by Ian Rowlands
Surprisingly (well, to me, anyway), there still seems to be a lack of consensus about what “Data Governance” really is. The DAMA DMBOK says that it is “The exercise of authority and control (planning, monitoring, and enforcement) over the management of data assets. Personally, I think that’s pretty good – although it begs the question as to what is intended by “management”. Wikipedia (the fount of all knowledge and truth!) says, “Data governance is an emerging discipline with an evolving definition. The discipline embodies a convergence of data quality, data management, data policies, business process management, and risk management surrounding the handling of data in an organization”. I’m inclining to the view that Data Governance is “the discipline that ensures that the enterprise has the necessary and sufficient set of information assets to support operation, decision making and business governance”. (Did you notice I broadened from “Data” to “Information”?) I’m prepared to accept that my definition begs as many questions as anybody else’s, and to defend it against all comers!
If we accept my definition then how do we decide what “the necessary and sufficient” set of information assets is? And how do we prevent unnecessary proliferation? Two key macro processes come into play, both based on acquiring the metadata related to information. One process is life cycle management, and the other is portfolio management.
Information Asset Lifecycle Management (IALM for short) might be the least practiced of all Information Management disciplines. Just like any other asset data stores, reports, models and so on should have a life cycle – from need identification, to proposal, to definition, to delivery, to management to disposal. Unfortunately, the “front end” of the cycle is often ignored – people create what they “need” without governance, and assets proliferate. The proliferation of assets multiplies the costs and risks associated with information. As to the “back end” of the cycle, I’d say it is even more neglected! Any organization could eliminate a lot of risk, cost and information-driven error by rigorously disposing of obsolete information. Of course, there is an implication in all of this that there needs to be an inventory of information assets, and workflows to manage the lifecycle. I’m only seeing this get put in place when (as has happened with a few of the companies I deal with recently) there is a regulatory requirement to manage the flow of information into and out of the enterprise.
The story is similar – but perhaps marginally less bleak when it comes to Information Asset Portfolio Management. There are key questions to ask about any information asset: “Why have we got it?”, “what business process does it support”, “what does it cost”, “how is it regulated” … these (and many others) are Portfolio Management questions and the answers are metadata.
All this leads to a plea for a process-oriented approach to information management. There is a lot of great work being done on understanding what is being done with information assets – but much less on the “why” – and understanding why is the key to governance.