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Three Ways to Connect Data Integration to Business Strategy

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In this week's ebizQ column, David Linthicum makes a strong case for why data integration should be a top priority for businesses. After all, he explains, those who neglect data and integration with other systems "are going to find the bitter truth at some point," and that bitter truth is bad data, expensive repairs, and lost faith in IT.

 

Then he asked a question that's been bugging me all week: How do you make data integration a priority?

 

For those of you unfamiliar with Linthicum, he's the CTO of Bick Group, but he's also a well-known SOA writer and speaker who's branching into cloud issues. Before SOA, his focus was (and arguably still is) distributed computing and application integration; he often tackles data issues as well.

 

Those of you who are familiar with Linthicum will know he doesn't ask a question like that without answering it.

 

"It's really a matter of just looking at the business benefits, and thus the business case for data integration," he writes. "Without a sound data integration strategy you're simply not going to be able to meet the requirements of the business, and can't get more clear than that. Moreover, you need to consider data integration as something that's systemic to your architecture, and not just an afterthought."

 

To me, that actually answers the why more than the how. How do you go about finding the business case for data integration? And how do you ensure data integration becomes and remains a priority?

 

So, I did a bit of digging and I've found a few items that might help you identify the business case and institutionalize data integration as a strategic discipline.

 

As luck would have it, John Schmidt of Informatica recently launched a blog series on data as an asset. In his first post, he writes about the pros and cons of viewing data as an asset. I particularly appreciated his point that if it's not an asset, it's measured as a cost-and you know what happens to cost centers in tough times.

 

But for my money, the really good stuff is in the next three posts, starting with the second post, in which he explains accounting methods for determining an asset's value and applies those concepts to data. In the third post, he outlines how to calculate the EVA (Economic Value Add) for data. If that doesn't work out for you, in the most recent post, he explores a market-based approach to valuing data.

 

Schmidt's series will go a long way toward helping you attach value and thus build a business case for data initiatives.

 

Now-how to institutionalize data integration as a strategic process?

 

There are several good answers to this question. First, as I've shared many times, there's the old standby, the Integration Competency Center. If your problem is more about overcoming corporate politics and rallying support than organizing change, then I recommend you check out Rick Sherman's suggestions on creating support for holistic data integration.

 

But I'm actually most excited about a third possible answer that's just emerging on the horizon: the technology solution. I know, I know - tools are never a replacement for strategy. But hear me out. There's already a trend for business analysts to handle more integration. Not surprisingly, data management vendors have noticed this trend - in fact, I've talked with several vendors who say they now have to talk to the business and IT if they want to sell a solution.

 

Their products are starting to reflect and support this shift, and I think it's a promising development in terms of making data integration a strategic priority. For instance, Informatica recently rolled out Informatica 9, and one of the key selling points is that it's designed for both business analysts and IT.

 

And just this afternoon, I learned that DataFlux plans to unveil next week a new data management platform, with support for data governance, integration, data services and master data management-and it's designed to be used by business analysts and IT.

 

Increasingly, data management tools are marrying all the elements of data-integration, governance and quality-into one, business-friendly package. Perhaps in this case, the tools will soon help solve the challenge of data integration by strategy, rather than happenstance.

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