The year 2007 brought many changes to the data management area, one of which was a greater emphasis on alignment. Business and IT alignment, technology and application alignment, business partner to business partner alignment and vendor to vendor alignment were all hot topics.
This coming year will open up the age of convergence. While alignment is concerned with making sure the various constituencies are united to the same goals and end game, convergence brings disciplines together where the differences between the disciplines are merged into one blended solution.
In our industry, there has been a growing divergence causing areas that naturally fit together to be treated as distinct and separate disciplines. While this may work out well for some in the short term, in the long term the continued divergence will eat away at business value and ROI. The four areas that will see convergence are:
Enterprise performance management and master data management (MDM). Although the industry treats this as two distinct disciplines with their own methodologies, tools and implementations, in reality, they are two dimensions of an enterprise information management strategy. Without the key performance indicators (KPIs) of performance management, MDM becomes an exercise in data integration, and without MDM, performance management cannot achieve the promised enterprise level impact.
ETL and messaging. The reality is that ETL and messaging are two ways of achieving similar results, and they need to be driven by business requirements and ROI, not technical zealots. Sometimes the answer is not mutually exclusive, but mutually inclusive.
Business intelligence (BI) platforms and BI applications. The BI industry is moving through a similar change as the enterprise resource planning (ERP)/customer relationship management (CRM) marketplace did in the ‘90s. Instead of pure platforms, businesses are demanding a more application-based approach geared toward functional areas. Much of the divergence is based on the classic build-versus-buy argument. More likely the answer is not build versus buy, but build and buy, mixing prebuilt applications with scalable platforms.
Structured versus unstructured data. The integration of the two is moving directly to the front burner of businesses. As metrics are created and communicated, they tend to answer the “what” questions (what is my revenue, what is my customer churn, etc.). Conversely, the answers to the “why” questions (why did my revenue drop, why is my customer churn skyrocketing) often reside in the vast amounts of unstructured data. Answering the business questions will require a converged approach of structured, unstructured and semistructured data integration.
Whether organizations have achieved alignment nirvana or not, they will be forced to move into the age of convergence. Driving this will be the metaconvergence of business and IT, and the catalyst for this convergence is governance, stewardship and change management and business wishing to further rein in and control IT. It can be thought of as an elongated response to the technical bloating of Y2K and dot-com run up in technology spending. Businesses have now seen that the only way to digest this technical mound is to have a structured, governed approach to managing IT.
This approach steps beyond alignment and into shared ownership and control. Governance, stewardship and change management strike at the heart of the chasm between IT and business, a kind of no-man’s land that neither group owns or controls.
With the business metaconvergence driving organizational change, the various technically oriented convergences will be the result of natural progressions. For example, establishment of a data governance program will not try to unnaturally separate the KPIs from the master data. Instead, the governance and stewardship program will drive the technical convergence of these disciplines. In the end, all business data will fall under the governance and stewardship program.
Conversely, if the convergence of ETL and messaging is already underway, it will only further emphasize the need for an enterprise-wide, technically agnostic governance and stewardship program. Regardless of how the data moves, it all falls under the governance and stewardship umbrella.
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