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Expect a greater focus on MDM and business process alignment in 2011

Technology professionals will be hearing a great deal about MDM and business process alignment in 2011, according to one data management expert.

Rob KarelRob Karel

Organizations will spend more time attempting to bridge the gap between master data management (MDM) and the business processes that MDM initiatives are designed to support, according to Rob Karel, a principal analyst and all around data management expert with Cambridge, Mass.-based Forrester Research Inc. caught up with Karel recently to find out his key predictions and forecasts for 2011.

Data governance will be the key to MDM and business process alignment in 2011 and beyond, said Karel, who also offered some tips on how to make that alignment happen. He added that technology professionals can expect more consolidation in the data quality, data governance, data integration and MDM software markets in 2011. Here are some excerpts from the conversation:

What do you think will be the defining trend for MDM initiatives in 2011?

Rob Karel: The main focus that Forrester and I have been working on is putting MDM in a business context. Everyone and their brother and sister [agrees] that business owns the data. But the issue isn’t the fact that the business owns the data. The business owns the processes that run the business, and so the key trend that we hope to see and that we’re really evangelizing is that business process and decision support type initiatives are going to take more accountability for master data.

You’re not going to get to MDM if you don’t understand data quality competencies and best practices.

Rob Karel, principal analyst, Forrester Research Inc.

Could you elaborate on that?

Karel: Business initiatives that drive business process improvement and optimizations such as an order-to-cash process or procure-to-pay process or a set of call center operational processes -- these business processes are clearly owned by the business. There has never been a question of whether IT owns the processes that business people go through when interacting with each other or customers. Once defined, each of these processes [involves accessing trusted data and making the right decisions]. And there has been an assumption that trusted data is just always around for the process to be successful. But the reality is that process failure is a huge issue with business process efforts and a lot of the process failure occurs because there is no trusted data.

Why are MDM-related considerations often left out of business processes?

Karel: The business process owners figure IT is responsible for getting that trusted data to them. It’s this mismatch, this chasm between business and IT that says, “I own the process but you own the data and magically all this stuff is just going to work.”

How can organizations achieve the goal of putting MDM into a business context?

Karel: The hottest thing in the last year and a half has been data governance. What data governance is all about, when articulated appropriately, is that it’s a collaboration between business and IT to define the business value, the policies, the stewardship rules and responsibilities [and the] organizational structure [needed] to manage data as an asset. Data governance is the link, the bridge, between what the business is trying to accomplish and what IT needs to do to get them there. surveys have shown that IT organizations are still having trouble selling data governance to upper management. Do you think this will continue to be a problem in 2011?

Karel: Absolutely. The data governance problem is all about executive sponsorship and linking to business value and business strategy. Over the past 18 months, I’ve seen more and more organizations investing in top-down data governance and just trying to figure out what it means and how they need to proceed. But it’s very immature. I’m hoping that over the coming years as the economy slowly recovers [that we’re] going to see some more bottom-up foundational governance in place that will allow technology initiatives like MDM and business intelligence (BI) to be more successful.

Can you offer any more tips on how organizations can include MDM in business processes?

Karel: It’s really about recognizing that a lot of the roles and responsibilities in terms of the actual deliverables between data governance and process governance are very similar. A lot of the same jobs that [data stewards] would do -- [such as] requirements analysis and defining policies and standards and defining KPIs [key performance indicators] and metrics -- these are responsibilities [that you’ll need] across both types governance. They’re not so separate. The only thing that is separate is your entry point. Very often your data governance entry point is from a data domain standpoint. We want to get control of our customer data. We want to get control of our financial data or our product data. Business process governance, however, is saying that we have to get control over our order management process or our direct marketing process. But it’s two sides of the same coin. You can’t fulfill an order management process without good data, and customer data in and of itself is a useless asset unless it’s in the context of a process that it’s solving.

Do you expect more consolidation between the data quality, data integration and MDM software markets in 2011?

Karel: You will certainly continue to see a lot of consolidation in the data quality space. You’re going to see more data integration and data quality coming together. You’re going to see more MDM and data quality coming together. You’re going to see data quality and analytics vendors, BI vendors and apps vendors coming together. Data quality is [increasingly] becoming part of a broader set of capabilities, although it’s still a very healthy standalone market. The key is that data quality is a step in MDM maturity. It’s a prerequisite. You’re not going to get to MDM if you don’t understand data quality competencies and best practices. You’re going to see more and more folks leveraging these technologies as part of their [data and applications infrastructure as they proceed toward] that master data vision.

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