When I work with clients to help reset their data strategy
, they often complain that there isn’t much they can do toward a rational enterprise approach because they just can’t get the funding they need. They explain that this lack of funding is systemic in the organization – any project that isn’t directly related to top business initiatives is likely to be cut.
When I hear this, I know my job is going to be much easier than it otherwise would be. Yes, easier. How can a lack of funding be a blessing for an enterprise data strategy? It keeps you focused on the right things and steers you away from common traps. If you don’t have much funding for your enterprise data strategy, you’ll be forced to show how your work is essential to the success of already-funded business initiatives. And the value-producing application projects within those initiatives will provide a scoping mechanism to keep your supporting data projects under control, while ensuring the data will be used when implemented. So being compelled to attach to these efforts for funding keeps you focused and prevents you from getting lost in vague ideas about “improving the data situation around here” or “creating an enterprise data foundation” or some other aimless notion.
I once worked with a large retailer
who was just getting into online sales – obviously an important, well-funded business initiative. When their director of data management brought up the initiative, I asked how his work was supporting it. He explained that he was providing the underlying data. For example, for his first project, he was planning to deploy “order data” because that’s so foundational. But when I asked which specific application project was set to leverage his order data, he couldn’t name one. That’s a problem. In our conversations, I learned that the web site application team was planning to build an innovative recommendation engine as part of the site. Great, why not support that application with the data it needs and extend the data resource from there as additional application projects are identified? This may seem like a subtle distinction, but the difference in results is dramatic. A project to deliver order data for all possible uses would be five to ten times the size of a project to deliver order data for a specific use, and it’s vulnerable to being cut before it even gets started. And a project like that should be cut.
Any organization can develop and implement a successful enterprise data strategy, even with little to no funding initially earmarked for that purpose. Even the most cost-conscious enterprises have some initiatives that survive the funding process. And most, if not all, have significant data and analytic requirements. So by proposing a data strategy in direct support of top initiatives, you are simply proposing to reorganize work that was going to be done anyway. But now you’ll do it in a way that is more efficient and creates an extensible and continuously improving data foundation as a natural byproduct, creating even more efficiencies. With the work organized appropriately, you can build a dedicated team, tools, governance structures – everything you wanted to create in the first place, except more focused and much more easily justified.
In a cost-cutting culture, directly linking data projects to top business initiatives is a good way to keep them from getting clipped. But this is how all organizations should be approaching data strategy anyway, regardless of the funding situation.
When I help clients who have abundant funding for their data strategy, independent of the other top initiatives, it’s much more difficult to make this case. They’ll say, “We have all the funding we need, why should we try to catch the tailwind of those other initiatives?” I try to help them see what the future will look like if they don’t – mushrooming project scope, limited data usage, and a general (and accurate) perception that the enterprise data program is just not crucial to the organization.
All else being equal, is it better to have direct funding at the outset for your enterprise data strategy? Yes, of course. When you approach the sponsors of important company initiatives seeking to provide the data and analytics they need, it’s a nice extra enticement to offer to pay for it with your own budget. But the risk of getting severely off track is very real, and without direct funding, you’ll have no choice but to earn internal customers to drive the program, at least initially.
So, if you have limited funding for an enterprise data strategy, look at the bright side – you just might be forced to do it the right way.
Kevin M Lewis is a Director of Data and Architecture Strategy with Teradata Corporation. Kevin shares best practices across all major industries, helping clients transform and modernize data and analytics programs including organization, process, and architecture. The practice advocates strategies that deliver value quickly while simultaneously contributing to a coherent ecosystem with every project.
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