Blog: Jill Dyche

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J'accuse!

In which Jill goes back to the basics with data management in Part 1 of a two-part blog entry.

I’ve gotten several well-intentioned e-mails from some blog readers who’ve accused me of targeting experienced data people. The e-mails gently suggest that I consider beginning at the beginning. They say something along the lines of:

“Hey, thanks for discussing customer data management and data governance and Information Centers of Excellence and the business value of data integration, but… we’re new to all of this. We don’t have any kind of data management in our company. It’s all being done by application developers in a one-off way. Heck, we can’t even get our management to fund a data modeler! Where do we start?”

The great French writer Victor Hugo once said, “Nothing else in the world…is so powerful as an idea whose time has come.” Perhaps you’re ready to establish some formal data management practices. In this blog entry and the next, I’ll provide some helpful tips to consider before going to management for support and funding:

1: Think local. It’s dangerous to pitch a big, behemoth, mother-of-all-data organization out of the gate. Better to identify a specific, consistent business problem that can be fixed with data, and fix it. Then show the benefits, and grow your data team from there.

2: Choose a good team. Just because someone understands technology doesn’t mean she understands the data that supports the business. As you begin formalizing data management practices, look for people who not only understand the business need for data, but ideally for those who have actually used that data to solve business problems. Round out your data management team with specific skill sets like data modeling, metadata management, and data quality. This might mean hiring from the outside, or retaining outside expertise to train your internal staff. Whatever you do, don’t succumb to the “warm body” syndrome that could doom your data management team from the get-go.

3: Keep current with business initiatives. The biggest sin of even the best data management teams is that they don’t keep business strategy on their radar. These teams go into their holes, focusing more on design conventions and metadata repository solutions than on new business initiatives hurtling through the strategic pipeline. CRM projects come to mind here: Show me a data management team poised to support customer-focused initiatives with data, and I’ll show you a data management team that will have no trouble securing ongoing support from the business.

In the next blog entry, I’ll talk about your company’s culture and why it matters in configuring a data management organization. This topic could be a novel worthy of Victor Hugo, but I’ll try to keep it short and sweet.

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