- Shifting from a defined project to an ongoing program is a challenge for many organizations
- Leverage the enthusiasm for a data cleanup project to establish ongoing data governance
- Ownership, a roadmap and internal promotion are key to transitioning into a sustainable program
All hail the new initiative!
In marketing ops, we talk a lot about avoiding Shiny New Object Syndrome – or what I affectionately render as SNOBS (also sometimes called SNOS). It’s important to avoid SNOBS so that your technology roadmap doesn’t get derailed by the latest “wouldn’t it be cool if…” piece of software. Avoiding SNOBS is also critical to the success of the various initiatives started by your organization – but with a bit of a twist.
Let’s take data governance, for example. Someone in the organization (maybe you) stands up and says, “Our data stinks and we finally need to do something about it!” So what happens? Scramble the jets! And all of a sudden, data quality, data governance and everything in between becomes a top priority.
This, in my opinion, is great. Data management is a topic that often falls between the cracks, and despite the knee-jerk approach, at least it’s now getting the attention it deserves. The problem? The energy that gets thrown at it is project-based.
Now, to be fair, this is understandable. We’ve identified very specific goals as part of the cleanup effort, we likely have a timeframe in mind, and we possibly even have a budget to be applied as well. This issue comes when the project is near its close. What happens next? How do we transition from a one-time cleanup to ongoing governance? How do we use the momentum we built during the project to create a sustainable program? Here are three tips that can help build that bridge:
- Assign ownership. Data management most often goes astray because no one owns it. During the cleanup project, it usually becomes clear what person (or collection of people) is best suited to carry the torch going forward. If you’re serious about adding data governance to a set of responsibilities, you’ll probably need to take something else off of that set. Don’t simply make this an additive set of tasks, or the program will likely fail.
- Roadmap the strategy for the next year. Data management doesn’t become a “thing” unless it becomes ingrained as a run-rate part of the business. To this end, it requires a plan for the coming year, a discrete set of initiatives, and a budget. Undoubtedly, there will be unfinished business from the project; use those punch-list items and the overall lessons learned to guide the initial set of data management activities.
- Measure and promote. As with other sets of activities, data management will ultimately be ranked in priority based on its perceived value to the business. Elevate its stature by measuring and publicizing the progress made during the project, and continue to track the gains made year over year. Without hard evidence as to how data improvement efforts are benefitting the organization, it becomes much easier to sweep aside these efforts in favor or other, shinier objects.
What’s worked well for you in moving from that big cleanup project to sustained discipline around data? Where are you still struggling? Leave a comment and let’s discuss – we’d love to hear what the community thinks.