# IT, Analytics, and Insights By:: [[Brian Heath]] 2023-01-21 There has long been a struggle between Information Technology (IT) and Analytics. At one point, the only computers that could handle Analytics problems were ones exclusively managed by IT. However, now computing power is abundant, and most Analytics needs are met by a simple laptop. Thus, control of data and processing has left the realm of IT. As with any organizational function, this loss of power has created tension and a desire to regain it. Typically when IT decides that they want Analytics under them they make one of the following arguments. First, data is the lifeblood of the organization and should be protected. Since IT is responsible for information security, analytics and data should reside within its walls. Second, for analytics to be successful, analyses must be embedded into business production systems. Since IT largely operates these systems and processes, analytics should reside within their walls. Finally, Analytics is a highly technical career, and IT has the most experience with managing and developing highly technical career fields. Thus, Analytics should be managed by IT and not the business. If all of these seem reasonable, you are missing the point of analytics within your organization. As a result, analytics will never reach its full potential, and it will always be a disappointment if you are honest with yourself. Analytics is not about data - it's about thinking and understanding the complexity of human and natural systems. Data is only a tool in the toolbox. Analytical success is not restricted to production systems and processes. The most insightful and successful analyses change strategies, not plans. IT production systems are not strategies, they are merely the execution of plans. Analytics can help optimize these plans, but optimizing the status quo is the fastest way to be destroyed by the competition. Finally, Analytics is much more than a technical career. This is probably the largest fallacy of them all. Average analysts build models about what is happening, good analysts build models that predict the future, and great analysts synthesize that which has yet to be. The further up you go, the further away you get from a purely technical career. To become a great analyst you must dive deep into philosophy, psychology, system dynamics, and art. This is hard work. It is much more than coaching someone to write better code and manage scrum projects (e.g. technical career development). IT, and every other business function, is not prepared to provide this level of career development. Surely this is unsettling for many business leaders, IT professionals, and analysts. From here I can feel the heat emanating from you as you find all the flaws in this argument. Continue fighting the uphill battle while wondering why the game-changing insights never come. Insights don't come from optimizing the status quo. They come from outside the box you live in. I welcome you to step outside the box and join us. We will be happy to have you because now is the time to develop ourselves and the field into what it needs to become. #### Related Items [[Analytics]] [[Business]] [[Technology]] [[Development]]