The need for data governance which actually means establishing control on data source to obsolescence has become a need for many organizations. I would be surprised if any CIO is not mentioning establishing data governance or enhancing data governance as one his primary IT investment objectives in the short term or long term. Lot of organizations have a baggage of multitude of IT systems each of which serves a specific business need and designed to serve it by sourcing the needed data all by itself. All organizations always keep evaluating the conflicting need to rationalize IT systems or building more robustness in the interfacing part so that the hold on to the best of the breed IT systems even though collectively they create lot of weak links. So if an organization is able to rationalize IT systems, then data governance is taken care by the rationalization itself but in case of the need to maintain the best of breed IT systems, then data governance becomes paramount as it can really break the weak links and exponentially increase the pain of maintaining such heterogeneity.
So the context of data governance is to arraign the sources of proliferation of data elements and data values and bring in much needed control. Basically strengthen the weak links in the heterogeneous IT systems landscape which I had mentioned earlier. As anybody can guess this is easier said than done. Additionally data governance needs harmonization as pre-requisite which can also turn out to be tough to crack. So achieving one source of truth and one value across all the IT systems is a tall order, but then is it not the fundamental requirement to be achieved through Data Governance. It is here my topic bears significance of having flexibility in data governance. I would say “Flexible Data Governance” is indeed an oxymoron but it is a practical need too. Let me explain with an example.
In a recent data governance implementation project we came across the field “Division” having available values as 10, 20, 30 & 40 in one SAP system and in other SAP systems there were multiple values additional like 60, 15 and even alpha numeric of two character length. Keep in mind all the systems involved are SAP, so it should be a piece of cake to harmonize this and that is how it started. We standardized the values as 10, 20, 30 & 40 in the data governance system and mapped the additional values available across all systems to these 4 values. But then we found case of hard coding in interface programs, middleware program, enhancement programs and even values in this field being used in user exits to execute specific activities etc. which ruled out harmonization of one value of after another. So what to do? Continuing with harmonization means costly program changes, elaborate testing efforts, risk of introducing production issues etc. Here comes the concept of “Flexible data governance” where-in we introduced scalable data governance where-in within a master data object we allowed values to be harmonized and controlled on a certain fields while in other fields it is allowed to have different values in different systems. So the data object is part of data governance but not all fields in it are controlled by the data governance tool.
I am sure each of us would have seen such conflicting requirements, but in a data governance project where-in the fundamental need to conformity, flexibility is a bad word but then life thrives in the gray. Please share such examples in your project experience.