Enterprise applications have been the technical foundation for running businesses for decades now. They have been the top priority for most IT organizations and consume a huge percentage of resources and budget. While they undoubtedly are critical to the business, the fact that the business is dependent on them can bring huge risk if they aren’t managed correctly.
CIOs and senior IT executives typically take a portfolio approach to the major application initiatives in which they invest. A certain percentage of their resources and time are spent sustaining their existing applications—basic keep-the-lights-on operations. Another percentage is spent enhancing applications, either by improving functionality or performance, or implementing new applications to better support business processes. And in some organizations, a portion of the investment is devoted to initiatives focused on truly transforming the business, by implementing technology that now allows the business to do something new that it has never been able to do before and thus potentially leap frog competitors.
Most IT shops strive to reduce the percentage of budget and time spent on merely sustaining applications, because there is no incremental value-add to the business. But one of the biggest factors that is increasing the cost and risk of sustaining existing applications is the data deluge. Enterprises are literally drowning in data, and the complexity of managing vast volumes of data across dozens or hundreds of different enterprise applications can be a huge cost sink.
By investing in a proper, proactive data management strategy that cuts across individual application silos, enterprises can significantly lower the costs of sustaining applications. This then frees up dollars and people to focus on enhancing and transforming applications, which is where IT actually makes a positive impact on the business. Moreover, a robust data management strategy is a critical foundation to any effort to enhance or transform applications. After all, what good is an application if the underlying data is a mess?
In my next three blogs, I’ll talk more about the myths and realities of applications and data, and dig into how data management applies to efforts to sustain, enhance, and transform applications.