Enhance Data Governance by Applying Business as the Context

Bookmark and Share

A look in any dictionary shows that most words have multiple meaning.  At its best, every language is riddled with ambiguity.  Many meanings and nuances are attributed to even the simplest of words, like “is.” It is part of human nature to muddy up the language by using one word to mean many differing things, and concurrently using many different words to refer the same thing. Playing with language is one of the things humans continually do. The comedian Steven Wright used to have a joke about a dog he named “Stay.”

He claimed to constantly confuse his dog by issuing the command, “Come here, Stay.” Navigating through the dark forest of multiple meanings is accomplished via the application of context. The confused dog would have overcome his circumstances if he simply understood that, in context, every command ends with his name, therefore “Come here, Stay” means “Come here” and only “Stay, Stay” would really mean “Stay.”

Obviously, there are times when ambiguity must be curbed in order to have situations run smoothly. One wouldn’t want a surgeon to request an instrument from the nurse and have the nurse provide the wrong instrument simply due to a lack of linguistic precision. Or worse, if the surgeon misunderstood what the nurse communicated about the status of some aspect of the patient, bad things could happen. Yet many businesses allow this level of ambiguity to creep along and cause fuzzy business metrics to exist across enterprise reporting. As organizations grow via mergers and acquisitions, more linguistic variations are added into the corporate word pile. Each addition requires a certain amount of care and nourishment to align critical business metrics.

Again, to navigate through the multiple meanings, context must be applied. In very mature industries it is possible that some context is found at that industry level, for example interpreting the symbols on a sheet of music. But more often the leveraged context becomes the organization itself. Using this filter, many different organizations may choose one word to mean multiple things, or many words to mean one thing. But within a single organization, and even more specifically, within the enterprise reporting metrics area of an organization, each word or term must have one single meaning.

This continuity must be applied to key business concepts and business metrics. Multiple source systems may each require unique and varying algorithms to arrive at each system’s contribution to that individual metric, but the intent is aligned and agreed to by those who understand what is happening with each system’s internals.  In this fashion an organization may be internally consistent and, “Say what it means, and mean what it says.”

Data governance is the function that strives to apply the needed care and nurturing that gives rise to corporate linguistic continuity. Proper data governance brings commonality to an organization; it leads the journey to a single version of the truth. A single version of the truth does not mean everyone must kowtow to a single metric; but it does mean distinct calculations unique to dissimilar sub-groups have different specific names at the corporate level, even if those naming differences are subtle. Then when folks are referring to a named metric, everyone knows that they are speaking of the same thing. Actual problems can then be the subject of focus, rather than farcical dialectic fire drills that waste organizational resources. Many organizations talk about data governance, but rather than establishing an ongoing governance process that is involved with every project, the governance is viewed as a one-time task to be slogged through, over with and done. Such myopic approaches will only lead to failure. Data governance is like life, it is the journey, not a destination.