9January 2016across business areas, this legacy of informality created difficulty as there was little consistency in approach and even definition. As the initial MDM initiatives began to take hold, architecture, quality and governance were quickly embraced as reasonable and necessary, but more to support the data aggregation initiative, as opposed to any overall broad organizational need.The initial activity which began to open organizational eyes to the need for formalized information management came from a risk initiative known as Critical Data Identification (CDI). It stemmed from the need to demonstrate, both internally and externally, that the critical data of the organization was being protected and controlled. While this seemed easy enough, when put in motion a key issue emerged in that there was no formal definition or inventory of what the critical data was. Surely it was somewhat intuitive, but there were many "versions" and individual opinions. What was needed was the organizational opinion. That took some work, not only to define, but then to identify, evaluate and document what the critical data was and what were the controls in place to protect it. Once definition was complete, the ongoing management of critical data needed to be operationalized so that the critical data question could be consistently responded to on an on-going basis. This operationalization will take some time to fully mature but that process has begun to be put in place Probably even more impactful than CDI in driving the awareness and acceptance of Information management was the emergence and momentum being generated within the business areas for data analytic capability. Initially this activity ran its normal, ad-hoc, iterative, question/response course between IS data experts and inquisitive business executives and analysts. However, as it became clear that this analytics thing was kind of a new ballgame, new players and skills were added to the mix. Very quickly these new players become frustrated. Getting the data was not so easy. Data was in a lot of places and no one was totally clear on what data was where and what it really meant from a business, end-state perspective. Yes, the experts knew how it was used in the running of the business but different data in different places could be called the same thing but be... well... different! Once again there were many individual opinions or understandings, but no organizational understanding of the data and thus locating and understanding data became the first difficult hurdle. While data understanding was now viewed as critical, that understanding needed to be operationalized so that it could continue to live to support the next set of needs. In addition, the data itself once understood and provisioned for one purpose must not be lost, as it could be used for other, as yet unidentified purposes. Through the evolution and understanding of this organizational pain came the organizational clarity of the WHY of information management. If we believe that our data has value, that it IS an asset, then in order to maximize the value of that asset, we need to have a formalized approach to understanding that data and the definition of how that asset will be managed. Without this formalization, we cannot effectivity take advantage of the opportunities that are presented by the increasing capabilities in data analytics. We cannot leverage our data assets until we have a good understanding of our data and can provide it to the data analysts efficiently. In its simplest of terms, this is the goal of all of the activity associated with the execution of our Information Management Strategy.Our journey into Information Management is like a lot of organizational change efforts. Just getting everyone to agree there is a problem is the most critical step in generating a solution for the organization. It took us awhile to get where we are and we still have quite a ways to go, but we have come a long way from our initial debates. We needed to find the specific issues and experience the pain before we saw the need for an organizational approach to managing our data. We were not able begin to solve the problem until we were collectively sure that we had one! Probably even more impactful than CDI in driving the awareness and acceptance of Information management was the emergence and momentum being generated within the business areas for data analytic capability
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