><strong>What is GRC?</strong></p><p>In February of 2002, Mr Michael Rasmussen, considered by many to be the “father” of GRC, was the one who first proposed using the abbreviation GRC. A model and a framework for GRC were initially made available in 2003 by the Open Compliance and Ethics Group (OCEG). The acronym is now recognised in its official capacity, and it signifies the three terms “Governance,” “Risk,” and “Compliance.”</p><p>Every global business engages in good governance, risk management, and compliance practices (GRC), even though many people are unaware of the value and meaning of GRC. In an official or informal setting, OCEG has stated, “GRC is not a recently developed concept”.</p><p>Let’s begin by discussing this anecdote to comprehend the rationale behind Mr Rasmussen and OCEG’s decision to merge these three words into a single acronym that has gained widespread reputation over the years.</p><p>In 2001, Fortune magazine honoured “America’s Most Innovative Company” for the sixth year in a row as one of the most successful corporations in the United States. The dot-com era had just reached its zenith; consequently, most investors and regulators were accustomed to the new normal of unusually high share prices. This, in conjunction with the lax regulatory climate of the period, allowed the CEO to be “creative,” enabling him to conceal hazardous assets and losses through a scheme that also involved the chief financial officer, other executives, and even the company’s auditor.</p><p>Enron went bankrupt in December of 2001, resulting in a loss of $74 billion for shareholders, the loss of billions of dollars in pension benefits for its employees, the collapse of the audit firm Arthur Andersen, and the loss of all employees, business partners, and other financial and societal implications as a result of people and businesses losing their income. We now know that this was the largest corporate bankruptcy that had ever occurred in the history of the financial world.</p><p>Even though Mr Rasmussen had a broad vision for GRC version 1.0, the Sarbanes-Oxley Act of 2002 (SOX), adopted as a direct response to the Enron scandal, was the focus of every organisation in the financial sector at that time. GRC 1.0 became, in essence, the recipe for managing your firm in a manner that complies with the SOX internal control criteria.</p><p><strong>Components: -</strong></p><p>To understand the term more comprehensively, let’s understand each one of its components individually:&nbsp;</p><p><strong>Governance:</strong> Governance is a term that refers to a collection of guiding principles, policies, and procedures that determine how an organization works towards achieving its objectives. When it comes to implementation, it takes a top-down approach, which involves essential stakeholders such as board members, senior management, and other high-level executives. The ability to carry out its operations honestly and openly depends on the robustness of its governance structure.</p><p>The higher-ups are given the ability to make decisions while keeping an awareness of the risks involved, engaging with the various stakeholders, and obtaining greater visibility into potential problems and incidents. The data is an indispensable component of this equation. The processes of data visualization, internal auditing, reporting, and risk assessment are all facilitated by a GRC programmed, making accessing relevant metrics easier.</p><p><strong>Risk Management: </strong>Identifying, analyzing, and taking preventative measures against possible risks is referred to as “risk management.” Cybersecurity risk, legal risk, financial risk, operational risk, contractual risk, third-party risk, and the unpredictable risk of natural disasters and crises are examples of the many types of risk that can exist. Risk managers and risk management software must work together as part of a successful risk management programme to address potential dangers before they can cause any damage.</p><p>As an alternative to implementing a separate risk management programme, you can choose to incorporate risk management processes into your daily operations. This improves risk visibility, making accessing risk data more straightforward, prioritizing threats, and implementing remediation strategies.</p><p>An organization needs to strike a balance between its risk appetite and the amount of risk it is willing to take to accomplish its business goals while reducing the amount of risk it is exposed to. You can significantly increase the rate at which threats are responded to and incidents are resolved if you have open communication channels and a well-established hierarchy. You can protect your organization on multiple fronts when you add automated controls and plans for business continuity.</p><p><strong>Compliance:</strong> You, as a business, will have to act with integrity by following the statutory government regulations that are particular to your practice area. The penalties for violating these regulations range from a reprimand that amounts to little more than a slap on the wrist to significant monetary harm.</p><p>The rules themselves are subject to ongoing revision and adjustment. You don’t want to end up in the headlines for violating some environmental regulation, do you?</p><p>You can keep tabs on many regulations, industry standards, rules, and policies while using only a few resources available if you have a compliance programme that works effectively. Establish transparent workflows to facilitate the acceleration of compliance management and conduct internal audits at regular intervals to ensure that everything is operating as it should.</p><p><strong>The Importance of GRC: -</strong><br>&nbsp;</p><p>If you have an integrated plan of action, managing risks will be much less demanding, even as those risks become more complicated and maintaining compliance becomes costlier.</p><p>The lessons learned from the pandemic caused by COVID-19 show that flexibility in risk management and compliance programmes is hugely beneficial. As a result of disruptions in supply chains, businesses are increasingly turning to third-party logistics (3PL) providers to capitalize on the explosive growth of the retail eCommerce industry.</p><p>However, increasing the number of relationships with third parties increases risk and the obligations to comply with regulations. When it comes to governance, risk, and compliance (GRC), having a framework that is clearly defined makes it possible to incorporate additional responsibilities with relatively little friction.</p><p>Greater visibility into governance, risk, and compliance programmes provides the data necessary to recognize areas of vulnerability and overcome challenges. It provides you with sufficient room to capitalize on potentially beneficial chances while minimizing the likelihood of potentially harmful incidents. Your company can expand its operations with the appropriate GRC programme, which will also assist it in managing the risks and regulations associated with its expansion.&nbsp;</p><p>&nbsp;</p><img src=\"/sites/default/files/inline-images/GRC%20framework_1.png\" data-entity-uuid=\"e34ad557-cfdb-4262-8bdc-7b53ff55ffa3\" data-entity-type=\"file\" width=\"1200\" height=\"936\"><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Renowned Frameworks:</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Framework</th><th>Area of Implementation</th><th>Description</th></tr></thead><tbody><tr><td>COSO</td><td>Enterprise Risk Management</td><td>The COSO Framework sets up internal controls for corporate processes. COSO was founded because of Enron. These controls ensure the organization operates ethically, transparently, and according to industry standards.</td></tr><tr><td>HACCP</td><td>Food Safety</td><td>HACCP is a preventive approach to food safety from biological, chemical, and physical hazards in production processes that might make the finished product dangerous. It proposes ways to minimize these risks to a safe level.</td></tr><tr><td>FAIR</td><td>IT Risk, Information Security Risk Assessment</td><td>Factor Analysis of Information Risk (FAIR) is a taxonomy of risk variables and their interactions. It’s focused chiefly on estimating the frequency and magnitude of data loss.</td></tr><tr><td>ISO 27005</td><td>IT Risk, Information Security Risk Assessment</td><td>ISO 27005 supports ISO/IEC 27001’s general concepts and aids in risk-based information security implementation.</td></tr><tr><td>ISO 31000</td><td>Risk Management</td><td>Using ISO 31000 can help organizations achieve goals, identify opportunities and hazards, and allocate and manage resources for risk treatment.</td></tr><tr><td>The Basel Committee</td><td>Operational Risk in Banking And Finance</td><td>Operational risk is embedded in all banking products, activities, processes, and systems, and effective management is a cornerstone of a bank’s risk management programme.</td></tr></tbody></table><p><strong>Critical Drivers For Adoption: -</strong></p><ul><li><strong>Risk Landscape is becoming more complex</strong> – Today’s exposure to risk entails a greater degree of complication and potential harm than it did thirty or forty years ago. It is no longer possible to combat every threat with legacy programmes or restrict fallout to a particular industry without allowing it to spread to other business divisions. The Good Governance, Risk, and Compliance (GRC) framework functions as a checks and balances system that maintains all risks within acceptable parameters.</li><li><strong>Constantly evolving Regulatory Compliance</strong> – You can build tactics to track the modifications made in real time to regulations. The vast majority of GRC solutions can fully automate this process, eliminating the requirement for additional resources to be invested.</li><li><strong>Data Privacy and Protection</strong> – On the one hand, the General Data Protection Regulation (GDPR), the Consumer Cancellation and Portability Act (CCPA), and the Personal Information Protection and Electronic Documents Act (PIPL) have mandated that businesses strengthen their cybersecurity defences. On the other hand, in contrast to adopting a standalone programme, implementing an integrated security solution has become significantly more cost-effective and efficient.</li><li><strong>Third-Party Engagements</strong> – Due to shifting legislation and disturbances in the supply chain, relationships with third-party entities and suppliers have become significantly more complicated. GRC allows you to review and manage your connections with third parties so that they are in your best interests.</li><li><strong>Big Data &amp; Analytics</strong> – Having a foundation in GRC enables you to gain additional insights from risk data, which is especially helpful in light of recent advancements in big data analytics.</li></ul><p><strong>Essential Benefits of GRC: -</strong></p><p><img src=\"/sites/default/files/inline-images/GRC%20benefits.jpg\" data-entity-uuid=\"89073301-09d3-478e-9dc0-ea6e549e7dd6\" data-entity-type=\"file\" width=\"750\" height=\"411\"></p><ul><li><strong>Visibility</strong> – Thanks to GRC, which provides a unified framework for managing governance, risk, and compliance issues, you may find all your data in a single location. This, in turn, enables you to delve deeper into risk data and acquire contextual information on fundamental weaknesses. It is not enough to be aware of what is incorrect; GRC enables you to comprehend the modifications you need to implement into the three systems to forestall future problems. Gaining visibility into your organisation’s financial and operational health helps you to make real-time adjustments and benchmark key performance indicators (KPIs).</li><li><strong>Optimising Costs &amp; Resources</strong> – The potential to save time and money is the key benefit of implementing a GRC programme in your organisation. As a result of the unification of these three processes, you will no longer be required to allocate resources distinctly for each unit. In addition, if you opt to go with GRC software, you can automate day-to-day processes. This will allow your personnel to spend more time on billable activities, ultimately increasing your revenue. You can even integrate chatbots and natural language processing (NLP) to build rules for responding to and dealing with risk situations without involving a natural person if you combine artificial intelligence (AI) and machine learning (ML).</li><li><strong>Centralised Access To Risk Data</strong> – Maintain a record of every piece of information about risks in a single database. You can view the data remotely, allowing you to respond to risk situations more quickly. For safety and privacy reasons, you may choose who can access the risk data and what devices can access it.</li><li><strong>Process Unification</strong> - is one of the more understated benefits; you won’t notice it immediately, but it will pay dividends in the long run. A uniform process, taxonomy, and terminology are all things that can be established using GRC. Standardised methods simplify training new employees, evaluating and benchmarking performance, and ensuring that the platform continues to operate smoothly even when staff members leave or are replaced. Additionally, over time, it fosters a more risk-aware culture at work, ultimately reducing the number of risk-related occurrences. This increases the organisations’ ability to withstand risks and breaks down the functional and operational walls built up.</li><li><strong>Analytics</strong> - You are provided unrestricted access to the risk data, enabling you to go deeper into the information to unearth hidden insights that might have otherwise been missed owing to a lack of oversight. Additionally, integrated advanced analytics tools and reporting capabilities assist in analysing, sharing, and utilising risk information advantageous to the organisation and its customers.</li></ul><p><strong>How Does GRC Function?</strong></p><p>The following are the underlying principles that enable a successful implementation of a GRC framework.</p><p><strong>Key Stakeholder Management</strong> - Collaboration between departments that practise governance, risk management, and regulatory compliance is necessary for GRC, which necessitates cross-functional working relationships. The following are a few examples that illustrate this point:</p><ul><li>Senior Level Executives responsible for making strategic decisions after risk assessment.</li><li>Legal professionals who help in preparing and mitigating legal implications.</li><li>Financial experts responsible for statutory compliance.</li><li>The HR function manages critical and confidential information.</li><li>IT function taking care of cybersecurity and cybersecurity resilience.</li></ul><p><strong>GRC Framework</strong> - A GRC framework is a paradigm for managing an organisation\'s governance and compliance risks. It entails the process of defining the essential policies that can push the firm toward the goals that it has set for itself. You may take a proactive approach to managing risks, make well-informed decisions, and guarantee business continuity if you adopt a GRC framework. This enables you to take advantage of the many benefits of using such a framework.</p><p>Companies put in place GRC by adopting GRC frameworks, which include essential policies that align with the organisation’s strategic objectives. When formulating company policies, organising processes, and exercising governance over the business, key stakeholders base their work on a shared understanding derived from the GRC framework. Companies can use specialised software and other resources to coordinate and keep track of the progress made using the GRC framework.</p><p><strong>GRC Maturity</strong> - An organisation’s level of GRC maturity can be defined as the degree to which it has successfully integrated governance, risk assessment, and compliance. You have reached a high degree of GRC maturity when implementing a well-planned GRC strategy yields positive cost efficiency, productivity, and the efficacy of risk mitigation. On the other hand, a low level of GRC maturity is inefficient and causes business units to continue functioning in isolation.</p><p><strong>Implementing GRC Effectively: -</strong></p><p><br>To implement a GRC solution effectively, below are the tips to ensure a successful implementation</p><p><strong>Value Creation:</strong> It is essential to understand the actual benefit of GRC implementation. The start of a successful implementation starts by identifying the already existing multiple methods across different business segments. In addition, the process enables you to determine which procedures are successful and must be maintained in constructing a unified system.</p><p>Similarly, you can get rid of any data, technologies, or assets that aren\'t needed, are duplicates and hurt value while also having the ability to make the centralised process more difficult.</p><p>From this vantage point, you will be able to prioritise the assets of your company that bring in the highest revenue, and you will be able to direct your GRC strategy toward improving these assets.</p><p><strong>Creating A GRC Roadmap:</strong> To narrow the scope of your strategy, you will need a distinct goal that summarises the primary GRC functions performed by the framework. These results have to be the product of ongoing collaboration between all stakeholders to guarantee that they are by the requirements of each division. Your targeted results can be more easily achieved if you have a solid understanding of the potential benefits that could be gained from a successful GRC framework. Some pertinent benefits of a practical GRC framework are:</p><ul><li>Cohesive approach and better alignment of every department and business goals.</li><li>Ensures effective risk mitigation and management entailing financial, legal, strategic, operational, and cyber.</li><li>Well Informed and quick decision making.</li></ul><p><strong>GAP Analysis:</strong> Once you have identified all the details about your existing GRC processes, you need to zero in on the following</p><ol><li>Maturity of the processes.</li><li>Quality of Data.</li><li>Existing Gaps.</li></ol><p>The following are next steps are to record the following</p><ol><li>Any missing or duplicate data.</li><li>Any duplication or redundant processes.</li><li>Identify the scope for automating or removing manual workflows.</li></ol><p><strong>Managing Stakeholder Expectations:</strong> Your GRC implementation strategy\'s success needs to ensure that your entire organisation is on the same page, even though this is frequently neglected. Every department is involved in an effectively planned GRC project. All significant stakeholders must be allowed to express their thoughts and concerns about your plan. Organisational alignment can be achieved as shared below:</p><ul><li>Alignment of Executive Team With Critical Factors - The first stage in securing organisational common ground is to create a detailed plan that includes essential aspects of the project, such as the timetable and the budget. Before taking additional action, you must confirm that leadership agrees with your strategy. Then it would be best if you made any necessary adjustments before telling the rest of the organisation.</li><li>Moving Down From The Top - As soon as you have received executive approval, you will need to put change management practices into effect across all other business units. These processes need to be realistic and conveyed understandably.<br>For instance, it is reasonable to anticipate that the modifications you have suggested will be met with some level of opposition. Processes and procedures that have been in a department for a long time often need to be gradually phased out before they can be eliminated.</li></ul><p>It is to be ensured that each team receives consistent and informative updates if you want a seamless transition. These updates should inform all the leading stakeholders about the essential changes that have been made and how those changes will influence their roles. Make sure that any team member can easily share any concerns, suggestions, or other significant input that may be why it is required to adjust your approach. Create a process that is open and transparent.</p><p><strong>Create A Robust GRC Approach</strong> - Putting in the necessary foundation is necessary if you want to ensure that your GRC system is practical and adaptive. Because of the ever-evolving nature of cyber threats and vulnerabilities, the ever-changing landscape of cyber threats, and the severe repercussions of data breaches, these components are of the utmost importance in information technology governance and risk management (IT GRC).</p><p>Even more, emphasis needs to be paid to guaranteeing that the GRC methods employed by financial institutions and health organisations are flexible enough to accommodate the regular changes in regulatory requirements that their respective businesses are subject to.</p><p><strong>Invest In A GRC Software Solution Of Repute</strong> - Putting in place a GRC programme from the beginning necessitates the utilisation of many different moving elements, such as the consolidation of information silos, continual upgrades, and the utilisation of manual procedures such as spreadsheets. You can direct more of your implementation efforts to higher-level activities using a GRC platform because it can simplify many of these problematic areas.</p><p>When selecting a GRC tool for your firm, just as you would with any other third-party vendor, you need to complete your due diligence to ensure that the tool complies with all compliance rules and does not put your organisation in a position where it faces extreme security risks.</p><p>The appropriate GRC technology should result in a return on investment (ROI) that can be measured in terms of money and time saved. Some critical questions that need to be addressed are</p><ul><li>Does the software solution offer ease of use?</li><li>Does it have automated workflows?</li><li>Is it customisable and scalable?</li><li>Does the solution offer detailed task management and execution?</li><li>Does it support the integration of third-party applications?</li><li>Is it cost-effective from a TCO (Total Cost of Ownership) perspective?</li></ul><p><strong>Use Industry Prevalent and Accepted Standards</strong> - The capacity to align with the requirements of the entire business is one of the essential characteristics of a GRC strategy that is both successful and efficient. A baseline should be established as a point of reference, even if every department will have its own unique set of criteria. For example, you can adopt an industry standard such as NIST 800-53 or ISO 27001 to standardise your control architecture.</p><p><strong>Evaluate and Adjust Your GRC Strategy</strong> - Getting your new GRC programme up and running is not a \"set it and forget it\" kind of endeavour. After it has been implemented, you must ensure that your strategy can develop and adapt to your company\'s goals. Every group should maintain comprehensive and up-to-date records of their GRC requirements, highlighting any significant shifts in the situation, such as incorporating new tools.</p><p>This reporting can serve as a point of reference during the periodic meetings with stakeholders to ensure that the entirety of your organisation continues to follow the overall strategy. To ensure compliance management is being properly carried out, at least one annual audit must be performed. You should then prioritise the resolution of any compliance issues that have arisen.</p><p><strong>Concluding Remarks</strong> – Deploying a robust GRC framework is a tedious initiative. But If you partner with an expert partner like DivIHN Integration Inc., you do not have to worry about your ROI. To know more, please reach out to <a href=\"mailto:sgovilkar@divihn.com\">sgovilkar@divihn.com.</a></p>','','full_html'),('featured_article',0,79,559,'en',0,'<p><strong>GRC Definition: -</strong></p><p>GRC is the capability, or integrated collection of capabilities, that enables an organization to reliably achieve objectives, address uncertainty and act with integrity, including the governance, assurance and management of performance, risk, and compliance.<a href=\"https://www.oceg.org/glossary/en/\">www.grcglossary.org</a></p><p><strong>What is GRC?</strong></p><p>In February of 2002, Mr Michael Rasmussen, considered by many to be the “father” of GRC, was the one who first proposed using the abbreviation GRC. A model and a framework for GRC were initially made available in 2003 by the Open Compliance and Ethics Group (OCEG). The acronym is now recognised in its official capacity, and it signifies the three terms “Governance,” “Risk,” and “Compliance.”</p><p>Every global business engages in good governance, risk management, and compliance practices (GRC), even though many people are unaware of the value and meaning of GRC. In an official or informal setting, OCEG has stated, “GRC is not a recently developed concept”.</p><p>Let’s begin by discussing this anecdote to comprehend the rationale behind Mr Rasmussen and OCEG’s decision to merge these three words into a single acronym that has gained widespread reputation over the years.</p><p>In 2001, Fortune magazine honoured “America’s Most Innovative Company” for the sixth year in a row as one of the most successful corporations in the United States. The dot-com era had just reached its zenith; consequently, most investors and regulators were accustomed to the new normal of unusually high share prices. This, in conjunction with the lax regulatory climate of the period, allowed the CEO to be “creative,” enabling him to conceal hazardous assets and losses through a scheme that also involved the chief financial officer, other executives, and even the company’s auditor.</p><p>Enron went bankrupt in December of 2001, resulting in a loss of $74 billion for shareholders, the loss of billions of dollars in pension benefits for its employees, the collapse of the audit firm Arthur Andersen, and the loss of all employees, business partners, and other financial and societal implications as a result of people and businesses losing their income. We now know that this was the largest corporate bankruptcy that had ever occurred in the history of the financial world.</p><p>Even though Mr Rasmussen had a broad vision for GRC version 1.0, the Sarbanes-Oxley Act of 2002 (SOX), adopted as a direct response to the Enron scandal, was the focus of every organisation in the financial sector at that time. GRC 1.0 became, in essence, the recipe for managing your firm in a manner that complies with the SOX internal control criteria.</p><p><strong>Components: -</strong></p><p>To understand the term more comprehensively, let’s understand each one of its components individually:&nbsp;</p><p><strong>Governance:</strong> Governance is a term that refers to a collection of guiding principles, policies, and procedures that determine how an organization works towards achieving its objectives. When it comes to implementation, it takes a top-down approach, which involves essential stakeholders such as board members, senior management, and other high-level executives. The ability to carry out its operations honestly and openly depends on the robustness of its governance structure.</p><p>The higher-ups are given the ability to make decisions while keeping an awareness of the risks involved, engaging with the various stakeholders, and obtaining greater visibility into potential problems and incidents. The data is an indispensable component of this equation. The processes of data visualization, internal auditing, reporting, and risk assessment are all facilitated by a GRC programmed, making accessing relevant metrics easier.</p><p><strong>Risk Management: </strong>Identifying, analyzing, and taking preventative measures against possible risks is referred to as “risk management.” Cybersecurity risk, legal risk, financial risk, operational risk, contractual risk, third-party risk, and the unpredictable risk of natural disasters and crises are examples of the many types of risk that can exist. Risk managers and risk management software must work together as part of a successful risk management programme to address potential dangers before they can cause any damage.</p><p>As an alternative to implementing a separate risk management programme, you can choose to incorporate risk management processes into your daily operations. This improves risk visibility, making accessing risk data more straightforward, prioritizing threats, and implementing remediation strategies.</p><p>An organization needs to strike a balance between its risk appetite and the amount of risk it is willing to take to accomplish its business goals while reducing the amount of risk it is exposed to. You can significantly increase the rate at which threats are responded to and incidents are resolved if you have open communication channels and a well-established hierarchy. You can protect your organization on multiple fronts when you add automated controls and plans for business continuity.</p><p><strong>Compliance:</strong> You, as a business, will have to act with integrity by following the statutory government regulations that are particular to your practice area. The penalties for violating these regulations range from a reprimand that amounts to little more than a slap on the wrist to significant monetary harm.</p><p>The rules themselves are subject to ongoing revision and adjustment. You don’t want to end up in the headlines for violating some environmental regulation, do you?</p><p>You can keep tabs on many regulations, industry standards, rules, and policies while using only a few resources available if you have a compliance programme that works effectively. Establish transparent workflows to facilitate the acceleration of compliance management and conduct internal audits at regular intervals to ensure that everything is operating as it should.</p><p><strong>The Importance of GRC: -</strong><br>&nbsp;</p><p>If you have an integrated plan of action, managing risks will be much less demanding, even as those risks become more complicated and maintaining compliance becomes costlier.</p><p>The lessons learned from the pandemic caused by COVID-19 show that flexibility in risk management and compliance programmes is hugely beneficial. As a result of disruptions in supply chains, businesses are increasingly turning to third-party logistics (3PL) providers to capitalize on the explosive growth of the retail eCommerce industry.</p><p>However, increasing the number of relationships with third parties increases risk and the obligations to comply with regulations. When it comes to governance, risk, and compliance (GRC), having a framework that is clearly defined makes it possible to incorporate additional responsibilities with relatively little friction.</p><p>Greater visibility into governance, risk, and compliance programmes provides the data necessary to recognize areas of vulnerability and overcome challenges. It provides you with sufficient room to capitalize on potentially beneficial chances while minimizing the likelihood of potentially harmful incidents. Your company can expand its operations with the appropriate GRC programme, which will also assist it in managing the risks and regulations associated with its expansion.&nbsp;</p><p>&nbsp;</p><img src=\"/sites/default/files/inline-images/GRC%20framework_1.png\" data-entity-uuid=\"e34ad557-cfdb-4262-8bdc-7b53ff55ffa3\" data-entity-type=\"file\" width=\"1200\" height=\"936\"><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Renowned Frameworks:</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Framework</th><th>Area of Implementation</th><th>Description</th></tr></thead><tbody><tr><td>COSO</td><td>Enterprise Risk Management</td><td>The COSO Framework sets up internal controls for corporate processes. COSO was founded because of Enron. These controls ensure the organization operates ethically, transparently, and according to industry standards.</td></tr><tr><td>HACCP</td><td>Food Safety</td><td>HACCP is a preventive approach to food safety from biological, chemical, and physical hazards in production processes that might make the finished product dangerous. It proposes ways to minimize these risks to a safe level.</td></tr><tr><td>FAIR</td><td>IT Risk, Information Security Risk Assessment</td><td>Factor Analysis of Information Risk (FAIR) is a taxonomy of risk variables and their interactions. It’s focused chiefly on estimating the frequency and magnitude of data loss.</td></tr><tr><td>ISO 27005</td><td>IT Risk, Information Security Risk Assessment</td><td>ISO 27005 supports ISO/IEC 27001’s general concepts and aids in risk-based information security implementation.</td></tr><tr><td>ISO 31000</td><td>Risk Management</td><td>Using ISO 31000 can help organizations achieve goals, identify opportunities and hazards, and allocate and manage resources for risk treatment.</td></tr><tr><td>The Basel Committee</td><td>Operational Risk in Banking And Finance</td><td>Operational risk is embedded in all banking products, activities, processes, and systems, and effective management is a cornerstone of a bank’s risk management programme.</td></tr></tbody></table><p><strong>Critical Drivers For Adoption: -</strong></p><ul><li><strong>Risk Landscape is becoming more complex</strong> – Today’s exposure to risk entails a greater degree of complication and potential harm than it did thirty or forty years ago. It is no longer possible to combat every threat with legacy programmes or restrict fallout to a particular industry without allowing it to spread to other business divisions. The Good Governance, Risk, and Compliance (GRC) framework functions as a checks and balances system that maintains all risks within acceptable parameters.</li><li><strong>Constantly evolving Regulatory Compliance</strong> – You can build tactics to track the modifications made in real time to regulations. The vast majority of GRC solutions can fully automate this process, eliminating the requirement for additional resources to be invested.</li><li><strong>Data Privacy and Protection</strong> – On the one hand, the General Data Protection Regulation (GDPR), the Consumer Cancellation and Portability Act (CCPA), and the Personal Information Protection and Electronic Documents Act (PIPL) have mandated that businesses strengthen their cybersecurity defences. On the other hand, in contrast to adopting a standalone programme, implementing an integrated security solution has become significantly more cost-effective and efficient.</li><li><strong>Third-Party Engagements</strong> – Due to shifting legislation and disturbances in the supply chain, relationships with third-party entities and suppliers have become significantly more complicated. GRC allows you to review and manage your connections with third parties so that they are in your best interests.</li><li><strong>Big Data &amp; Analytics</strong> – Having a foundation in GRC enables you to gain additional insights from risk data, which is especially helpful in light of recent advancements in big data analytics.</li></ul><p><strong>Essential Benefits of GRC: -</strong></p><p><img src=\"/sites/default/files/inline-images/GRC%20benefits.jpg\" data-entity-uuid=\"89073301-09d3-478e-9dc0-ea6e549e7dd6\" data-entity-type=\"file\" width=\"750\" height=\"411\"></p><ul><li><strong>Visibility</strong> – Thanks to GRC, which provides a unified framework for managing governance, risk, and compliance issues, you may find all your data in a single location. This, in turn, enables you to delve deeper into risk data and acquire contextual information on fundamental weaknesses. It is not enough to be aware of what is incorrect; GRC enables you to comprehend the modifications you need to implement into the three systems to forestall future problems. Gaining visibility into your organisation’s financial and operational health helps you to make real-time adjustments and benchmark key performance indicators (KPIs).</li><li><strong>Optimising Costs &amp; Resources</strong> – The potential to save time and money is the key benefit of implementing a GRC programme in your organisation. As a result of the unification of these three processes, you will no longer be required to allocate resources distinctly for each unit. In addition, if you opt to go with GRC software, you can automate day-to-day processes. This will allow your personnel to spend more time on billable activities, ultimately increasing your revenue. You can even integrate chatbots and natural language processing (NLP) to build rules for responding to and dealing with risk situations without involving a natural person if you combine artificial intelligence (AI) and machine learning (ML).</li><li><strong>Centralised Access To Risk Data</strong> – Maintain a record of every piece of information about risks in a single database. You can view the data remotely, allowing you to respond to risk situations more quickly. For safety and privacy reasons, you may choose who can access the risk data and what devices can access it.</li><li><strong>Process Unification</strong> - is one of the more understated benefits; you won’t notice it immediately, but it will pay dividends in the long run. A uniform process, taxonomy, and terminology are all things that can be established using GRC. Standardised methods simplify training new employees, evaluating and benchmarking performance, and ensuring that the platform continues to operate smoothly even when staff members leave or are replaced. Additionally, over time, it fosters a more risk-aware culture at work, ultimately reducing the number of risk-related occurrences. This increases the organisations’ ability to withstand risks and breaks down the functional and operational walls built up.</li><li><strong>Analytics</strong> - You are provided unrestricted access to the risk data, enabling you to go deeper into the information to unearth hidden insights that might have otherwise been missed owing to a lack of oversight. Additionally, integrated advanced analytics tools and reporting capabilities assist in analysing, sharing, and utilising risk information advantageous to the organisation and its customers.</li></ul><p><strong>How Does GRC Function?</strong></p><p>The following are the underlying principles that enable a successful implementation of a GRC framework.</p><p><strong>Key Stakeholder Management</strong> - Collaboration between departments that practise governance, risk management, and regulatory compliance is necessary for GRC, which necessitates cross-functional working relationships. The following are a few examples that illustrate this point:</p><ul><li>Senior Level Executives responsible for making strategic decisions after risk assessment.</li><li>Legal professionals who help in preparing and mitigating legal implications.</li><li>Financial experts responsible for statutory compliance.</li><li>The HR function manages critical and confidential information.</li><li>IT function taking care of cybersecurity and cybersecurity resilience.</li></ul><p><strong>GRC Framework</strong> - A GRC framework is a paradigm for managing an organisation\'s governance and compliance risks. It entails the process of defining the essential policies that can push the firm toward the goals that it has set for itself. You may take a proactive approach to managing risks, make well-informed decisions, and guarantee business continuity if you adopt a GRC framework. This enables you to take advantage of the many benefits of using such a framework.</p><p>Companies put in place GRC by adopting GRC frameworks, which include essential policies that align with the organisation’s strategic objectives. When formulating company policies, organising processes, and exercising governance over the business, key stakeholders base their work on a shared understanding derived from the GRC framework. Companies can use specialised software and other resources to coordinate and keep track of the progress made using the GRC framework.</p><p><strong>GRC Maturity</strong> - An organisation’s level of GRC maturity can be defined as the degree to which it has successfully integrated governance, risk assessment, and compliance. You have reached a high degree of GRC maturity when implementing a well-planned GRC strategy yields positive cost efficiency, productivity, and the efficacy of risk mitigation. On the other hand, a low level of GRC maturity is inefficient and causes business units to continue functioning in isolation.</p><p><strong>Implementing GRC Effectively: -</strong></p><p><br>To implement a GRC solution effectively, below are the tips to ensure a successful implementation</p><p><strong>Value Creation:</strong> It is essential to understand the actual benefit of GRC implementation. The start of a successful implementation starts by identifying the already existing multiple methods across different business segments. In addition, the process enables you to determine which procedures are successful and must be maintained in constructing a unified system.</p><p>Similarly, you can get rid of any data, technologies, or assets that aren\'t needed, are duplicates and hurt value while also having the ability to make the centralised process more difficult.</p><p>From this vantage point, you will be able to prioritise the assets of your company that bring in the highest revenue, and you will be able to direct your GRC strategy toward improving these assets.</p><p><strong>Creating A GRC Roadmap:</strong> To narrow the scope of your strategy, you will need a distinct goal that summarises the primary GRC functions performed by the framework. These results have to be the product of ongoing collaboration between all stakeholders to guarantee that they are by the requirements of each division. Your targeted results can be more easily achieved if you have a solid understanding of the potential benefits that could be gained from a successful GRC framework. Some pertinent benefits of a practical GRC framework are:</p><ul><li>Cohesive approach and better alignment of every department and business goals.</li><li>Ensures effective risk mitigation and management entailing financial, legal, strategic, operational, and cyber.</li><li>Well Informed and quick decision making.</li></ul><p><strong>GAP Analysis:</strong> Once you have identified all the details about your existing GRC processes, you need to zero in on the following</p><ol><li>Maturity of the processes.</li><li>Quality of Data.</li><li>Existing Gaps.</li></ol><p>The following are next steps are to record the following</p><ol><li>Any missing or duplicate data.</li><li>Any duplication or redundant processes.</li><li>Identify the scope for automating or removing manual workflows.</li></ol><p><strong>Managing Stakeholder Expectations:</strong> Your GRC implementation strategy\'s success needs to ensure that your entire organisation is on the same page, even though this is frequently neglected. Every department is involved in an effectively planned GRC project. All significant stakeholders must be allowed to express their thoughts and concerns about your plan. Organisational alignment can be achieved as shared below:</p><ul><li>Alignment of Executive Team With Critical Factors - The first stage in securing organisational common ground is to create a detailed plan that includes essential aspects of the project, such as the timetable and the budget. Before taking additional action, you must confirm that leadership agrees with your strategy. Then it would be best if you made any necessary adjustments before telling the rest of the organisation.</li><li>Moving Down From The Top - As soon as you have received executive approval, you will need to put change management practices into effect across all other business units. These processes need to be realistic and conveyed understandably.<br>For instance, it is reasonable to anticipate that the modifications you have suggested will be met with some level of opposition. Processes and procedures that have been in a department for a long time often need to be gradually phased out before they can be eliminated.</li></ul><p>It is to be ensured that each team receives consistent and informative updates if you want a seamless transition. These updates should inform all the leading stakeholders about the essential changes that have been made and how those changes will influence their roles. Make sure that any team member can easily share any concerns, suggestions, or other significant input that may be why it is required to adjust your approach. Create a process that is open and transparent.</p><p><strong>Create A Robust GRC Approach</strong> - Putting in the necessary foundation is necessary if you want to ensure that your GRC system is practical and adaptive. Because of the ever-evolving nature of cyber threats and vulnerabilities, the ever-changing landscape of cyber threats, and the severe repercussions of data breaches, these components are of the utmost importance in information technology governance and risk management (IT GRC).</p><p>Even more, emphasis needs to be paid to guaranteeing that the GRC methods employed by financial institutions and health organisations are flexible enough to accommodate the regular changes in regulatory requirements that their respective businesses are subject to.</p><p><strong>Invest In A GRC Software Solution Of Repute</strong> - Putting in place a GRC programme from the beginning necessitates the utilisation of many different moving elements, such as the consolidation of information silos, continual upgrades, and the utilisation of manual procedures such as spreadsheets. You can direct more of your implementation efforts to higher-level activities using a GRC platform because it can simplify many of these problematic areas.</p><p>When selecting a GRC tool for your firm, just as you would with any other third-party vendor, you need to complete your due diligence to ensure that the tool complies with all compliance rules and does not put your organisation in a position where it faces extreme security risks.</p><p>The appropriate GRC technology should result in a return on investment (ROI) that can be measured in terms of money and time saved. Some critical questions that need to be addressed are</p><ul><li>Does the software solution offer ease of use?</li><li>Does it have automated workflows?</li><li>Is it customisable and scalable?</li><li>Does the solution offer detailed task management and execution?</li><li>Does it support the integration of third-party applications?</li><li>Is it cost-effective from a TCO (Total Cost of Ownership) perspective?</li></ul><p><strong>Use Industry Prevalent and Accepted Standards</strong> - The capacity to align with the requirements of the entire business is one of the essential characteristics of a GRC strategy that is both successful and efficient. A baseline should be established as a point of reference, even if every department will have its own unique set of criteria. For example, you can adopt an industry standard such as NIST 800-53 or ISO 27001 to standardise your control architecture.</p><p><strong>Evaluate and Adjust Your GRC Strategy</strong> - Getting your new GRC programme up and running is not a \"set it and forget it\" kind of endeavour. After it has been implemented, you must ensure that your strategy can develop and adapt to your company\'s goals. Every group should maintain comprehensive and up-to-date records of their GRC requirements, highlighting any significant shifts in the situation, such as incorporating new tools.</p><p>This reporting can serve as a point of reference during the periodic meetings with stakeholders to ensure that the entirety of your organisation continues to follow the overall strategy. To ensure compliance management is being properly carried out, at least one annual audit must be performed. You should then prioritise the resolution of any compliance issues that have arisen.</p><p><strong>Concluding Remarks</strong> – Deploying a robust GRC framework is a tedious initiative. But If you partner with an expert partner like DivIHN Integration Inc., you do not have to worry about your ROI. To know more, please reach out to <a href=\"mailto:sgovilkar@divihn.com\">sgovilkar@divihn.com.</a></p>','','full_html'),('featured_article',0,79,634,'en',0,'<p><strong>GRC Definition: -</strong></p><p>GRC is the capability, or integrated collection of capabilities, that enables an organization to reliably achieve objectives, address uncertainty and act with integrity, including the governance, assurance and management of performance, risk, and compliance.<a href=\"https://www.oceg.org/glossary/en/\">www.grcglossary.org</a></p><p><strong>What is GRC?</strong></p><p>In February of 2002, Mr Michael Rasmussen, considered by many to be the “father” of GRC, was the one who first proposed using the abbreviation GRC. A model and a framework for GRC were initially made available in 2003 by the Open Compliance and Ethics Group (OCEG). The acronym is now recognised in its official capacity, and it signifies the three terms “Governance,” “Risk,” and “Compliance.”</p><p>Every global business engages in good governance, risk management, and compliance practices (GRC), even though many people are unaware of the value and meaning of GRC. In an official or informal setting, OCEG has stated, “GRC is not a recently developed concept”.</p><p>Let’s begin by discussing this anecdote to comprehend the rationale behind Mr Rasmussen and OCEG’s decision to merge these three words into a single acronym that has gained widespread reputation over the years.</p><p>In 2001, Fortune magazine honoured “America’s Most Innovative Company” for the sixth year in a row as one of the most successful corporations in the United States. The dot-com era had just reached its zenith; consequently, most investors and regulators were accustomed to the new normal of unusually high share prices. This, in conjunction with the lax regulatory climate of the period, allowed the CEO to be “creative,” enabling him to conceal hazardous assets and losses through a scheme that also involved the chief financial officer, other executives, and even the company’s auditor.</p><p>Enron went bankrupt in December of 2001, resulting in a loss of $74 billion for shareholders, the loss of billions of dollars in pension benefits for its employees, the collapse of the audit firm Arthur Andersen, and the loss of all employees, business partners, and other financial and societal implications as a result of people and businesses losing their income. We now know that this was the largest corporate bankruptcy that had ever occurred in the history of the financial world.</p><p>Even though Mr Rasmussen had a broad vision for GRC version 1.0, the Sarbanes-Oxley Act of 2002 (SOX), adopted as a direct response to the Enron scandal, was the focus of every organisation in the financial sector at that time. GRC 1.0 became, in essence, the recipe for managing your firm in a manner that complies with the SOX internal control criteria.</p><p><strong>Components: -</strong></p><p>To understand the term more comprehensively, let’s understand each one of its components individually:&nbsp;</p><p><strong>Governance:</strong> Governance is a term that refers to a collection of guiding principles, policies, and procedures that determine how an organization works towards achieving its objectives. When it comes to implementation, it takes a top-down approach, which involves essential stakeholders such as board members, senior management, and other high-level executives. The ability to carry out its operations honestly and openly depends on the robustness of its governance structure.</p><p>The higher-ups are given the ability to make decisions while keeping an awareness of the risks involved, engaging with the various stakeholders, and obtaining greater visibility into potential problems and incidents. The data is an indispensable component of this equation. The processes of data visualization, internal auditing, reporting, and risk assessment are all facilitated by a GRC programmed, making accessing relevant metrics easier.</p><p><strong>Risk Management: </strong>Identifying, analyzing, and taking preventative measures against possible risks is referred to as “risk management.” Cybersecurity risk, legal risk, financial risk, operational risk, contractual risk, third-party risk, and the unpredictable risk of natural disasters and crises are examples of the many types of risk that can exist. Risk managers and risk management software must work together as part of a successful risk management programme to address potential dangers before they can cause any damage.</p><p>As an alternative to implementing a separate risk management programme, you can choose to incorporate risk management processes into your daily operations. This improves risk visibility, making accessing risk data more straightforward, prioritizing threats, and implementing remediation strategies.</p><p>An organization needs to strike a balance between its risk appetite and the amount of risk it is willing to take to accomplish its business goals while reducing the amount of risk it is exposed to. You can significantly increase the rate at which threats are responded to and incidents are resolved if you have open communication channels and a well-established hierarchy. You can protect your organization on multiple fronts when you add automated controls and plans for business continuity.</p><p><strong>Compliance:</strong> You, as a business, will have to act with integrity by following the statutory government regulations that are particular to your practice area. The penalties for violating these regulations range from a reprimand that amounts to little more than a slap on the wrist to significant monetary harm.</p><p>The rules themselves are subject to ongoing revision and adjustment. You don’t want to end up in the headlines for violating some environmental regulation, do you?</p><p>You can keep tabs on many regulations, industry standards, rules, and policies while using only a few resources available if you have a compliance programme that works effectively. Establish transparent workflows to facilitate the acceleration of compliance management and conduct internal audits at regular intervals to ensure that everything is operating as it should.</p><p><strong>The Importance of GRC: -</strong><br>&nbsp;</p><p>If you have an integrated plan of action, managing risks will be much less demanding, even as those risks become more complicated and maintaining compliance becomes costlier.</p><p>The lessons learned from the pandemic caused by COVID-19 show that flexibility in risk management and compliance programmes is hugely beneficial. As a result of disruptions in supply chains, businesses are increasingly turning to third-party logistics (3PL) providers to capitalize on the explosive growth of the retail eCommerce industry.</p><p>However, increasing the number of relationships with third parties increases risk and the obligations to comply with regulations. When it comes to governance, risk, and compliance (GRC), having a framework that is clearly defined makes it possible to incorporate additional responsibilities with relatively little friction.</p><p>Greater visibility into governance, risk, and compliance programmes provides the data necessary to recognize areas of vulnerability and overcome challenges. It provides you with sufficient room to capitalize on potentially beneficial chances while minimizing the likelihood of potentially harmful incidents. Your company can expand its operations with the appropriate GRC programme, which will also assist it in managing the risks and regulations associated with its expansion.&nbsp;</p><p>&nbsp;</p><img src=\"/sites/default/files/inline-images/GRC%20framework_1.png\" data-entity-uuid=\"e34ad557-cfdb-4262-8bdc-7b53ff55ffa3\" data-entity-type=\"file\" width=\"1200\" height=\"936\"><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p>&nbsp;</p><p><strong>Renowned Frameworks:</strong></p><table border=\"1\" cellspacing=\"0\" cellpadding=\"8\"><thead><tr><th>Framework</th><th>Area of Implementation</th><th>Description</th></tr></thead><tbody><tr><td>COSO</td><td>Enterprise Risk Management</td><td>The COSO Framework sets up internal controls for corporate processes. COSO was founded because of Enron. These controls ensure the organization operates ethically, transparently, and according to industry standards.</td></tr><tr><td>HACCP</td><td>Food Safety</td><td>HACCP is a preventive approach to food safety from biological, chemical, and physical hazards in production processes that might make the finished product dangerous. It proposes ways to minimize these risks to a safe level.</td></tr><tr><td>FAIR</td><td>IT Risk, Information Security Risk Assessment</td><td>Factor Analysis of Information Risk (FAIR) is a taxonomy of risk variables and their interactions. It’s focused chiefly on estimating the frequency and magnitude of data loss.</td></tr><tr><td>ISO 27005</td><td>IT Risk, Information Security Risk Assessment</td><td>ISO 27005 supports ISO/IEC 27001’s general concepts and aids in risk-based information security implementation.</td></tr><tr><td>ISO 31000</td><td>Risk Management</td><td>Using ISO 31000 can help organizations achieve goals, identify opportunities and hazards, and allocate and manage resources for risk treatment.</td></tr><tr><td>The Basel Committee</td><td>Operational Risk in Banking And Finance</td><td>Operational risk is embedded in all banking products, activities, processes, and systems, and effective management is a cornerstone of a bank’s risk management programme.</td></tr></tbody></table><p><strong>Critical Drivers For Adoption: -</strong></p><ul><li><strong>Risk Landscape is becoming more complex</strong> – Today’s exposure to risk entails a greater degree of complication and potential harm than it did thirty or forty years ago. It is no longer possible to combat every threat with legacy programmes or restrict fallout to a particular industry without allowing it to spread to other business divisions. The Good Governance, Risk, and Compliance (GRC) framework functions as a checks and balances system that maintains all risks within acceptable parameters.</li><li><strong>Constantly evolving Regulatory Compliance</strong> – You can build tactics to track the modifications made in real time to regulations. The vast majority of GRC solutions can fully automate this process, eliminating the requirement for additional resources to be invested.</li><li><strong>Data Privacy and Protection</strong> – On the one hand, the General Data Protection Regulation (GDPR), the Consumer Cancellation and Portability Act (CCPA), and the Personal Information Protection and Electronic Documents Act (PIPL) have mandated that businesses strengthen their cybersecurity defences. On the other hand, in contrast to adopting a standalone programme, implementing an integrated security solution has become significantly more cost-effective and efficient.</li><li><strong>Third-Party Engagements</strong> – Due to shifting legislation and disturbances in the supply chain, relationships with third-party entities and suppliers have become significantly more complicated. GRC allows you to review and manage your connections with third parties so that they are in your best interests.</li><li><strong>Big Data &amp; Analytics</strong> – Having a foundation in GRC enables you to gain additional insights from risk data, which is especially helpful in light of recent advancements in big data analytics.</li></ul><p><strong>Essential Benefits of GRC: -</strong></p><p><img src=\"/sites/default/files/inline-images/GRC%20benefits.jpg\" data-entity-uuid=\"89073301-09d3-478e-9dc0-ea6e549e7dd6\" data-entity-type=\"file\" width=\"750\" height=\"411\"></p><ul><li><strong>Visibility</strong> – Thanks to GRC, which provides a unified framework for managing governance, risk, and compliance issues, you may find all your data in a single location. This, in turn, enables you to delve deeper into risk data and acquire contextual information on fundamental weaknesses. It is not enough to be aware of what is incorrect; GRC enables you to comprehend the modifications you need to implement into the three systems to forestall future problems. Gaining visibility into your organisation’s financial and operational health helps you to make real-time adjustments and benchmark key performance indicators (KPIs).</li><li><strong>Optimising Costs &amp; Resources</strong> – The potential to save time and money is the key benefit of implementing a GRC programme in your organisation. As a result of the unification of these three processes, you will no longer be required to allocate resources distinctly for each unit. In addition, if you opt to go with GRC software, you can automate day-to-day processes. This will allow your personnel to spend more time on billable activities, ultimately increasing your revenue. You can even integrate chatbots and natural language processing (NLP) to build rules for responding to and dealing with risk situations without involving a natural person if you combine artificial intelligence (AI) and machine learning (ML).</li><li><strong>Centralised Access To Risk Data</strong> – Maintain a record of every piece of information about risks in a single database. You can view the data remotely, allowing you to respond to risk situations more quickly. For safety and privacy reasons, you may choose who can access the risk data and what devices can access it.</li><li><strong>Process Unification</strong> - is one of the more understated benefits; you won’t notice it immediately, but it will pay dividends in the long run. A uniform process, taxonomy, and terminology are all things that can be established using GRC. Standardised methods simplify training new employees, evaluating and benchmarking performance, and ensuring that the platform continues to operate smoothly even when staff members leave or are replaced. Additionally, over time, it fosters a more risk-aware culture at work, ultimately reducing the number of risk-related occurrences. This increases the organisations’ ability to withstand risks and breaks down the functional and operational walls built up.</li><li><strong>Analytics</strong> - You are provided unrestricted access to the risk data, enabling you to go deeper into the information to unearth hidden insights that might have otherwise been missed owing to a lack of oversight. Additionally, integrated advanced analytics tools and reporting capabilities assist in analysing, sharing, and utilising risk information advantageous to the organisation and its customers.</li></ul><p><strong>How Does GRC Function?</strong></p><p>The following are the underlying principles that enable a successful implementation of a GRC framework.</p><p><strong>Key Stakeholder Management</strong> - Collaboration between departments that practise governance, risk management, and regulatory compliance is necessary for GRC, which necessitates cross-functional working relationships. The following are a few examples that illustrate this point:</p><ul><li>Senior Level Executives responsible for making strategic decisions after risk assessment.</li><li>Legal professionals who help in preparing and mitigating legal implications.</li><li>Financial experts responsible for statutory compliance.</li><li>The HR function manages critical and confidential information.</li><li>IT function taking care of cybersecurity and cybersecurity resilience.</li></ul><p><strong>GRC Framework</strong> - A GRC framework is a paradigm for managing an organisation\'s governance and compliance risks. It entails the process of defining the essential policies that can push the firm toward the goals that it has set for itself. You may take a proactive approach to managing risks, make well-informed decisions, and guarantee business continuity if you adopt a GRC framework. This enables you to take advantage of the many benefits of using such a framework.</p><p>Companies put in place GRC by adopting GRC frameworks, which include essential policies that align with the organisation’s strategic objectives. When formulating company policies, organising processes, and exercising governance over the business, key stakeholders base their work on a shared understanding derived from the GRC framework. Companies can use specialised software and other resources to coordinate and keep track of the progress made using the GRC framework.</p><p><strong>GRC Maturity</strong> - An organisation’s level of GRC maturity can be defined as the degree to which it has successfully integrated governance, risk assessment, and compliance. You have reached a high degree of GRC maturity when implementing a well-planned GRC strategy yields positive cost efficiency, productivity, and the efficacy of risk mitigation. On the other hand, a low level of GRC maturity is inefficient and causes business units to continue functioning in isolation.</p><p><strong>Implementing GRC Effectively: -</strong></p><p><br>To implement a GRC solution effectively, below are the tips to ensure a successful implementation</p><p><strong>Value Creation:</strong> It is essential to understand the actual benefit of GRC implementation. The start of a successful implementation starts by identifying the already existing multiple methods across different business segments. In addition, the process enables you to determine which procedures are successful and must be maintained in constructing a unified system.</p><p>Similarly, you can get rid of any data, technologies, or assets that aren\'t needed, are duplicates and hurt value while also having the ability to make the centralised process more difficult.</p><p>From this vantage point, you will be able to prioritise the assets of your company that bring in the highest revenue, and you will be able to direct your GRC strategy toward improving these assets.</p><p><strong>Creating A GRC Roadmap:</strong> To narrow the scope of your strategy, you will need a distinct goal that summarises the primary GRC functions performed by the framework. These results have to be the product of ongoing collaboration between all stakeholders to guarantee that they are by the requirements of each division. Your targeted results can be more easily achieved if you have a solid understanding of the potential benefits that could be gained from a successful GRC framework. Some pertinent benefits of a practical GRC framework are:</p><ul><li>Cohesive approach and better alignment of every department and business goals.</li><li>Ensures effective risk mitigation and management entailing financial, legal, strategic, operational, and cyber.</li><li>Well Informed and quick decision making.</li></ul><p><strong>GAP Analysis:</strong> Once you have identified all the details about your existing GRC processes, you need to zero in on the following</p><ol><li>Maturity of the processes.</li><li>Quality of Data.</li><li>Existing Gaps.</li></ol><p>The following are next steps are to record the following</p><ol><li>Any missing or duplicate data.</li><li>Any duplication or redundant processes.</li><li>Identify the scope for automating or removing manual workflows.</li></ol><p><strong>Managing Stakeholder Expectations:</strong> Your GRC implementation strategy\'s success needs to ensure that your entire organisation is on the same page, even though this is frequently neglected. Every department is involved in an effectively planned GRC project. All significant stakeholders must be allowed to express their thoughts and concerns about your plan. Organisational alignment can be achieved as shared below:</p><ul><li>Alignment of Executive Team With Critical Factors - The first stage in securing organisational common ground is to create a detailed plan that includes essential aspects of the project, such as the timetable and the budget. Before taking additional action, you must confirm that leadership agrees with your strategy. Then it would be best if you made any necessary adjustments before telling the rest of the organisation.</li><li>Moving Down From The Top - As soon as you have received executive approval, you will need to put change management practices into effect across all other business units. These processes need to be realistic and conveyed understandably.<br>For instance, it is reasonable to anticipate that the modifications you have suggested will be met with some level of opposition. Processes and procedures that have been in a department for a long time often need to be gradually phased out before they can be eliminated.</li></ul><p>It is to be ensured that each team receives consistent and informative updates if you want a seamless transition. These updates should inform all the leading stakeholders about the essential changes that have been made and how those changes will influence their roles. Make sure that any team member can easily share any concerns, suggestions, or other significant input that may be why it is required to adjust your approach. Create a process that is open and transparent.</p><p><strong>Create A Robust GRC Approach</strong> - Putting in the necessary foundation is necessary if you want to ensure that your GRC system is practical and adaptive. Because of the ever-evolving nature of cyber threats and vulnerabilities, the ever-changing landscape of cyber threats, and the severe repercussions of data breaches, these components are of the utmost importance in information technology governance and risk management (IT GRC).</p><p>Even more, emphasis needs to be paid to guaranteeing that the GRC methods employed by financial institutions and health organisations are flexible enough to accommodate the regular changes in regulatory requirements that their respective businesses are subject to.</p><p><strong>Invest In A GRC Software Solution Of Repute</strong> - Putting in place a GRC programme from the beginning necessitates the utilisation of many different moving elements, such as the consolidation of information silos, continual upgrades, and the utilisation of manual procedures such as spreadsheets. You can direct more of your implementation efforts to higher-level activities using a GRC platform because it can simplify many of these problematic areas.</p><p>When selecting a GRC tool for your firm, just as you would with any other third-party vendor, you need to complete your due diligence to ensure that the tool complies with all compliance rules and does not put your organisation in a position where it faces extreme security risks.</p><p>The appropriate GRC technology should result in a return on investment (ROI) that can be measured in terms of money and time saved. Some critical questions that need to be addressed are</p><ul><li>Does the software solution offer ease of use?</li><li>Does it have automated workflows?</li><li>Is it customisable and scalable?</li><li>Does the solution offer detailed task management and execution?</li><li>Does it support the integration of third-party applications?</li><li>Is it cost-effective from a TCO (Total Cost of Ownership) perspective?</li></ul><p><strong>Use Industry Prevalent and Accepted Standards</strong> - The capacity to align with the requirements of the entire business is one of the essential characteristics of a GRC strategy that is both successful and efficient. A baseline should be established as a point of reference, even if every department will have its own unique set of criteria. For example, you can adopt an industry standard such as NIST 800-53 or ISO 27001 to standardise your control architecture.</p><p><strong>Evaluate and Adjust Your GRC Strategy</strong> - Getting your new GRC programme up and running is not a \"set it and forget it\" kind of endeavour. After it has been implemented, you must ensure that your strategy can develop and adapt to your company\'s goals. Every group should maintain comprehensive and up-to-date records of their GRC requirements, highlighting any significant shifts in the situation, such as incorporating new tools.</p><p>This reporting can serve as a point of reference during the periodic meetings with stakeholders to ensure that the entirety of your organisation continues to follow the overall strategy. To ensure compliance management is being properly carried out, at least one annual audit must be performed. You should then prioritise the resolution of any compliance issues that have arisen.</p><p><strong>Concluding Remarks</strong> – Deploying a robust GRC framework is a tedious initiative. But If you partner with an expert partner like DivIHN Integration Inc., you do not have to worry about your ROI. To know more, please reach out to <a href=\"mailto:sgovilkar@divihn.com\">sgovilkar@divihn.com.</a></p>','','full_html'),('featured_article',0,80,207,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,80,259,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,80,446,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,80,480,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,80,560,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,80,635,'en',0,'<p><strong>Introduction: -</strong></p><p>Many businesses have decided to use Salesforce\'s customer relationship management solution. Over the past few years, there has been a dramatic increase in the number of people using Salesforce, which has propelled the company to be one of the enterprise software vendors currently experiencing the most significant rate of expansion.</p><p>If you want the best possible results from your Salesforce implementation, you must adjust as your company grows and its business needs shift. When developing new functionality for Salesforce or customising the features, there are many factors to consider.</p><p>The out-of-the-box capabilities of Salesforce deliver a plethora of cutting-edge features that make it easier for contemporary businesses to fulfil their operational requirements. These capabilities help modern organisations meet the demands of their customers. Although many companies can generate value with these features, others must develop and customise the solution further to better meet their unique business goals.</p><p>When done correctly, Salesforce development can enable companies to build specific features, services, and applications into the Salesforce platform while easily and quickly achieving their business goals. Taking advantage of the solution\'s multi-tenant architecture and integration capabilities, businesses can customise it to create outstanding elements that benefit the company.</p><p><strong>Notable Facts About Salesforce: -&nbsp;</strong></p><ul><li>More than 150,000 businesses use Salesforce, generating $21.25Bn in revenue in 2021.</li><li>The market share of Salesforce CRM is 19.8%. It is higher than the combined share of the top four competitors.</li><li>Salesforce has more than 56,000 employees globally.</li><li>The revenue of Salesforce has consistently grown in the last twenty years at a CAGR of 51.22%.</li><li>The Salesforce subscription and support division contributes to 93.99% of the overall revenue worth $19.98Bn.</li></ul><p><strong>Benefits of Salesforce Development: -</strong></p><ol><li>Build user-friendly applications and modules that technical and non-technical users may easily traverse with drag-and-drop functionality.</li><li>Integrate features and capabilities that can be customised for teams and departments and enhance workforce productivity.</li><li>Salesforce Cooperation Cloud improves communication and collaboration through updates, projects, and bottlenecks.</li><li>Create functions that address customer questions, requirements, comments, and deliveries to improve your relationship with your customers.</li><li>Utilize the built-in analytic capabilities to your full advantage to generate predictive reports covering organisation development, the status of competitors or markets, and brand reputation.</li><li>Enable Salesforce integration with pre-existing enterprise systems and applications that will be developed to improve overall business performance.</li></ol><p><strong>Best Practices De-Coded: -</strong></p><ol><li><strong>Develop A Complete Plan –</strong> It is a no-brainer that without a well-thought plan, success is not possible. It is in your best interest to have a well-thought-out strategy outlining how you intend to build and roll out your solution before starting the Salesforce development process. Planning allows you to understand where you are in the process, where you want to get to in the future, and what steps you need to take to get there.</li><li><strong>Uncover The Finer Nuances of Salesforce Architecture –</strong> After establishing a road map, it is an excellent idea to understand the Salesforce architecture, which includes the various layers, the interactions between them, the different components, APIs, and databases. In addition, it is essential to have a solid understanding of the distinctions between the fundamental capabilities of the platform and the pre-packaged applications that run on it, as well as the communication and data flow between the various servers.</li><li><strong>Explore and Exploit The Test Environment –</strong> Although Salesforce does provide the option of developing modules and customising features in a live environment, it is recommended that the sandbox be used for development because it will not impact the performance of your system. You can use the developer sandbox to create new features, the partial sandbox to determine how the development process might affect your system, or the full sandbox to deploy customisations and determine how they will operate within your system.</li><li><strong>Ensure Consistency in Coding –</strong> Because it is only natural to have multiple developers working on your Salesforce development project simultaneously, adhering to a consistent coding style can help ease the development process significantly. Adhering to standard coding conventions can not only pave the way for establishing legal guidelines but can also add consistency, ensuring that all team members reach the same conclusions regarding standards and patterns and adhere to the same principles.</li><li><strong>Utilise Salesforce\'s Built-in Trigger Frameworks –</strong> The use of trigger frameworks can help significantly reduce the amount of time and effort spent developing software, which is especially helpful as your requirements expand. They make it possible to remove logic and ensure consistency across the platform, making unit testing, integrating changes, and maintenance much more straightforward. Once standardised, you can be sure that all your triggers work consistently, giving you complete control over the order in which operations are carried out.</li><li><strong>Embrace a Modular Approach to Your Salesforce Development –</strong> The ability to develop functions or modules in isolation from one another is one of the most significant benefits offered by Salesforce development. You can design the system in such a way that its various functions can be optimised independently if you take a modular approach and do so. This is possible because the failure of one part will not influence the other processes.</li><li><strong>Deploy Appropriate Tools –</strong> In addition to selecting the appropriate features, it is also essential to use the proper tools for development. This will allow you to begin developing and testing your Salesforce platform as soon as possible. Conduct a thorough analysis of the tools at your disposal, considering the requirements you have specified, and select the ones that will assist you in efficiently meeting your needs.</li><li><strong>Refrain from DML/SOQL Queries –</strong> There will be times when you want to insert/update multiple records simultaneously and query sets of documents based on specific contexts. While iterating through the forms using the loop, you might feel tempted to perform a query or DML operation on these records. After all, what\'s the worst that could happen? Well, quite a lot.</li></ol><p>Both SOQL and DML are some of the most expensive operations that can be carried out within Salesforce Apex. As a result, governor limits for both processes are highly stringent. Therefore, placing them in a loop is a recipe for disaster because we can quickly and unknowingly reach these limits, particularly when triggers are involved in the process!</p><p>When it comes to DML statements, we have the option of moving those statements outside of the loop. In their place, we can add the records we want to perform those operations on to a list within the circle and then run the DML statement on the list rather than the records themselves. This is the most prudent course of action to take in many circumstances. Moving SOQL to a position outside a loop can be more challenging because the decision depends heavily on the context.</p><ol start=\"9\"><li><strong>Only Hard-Code IDs When Needed </strong>- When IDs are hardcoded, they may function correctly and without incident when they are being developed; however, as soon as our code is migrated into production, those IDs will no longer reference the appropriate record. This is especially true for Record Types that were initially developed in a sandbox environment and later transferred into a production environment. Consider the opposite scenario: if we create a sandbox from production, our hard-coded identifiers will no longer point to the appropriate records.</li></ol><p>If we want to use record types, we can instead make references to them using their Developer Name, which will remain the same across all environments. Suppose the ID we want to use is associated with a particular record. In that case, we can store this ID within our custom metadata and retrieve the value during runtime. This allows the developers to freely alter the value depending on the environment in which the code is being written or the requirements imposed on us.</p><p>There is only one situation in which we are not required to adhere to either of the two methods described above, and that is when we are explicitly referencing the Master Record Type. This record type is the default and is consistent across all instances. On the other hand, the fact that it is static right now does not guarantee that it will remain so in the future; consequently, we ought to store it probably also in custom metadata (if doing so is necessary) to be on the safe side.</p><ol start=\"10\"><li><p><strong>Declare Openly the Existence of a Sharing Model</strong> - When we start writing brand-new code, one of the very first things we should do is declare our sharing model. This is one of the most important things to do. When we want our code to enforce sharing rules, we must always advise that, but when we want it to bypass record access, we must always say that it is not sharing. Developers often find themselves skipping this step.&nbsp;</p><p>Declaring our sharing model explicitly enables us to communicate our goals to anyone else who may work on our code in the future. This includes anyone who may work on our code. If we omit this, it will make it more difficult for them to comprehend what is going on within the code; on the other hand, if we include it, they will have a much easier time understanding it.&nbsp;</p><p>You can safely omit only if your code does not perform any DML or queries. This is the only time it is safe to do so. However, if this is possible, or if you want to play it safe, it is wise to declare the sharing model anyway, specifying it as \'inherited\' to allow a consumer of your course to control the model instead. Declaring the model in this manner will enable you to play it safe.</p></li><li><p><strong>Use Only One Trigger Per Single Object Type</strong> - The principle of using only a single trigger for each object is ingrained in the minds of many programmers. This is because the focus is both simple to remember and straightforward to put into practice. But why is this relatively straightforward \"best practice\" such a significant one to adhere to?&nbsp;</p><p>The order in which individual triggers are executed cannot be guaranteed when multiple stimuli are defined on a single object. When a record is saved and the triggers are invoked, the order in which the individual triggers are executed is utterly arbitrary for all intents and purposes. It\'s not uncommon for the individual actions that make up a trigger to have their order of priority, or they might have a condition that requires an initial step to have been finished before they can proceed (e.g., assigning a parent lookup which is then expected to be populated in the following action).&nbsp;</p><p>An entirely random trigger order also introduces randomness into our code. This randomness makes it more difficult to debug and develop code because there is always some element of randomness present, and we cannot accurately replicate scenarios.</p></li><li><p><strong>Test Multiple Scenarios</strong> - When it comes to testing, having a high number of lines covered by tests is a good goal, but it does not tell the whole story. Salesforce mandates to have at least 75% code coverage whenever you wish to deploy Apex code into production.&nbsp;</p><p>You are writing tests solely to meet the code coverage requirement, demonstrating that your code has been executed and doesn\'t provide any value other than showing that in a particular scenario. It might work or might not when deployed in real-time.&nbsp;</p><p>When writing our tests, we should worry less about code coverage and more about covering different use cases for our code. This will ensure that we protect the scenarios in which the code is being executed. This is accomplished by writing multiple test methods, some of which may be testing the same and not generating additional covered lines. Each test method executes our code by a distinct scenario, allowing us to test the system effectively.&nbsp;</p><p>One possible application would be to cover both positive and negative test cases in a trigger. After the tests run, the next step is to verify that the code has successfully carried out the intended action; if it hasn\'t, we want to fail the test manually. If the code hasn\'t successfully acted, we want to forget the test manually.&nbsp;</p><p>Writing tests for code coverage isn\'t the only reason to run these kinds of tests; they can also serve as an early warning system for problems that may crop up if an administrator adds some new functionality or a different section of code is modified. This testing offers much more value than just writing tests for code coverage. Testing for these scenarios ensures that we are alerted about the issues and can resolve them (before they hit production and cause late nights!). Testing for these scenarios also ensures we don\'t miss any opportunities to save money.</p></li><li><strong>Double Check Tests</strong> - The quality of the Salesforce solution you develop is directly proportional to the amount of testing you do. You must test the platform’s functionality to ensure that it can meet the requirements of your client, who will use it daily. Try every functionality and feature you\'ve developed to ensure that it functions as intended in any circumstances.</li><li><strong>Keep Documentation Clean and Complete</strong> - When developing a solution for Salesforce, it is also a good practice to document everything that programmers are working on. This can help avoid any misunderstandings. This practice, which entails keeping a log of every development effort, can assist other administrators and developers in comprehending the advancements that have been made, as well as preventing those advancements from being duplicated or altered when they should not be.</li><li><strong>Avoid Business Logic In Triggers</strong> - When we write triggers, placing our logic directly in the trigger becomes very difficult to test and maintain the triggers. It would help if you used classes designed to handle our senses. These classes can then be easily tested, kept, and reused. These classes are typically referred to by their shorthand name, TriggerHandlers.</li></ol><p>These TriggerHandler classes take the inputs provided by the trigger and then, as a final step, call the specific courses that hold the business logic we have written. They can be as straightforward as updating the handlers to name the new code as we add it, or they can be as intricate as utilising things like custom metadata types to allow admins to configure our triggers in various ways.</p><p>However, it is a common mistake to put your logic and functionality directly into a TriggerHandler or TriggerHelper class. This can lead to unexpected results. It is recommended that separate categories be created for each piece of functionality and that the TriggerHandler be the one to invoke these classes.</p><p>If we do not follow this procedure, we will very quickly produce code that cannot be maintained. This violates the \"Single-Responsibility Principle\" because it causes it to do everything about an object\'s trigger actions, which results in the creation of a \"God object,\" which is an anti-pattern.</p><p>Suppose an object\'s trigger is exceptionally straightforward (for example, it only invokes a single action). In that case, it may be appropriate to forego a handler class and instead make a direct call to the action invoked by the trigger from within the spur itself. However, the steps should be written with a handler in mind and migrated to a handler as soon as the complexity of the trigger increases.</p><p><strong>Concluding Remarks: -</strong></p><p>Implementing industry standards and best practices is essential to any solution provider’s core capabilities. For excellent results out of your Salesforce Development initiatives, it will be beneficial to understand the why and the what of the development process. This will enable us to make more educated and intelligent decisions regarding our choices\' potential short-term and long-term effects.</p><p>DivIHN Integration Inc. offers seamless, robust and scalable Salesforce solutions. For more information, please get in touch with Kannan Venkataraman at <a href=\"mailto:kannan@divihn.com\">kannan@divihn.com.</a></p>','','full_html'),('featured_article',0,81,208,'en',0,'<p>In the digital age, businesses must adopt an adaptive Enterprise Architecture to succeed. The vision, once realized, enables leveraging emerging technologies, scalability, agility, integration, cost optimization, regulatory compliance, and maximum business value.</p><p>Transitioning requires careful planning, change management, and a strategic vision. Partnering with experienced IT consultants facilitates the process. An adaptive Enterprise Architecture is the key for efficiency, agility, and innovation, empowering businesses to meet customer demands and stay competitive. By embracing this approach, organizations can streamline operations, enhance collaboration, create value for all stakeholders, and achieve sustainable growth.</p><p><strong>Introduction</strong></p><p>In today\'s dynamic business environment, the ability to quickly deploy new capabilities is a competitive necessity. However, organizations often fail to seize opportunities due to the perceived cost and risk of modernizing the systems that enable business capabilities. Information systems and technology platforms exist for a relatively simple set of reasons – to enable business operations and facilitate decision-making as the organization pursues evolving goals and opportunities.</p><p>Technology leaders must have a seat at the organization’s strategy table and allow for the inevitable changes of plan so that when requirements change, the business technology they manage is an enabler, not an impediment. Internal and external forces of change are permanent and pervasive. “Enterprise Architecture” sounds like something slow-moving, but today’s Enterprise Architects must design with continuous change in mind.</p><p><strong>Technological Forces of Change</strong></p><p>In 1965, Gordon Moore suggested the number of transistors on a typical computer chip would roughly double about every two years. Although we do not measure our progress in transistors per chip, Moore’s hypothesis has been validated in real life. In the ensuing 60 years, advances in computational capabilities have given mainstream businesses the ability to solve computational and information management problems at a scale that would have been considered far-fetched a generation ago.</p><p>In the first quarter of the 21st Century, we have seen an explosion of data – beyond a tsunami, more like a Big Bang. The good news is data management and processing capabilities have kept pace, allowing us to do interesting and useful things with all that data, enabling more efficient operations and facilitating informed decision-making.</p><p>Combined with the Internet, massive computing power and vast pools of information have created the real potential of a global data fabric and data marketplace based on broadly adopted cloud computing and democratized artificial intelligence. Nobody talks about data processing anymore. The daily conversations about automating operational and accounting processes to gain efficiency and reduce costs are a dim memory. Today we talk about information as a strategic asset and the ability to make the best use of it as a strategic capability.</p><p>In about ten years, Cloud computing has outgrown mere widespread adoption. It is now a standard feature of almost all enterprises’ information technology architecture. At the same time, Artificial Intelligence is advancing so rapidly that it has drawn the attention of ethicists and legislators. While they are thinking about the responsible use of AI, completely novel applications as well as spot solutions built into existing solutions appear in the marketplace almost daily.</p><p>The rapid pace of technological advancements requires businesses to constantly innovate and leverage new capabilities. Inflexible architectures and solutions hinder the adoption of emerging technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies have the potential to revolutionize operations, drive efficiency, and unlock valuable insights from data.</p><p><strong>Competitive Forces of Change</strong></p><p>Considering technological advances, competition has in no corner become less intense. Competitors are becoming more numerous, diverse, and global. In some markets the competition is consolidating, raising the barrier to entry, and making life increasingly difficult for independent players. Simultaneously, agile startups enter the market every day with new business models and game-changing technologies, challenging established firms to rethink the status quo, and in some cases, to adapt or perish.</p><p>In both mature and emerging markets architectural rigidity can lead to falling behind while competitors who have successfully integrated these technologies into their workflows, customer experiences, and decision-making processes.</p><p>An adaptive IT architecture that enables businesses to harness the power of emerging technologies and is a competitive necessity. The ability to seamlessly integrate innovative tools and systems empowers organizations to further automate processes, optimize resource allocation, and deliver personalized experiences to customers. The ability to quickly respond to market changes, customer demands, and disruptive forces is essential for sustained success in today\'s digital landscape.</p><p><strong>The Hybridization of Everything</strong></p><p>Thinking about the most successful organizations, and the most successful people in them, we can observe a trend: The Hybridization of Everything. Since the mid-1990s, hybridization has been seen as a necessity in organizations that want to do more, better, faster, and cheaper.</p><p>In the old organizations, the organizing principle was specialization: discrete departments, separate functions, independent projects. In the new organizations, it’s hybridization: inter-departmental meetings, cross-functional teams, integrated systems. Enterprise architectures must support pervasive hybridization.</p><p><strong>Hybrid Technology</strong></p><p>The Hybrid Cloud was one of the early materializations of this idea. It meant, some of our stuff is on premises and some of it in the cloud.” Today hybrid solutions take many forms, combining the benefits of disparate technologies for a single, mission-specific purpose. Information processing itself is becoming hybridized with traditional deterministic algorithms answering traditional questions alongside artificial intelligence which can suggest new questions.</p><p>AI-enhanced solutions are becoming commonplace, appearing in everything from office productivity suites to facial recognition solutions for border security, to large computational problems in climate science, economics, and more. The analog world in which we live is increasingly digitized by hybrid analog-digital devices that populate the Internet of Things, from talking (and listening) appliances to home security systems that allow you to close your garage door from the other side of the planet.</p><p>Adaptive Enterprise Architectures exploit hybrid technologies, both as a preference for the capabilities or adaptive technologies and as a response to the need to design for efficiency and responsiveness in today’s dynamic and competitive environment.</p><p><strong>The Demand for Modernization</strong></p><p>Several forces of change drive the demand for application modernization. Among them are…</p><ul><li><strong>Technical obsolescence of the infrastructure</strong> – The age of technology itself, and the aging of the workforce having the skills to support it can make a compelling case for replacement. Support gets more expensive and harder to find almost daily. Also known as Technical Debt, like most forms of debt it gets more expensive with the passage of time.</li><li><strong>Demand for a modern user experience</strong> – Some internal users of older information systems are often productive and happy doing their job by pressing F2 twice, typing something, and then pressing Enter twice. External users and most internal users expect a modern experience.</li><li><strong>Not Designed for Flexibility</strong> – Legacy applications were not based on today’s service-oriented design patterns and other innately adaptive frameworks. Even when they can be adapted to modern requirements, changes to monolithic applications can require extensive and widespread testing.</li></ul><p><strong>Enterprise Architecture and the Business of IT&nbsp;</strong></p><p>Technology Portfolio Management and Technology Business Management are closely related to Enterprise Architecture. Some consider them a discipline within Enterprise Architecture. They provide IT management frameworks that implement a standard IT spending taxonomy and process-enablement catalog.</p><p>Having a standard way to categorize IT costs, technologies, resources, applications, and services enables organizations to disaggregate IT spending into smaller, consistent categories to provide the leadership team with a more accurate and detailed understanding of their organization’s IT costs. This disciplined and business-like approach to managing IT enables enterprise architects to identify duplicate spending and redundant capabilities to make better informed decisions regarding future investments.</p><p>Organizations seeking to reduce IT sprawl or to rationalize their portfolio can develop a roadmap to deal with overspending and redundancy. Fully redundant applications can be retired. Other applications can be designated for migration to more cost-effective implementations. Some applications can be left alone. Those with the greatest potential for business value can be targeted for further investment as savings are achieved in other areas.</p><p><strong>The Adaptive Enterprise Architecture Response&nbsp;</strong></p><p>The core purpose of Enterprise Architecture is to apply holistic technology concepts to the enablement of business processes in furtherance of the organization’s mission. An Adaptive Enterprise Architecture perspective requires that flexibility and adaptability, without security compromises, are highly valued criteria for enterprise Information Technology decision-making.</p><p>Further, holistic Enterprise Architecture thinking encompasses the people and processes that plan, deploy, and operate Information Technology. Those people responsible for the architecture require a fulsome appreciation of the relationships between business goals, operational processes, to make informed decisions about information management systems and technology foundations. An Adaptive Enterprise Architecture strategy prioritizes pragmatism and flexibility not just in reaction to changing business needs but in anticipation of them.</p><p><strong>Threats&nbsp;</strong></p><p>The increasing number and sophistication of bad actors means changes the question from “Will I be attacked?” to “When will I be attacked?”. Cyber Security defenses must be incorporated into your technology blueprint with holistic architectural thinking. Every building block must be imagined as an element of the attack surface visible to bad actors.</p><p>An inflexible IT architecture based on monolithic systems poses a variety of related security and compliance risks. Older systems may lack the robust security measures needed to withstand advanced threats, making them vulnerable to cyber threats and data breaches. An adaptivity-focused architecture, having by nature a more complex attack surface poses a different of problems. In all cases, a holistic architectural approach based on Zero Trust principles and technologies like software-defined networks, and advanced vulnerability detection, along with a security-aware organizational culture, create a robust cyber immune system.</p><p>A strong perimeter defense is no longer good enough. Unless your systems are completely disconnected from the outside world, a bad actor will eventually penetrate even the strongest barriers. A holistic architecture incorporating Zero-Trust principles prevents free movement within your environment once that bad actor penetrates the perimeter.</p><p>Organizations must ensure that their IT architecture can adapt and withstand evolving security challenges. Non-compliance with industry regulations can result in substantial financial penalties and reputational damage. Adaptive IT architecture, on the other hand, allows for timely updates and enhancements to address emerging security and compliance requirements, providing organizations with peace of mind and a competitive advantage.</p><p><strong>The Adaptive Enterprise Architecture Journey – An Approach</strong></p><ol><li><p><strong>Define Business Objectives:</strong> The organization must articulate a strategy and business objectives, growth targets, and customer-centric goals.</p><p>Align IT strategies with these objectives to ensure that technology investments are aligned with business priorities. Engage key stakeholders from both IT and business units to gain a comprehensive understanding of the organization\'s strategic direction. The Enterprise Architecture function guides the evolution of the IT ecosystem to achieve and maintain alignment with organizational goals.</p><p>Identify the key areas where adaptive architecture can drive value, such as improving customer experience, enhancing operational efficiency, reducing costs, or enabling new revenue streams. By aligning your IT strategy with your business goals, you can ensure that your adaptive architecture initiatives have a meaningful impact on your organization\'s success.</p></li><li><p><strong>Assess the Current IT Landscape:</strong> Every passionate Enterprise Architect would love an opportunity to start with a clean sheet of paper. They rarely get one. Instead, they begin by conducting a thorough assessment of the existing IT infrastructure, systems, and applications.</p><p>Identify the strengths and weaknesses of your current architecture, using established frameworks for assessing architectural health to identify areas that hinder flexibility, scalability, and integration as well as apparent redundancies and potential areas of overspending. This assessment will provide valuable insights into the specific challenges your organization faces and help define the goals and objectives of your adaptive architecture.</p></li><li><p><strong>Develop a Future State Vision:</strong> Every good plan begins with the end in mind. Choose a foundation. Although adaptivity is the goal discussed here, stability is essential for effective support of business operations. Some long-term decision-making is unavoidable. The ability to swap components, redesign integrations, and so on is not a reason to avoid making big decisions about the core infrastructure and foundational technologies.</p><p>Design a sound foundation that innately supports swappable and scalable components. You might want to paint the house a new color every Spring. You will probably need to update the furniture appliances from time to time or even change the layout of the interior spaces, but build the house on a solid, long-lasting foundation.</p></li><li><strong>Develop a Roadmap:</strong> Create a comprehensive roadmap that outlines the steps, milestones, and timelines for transitioning to an adaptive IT architecture.<ol type=\"a\"><li>Don’t change everything at once! Segment the journey into manageable phases, prioritizing areas of critical need or areas that can provide immediate value. Consider the dependencies and interdependencies between different systems and processes, in-flight and planned projects, costs, and value and plan for effective change management to ensure a smooth transition and minimal disruption to ongoing operations.</li><li>Don’t set the roadmap in stone. Adaptivity involves continuous change in response to forces that are often unforeseen. It’s true that every well-managed program needs a roadmap, but in a future, adaptive world, there will be fewer roadmaps and more dynamic routing.</li></ol></li><li><p><strong>Continuously Monitor, Evolve and Adapt:</strong> Establish a framework for monitoring and evaluating the effectiveness of adaptive IT architecture. Regularly review performance metrics, customer feedback, and industry trends to identify areas for improvement and adapt strategies accordingly. Embrace a culture of continuous improvement and be open to feedback and suggestions from employees and customers.</p><p>An adaptive IT architecture is not a one-time implementation but an ongoing process of evolution and iteration. Continuously evaluate the effectiveness of your architecture, gather feedback from users, and adapt as needed. Embrace an agile mindset that embraces change and allows for iterative improvements. Regularly assess the alignment of your IT architecture with business goals and adjust strategies accordingly.</p></li><li><strong>Collaborate with Technology Partners:</strong> Engage with technology partners and vendors who can provide expertise, solutions, and support for your adaptive IT architecture journey. Leverage their knowledge and experience to accelerate implementation.</li></ol><p><strong>Five Reasons to Pursue Adaptive Architecture</strong></p><ol><li><strong>Enhanced Scalability and Agility:</strong> In a rapidly changing business environment, scalability and agility are essential for organizations to respond quickly to market demands and seize new opportunities. Adaptive IT architecture provides the flexibility to scale resources up or down as needed, accommodating fluctuating workloads and business requirements. This scalability enables businesses to handle increased customer demands, seasonal peaks, or sudden growth without disruptions or resource constraints. Additionally, adaptive architecture allows for agile development and deployment of new applications and services, enabling businesses to stay ahead of the competition by rapidly delivering innovative solutions.</li><li><strong>Improved Integration and Interoperability:</strong> In today\'s interconnected business landscape, integration and interoperability are critical for seamless data exchange and collaboration across systems, departments, and external partners. An adaptive IT architecture facilitates smooth integration of disparate systems and applications, enabling efficient data flow and real-time information sharing. By breaking down silos and promoting interoperability, businesses can optimize their operations, streamline workflows, and enhance productivity. This integration also paves the way for future growth and expansion, as businesses can easily incorporate new technologies, platforms, and partnerships into their ecosystem.</li><li><strong>Cost Efficiency and Resource Optimization:</strong> While transitioning to adaptive IT architecture requires initial investments, it can result in long-term cost savings and resource optimization. Outdated systems often require extensive maintenance, support, and upgrades, leading to high operational costs. In contrast, adaptive architecture enables businesses to adopt a more modular and scalable approach, allowing them to optimize resource allocation and reduce unnecessary expenses. Cloud-based solutions, for example, eliminate the need for on-premises infrastructure, reducing hardware and maintenance costs. Additionally, an adaptive architecture allows businesses to leverage automation and self-service capabilities, freeing up IT resources for more strategic initiatives and reducing labor costs.</li><li><strong>Enhanced Business Continuity and Resilience:</strong> An adaptive IT architecture provides organizations with the necessary tools to enhance business continuity and resilience in the face of disruptions or unforeseen events. Traditional architectures with single points of failure or limited redundancy are susceptible to downtime and data loss. By leveraging cloud technologies, virtualization, and distributed systems, businesses can ensure data redundancy, implement robust disaster recovery strategies, and achieve high availability. This enables businesses to minimize downtime, protect critical data, and quickly recover from disruptions, safeguarding their operations and reputation.</li><li><strong>Compliance and Security:</strong> In an era where data privacy and security are paramount, an adaptive IT architecture offers significant advantages in terms of compliance and data protection. Regulations such as the General Data Protection Regulation (GDPR) and industry-specific requirements impose strict guidelines on how businesses handle and secure sensitive data. An adaptive architecture enables organizations to implement advanced security measures, such as encryption, access controls, and audit trails, to protect data throughout their lifecycle. Furthermore, the ability to quickly update and patch systems ensures that businesses stay compliant with evolving regulations and industry best practices.</li></ol><p><strong>Additional Considerations</strong></p><ol><li><strong>Emphasize User Experience:</strong> As technology evolves, so do user expectations. Prioritize user experience in your adaptive IT architecture by designing intuitive interfaces, seamless workflows, and personalized interactions. Incorporate user feedback and conduct usability tests to refine your systems and ensure they align with user needs and preferences.</li><li><strong>Leverage Automation and Intelligent Workflows:</strong> Automation plays a crucial role in adaptive IT architecture. Identify repetitive and manual processes that can be automated to streamline operations, reduce errors, and free up resources for more strategic tasks. Embrace intelligent workflows powered by AI and machine learning to enhance decision-making, optimize resource allocation, and improve efficiency.</li><li><strong>Implement Agile Development Methodologies:</strong> Agile methodologies, such as Scrum or Kanban, can greatly enhance the adaptability of your IT architecture. By breaking projects into smaller, manageable chunks, you can deliver incremental value and respond quickly to changing requirements. Regularly review and adapt your development processes to foster collaboration, transparency, and continuous improvement.</li><li><strong>Embrace DevOps Practices:</strong> DevOps is a set of practices that emphasize collaboration and integration between development and operations teams. By adopting DevOps principles, you can accelerate software delivery, increase deployment frequency, and improve overall system stability. Encourage cross-functional collaboration, automate testing and deployment processes, and foster a culture of shared responsibility and continuous improvement.</li><li><strong>Establish an Architecture Governance Framework:</strong> To ensure the effectiveness and sustainability of your adaptive IT architecture, establish a robust governance framework. Regularly review and update governance policies to adapt to changing circumstances and emerging technologies.</li></ol><p><strong>Conclusion</strong></p><p>By adopting an adaptive IT architecture, organizations can proactively respond to market dynamics, seize new opportunities, and deliver exceptional value to customers. Embrace change, embrace innovation, and embark on the journey to building an adaptive IT architecture that will position your business for long-term success in the digital age.</p><p>The journey towards adaptive IT architecture requires careful planning, effective management, and ongoing evaluation. It is not a one-time effort but a continuous process of optimization and adaptation. However, the rewards are substantial – increased operational efficiency, accelerated innovation, reduced costs, enhanced customer satisfaction, and sustainable business growth. Embrace the potential of an adaptive IT architecture and position your organization for success in the digital era.</p><p>In today\'s rapidly evolving business landscape, adaptive IT architecture is the key to unlocking business potential, driving innovation, and maintaining a competitive edge. By embracing flexibility, modularity, and agility, organizations can navigate the complexities of the digital age and capitalize on emerging opportunities.</p><p>Building an adaptive IT architecture requires a holistic mindset, organizational commitment, and a willingness to invest in technology, talent, and cultural transformation. By following best practices such as embracing cloud computing and other innately adaptive technologies, fostering a culture of innovation, prioritizing integration, swappable components, interoperability, and staying abreast of technological advancements, businesses can create a robust foundation for future growth and success.</p><p>The journey towards adaptive IT architecture is not merely a technical transformation but a cultural shift that embraces change, continuous learning, and collaboration. By aligning technology with business goals, managing risks, and fostering a culture of adaptability, businesses can position themselves as agile, resilient, and future-ready entities capable of thriving in the dynamic digital landscape. Embrace the power of an adaptive IT architecture and unleash your business\'s full potential.</p><p><strong>About The Author</strong></p><p><a href=\"https://www.linkedin.com/in/dougpicirillo/\">Douglas Picirillo</a> is a Senior Enterprise and Solutions Architect and IT Program Management Consultant. He specializes in Business Transformation and Value Creation enabled by Information Technology, IT transformation and cost reduction, Enterprise Systems Development, and IT Integration and Separation in Mergers and Acquisitions.</p><p>Mr. Picirillo has more than 30 years of IT experience in the public and non-profit sectors and numerous private sector industries, from SMBs to the Fortune 500. Doug’s paper, \"Artificial Intelligence in Mainstream Enterprise Applications\", was published in the peer-reviewed World Complexity Science Academy Journal (ISSN online: 2724-0606) in 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/artificial-intelligence-in-mainstream-enterprise-applications/\">https://lnkd.in/dgQEr8VE</a></p><p>To know more about how DivIHN Integration Inc. can help you in your journey for deploying robust \"Adaptive Enterprise Architecture\" please get in touch with him at Doug. <a href=\"mailto:doug.picirillo@divihn.com\">doug.picirillo@divihn.com</a></p>','','full_html'),('featured_article',0,81,258,'en',0,'<p>In the digital age, businesses must adopt an adaptive Enterprise Architecture to succeed. The vision, once realized, enables leveraging emerging technologies, scalability, agility, integration, cost optimization, regulatory compliance, and maximum business value.</p><p>Transitioning requires careful planning, change management, and a strategic vision. Partnering with experienced IT consultants facilitates the process. An adaptive Enterprise Architecture is the key for efficiency, agility, and innovation, empowering businesses to meet customer demands and stay competitive. By embracing this approach, organizations can streamline operations, enhance collaboration, create value for all stakeholders, and achieve sustainable growth.</p><p><strong>Introduction</strong></p><p>In today\'s dynamic business environment, the ability to quickly deploy new capabilities is a competitive necessity. However, organizations often fail to seize opportunities due to the perceived cost and risk of modernizing the systems that enable business capabilities. Information systems and technology platforms exist for a relatively simple set of reasons – to enable business operations and facilitate decision-making as the organization pursues evolving goals and opportunities.</p><p>Technology leaders must have a seat at the organization’s strategy table and allow for the inevitable changes of plan so that when requirements change, the business technology they manage is an enabler, not an impediment. Internal and external forces of change are permanent and pervasive. “Enterprise Architecture” sounds like something slow-moving, but today’s Enterprise Architects must design with continuous change in mind.</p><p><strong>Technological Forces of Change</strong></p><p>In 1965, Gordon Moore suggested the number of transistors on a typical computer chip would roughly double about every two years. Although we do not measure our progress in transistors per chip, Moore’s hypothesis has been validated in real life. In the ensuing 60 years, advances in computational capabilities have given mainstream businesses the ability to solve computational and information management problems at a scale that would have been considered far-fetched a generation ago.</p><p>In the first quarter of the 21st Century, we have seen an explosion of data – beyond a tsunami, more like a Big Bang. The good news is data management and processing capabilities have kept pace, allowing us to do interesting and useful things with all that data, enabling more efficient operations and facilitating informed decision-making.</p><p>Combined with the Internet, massive computing power and vast pools of information have created the real potential of a global data fabric and data marketplace based on broadly adopted cloud computing and democratized artificial intelligence. Nobody talks about data processing anymore. The daily conversations about automating operational and accounting processes to gain efficiency and reduce costs are a dim memory. Today we talk about information as a strategic asset and the ability to make the best use of it as a strategic capability.</p><p>In about ten years, Cloud computing has outgrown mere widespread adoption. It is now a standard feature of almost all enterprises’ information technology architecture. At the same time, Artificial Intelligence is advancing so rapidly that it has drawn the attention of ethicists and legislators. While they are thinking about the responsible use of AI, completely novel applications as well as spot solutions built into existing solutions appear in the marketplace almost daily.</p><p>The rapid pace of technological advancements requires businesses to constantly innovate and leverage new capabilities. Inflexible architectures and solutions hinder the adoption of emerging technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies have the potential to revolutionize operations, drive efficiency, and unlock valuable insights from data.</p><p><strong>Competitive Forces of Change</strong></p><p>Considering technological advances, competition has in no corner become less intense. Competitors are becoming more numerous, diverse, and global. In some markets the competition is consolidating, raising the barrier to entry, and making life increasingly difficult for independent players. Simultaneously, agile startups enter the market every day with new business models and game-changing technologies, challenging established firms to rethink the status quo, and in some cases, to adapt or perish.</p><p>In both mature and emerging markets architectural rigidity can lead to falling behind while competitors who have successfully integrated these technologies into their workflows, customer experiences, and decision-making processes.</p><p>An adaptive IT architecture that enables businesses to harness the power of emerging technologies and is a competitive necessity. The ability to seamlessly integrate innovative tools and systems empowers organizations to further automate processes, optimize resource allocation, and deliver personalized experiences to customers. The ability to quickly respond to market changes, customer demands, and disruptive forces is essential for sustained success in today\'s digital landscape.</p><p><strong>The Hybridization of Everything</strong></p><p>Thinking about the most successful organizations, and the most successful people in them, we can observe a trend: The Hybridization of Everything. Since the mid-1990s, hybridization has been seen as a necessity in organizations that want to do more, better, faster, and cheaper.</p><p>In the old organizations, the organizing principle was specialization: discrete departments, separate functions, independent projects. In the new organizations, it’s hybridization: inter-departmental meetings, cross-functional teams, integrated systems. Enterprise architectures must support pervasive hybridization.</p><p><strong>Hybrid Technology</strong></p><p>The Hybrid Cloud was one of the early materializations of this idea. It meant, some of our stuff is on premises and some of it in the cloud.” Today hybrid solutions take many forms, combining the benefits of disparate technologies for a single, mission-specific purpose. Information processing itself is becoming hybridized with traditional deterministic algorithms answering traditional questions alongside artificial intelligence which can suggest new questions.</p><p>AI-enhanced solutions are becoming commonplace, appearing in everything from office productivity suites to facial recognition solutions for border security, to large computational problems in climate science, economics, and more. The analog world in which we live is increasingly digitized by hybrid analog-digital devices that populate the Internet of Things, from talking (and listening) appliances to home security systems that allow you to close your garage door from the other side of the planet.</p><p>Adaptive Enterprise Architectures exploit hybrid technologies, both as a preference for the capabilities or adaptive technologies and as a response to the need to design for efficiency and responsiveness in today’s dynamic and competitive environment.</p><p><strong>The Demand for Modernization</strong></p><p>Several forces of change drive the demand for application modernization. Among them are…</p><ul><li><strong>Technical obsolescence of the infrastructure</strong> – The age of technology itself, and the aging of the workforce having the skills to support it can make a compelling case for replacement. Support gets more expensive and harder to find almost daily. Also known as Technical Debt, like most forms of debt it gets more expensive with the passage of time.</li><li><strong>Demand for a modern user experience</strong> – Some internal users of older information systems are often productive and happy doing their job by pressing F2 twice, typing something, and then pressing Enter twice. External users and most internal users expect a modern experience.</li><li><strong>Not Designed for Flexibility</strong> – Legacy applications were not based on today’s service-oriented design patterns and other innately adaptive frameworks. Even when they can be adapted to modern requirements, changes to monolithic applications can require extensive and widespread testing.</li></ul><p><strong>Enterprise Architecture and the Business of IT&nbsp;</strong></p><p>Technology Portfolio Management and Technology Business Management are closely related to Enterprise Architecture. Some consider them a discipline within Enterprise Architecture. They provide IT management frameworks that implement a standard IT spending taxonomy and process-enablement catalog.</p><p>Having a standard way to categorize IT costs, technologies, resources, applications, and services enables organizations to disaggregate IT spending into smaller, consistent categories to provide the leadership team with a more accurate and detailed understanding of their organization’s IT costs. This disciplined and business-like approach to managing IT enables enterprise architects to identify duplicate spending and redundant capabilities to make better informed decisions regarding future investments.</p><p>Organizations seeking to reduce IT sprawl or to rationalize their portfolio can develop a roadmap to deal with overspending and redundancy. Fully redundant applications can be retired. Other applications can be designated for migration to more cost-effective implementations. Some applications can be left alone. Those with the greatest potential for business value can be targeted for further investment as savings are achieved in other areas.</p><p><strong>The Adaptive Enterprise Architecture Response&nbsp;</strong></p><p>The core purpose of Enterprise Architecture is to apply holistic technology concepts to the enablement of business processes in furtherance of the organization’s mission. An Adaptive Enterprise Architecture perspective requires that flexibility and adaptability, without security compromises, are highly valued criteria for enterprise Information Technology decision-making.</p><p>Further, holistic Enterprise Architecture thinking encompasses the people and processes that plan, deploy, and operate Information Technology. Those people responsible for the architecture require a fulsome appreciation of the relationships between business goals, operational processes, to make informed decisions about information management systems and technology foundations. An Adaptive Enterprise Architecture strategy prioritizes pragmatism and flexibility not just in reaction to changing business needs but in anticipation of them.</p><p><strong>Threats&nbsp;</strong></p><p>The increasing number and sophistication of bad actors means changes the question from “Will I be attacked?” to “When will I be attacked?”. Cyber Security defenses must be incorporated into your technology blueprint with holistic architectural thinking. Every building block must be imagined as an element of the attack surface visible to bad actors.</p><p>An inflexible IT architecture based on monolithic systems poses a variety of related security and compliance risks. Older systems may lack the robust security measures needed to withstand advanced threats, making them vulnerable to cyber threats and data breaches. An adaptivity-focused architecture, having by nature a more complex attack surface poses a different of problems. In all cases, a holistic architectural approach based on Zero Trust principles and technologies like software-defined networks, and advanced vulnerability detection, along with a security-aware organizational culture, create a robust cyber immune system.</p><p>A strong perimeter defense is no longer good enough. Unless your systems are completely disconnected from the outside world, a bad actor will eventually penetrate even the strongest barriers. A holistic architecture incorporating Zero-Trust principles prevents free movement within your environment once that bad actor penetrates the perimeter.</p><p>Organizations must ensure that their IT architecture can adapt and withstand evolving security challenges. Non-compliance with industry regulations can result in substantial financial penalties and reputational damage. Adaptive IT architecture, on the other hand, allows for timely updates and enhancements to address emerging security and compliance requirements, providing organizations with peace of mind and a competitive advantage.</p><p><strong>The Adaptive Enterprise Architecture Journey – An Approach</strong></p><ol><li><p><strong>Define Business Objectives:</strong> The organization must articulate a strategy and business objectives, growth targets, and customer-centric goals.</p><p>Align IT strategies with these objectives to ensure that technology investments are aligned with business priorities. Engage key stakeholders from both IT and business units to gain a comprehensive understanding of the organization\'s strategic direction. The Enterprise Architecture function guides the evolution of the IT ecosystem to achieve and maintain alignment with organizational goals.</p><p>Identify the key areas where adaptive architecture can drive value, such as improving customer experience, enhancing operational efficiency, reducing costs, or enabling new revenue streams. By aligning your IT strategy with your business goals, you can ensure that your adaptive architecture initiatives have a meaningful impact on your organization\'s success.</p></li><li><p><strong>Assess the Current IT Landscape:</strong> Every passionate Enterprise Architect would love an opportunity to start with a clean sheet of paper. They rarely get one. Instead, they begin by conducting a thorough assessment of the existing IT infrastructure, systems, and applications.</p><p>Identify the strengths and weaknesses of your current architecture, using established frameworks for assessing architectural health to identify areas that hinder flexibility, scalability, and integration as well as apparent redundancies and potential areas of overspending. This assessment will provide valuable insights into the specific challenges your organization faces and help define the goals and objectives of your adaptive architecture.</p></li><li><p><strong>Develop a Future State Vision:</strong> Every good plan begins with the end in mind. Choose a foundation. Although adaptivity is the goal discussed here, stability is essential for effective support of business operations. Some long-term decision-making is unavoidable. The ability to swap components, redesign integrations, and so on is not a reason to avoid making big decisions about the core infrastructure and foundational technologies.</p><p>Design a sound foundation that innately supports swappable and scalable components. You might want to paint the house a new color every Spring. You will probably need to update the furniture appliances from time to time or even change the layout of the interior spaces, but build the house on a solid, long-lasting foundation.</p></li><li><strong>Develop a Roadmap:</strong> Create a comprehensive roadmap that outlines the steps, milestones, and timelines for transitioning to an adaptive IT architecture.<ol type=\"a\"><li>Don’t change everything at once! Segment the journey into manageable phases, prioritizing areas of critical need or areas that can provide immediate value. Consider the dependencies and interdependencies between different systems and processes, in-flight and planned projects, costs, and value and plan for effective change management to ensure a smooth transition and minimal disruption to ongoing operations.</li><li>Don’t set the roadmap in stone. Adaptivity involves continuous change in response to forces that are often unforeseen. It’s true that every well-managed program needs a roadmap, but in a future, adaptive world, there will be fewer roadmaps and more dynamic routing.</li></ol></li><li><p><strong>Continuously Monitor, Evolve and Adapt:</strong> Establish a framework for monitoring and evaluating the effectiveness of adaptive IT architecture. Regularly review performance metrics, customer feedback, and industry trends to identify areas for improvement and adapt strategies accordingly. Embrace a culture of continuous improvement and be open to feedback and suggestions from employees and customers.</p><p>An adaptive IT architecture is not a one-time implementation but an ongoing process of evolution and iteration. Continuously evaluate the effectiveness of your architecture, gather feedback from users, and adapt as needed. Embrace an agile mindset that embraces change and allows for iterative improvements. Regularly assess the alignment of your IT architecture with business goals and adjust strategies accordingly.</p></li><li><strong>Collaborate with Technology Partners:</strong> Engage with technology partners and vendors who can provide expertise, solutions, and support for your adaptive IT architecture journey. Leverage their knowledge and experience to accelerate implementation.</li></ol><p><strong>Five Reasons to Pursue Adaptive Architecture</strong></p><ol><li><strong>Enhanced Scalability and Agility:</strong> In a rapidly changing business environment, scalability and agility are essential for organizations to respond quickly to market demands and seize new opportunities. Adaptive IT architecture provides the flexibility to scale resources up or down as needed, accommodating fluctuating workloads and business requirements. This scalability enables businesses to handle increased customer demands, seasonal peaks, or sudden growth without disruptions or resource constraints. Additionally, adaptive architecture allows for agile development and deployment of new applications and services, enabling businesses to stay ahead of the competition by rapidly delivering innovative solutions.</li><li><strong>Improved Integration and Interoperability:</strong> In today\'s interconnected business landscape, integration and interoperability are critical for seamless data exchange and collaboration across systems, departments, and external partners. An adaptive IT architecture facilitates smooth integration of disparate systems and applications, enabling efficient data flow and real-time information sharing. By breaking down silos and promoting interoperability, businesses can optimize their operations, streamline workflows, and enhance productivity. This integration also paves the way for future growth and expansion, as businesses can easily incorporate new technologies, platforms, and partnerships into their ecosystem.</li><li><strong>Cost Efficiency and Resource Optimization:</strong> While transitioning to adaptive IT architecture requires initial investments, it can result in long-term cost savings and resource optimization. Outdated systems often require extensive maintenance, support, and upgrades, leading to high operational costs. In contrast, adaptive architecture enables businesses to adopt a more modular and scalable approach, allowing them to optimize resource allocation and reduce unnecessary expenses. Cloud-based solutions, for example, eliminate the need for on-premises infrastructure, reducing hardware and maintenance costs. Additionally, an adaptive architecture allows businesses to leverage automation and self-service capabilities, freeing up IT resources for more strategic initiatives and reducing labor costs.</li><li><strong>Enhanced Business Continuity and Resilience:</strong> An adaptive IT architecture provides organizations with the necessary tools to enhance business continuity and resilience in the face of disruptions or unforeseen events. Traditional architectures with single points of failure or limited redundancy are susceptible to downtime and data loss. By leveraging cloud technologies, virtualization, and distributed systems, businesses can ensure data redundancy, implement robust disaster recovery strategies, and achieve high availability. This enables businesses to minimize downtime, protect critical data, and quickly recover from disruptions, safeguarding their operations and reputation.</li><li><strong>Compliance and Security:</strong> In an era where data privacy and security are paramount, an adaptive IT architecture offers significant advantages in terms of compliance and data protection. Regulations such as the General Data Protection Regulation (GDPR) and industry-specific requirements impose strict guidelines on how businesses handle and secure sensitive data. An adaptive architecture enables organizations to implement advanced security measures, such as encryption, access controls, and audit trails, to protect data throughout their lifecycle. Furthermore, the ability to quickly update and patch systems ensures that businesses stay compliant with evolving regulations and industry best practices.</li></ol><p><strong>Additional Considerations</strong></p><ol><li><strong>Emphasize User Experience:</strong> As technology evolves, so do user expectations. Prioritize user experience in your adaptive IT architecture by designing intuitive interfaces, seamless workflows, and personalized interactions. Incorporate user feedback and conduct usability tests to refine your systems and ensure they align with user needs and preferences.</li><li><strong>Leverage Automation and Intelligent Workflows:</strong> Automation plays a crucial role in adaptive IT architecture. Identify repetitive and manual processes that can be automated to streamline operations, reduce errors, and free up resources for more strategic tasks. Embrace intelligent workflows powered by AI and machine learning to enhance decision-making, optimize resource allocation, and improve efficiency.</li><li><strong>Implement Agile Development Methodologies:</strong> Agile methodologies, such as Scrum or Kanban, can greatly enhance the adaptability of your IT architecture. By breaking projects into smaller, manageable chunks, you can deliver incremental value and respond quickly to changing requirements. Regularly review and adapt your development processes to foster collaboration, transparency, and continuous improvement.</li><li><strong>Embrace DevOps Practices:</strong> DevOps is a set of practices that emphasize collaboration and integration between development and operations teams. By adopting DevOps principles, you can accelerate software delivery, increase deployment frequency, and improve overall system stability. Encourage cross-functional collaboration, automate testing and deployment processes, and foster a culture of shared responsibility and continuous improvement.</li><li><strong>Establish an Architecture Governance Framework:</strong> To ensure the effectiveness and sustainability of your adaptive IT architecture, establish a robust governance framework. Regularly review and update governance policies to adapt to changing circumstances and emerging technologies.</li></ol><p><strong>Conclusion</strong></p><p>By adopting an adaptive IT architecture, organizations can proactively respond to market dynamics, seize new opportunities, and deliver exceptional value to customers. Embrace change, embrace innovation, and embark on the journey to building an adaptive IT architecture that will position your business for long-term success in the digital age.</p><p>The journey towards adaptive IT architecture requires careful planning, effective management, and ongoing evaluation. It is not a one-time effort but a continuous process of optimization and adaptation. However, the rewards are substantial – increased operational efficiency, accelerated innovation, reduced costs, enhanced customer satisfaction, and sustainable business growth. Embrace the potential of an adaptive IT architecture and position your organization for success in the digital era.</p><p>In today\'s rapidly evolving business landscape, adaptive IT architecture is the key to unlocking business potential, driving innovation, and maintaining a competitive edge. By embracing flexibility, modularity, and agility, organizations can navigate the complexities of the digital age and capitalize on emerging opportunities.</p><p>Building an adaptive IT architecture requires a holistic mindset, organizational commitment, and a willingness to invest in technology, talent, and cultural transformation. By following best practices such as embracing cloud computing and other innately adaptive technologies, fostering a culture of innovation, prioritizing integration, swappable components, interoperability, and staying abreast of technological advancements, businesses can create a robust foundation for future growth and success.</p><p>The journey towards adaptive IT architecture is not merely a technical transformation but a cultural shift that embraces change, continuous learning, and collaboration. By aligning technology with business goals, managing risks, and fostering a culture of adaptability, businesses can position themselves as agile, resilient, and future-ready entities capable of thriving in the dynamic digital landscape. Embrace the power of an adaptive IT architecture and unleash your business\'s full potential.</p><p><strong>About The Author</strong></p><p><a href=\"https://www.linkedin.com/in/dougpicirillo/\">Douglas Picirillo</a> is a Senior Enterprise and Solutions Architect and IT Program Management Consultant. He specializes in Business Transformation and Value Creation enabled by Information Technology, IT transformation and cost reduction, Enterprise Systems Development, and IT Integration and Separation in Mergers and Acquisitions.</p><p>Mr. Picirillo has more than 30 years of IT experience in the public and non-profit sectors and numerous private sector industries, from SMBs to the Fortune 500. Doug’s paper, \"Artificial Intelligence in Mainstream Enterprise Applications\", was published in the peer-reviewed World Complexity Science Academy Journal (ISSN online: 2724-0606) in 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/artificial-intelligence-in-mainstream-enterprise-applications/\">https://lnkd.in/dgQEr8VE</a></p><p>To know more about how DivIHN Integration Inc. can help you in your journey for deploying robust \"Adaptive Enterprise Architecture\" please get in touch with him at Doug. <a href=\"mailto:doug.picirillo@divihn.com\">doug.picirillo@divihn.com</a></p>','','full_html'),('featured_article',0,81,481,'en',0,'<p>In the digital age, businesses must adopt an adaptive Enterprise Architecture to succeed. The vision, once realized, enables leveraging emerging technologies, scalability, agility, integration, cost optimization, regulatory compliance, and maximum business value.</p><p>Transitioning requires careful planning, change management, and a strategic vision. Partnering with experienced IT consultants facilitates the process. An adaptive Enterprise Architecture is the key for efficiency, agility, and innovation, empowering businesses to meet customer demands and stay competitive. By embracing this approach, organizations can streamline operations, enhance collaboration, create value for all stakeholders, and achieve sustainable growth.</p><p><strong>Introduction</strong></p><p>In today\'s dynamic business environment, the ability to quickly deploy new capabilities is a competitive necessity. However, organizations often fail to seize opportunities due to the perceived cost and risk of modernizing the systems that enable business capabilities. Information systems and technology platforms exist for a relatively simple set of reasons – to enable business operations and facilitate decision-making as the organization pursues evolving goals and opportunities.</p><p>Technology leaders must have a seat at the organization’s strategy table and allow for the inevitable changes of plan so that when requirements change, the business technology they manage is an enabler, not an impediment. Internal and external forces of change are permanent and pervasive. “Enterprise Architecture” sounds like something slow-moving, but today’s Enterprise Architects must design with continuous change in mind.</p><p><strong>Technological Forces of Change</strong></p><p>In 1965, Gordon Moore suggested the number of transistors on a typical computer chip would roughly double about every two years. Although we do not measure our progress in transistors per chip, Moore’s hypothesis has been validated in real life. In the ensuing 60 years, advances in computational capabilities have given mainstream businesses the ability to solve computational and information management problems at a scale that would have been considered far-fetched a generation ago.</p><p>In the first quarter of the 21st Century, we have seen an explosion of data – beyond a tsunami, more like a Big Bang. The good news is data management and processing capabilities have kept pace, allowing us to do interesting and useful things with all that data, enabling more efficient operations and facilitating informed decision-making.</p><p>Combined with the Internet, massive computing power and vast pools of information have created the real potential of a global data fabric and data marketplace based on broadly adopted cloud computing and democratized artificial intelligence. Nobody talks about data processing anymore. The daily conversations about automating operational and accounting processes to gain efficiency and reduce costs are a dim memory. Today we talk about information as a strategic asset and the ability to make the best use of it as a strategic capability.</p><p>In about ten years, Cloud computing has outgrown mere widespread adoption. It is now a standard feature of almost all enterprises’ information technology architecture. At the same time, Artificial Intelligence is advancing so rapidly that it has drawn the attention of ethicists and legislators. While they are thinking about the responsible use of AI, completely novel applications as well as spot solutions built into existing solutions appear in the marketplace almost daily.</p><p>The rapid pace of technological advancements requires businesses to constantly innovate and leverage new capabilities. Inflexible architectures and solutions hinder the adoption of emerging technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies have the potential to revolutionize operations, drive efficiency, and unlock valuable insights from data.</p><p><strong>Competitive Forces of Change</strong></p><p>Considering technological advances, competition has in no corner become less intense. Competitors are becoming more numerous, diverse, and global. In some markets the competition is consolidating, raising the barrier to entry, and making life increasingly difficult for independent players. Simultaneously, agile startups enter the market every day with new business models and game-changing technologies, challenging established firms to rethink the status quo, and in some cases, to adapt or perish.</p><p>In both mature and emerging markets architectural rigidity can lead to falling behind while competitors who have successfully integrated these technologies into their workflows, customer experiences, and decision-making processes.</p><p>An adaptive IT architecture that enables businesses to harness the power of emerging technologies and is a competitive necessity. The ability to seamlessly integrate innovative tools and systems empowers organizations to further automate processes, optimize resource allocation, and deliver personalized experiences to customers. The ability to quickly respond to market changes, customer demands, and disruptive forces is essential for sustained success in today\'s digital landscape.</p><p><strong>The Hybridization of Everything</strong></p><p>Thinking about the most successful organizations, and the most successful people in them, we can observe a trend: The Hybridization of Everything. Since the mid-1990s, hybridization has been seen as a necessity in organizations that want to do more, better, faster, and cheaper.</p><p>In the old organizations, the organizing principle was specialization: discrete departments, separate functions, independent projects. In the new organizations, it’s hybridization: inter-departmental meetings, cross-functional teams, integrated systems. Enterprise architectures must support pervasive hybridization.</p><p><strong>Hybrid Technology</strong></p><p>The Hybrid Cloud was one of the early materializations of this idea. It meant, some of our stuff is on premises and some of it in the cloud.” Today hybrid solutions take many forms, combining the benefits of disparate technologies for a single, mission-specific purpose. Information processing itself is becoming hybridized with traditional deterministic algorithms answering traditional questions alongside artificial intelligence which can suggest new questions.</p><p>AI-enhanced solutions are becoming commonplace, appearing in everything from office productivity suites to facial recognition solutions for border security, to large computational problems in climate science, economics, and more. The analog world in which we live is increasingly digitized by hybrid analog-digital devices that populate the Internet of Things, from talking (and listening) appliances to home security systems that allow you to close your garage door from the other side of the planet.</p><p>Adaptive Enterprise Architectures exploit hybrid technologies, both as a preference for the capabilities or adaptive technologies and as a response to the need to design for efficiency and responsiveness in today’s dynamic and competitive environment.</p><p><strong>The Demand for Modernization</strong></p><p>Several forces of change drive the demand for application modernization. Among them are…</p><ul><li><strong>Technical obsolescence of the infrastructure</strong> – The age of technology itself, and the aging of the workforce having the skills to support it can make a compelling case for replacement. Support gets more expensive and harder to find almost daily. Also known as Technical Debt, like most forms of debt it gets more expensive with the passage of time.</li><li><strong>Demand for a modern user experience</strong> – Some internal users of older information systems are often productive and happy doing their job by pressing F2 twice, typing something, and then pressing Enter twice. External users and most internal users expect a modern experience.</li><li><strong>Not Designed for Flexibility</strong> – Legacy applications were not based on today’s service-oriented design patterns and other innately adaptive frameworks. Even when they can be adapted to modern requirements, changes to monolithic applications can require extensive and widespread testing.</li></ul><p><strong>Enterprise Architecture and the Business of IT&nbsp;</strong></p><p>Technology Portfolio Management and Technology Business Management are closely related to Enterprise Architecture. Some consider them a discipline within Enterprise Architecture. They provide IT management frameworks that implement a standard IT spending taxonomy and process-enablement catalog.</p><p>Having a standard way to categorize IT costs, technologies, resources, applications, and services enables organizations to disaggregate IT spending into smaller, consistent categories to provide the leadership team with a more accurate and detailed understanding of their organization’s IT costs. This disciplined and business-like approach to managing IT enables enterprise architects to identify duplicate spending and redundant capabilities to make better informed decisions regarding future investments.</p><p>Organizations seeking to reduce IT sprawl or to rationalize their portfolio can develop a roadmap to deal with overspending and redundancy. Fully redundant applications can be retired. Other applications can be designated for migration to more cost-effective implementations. Some applications can be left alone. Those with the greatest potential for business value can be targeted for further investment as savings are achieved in other areas.</p><p><strong>The Adaptive Enterprise Architecture Response&nbsp;</strong></p><p>The core purpose of Enterprise Architecture is to apply holistic technology concepts to the enablement of business processes in furtherance of the organization’s mission. An Adaptive Enterprise Architecture perspective requires that flexibility and adaptability, without security compromises, are highly valued criteria for enterprise Information Technology decision-making.</p><p>Further, holistic Enterprise Architecture thinking encompasses the people and processes that plan, deploy, and operate Information Technology. Those people responsible for the architecture require a fulsome appreciation of the relationships between business goals, operational processes, to make informed decisions about information management systems and technology foundations. An Adaptive Enterprise Architecture strategy prioritizes pragmatism and flexibility not just in reaction to changing business needs but in anticipation of them.</p><p><strong>Threats&nbsp;</strong></p><p>The increasing number and sophistication of bad actors means changes the question from “Will I be attacked?” to “When will I be attacked?”. Cyber Security defenses must be incorporated into your technology blueprint with holistic architectural thinking. Every building block must be imagined as an element of the attack surface visible to bad actors.</p><p>An inflexible IT architecture based on monolithic systems poses a variety of related security and compliance risks. Older systems may lack the robust security measures needed to withstand advanced threats, making them vulnerable to cyber threats and data breaches. An adaptivity-focused architecture, having by nature a more complex attack surface poses a different of problems. In all cases, a holistic architectural approach based on Zero Trust principles and technologies like software-defined networks, and advanced vulnerability detection, along with a security-aware organizational culture, create a robust cyber immune system.</p><p>A strong perimeter defense is no longer good enough. Unless your systems are completely disconnected from the outside world, a bad actor will eventually penetrate even the strongest barriers. A holistic architecture incorporating Zero-Trust principles prevents free movement within your environment once that bad actor penetrates the perimeter.</p><p>Organizations must ensure that their IT architecture can adapt and withstand evolving security challenges. Non-compliance with industry regulations can result in substantial financial penalties and reputational damage. Adaptive IT architecture, on the other hand, allows for timely updates and enhancements to address emerging security and compliance requirements, providing organizations with peace of mind and a competitive advantage.</p><p><strong>The Adaptive Enterprise Architecture Journey – An Approach</strong></p><ol><li><p><strong>Define Business Objectives:</strong> The organization must articulate a strategy and business objectives, growth targets, and customer-centric goals.</p><p>Align IT strategies with these objectives to ensure that technology investments are aligned with business priorities. Engage key stakeholders from both IT and business units to gain a comprehensive understanding of the organization\'s strategic direction. The Enterprise Architecture function guides the evolution of the IT ecosystem to achieve and maintain alignment with organizational goals.</p><p>Identify the key areas where adaptive architecture can drive value, such as improving customer experience, enhancing operational efficiency, reducing costs, or enabling new revenue streams. By aligning your IT strategy with your business goals, you can ensure that your adaptive architecture initiatives have a meaningful impact on your organization\'s success.</p></li><li><p><strong>Assess the Current IT Landscape:</strong> Every passionate Enterprise Architect would love an opportunity to start with a clean sheet of paper. They rarely get one. Instead, they begin by conducting a thorough assessment of the existing IT infrastructure, systems, and applications.</p><p>Identify the strengths and weaknesses of your current architecture, using established frameworks for assessing architectural health to identify areas that hinder flexibility, scalability, and integration as well as apparent redundancies and potential areas of overspending. This assessment will provide valuable insights into the specific challenges your organization faces and help define the goals and objectives of your adaptive architecture.</p></li><li><p><strong>Develop a Future State Vision:</strong> Every good plan begins with the end in mind. Choose a foundation. Although adaptivity is the goal discussed here, stability is essential for effective support of business operations. Some long-term decision-making is unavoidable. The ability to swap components, redesign integrations, and so on is not a reason to avoid making big decisions about the core infrastructure and foundational technologies.</p><p>Design a sound foundation that innately supports swappable and scalable components. You might want to paint the house a new color every Spring. You will probably need to update the furniture appliances from time to time or even change the layout of the interior spaces, but build the house on a solid, long-lasting foundation.</p></li><li><strong>Develop a Roadmap:</strong> Create a comprehensive roadmap that outlines the steps, milestones, and timelines for transitioning to an adaptive IT architecture.<ol type=\"a\"><li>Don’t change everything at once! Segment the journey into manageable phases, prioritizing areas of critical need or areas that can provide immediate value. Consider the dependencies and interdependencies between different systems and processes, in-flight and planned projects, costs, and value and plan for effective change management to ensure a smooth transition and minimal disruption to ongoing operations.</li><li>Don’t set the roadmap in stone. Adaptivity involves continuous change in response to forces that are often unforeseen. It’s true that every well-managed program needs a roadmap, but in a future, adaptive world, there will be fewer roadmaps and more dynamic routing.</li></ol></li><li><p><strong>Continuously Monitor, Evolve and Adapt:</strong> Establish a framework for monitoring and evaluating the effectiveness of adaptive IT architecture. Regularly review performance metrics, customer feedback, and industry trends to identify areas for improvement and adapt strategies accordingly. Embrace a culture of continuous improvement and be open to feedback and suggestions from employees and customers.</p><p>An adaptive IT architecture is not a one-time implementation but an ongoing process of evolution and iteration. Continuously evaluate the effectiveness of your architecture, gather feedback from users, and adapt as needed. Embrace an agile mindset that embraces change and allows for iterative improvements. Regularly assess the alignment of your IT architecture with business goals and adjust strategies accordingly.</p></li><li><strong>Collaborate with Technology Partners:</strong> Engage with technology partners and vendors who can provide expertise, solutions, and support for your adaptive IT architecture journey. Leverage their knowledge and experience to accelerate implementation.</li></ol><p><strong>Five Reasons to Pursue Adaptive Architecture</strong></p><ol><li><strong>Enhanced Scalability and Agility:</strong> In a rapidly changing business environment, scalability and agility are essential for organizations to respond quickly to market demands and seize new opportunities. Adaptive IT architecture provides the flexibility to scale resources up or down as needed, accommodating fluctuating workloads and business requirements. This scalability enables businesses to handle increased customer demands, seasonal peaks, or sudden growth without disruptions or resource constraints. Additionally, adaptive architecture allows for agile development and deployment of new applications and services, enabling businesses to stay ahead of the competition by rapidly delivering innovative solutions.</li><li><strong>Improved Integration and Interoperability:</strong> In today\'s interconnected business landscape, integration and interoperability are critical for seamless data exchange and collaboration across systems, departments, and external partners. An adaptive IT architecture facilitates smooth integration of disparate systems and applications, enabling efficient data flow and real-time information sharing. By breaking down silos and promoting interoperability, businesses can optimize their operations, streamline workflows, and enhance productivity. This integration also paves the way for future growth and expansion, as businesses can easily incorporate new technologies, platforms, and partnerships into their ecosystem.</li><li><strong>Cost Efficiency and Resource Optimization:</strong> While transitioning to adaptive IT architecture requires initial investments, it can result in long-term cost savings and resource optimization. Outdated systems often require extensive maintenance, support, and upgrades, leading to high operational costs. In contrast, adaptive architecture enables businesses to adopt a more modular and scalable approach, allowing them to optimize resource allocation and reduce unnecessary expenses. Cloud-based solutions, for example, eliminate the need for on-premises infrastructure, reducing hardware and maintenance costs. Additionally, an adaptive architecture allows businesses to leverage automation and self-service capabilities, freeing up IT resources for more strategic initiatives and reducing labor costs.</li><li><strong>Enhanced Business Continuity and Resilience:</strong> An adaptive IT architecture provides organizations with the necessary tools to enhance business continuity and resilience in the face of disruptions or unforeseen events. Traditional architectures with single points of failure or limited redundancy are susceptible to downtime and data loss. By leveraging cloud technologies, virtualization, and distributed systems, businesses can ensure data redundancy, implement robust disaster recovery strategies, and achieve high availability. This enables businesses to minimize downtime, protect critical data, and quickly recover from disruptions, safeguarding their operations and reputation.</li><li><strong>Compliance and Security:</strong> In an era where data privacy and security are paramount, an adaptive IT architecture offers significant advantages in terms of compliance and data protection. Regulations such as the General Data Protection Regulation (GDPR) and industry-specific requirements impose strict guidelines on how businesses handle and secure sensitive data. An adaptive architecture enables organizations to implement advanced security measures, such as encryption, access controls, and audit trails, to protect data throughout their lifecycle. Furthermore, the ability to quickly update and patch systems ensures that businesses stay compliant with evolving regulations and industry best practices.</li></ol><p><strong>Additional Considerations</strong></p><ol><li><strong>Emphasize User Experience:</strong> As technology evolves, so do user expectations. Prioritize user experience in your adaptive IT architecture by designing intuitive interfaces, seamless workflows, and personalized interactions. Incorporate user feedback and conduct usability tests to refine your systems and ensure they align with user needs and preferences.</li><li><strong>Leverage Automation and Intelligent Workflows:</strong> Automation plays a crucial role in adaptive IT architecture. Identify repetitive and manual processes that can be automated to streamline operations, reduce errors, and free up resources for more strategic tasks. Embrace intelligent workflows powered by AI and machine learning to enhance decision-making, optimize resource allocation, and improve efficiency.</li><li><strong>Implement Agile Development Methodologies:</strong> Agile methodologies, such as Scrum or Kanban, can greatly enhance the adaptability of your IT architecture. By breaking projects into smaller, manageable chunks, you can deliver incremental value and respond quickly to changing requirements. Regularly review and adapt your development processes to foster collaboration, transparency, and continuous improvement.</li><li><strong>Embrace DevOps Practices:</strong> DevOps is a set of practices that emphasize collaboration and integration between development and operations teams. By adopting DevOps principles, you can accelerate software delivery, increase deployment frequency, and improve overall system stability. Encourage cross-functional collaboration, automate testing and deployment processes, and foster a culture of shared responsibility and continuous improvement.</li><li><strong>Establish an Architecture Governance Framework:</strong> To ensure the effectiveness and sustainability of your adaptive IT architecture, establish a robust governance framework. Regularly review and update governance policies to adapt to changing circumstances and emerging technologies.</li></ol><p><strong>Conclusion</strong></p><p>By adopting an adaptive IT architecture, organizations can proactively respond to market dynamics, seize new opportunities, and deliver exceptional value to customers. Embrace change, embrace innovation, and embark on the journey to building an adaptive IT architecture that will position your business for long-term success in the digital age.</p><p>The journey towards adaptive IT architecture requires careful planning, effective management, and ongoing evaluation. It is not a one-time effort but a continuous process of optimization and adaptation. However, the rewards are substantial – increased operational efficiency, accelerated innovation, reduced costs, enhanced customer satisfaction, and sustainable business growth. Embrace the potential of an adaptive IT architecture and position your organization for success in the digital era.</p><p>In today\'s rapidly evolving business landscape, adaptive IT architecture is the key to unlocking business potential, driving innovation, and maintaining a competitive edge. By embracing flexibility, modularity, and agility, organizations can navigate the complexities of the digital age and capitalize on emerging opportunities.</p><p>Building an adaptive IT architecture requires a holistic mindset, organizational commitment, and a willingness to invest in technology, talent, and cultural transformation. By following best practices such as embracing cloud computing and other innately adaptive technologies, fostering a culture of innovation, prioritizing integration, swappable components, interoperability, and staying abreast of technological advancements, businesses can create a robust foundation for future growth and success.</p><p>The journey towards adaptive IT architecture is not merely a technical transformation but a cultural shift that embraces change, continuous learning, and collaboration. By aligning technology with business goals, managing risks, and fostering a culture of adaptability, businesses can position themselves as agile, resilient, and future-ready entities capable of thriving in the dynamic digital landscape. Embrace the power of an adaptive IT architecture and unleash your business\'s full potential.</p><p><strong>About The Author</strong></p><p><a href=\"https://www.linkedin.com/in/dougpicirillo/\">Douglas Picirillo</a> is a Senior Enterprise and Solutions Architect and IT Program Management Consultant. He specializes in Business Transformation and Value Creation enabled by Information Technology, IT transformation and cost reduction, Enterprise Systems Development, and IT Integration and Separation in Mergers and Acquisitions.</p><p>Mr. Picirillo has more than 30 years of IT experience in the public and non-profit sectors and numerous private sector industries, from SMBs to the Fortune 500. Doug’s paper, \"Artificial Intelligence in Mainstream Enterprise Applications\", was published in the peer-reviewed World Complexity Science Academy Journal (ISSN online: 2724-0606) in 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/artificial-intelligence-in-mainstream-enterprise-applications/\">https://lnkd.in/dgQEr8VE</a></p><p>To know more about how DivIHN Integration Inc. can help you in your journey for deploying robust \"Adaptive Enterprise Architecture\" please get in touch with him at Doug. <a href=\"mailto:doug.picirillo@divihn.com\">doug.picirillo@divihn.com</a></p>','','full_html'),('featured_article',0,81,561,'en',0,'<p>In the digital age, businesses must adopt an adaptive Enterprise Architecture to succeed. The vision, once realized, enables leveraging emerging technologies, scalability, agility, integration, cost optimization, regulatory compliance, and maximum business value.</p><p>Transitioning requires careful planning, change management, and a strategic vision. Partnering with experienced IT consultants facilitates the process. An adaptive Enterprise Architecture is the key for efficiency, agility, and innovation, empowering businesses to meet customer demands and stay competitive. By embracing this approach, organizations can streamline operations, enhance collaboration, create value for all stakeholders, and achieve sustainable growth.</p><p><strong>Introduction</strong></p><p>In today\'s dynamic business environment, the ability to quickly deploy new capabilities is a competitive necessity. However, organizations often fail to seize opportunities due to the perceived cost and risk of modernizing the systems that enable business capabilities. Information systems and technology platforms exist for a relatively simple set of reasons – to enable business operations and facilitate decision-making as the organization pursues evolving goals and opportunities.</p><p>Technology leaders must have a seat at the organization’s strategy table and allow for the inevitable changes of plan so that when requirements change, the business technology they manage is an enabler, not an impediment. Internal and external forces of change are permanent and pervasive. “Enterprise Architecture” sounds like something slow-moving, but today’s Enterprise Architects must design with continuous change in mind.</p><p><strong>Technological Forces of Change</strong></p><p>In 1965, Gordon Moore suggested the number of transistors on a typical computer chip would roughly double about every two years. Although we do not measure our progress in transistors per chip, Moore’s hypothesis has been validated in real life. In the ensuing 60 years, advances in computational capabilities have given mainstream businesses the ability to solve computational and information management problems at a scale that would have been considered far-fetched a generation ago.</p><p>In the first quarter of the 21st Century, we have seen an explosion of data – beyond a tsunami, more like a Big Bang. The good news is data management and processing capabilities have kept pace, allowing us to do interesting and useful things with all that data, enabling more efficient operations and facilitating informed decision-making.</p><p>Combined with the Internet, massive computing power and vast pools of information have created the real potential of a global data fabric and data marketplace based on broadly adopted cloud computing and democratized artificial intelligence. Nobody talks about data processing anymore. The daily conversations about automating operational and accounting processes to gain efficiency and reduce costs are a dim memory. Today we talk about information as a strategic asset and the ability to make the best use of it as a strategic capability.</p><p>In about ten years, Cloud computing has outgrown mere widespread adoption. It is now a standard feature of almost all enterprises’ information technology architecture. At the same time, Artificial Intelligence is advancing so rapidly that it has drawn the attention of ethicists and legislators. While they are thinking about the responsible use of AI, completely novel applications as well as spot solutions built into existing solutions appear in the marketplace almost daily.</p><p>The rapid pace of technological advancements requires businesses to constantly innovate and leverage new capabilities. Inflexible architectures and solutions hinder the adoption of emerging technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies have the potential to revolutionize operations, drive efficiency, and unlock valuable insights from data.</p><p><strong>Competitive Forces of Change</strong></p><p>Considering technological advances, competition has in no corner become less intense. Competitors are becoming more numerous, diverse, and global. In some markets the competition is consolidating, raising the barrier to entry, and making life increasingly difficult for independent players. Simultaneously, agile startups enter the market every day with new business models and game-changing technologies, challenging established firms to rethink the status quo, and in some cases, to adapt or perish.</p><p>In both mature and emerging markets architectural rigidity can lead to falling behind while competitors who have successfully integrated these technologies into their workflows, customer experiences, and decision-making processes.</p><p>An adaptive IT architecture that enables businesses to harness the power of emerging technologies and is a competitive necessity. The ability to seamlessly integrate innovative tools and systems empowers organizations to further automate processes, optimize resource allocation, and deliver personalized experiences to customers. The ability to quickly respond to market changes, customer demands, and disruptive forces is essential for sustained success in today\'s digital landscape.</p><p><strong>The Hybridization of Everything</strong></p><p>Thinking about the most successful organizations, and the most successful people in them, we can observe a trend: The Hybridization of Everything. Since the mid-1990s, hybridization has been seen as a necessity in organizations that want to do more, better, faster, and cheaper.</p><p>In the old organizations, the organizing principle was specialization: discrete departments, separate functions, independent projects. In the new organizations, it’s hybridization: inter-departmental meetings, cross-functional teams, integrated systems. Enterprise architectures must support pervasive hybridization.</p><p><strong>Hybrid Technology</strong></p><p>The Hybrid Cloud was one of the early materializations of this idea. It meant, some of our stuff is on premises and some of it in the cloud.” Today hybrid solutions take many forms, combining the benefits of disparate technologies for a single, mission-specific purpose. Information processing itself is becoming hybridized with traditional deterministic algorithms answering traditional questions alongside artificial intelligence which can suggest new questions.</p><p>AI-enhanced solutions are becoming commonplace, appearing in everything from office productivity suites to facial recognition solutions for border security, to large computational problems in climate science, economics, and more. The analog world in which we live is increasingly digitized by hybrid analog-digital devices that populate the Internet of Things, from talking (and listening) appliances to home security systems that allow you to close your garage door from the other side of the planet.</p><p>Adaptive Enterprise Architectures exploit hybrid technologies, both as a preference for the capabilities or adaptive technologies and as a response to the need to design for efficiency and responsiveness in today’s dynamic and competitive environment.</p><p><strong>The Demand for Modernization</strong></p><p>Several forces of change drive the demand for application modernization. Among them are…</p><ul><li><strong>Technical obsolescence of the infrastructure</strong> – The age of technology itself, and the aging of the workforce having the skills to support it can make a compelling case for replacement. Support gets more expensive and harder to find almost daily. Also known as Technical Debt, like most forms of debt it gets more expensive with the passage of time.</li><li><strong>Demand for a modern user experience</strong> – Some internal users of older information systems are often productive and happy doing their job by pressing F2 twice, typing something, and then pressing Enter twice. External users and most internal users expect a modern experience.</li><li><strong>Not Designed for Flexibility</strong> – Legacy applications were not based on today’s service-oriented design patterns and other innately adaptive frameworks. Even when they can be adapted to modern requirements, changes to monolithic applications can require extensive and widespread testing.</li></ul><p><strong>Enterprise Architecture and the Business of IT&nbsp;</strong></p><p>Technology Portfolio Management and Technology Business Management are closely related to Enterprise Architecture. Some consider them a discipline within Enterprise Architecture. They provide IT management frameworks that implement a standard IT spending taxonomy and process-enablement catalog.</p><p>Having a standard way to categorize IT costs, technologies, resources, applications, and services enables organizations to disaggregate IT spending into smaller, consistent categories to provide the leadership team with a more accurate and detailed understanding of their organization’s IT costs. This disciplined and business-like approach to managing IT enables enterprise architects to identify duplicate spending and redundant capabilities to make better informed decisions regarding future investments.</p><p>Organizations seeking to reduce IT sprawl or to rationalize their portfolio can develop a roadmap to deal with overspending and redundancy. Fully redundant applications can be retired. Other applications can be designated for migration to more cost-effective implementations. Some applications can be left alone. Those with the greatest potential for business value can be targeted for further investment as savings are achieved in other areas.</p><p><strong>The Adaptive Enterprise Architecture Response&nbsp;</strong></p><p>The core purpose of Enterprise Architecture is to apply holistic technology concepts to the enablement of business processes in furtherance of the organization’s mission. An Adaptive Enterprise Architecture perspective requires that flexibility and adaptability, without security compromises, are highly valued criteria for enterprise Information Technology decision-making.</p><p>Further, holistic Enterprise Architecture thinking encompasses the people and processes that plan, deploy, and operate Information Technology. Those people responsible for the architecture require a fulsome appreciation of the relationships between business goals, operational processes, to make informed decisions about information management systems and technology foundations. An Adaptive Enterprise Architecture strategy prioritizes pragmatism and flexibility not just in reaction to changing business needs but in anticipation of them.</p><p><strong>Threats&nbsp;</strong></p><p>The increasing number and sophistication of bad actors means changes the question from “Will I be attacked?” to “When will I be attacked?”. Cyber Security defenses must be incorporated into your technology blueprint with holistic architectural thinking. Every building block must be imagined as an element of the attack surface visible to bad actors.</p><p>An inflexible IT architecture based on monolithic systems poses a variety of related security and compliance risks. Older systems may lack the robust security measures needed to withstand advanced threats, making them vulnerable to cyber threats and data breaches. An adaptivity-focused architecture, having by nature a more complex attack surface poses a different of problems. In all cases, a holistic architectural approach based on Zero Trust principles and technologies like software-defined networks, and advanced vulnerability detection, along with a security-aware organizational culture, create a robust cyber immune system.</p><p>A strong perimeter defense is no longer good enough. Unless your systems are completely disconnected from the outside world, a bad actor will eventually penetrate even the strongest barriers. A holistic architecture incorporating Zero-Trust principles prevents free movement within your environment once that bad actor penetrates the perimeter.</p><p>Organizations must ensure that their IT architecture can adapt and withstand evolving security challenges. Non-compliance with industry regulations can result in substantial financial penalties and reputational damage. Adaptive IT architecture, on the other hand, allows for timely updates and enhancements to address emerging security and compliance requirements, providing organizations with peace of mind and a competitive advantage.</p><p><strong>The Adaptive Enterprise Architecture Journey – An Approach</strong></p><ol><li><p><strong>Define Business Objectives:</strong> The organization must articulate a strategy and business objectives, growth targets, and customer-centric goals.</p><p>Align IT strategies with these objectives to ensure that technology investments are aligned with business priorities. Engage key stakeholders from both IT and business units to gain a comprehensive understanding of the organization\'s strategic direction. The Enterprise Architecture function guides the evolution of the IT ecosystem to achieve and maintain alignment with organizational goals.</p><p>Identify the key areas where adaptive architecture can drive value, such as improving customer experience, enhancing operational efficiency, reducing costs, or enabling new revenue streams. By aligning your IT strategy with your business goals, you can ensure that your adaptive architecture initiatives have a meaningful impact on your organization\'s success.</p></li><li><p><strong>Assess the Current IT Landscape:</strong> Every passionate Enterprise Architect would love an opportunity to start with a clean sheet of paper. They rarely get one. Instead, they begin by conducting a thorough assessment of the existing IT infrastructure, systems, and applications.</p><p>Identify the strengths and weaknesses of your current architecture, using established frameworks for assessing architectural health to identify areas that hinder flexibility, scalability, and integration as well as apparent redundancies and potential areas of overspending. This assessment will provide valuable insights into the specific challenges your organization faces and help define the goals and objectives of your adaptive architecture.</p></li><li><p><strong>Develop a Future State Vision:</strong> Every good plan begins with the end in mind. Choose a foundation. Although adaptivity is the goal discussed here, stability is essential for effective support of business operations. Some long-term decision-making is unavoidable. The ability to swap components, redesign integrations, and so on is not a reason to avoid making big decisions about the core infrastructure and foundational technologies.</p><p>Design a sound foundation that innately supports swappable and scalable components. You might want to paint the house a new color every Spring. You will probably need to update the furniture appliances from time to time or even change the layout of the interior spaces, but build the house on a solid, long-lasting foundation.</p></li><li><strong>Develop a Roadmap:</strong> Create a comprehensive roadmap that outlines the steps, milestones, and timelines for transitioning to an adaptive IT architecture.<ol type=\"a\"><li>Don’t change everything at once! Segment the journey into manageable phases, prioritizing areas of critical need or areas that can provide immediate value. Consider the dependencies and interdependencies between different systems and processes, in-flight and planned projects, costs, and value and plan for effective change management to ensure a smooth transition and minimal disruption to ongoing operations.</li><li>Don’t set the roadmap in stone. Adaptivity involves continuous change in response to forces that are often unforeseen. It’s true that every well-managed program needs a roadmap, but in a future, adaptive world, there will be fewer roadmaps and more dynamic routing.</li></ol></li><li><p><strong>Continuously Monitor, Evolve and Adapt:</strong> Establish a framework for monitoring and evaluating the effectiveness of adaptive IT architecture. Regularly review performance metrics, customer feedback, and industry trends to identify areas for improvement and adapt strategies accordingly. Embrace a culture of continuous improvement and be open to feedback and suggestions from employees and customers.</p><p>An adaptive IT architecture is not a one-time implementation but an ongoing process of evolution and iteration. Continuously evaluate the effectiveness of your architecture, gather feedback from users, and adapt as needed. Embrace an agile mindset that embraces change and allows for iterative improvements. Regularly assess the alignment of your IT architecture with business goals and adjust strategies accordingly.</p></li><li><strong>Collaborate with Technology Partners:</strong> Engage with technology partners and vendors who can provide expertise, solutions, and support for your adaptive IT architecture journey. Leverage their knowledge and experience to accelerate implementation.</li></ol><p><strong>Five Reasons to Pursue Adaptive Architecture</strong></p><ol><li><strong>Enhanced Scalability and Agility:</strong> In a rapidly changing business environment, scalability and agility are essential for organizations to respond quickly to market demands and seize new opportunities. Adaptive IT architecture provides the flexibility to scale resources up or down as needed, accommodating fluctuating workloads and business requirements. This scalability enables businesses to handle increased customer demands, seasonal peaks, or sudden growth without disruptions or resource constraints. Additionally, adaptive architecture allows for agile development and deployment of new applications and services, enabling businesses to stay ahead of the competition by rapidly delivering innovative solutions.</li><li><strong>Improved Integration and Interoperability:</strong> In today\'s interconnected business landscape, integration and interoperability are critical for seamless data exchange and collaboration across systems, departments, and external partners. An adaptive IT architecture facilitates smooth integration of disparate systems and applications, enabling efficient data flow and real-time information sharing. By breaking down silos and promoting interoperability, businesses can optimize their operations, streamline workflows, and enhance productivity. This integration also paves the way for future growth and expansion, as businesses can easily incorporate new technologies, platforms, and partnerships into their ecosystem.</li><li><strong>Cost Efficiency and Resource Optimization:</strong> While transitioning to adaptive IT architecture requires initial investments, it can result in long-term cost savings and resource optimization. Outdated systems often require extensive maintenance, support, and upgrades, leading to high operational costs. In contrast, adaptive architecture enables businesses to adopt a more modular and scalable approach, allowing them to optimize resource allocation and reduce unnecessary expenses. Cloud-based solutions, for example, eliminate the need for on-premises infrastructure, reducing hardware and maintenance costs. Additionally, an adaptive architecture allows businesses to leverage automation and self-service capabilities, freeing up IT resources for more strategic initiatives and reducing labor costs.</li><li><strong>Enhanced Business Continuity and Resilience:</strong> An adaptive IT architecture provides organizations with the necessary tools to enhance business continuity and resilience in the face of disruptions or unforeseen events. Traditional architectures with single points of failure or limited redundancy are susceptible to downtime and data loss. By leveraging cloud technologies, virtualization, and distributed systems, businesses can ensure data redundancy, implement robust disaster recovery strategies, and achieve high availability. This enables businesses to minimize downtime, protect critical data, and quickly recover from disruptions, safeguarding their operations and reputation.</li><li><strong>Compliance and Security:</strong> In an era where data privacy and security are paramount, an adaptive IT architecture offers significant advantages in terms of compliance and data protection. Regulations such as the General Data Protection Regulation (GDPR) and industry-specific requirements impose strict guidelines on how businesses handle and secure sensitive data. An adaptive architecture enables organizations to implement advanced security measures, such as encryption, access controls, and audit trails, to protect data throughout their lifecycle. Furthermore, the ability to quickly update and patch systems ensures that businesses stay compliant with evolving regulations and industry best practices.</li></ol><p><strong>Additional Considerations</strong></p><ol><li><strong>Emphasize User Experience:</strong> As technology evolves, so do user expectations. Prioritize user experience in your adaptive IT architecture by designing intuitive interfaces, seamless workflows, and personalized interactions. Incorporate user feedback and conduct usability tests to refine your systems and ensure they align with user needs and preferences.</li><li><strong>Leverage Automation and Intelligent Workflows:</strong> Automation plays a crucial role in adaptive IT architecture. Identify repetitive and manual processes that can be automated to streamline operations, reduce errors, and free up resources for more strategic tasks. Embrace intelligent workflows powered by AI and machine learning to enhance decision-making, optimize resource allocation, and improve efficiency.</li><li><strong>Implement Agile Development Methodologies:</strong> Agile methodologies, such as Scrum or Kanban, can greatly enhance the adaptability of your IT architecture. By breaking projects into smaller, manageable chunks, you can deliver incremental value and respond quickly to changing requirements. Regularly review and adapt your development processes to foster collaboration, transparency, and continuous improvement.</li><li><strong>Embrace DevOps Practices:</strong> DevOps is a set of practices that emphasize collaboration and integration between development and operations teams. By adopting DevOps principles, you can accelerate software delivery, increase deployment frequency, and improve overall system stability. Encourage cross-functional collaboration, automate testing and deployment processes, and foster a culture of shared responsibility and continuous improvement.</li><li><strong>Establish an Architecture Governance Framework:</strong> To ensure the effectiveness and sustainability of your adaptive IT architecture, establish a robust governance framework. Regularly review and update governance policies to adapt to changing circumstances and emerging technologies.</li></ol><p><strong>Conclusion</strong></p><p>By adopting an adaptive IT architecture, organizations can proactively respond to market dynamics, seize new opportunities, and deliver exceptional value to customers. Embrace change, embrace innovation, and embark on the journey to building an adaptive IT architecture that will position your business for long-term success in the digital age.</p><p>The journey towards adaptive IT architecture requires careful planning, effective management, and ongoing evaluation. It is not a one-time effort but a continuous process of optimization and adaptation. However, the rewards are substantial – increased operational efficiency, accelerated innovation, reduced costs, enhanced customer satisfaction, and sustainable business growth. Embrace the potential of an adaptive IT architecture and position your organization for success in the digital era.</p><p>In today\'s rapidly evolving business landscape, adaptive IT architecture is the key to unlocking business potential, driving innovation, and maintaining a competitive edge. By embracing flexibility, modularity, and agility, organizations can navigate the complexities of the digital age and capitalize on emerging opportunities.</p><p>Building an adaptive IT architecture requires a holistic mindset, organizational commitment, and a willingness to invest in technology, talent, and cultural transformation. By following best practices such as embracing cloud computing and other innately adaptive technologies, fostering a culture of innovation, prioritizing integration, swappable components, interoperability, and staying abreast of technological advancements, businesses can create a robust foundation for future growth and success.</p><p>The journey towards adaptive IT architecture is not merely a technical transformation but a cultural shift that embraces change, continuous learning, and collaboration. By aligning technology with business goals, managing risks, and fostering a culture of adaptability, businesses can position themselves as agile, resilient, and future-ready entities capable of thriving in the dynamic digital landscape. Embrace the power of an adaptive IT architecture and unleash your business\'s full potential.</p><p><strong>About The Author</strong></p><p><a href=\"https://www.linkedin.com/in/dougpicirillo/\">Douglas Picirillo</a> is a Senior Enterprise and Solutions Architect and IT Program Management Consultant. He specializes in Business Transformation and Value Creation enabled by Information Technology, IT transformation and cost reduction, Enterprise Systems Development, and IT Integration and Separation in Mergers and Acquisitions.</p><p>Mr. Picirillo has more than 30 years of IT experience in the public and non-profit sectors and numerous private sector industries, from SMBs to the Fortune 500. Doug’s paper, \"Artificial Intelligence in Mainstream Enterprise Applications\", was published in the peer-reviewed World Complexity Science Academy Journal (ISSN online: 2724-0606) in 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/artificial-intelligence-in-mainstream-enterprise-applications/\">https://lnkd.in/dgQEr8VE</a></p><p>To know more about how DivIHN Integration Inc. can help you in your journey for deploying robust \"Adaptive Enterprise Architecture\" please get in touch with him at Doug. <a href=\"mailto:doug.picirillo@divihn.com\">doug.picirillo@divihn.com</a></p>','','full_html'),('featured_article',0,81,636,'en',0,'<p>In the digital age, businesses must adopt an adaptive Enterprise Architecture to succeed. The vision, once realized, enables leveraging emerging technologies, scalability, agility, integration, cost optimization, regulatory compliance, and maximum business value.</p><p>Transitioning requires careful planning, change management, and a strategic vision. Partnering with experienced IT consultants facilitates the process. An adaptive Enterprise Architecture is the key for efficiency, agility, and innovation, empowering businesses to meet customer demands and stay competitive. By embracing this approach, organizations can streamline operations, enhance collaboration, create value for all stakeholders, and achieve sustainable growth.</p><p><strong>Introduction</strong></p><p>In today\'s dynamic business environment, the ability to quickly deploy new capabilities is a competitive necessity. However, organizations often fail to seize opportunities due to the perceived cost and risk of modernizing the systems that enable business capabilities. Information systems and technology platforms exist for a relatively simple set of reasons – to enable business operations and facilitate decision-making as the organization pursues evolving goals and opportunities.</p><p>Technology leaders must have a seat at the organization’s strategy table and allow for the inevitable changes of plan so that when requirements change, the business technology they manage is an enabler, not an impediment. Internal and external forces of change are permanent and pervasive. “Enterprise Architecture” sounds like something slow-moving, but today’s Enterprise Architects must design with continuous change in mind.</p><p><strong>Technological Forces of Change</strong></p><p>In 1965, Gordon Moore suggested the number of transistors on a typical computer chip would roughly double about every two years. Although we do not measure our progress in transistors per chip, Moore’s hypothesis has been validated in real life. In the ensuing 60 years, advances in computational capabilities have given mainstream businesses the ability to solve computational and information management problems at a scale that would have been considered far-fetched a generation ago.</p><p>In the first quarter of the 21st Century, we have seen an explosion of data – beyond a tsunami, more like a Big Bang. The good news is data management and processing capabilities have kept pace, allowing us to do interesting and useful things with all that data, enabling more efficient operations and facilitating informed decision-making.</p><p>Combined with the Internet, massive computing power and vast pools of information have created the real potential of a global data fabric and data marketplace based on broadly adopted cloud computing and democratized artificial intelligence. Nobody talks about data processing anymore. The daily conversations about automating operational and accounting processes to gain efficiency and reduce costs are a dim memory. Today we talk about information as a strategic asset and the ability to make the best use of it as a strategic capability.</p><p>In about ten years, Cloud computing has outgrown mere widespread adoption. It is now a standard feature of almost all enterprises’ information technology architecture. At the same time, Artificial Intelligence is advancing so rapidly that it has drawn the attention of ethicists and legislators. While they are thinking about the responsible use of AI, completely novel applications as well as spot solutions built into existing solutions appear in the marketplace almost daily.</p><p>The rapid pace of technological advancements requires businesses to constantly innovate and leverage new capabilities. Inflexible architectures and solutions hinder the adoption of emerging technologies such as artificial intelligence, machine learning, and the Internet of Things. These technologies have the potential to revolutionize operations, drive efficiency, and unlock valuable insights from data.</p><p><strong>Competitive Forces of Change</strong></p><p>Considering technological advances, competition has in no corner become less intense. Competitors are becoming more numerous, diverse, and global. In some markets the competition is consolidating, raising the barrier to entry, and making life increasingly difficult for independent players. Simultaneously, agile startups enter the market every day with new business models and game-changing technologies, challenging established firms to rethink the status quo, and in some cases, to adapt or perish.</p><p>In both mature and emerging markets architectural rigidity can lead to falling behind while competitors who have successfully integrated these technologies into their workflows, customer experiences, and decision-making processes.</p><p>An adaptive IT architecture that enables businesses to harness the power of emerging technologies and is a competitive necessity. The ability to seamlessly integrate innovative tools and systems empowers organizations to further automate processes, optimize resource allocation, and deliver personalized experiences to customers. The ability to quickly respond to market changes, customer demands, and disruptive forces is essential for sustained success in today\'s digital landscape.</p><p><strong>The Hybridization of Everything</strong></p><p>Thinking about the most successful organizations, and the most successful people in them, we can observe a trend: The Hybridization of Everything. Since the mid-1990s, hybridization has been seen as a necessity in organizations that want to do more, better, faster, and cheaper.</p><p>In the old organizations, the organizing principle was specialization: discrete departments, separate functions, independent projects. In the new organizations, it’s hybridization: inter-departmental meetings, cross-functional teams, integrated systems. Enterprise architectures must support pervasive hybridization.</p><p><strong>Hybrid Technology</strong></p><p>The Hybrid Cloud was one of the early materializations of this idea. It meant, some of our stuff is on premises and some of it in the cloud.” Today hybrid solutions take many forms, combining the benefits of disparate technologies for a single, mission-specific purpose. Information processing itself is becoming hybridized with traditional deterministic algorithms answering traditional questions alongside artificial intelligence which can suggest new questions.</p><p>AI-enhanced solutions are becoming commonplace, appearing in everything from office productivity suites to facial recognition solutions for border security, to large computational problems in climate science, economics, and more. The analog world in which we live is increasingly digitized by hybrid analog-digital devices that populate the Internet of Things, from talking (and listening) appliances to home security systems that allow you to close your garage door from the other side of the planet.</p><p>Adaptive Enterprise Architectures exploit hybrid technologies, both as a preference for the capabilities or adaptive technologies and as a response to the need to design for efficiency and responsiveness in today’s dynamic and competitive environment.</p><p><strong>The Demand for Modernization</strong></p><p>Several forces of change drive the demand for application modernization. Among them are…</p><ul><li><strong>Technical obsolescence of the infrastructure</strong> – The age of technology itself, and the aging of the workforce having the skills to support it can make a compelling case for replacement. Support gets more expensive and harder to find almost daily. Also known as Technical Debt, like most forms of debt it gets more expensive with the passage of time.</li><li><strong>Demand for a modern user experience</strong> – Some internal users of older information systems are often productive and happy doing their job by pressing F2 twice, typing something, and then pressing Enter twice. External users and most internal users expect a modern experience.</li><li><strong>Not Designed for Flexibility</strong> – Legacy applications were not based on today’s service-oriented design patterns and other innately adaptive frameworks. Even when they can be adapted to modern requirements, changes to monolithic applications can require extensive and widespread testing.</li></ul><p><strong>Enterprise Architecture and the Business of IT&nbsp;</strong></p><p>Technology Portfolio Management and Technology Business Management are closely related to Enterprise Architecture. Some consider them a discipline within Enterprise Architecture. They provide IT management frameworks that implement a standard IT spending taxonomy and process-enablement catalog.</p><p>Having a standard way to categorize IT costs, technologies, resources, applications, and services enables organizations to disaggregate IT spending into smaller, consistent categories to provide the leadership team with a more accurate and detailed understanding of their organization’s IT costs. This disciplined and business-like approach to managing IT enables enterprise architects to identify duplicate spending and redundant capabilities to make better informed decisions regarding future investments.</p><p>Organizations seeking to reduce IT sprawl or to rationalize their portfolio can develop a roadmap to deal with overspending and redundancy. Fully redundant applications can be retired. Other applications can be designated for migration to more cost-effective implementations. Some applications can be left alone. Those with the greatest potential for business value can be targeted for further investment as savings are achieved in other areas.</p><p><strong>The Adaptive Enterprise Architecture Response&nbsp;</strong></p><p>The core purpose of Enterprise Architecture is to apply holistic technology concepts to the enablement of business processes in furtherance of the organization’s mission. An Adaptive Enterprise Architecture perspective requires that flexibility and adaptability, without security compromises, are highly valued criteria for enterprise Information Technology decision-making.</p><p>Further, holistic Enterprise Architecture thinking encompasses the people and processes that plan, deploy, and operate Information Technology. Those people responsible for the architecture require a fulsome appreciation of the relationships between business goals, operational processes, to make informed decisions about information management systems and technology foundations. An Adaptive Enterprise Architecture strategy prioritizes pragmatism and flexibility not just in reaction to changing business needs but in anticipation of them.</p><p><strong>Threats&nbsp;</strong></p><p>The increasing number and sophistication of bad actors means changes the question from “Will I be attacked?” to “When will I be attacked?”. Cyber Security defenses must be incorporated into your technology blueprint with holistic architectural thinking. Every building block must be imagined as an element of the attack surface visible to bad actors.</p><p>An inflexible IT architecture based on monolithic systems poses a variety of related security and compliance risks. Older systems may lack the robust security measures needed to withstand advanced threats, making them vulnerable to cyber threats and data breaches. An adaptivity-focused architecture, having by nature a more complex attack surface poses a different of problems. In all cases, a holistic architectural approach based on Zero Trust principles and technologies like software-defined networks, and advanced vulnerability detection, along with a security-aware organizational culture, create a robust cyber immune system.</p><p>A strong perimeter defense is no longer good enough. Unless your systems are completely disconnected from the outside world, a bad actor will eventually penetrate even the strongest barriers. A holistic architecture incorporating Zero-Trust principles prevents free movement within your environment once that bad actor penetrates the perimeter.</p><p>Organizations must ensure that their IT architecture can adapt and withstand evolving security challenges. Non-compliance with industry regulations can result in substantial financial penalties and reputational damage. Adaptive IT architecture, on the other hand, allows for timely updates and enhancements to address emerging security and compliance requirements, providing organizations with peace of mind and a competitive advantage.</p><p><strong>The Adaptive Enterprise Architecture Journey – An Approach</strong></p><ol><li><p><strong>Define Business Objectives:</strong> The organization must articulate a strategy and business objectives, growth targets, and customer-centric goals.</p><p>Align IT strategies with these objectives to ensure that technology investments are aligned with business priorities. Engage key stakeholders from both IT and business units to gain a comprehensive understanding of the organization\'s strategic direction. The Enterprise Architecture function guides the evolution of the IT ecosystem to achieve and maintain alignment with organizational goals.</p><p>Identify the key areas where adaptive architecture can drive value, such as improving customer experience, enhancing operational efficiency, reducing costs, or enabling new revenue streams. By aligning your IT strategy with your business goals, you can ensure that your adaptive architecture initiatives have a meaningful impact on your organization\'s success.</p></li><li><p><strong>Assess the Current IT Landscape:</strong> Every passionate Enterprise Architect would love an opportunity to start with a clean sheet of paper. They rarely get one. Instead, they begin by conducting a thorough assessment of the existing IT infrastructure, systems, and applications.</p><p>Identify the strengths and weaknesses of your current architecture, using established frameworks for assessing architectural health to identify areas that hinder flexibility, scalability, and integration as well as apparent redundancies and potential areas of overspending. This assessment will provide valuable insights into the specific challenges your organization faces and help define the goals and objectives of your adaptive architecture.</p></li><li><p><strong>Develop a Future State Vision:</strong> Every good plan begins with the end in mind. Choose a foundation. Although adaptivity is the goal discussed here, stability is essential for effective support of business operations. Some long-term decision-making is unavoidable. The ability to swap components, redesign integrations, and so on is not a reason to avoid making big decisions about the core infrastructure and foundational technologies.</p><p>Design a sound foundation that innately supports swappable and scalable components. You might want to paint the house a new color every Spring. You will probably need to update the furniture appliances from time to time or even change the layout of the interior spaces, but build the house on a solid, long-lasting foundation.</p></li><li><strong>Develop a Roadmap:</strong> Create a comprehensive roadmap that outlines the steps, milestones, and timelines for transitioning to an adaptive IT architecture.<ol type=\"a\"><li>Don’t change everything at once! Segment the journey into manageable phases, prioritizing areas of critical need or areas that can provide immediate value. Consider the dependencies and interdependencies between different systems and processes, in-flight and planned projects, costs, and value and plan for effective change management to ensure a smooth transition and minimal disruption to ongoing operations.</li><li>Don’t set the roadmap in stone. Adaptivity involves continuous change in response to forces that are often unforeseen. It’s true that every well-managed program needs a roadmap, but in a future, adaptive world, there will be fewer roadmaps and more dynamic routing.</li></ol></li><li><p><strong>Continuously Monitor, Evolve and Adapt:</strong> Establish a framework for monitoring and evaluating the effectiveness of adaptive IT architecture. Regularly review performance metrics, customer feedback, and industry trends to identify areas for improvement and adapt strategies accordingly. Embrace a culture of continuous improvement and be open to feedback and suggestions from employees and customers.</p><p>An adaptive IT architecture is not a one-time implementation but an ongoing process of evolution and iteration. Continuously evaluate the effectiveness of your architecture, gather feedback from users, and adapt as needed. Embrace an agile mindset that embraces change and allows for iterative improvements. Regularly assess the alignment of your IT architecture with business goals and adjust strategies accordingly.</p></li><li><strong>Collaborate with Technology Partners:</strong> Engage with technology partners and vendors who can provide expertise, solutions, and support for your adaptive IT architecture journey. Leverage their knowledge and experience to accelerate implementation.</li></ol><p><strong>Five Reasons to Pursue Adaptive Architecture</strong></p><ol><li><strong>Enhanced Scalability and Agility:</strong> In a rapidly changing business environment, scalability and agility are essential for organizations to respond quickly to market demands and seize new opportunities. Adaptive IT architecture provides the flexibility to scale resources up or down as needed, accommodating fluctuating workloads and business requirements. This scalability enables businesses to handle increased customer demands, seasonal peaks, or sudden growth without disruptions or resource constraints. Additionally, adaptive architecture allows for agile development and deployment of new applications and services, enabling businesses to stay ahead of the competition by rapidly delivering innovative solutions.</li><li><strong>Improved Integration and Interoperability:</strong> In today\'s interconnected business landscape, integration and interoperability are critical for seamless data exchange and collaboration across systems, departments, and external partners. An adaptive IT architecture facilitates smooth integration of disparate systems and applications, enabling efficient data flow and real-time information sharing. By breaking down silos and promoting interoperability, businesses can optimize their operations, streamline workflows, and enhance productivity. This integration also paves the way for future growth and expansion, as businesses can easily incorporate new technologies, platforms, and partnerships into their ecosystem.</li><li><strong>Cost Efficiency and Resource Optimization:</strong> While transitioning to adaptive IT architecture requires initial investments, it can result in long-term cost savings and resource optimization. Outdated systems often require extensive maintenance, support, and upgrades, leading to high operational costs. In contrast, adaptive architecture enables businesses to adopt a more modular and scalable approach, allowing them to optimize resource allocation and reduce unnecessary expenses. Cloud-based solutions, for example, eliminate the need for on-premises infrastructure, reducing hardware and maintenance costs. Additionally, an adaptive architecture allows businesses to leverage automation and self-service capabilities, freeing up IT resources for more strategic initiatives and reducing labor costs.</li><li><strong>Enhanced Business Continuity and Resilience:</strong> An adaptive IT architecture provides organizations with the necessary tools to enhance business continuity and resilience in the face of disruptions or unforeseen events. Traditional architectures with single points of failure or limited redundancy are susceptible to downtime and data loss. By leveraging cloud technologies, virtualization, and distributed systems, businesses can ensure data redundancy, implement robust disaster recovery strategies, and achieve high availability. This enables businesses to minimize downtime, protect critical data, and quickly recover from disruptions, safeguarding their operations and reputation.</li><li><strong>Compliance and Security:</strong> In an era where data privacy and security are paramount, an adaptive IT architecture offers significant advantages in terms of compliance and data protection. Regulations such as the General Data Protection Regulation (GDPR) and industry-specific requirements impose strict guidelines on how businesses handle and secure sensitive data. An adaptive architecture enables organizations to implement advanced security measures, such as encryption, access controls, and audit trails, to protect data throughout their lifecycle. Furthermore, the ability to quickly update and patch systems ensures that businesses stay compliant with evolving regulations and industry best practices.</li></ol><p><strong>Additional Considerations</strong></p><ol><li><strong>Emphasize User Experience:</strong> As technology evolves, so do user expectations. Prioritize user experience in your adaptive IT architecture by designing intuitive interfaces, seamless workflows, and personalized interactions. Incorporate user feedback and conduct usability tests to refine your systems and ensure they align with user needs and preferences.</li><li><strong>Leverage Automation and Intelligent Workflows:</strong> Automation plays a crucial role in adaptive IT architecture. Identify repetitive and manual processes that can be automated to streamline operations, reduce errors, and free up resources for more strategic tasks. Embrace intelligent workflows powered by AI and machine learning to enhance decision-making, optimize resource allocation, and improve efficiency.</li><li><strong>Implement Agile Development Methodologies:</strong> Agile methodologies, such as Scrum or Kanban, can greatly enhance the adaptability of your IT architecture. By breaking projects into smaller, manageable chunks, you can deliver incremental value and respond quickly to changing requirements. Regularly review and adapt your development processes to foster collaboration, transparency, and continuous improvement.</li><li><strong>Embrace DevOps Practices:</strong> DevOps is a set of practices that emphasize collaboration and integration between development and operations teams. By adopting DevOps principles, you can accelerate software delivery, increase deployment frequency, and improve overall system stability. Encourage cross-functional collaboration, automate testing and deployment processes, and foster a culture of shared responsibility and continuous improvement.</li><li><strong>Establish an Architecture Governance Framework:</strong> To ensure the effectiveness and sustainability of your adaptive IT architecture, establish a robust governance framework. Regularly review and update governance policies to adapt to changing circumstances and emerging technologies.</li></ol><p><strong>Conclusion</strong></p><p>By adopting an adaptive IT architecture, organizations can proactively respond to market dynamics, seize new opportunities, and deliver exceptional value to customers. Embrace change, embrace innovation, and embark on the journey to building an adaptive IT architecture that will position your business for long-term success in the digital age.</p><p>The journey towards adaptive IT architecture requires careful planning, effective management, and ongoing evaluation. It is not a one-time effort but a continuous process of optimization and adaptation. However, the rewards are substantial – increased operational efficiency, accelerated innovation, reduced costs, enhanced customer satisfaction, and sustainable business growth. Embrace the potential of an adaptive IT architecture and position your organization for success in the digital era.</p><p>In today\'s rapidly evolving business landscape, adaptive IT architecture is the key to unlocking business potential, driving innovation, and maintaining a competitive edge. By embracing flexibility, modularity, and agility, organizations can navigate the complexities of the digital age and capitalize on emerging opportunities.</p><p>Building an adaptive IT architecture requires a holistic mindset, organizational commitment, and a willingness to invest in technology, talent, and cultural transformation. By following best practices such as embracing cloud computing and other innately adaptive technologies, fostering a culture of innovation, prioritizing integration, swappable components, interoperability, and staying abreast of technological advancements, businesses can create a robust foundation for future growth and success.</p><p>The journey towards adaptive IT architecture is not merely a technical transformation but a cultural shift that embraces change, continuous learning, and collaboration. By aligning technology with business goals, managing risks, and fostering a culture of adaptability, businesses can position themselves as agile, resilient, and future-ready entities capable of thriving in the dynamic digital landscape. Embrace the power of an adaptive IT architecture and unleash your business\'s full potential.</p><p><strong>About The Author</strong></p><p><a href=\"https://www.linkedin.com/in/dougpicirillo/\">Douglas Picirillo</a> is a Senior Enterprise and Solutions Architect and IT Program Management Consultant. He specializes in Business Transformation and Value Creation enabled by Information Technology, IT transformation and cost reduction, Enterprise Systems Development, and IT Integration and Separation in Mergers and Acquisitions.</p><p>Mr. Picirillo has more than 30 years of IT experience in the public and non-profit sectors and numerous private sector industries, from SMBs to the Fortune 500. Doug’s paper, \"Artificial Intelligence in Mainstream Enterprise Applications\", was published in the peer-reviewed World Complexity Science Academy Journal (ISSN online: 2724-0606) in 2020.<a href=\"https://www.wcsaglobal.org/volume-1-issue-2-2020/artificial-intelligence-in-mainstream-enterprise-applications/\">https://lnkd.in/dgQEr8VE</a></p><p>To know more about how DivIHN Integration Inc. can help you in your journey for deploying robust \"Adaptive Enterprise Architecture\" please get in touch with him at Doug. <a href=\"mailto:doug.picirillo@divihn.com\">doug.picirillo@divihn.com</a></p>','','full_html'),