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Critical success factor: Data model architect

MM: That almost reminds me of a conversation I had with a data warehouse architect. She was building a data warehouse for an executive information system for Bank of America. She would talk about sitting down with a fairly senior marketing executive and saying, “What are the business decisions that you make in the course of a day?” And then, “What information do you need in order to make a fully-informed decision?” And, “Where do you go for that information?”

Of course, there are green bar reports here and a conversation here and a fax here. In the course of doing that, she’d talk about identifying the most important—the number 1 or number 2 most important—business decisions that an executive would make. Then doing a map of logical but physical data sources, so as to be able to identify what the data items were that needed to be collated into information that then supported an action or an insight.

That kind of describes what you’re talking about in terms of this top-down optimization strategy or top-down problem-solving sort of thing.

MB: My expectation is that a large percentage of the projects that have been successful have had practitioners working on them in the model that you just described. Here at Oco, we’ve really taken that notion and turned it into an art form. We sit down with a business for one or sometimes two days and go through a systematic approach to define the key problems they need to solve. We call this approach a profiling session.

We design the solution and figure out the data resources that are going to be required and so forth. We have a quite robust methodology we go through. It’s a precise recipe.

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