As the Holidays rush towards us, we’re reminded again that those considering pets as gifts must keep in mind the ongoing responsibility they represent: “A dog is for life, not just for the Holidays.” In considering this recently, it struck me that the adage could similarly be applied to data quality (without meaning to trivialize the original message). Data quality is not a one-off exercise, a gift to users or marketing campaigns, but an ongoing commitment that requires management buy-in and appropriate resourcing.
The challenges of data quality management
It’s well known that data decays rapidly, particularly in B2B. Individuals get promoted, change jobs, move companies and so on, and companies merge, get acquired, and go out of business. I often refer to this as the “data half-life,” meaning the time it takes for half of a database to become out-of-date, which can easily be two years or fewer. It’s this fact that makes data quality maintenance an ongoing task and not simply a one-and-done ahead of a big campaign or new system implementation.
But you’re wasting the effort and expense if your cleanups are ad hoc or piecemeal. Your data decays as contacts move and addresses change; people and applications disregard standardization rules and fail to complete fields properly, and other issues creep in. And all too soon the data is in the same state as it was before you did “the big clean-up.”
It’s tempting to suggest undertaking a regular batch cleanse to address these issues. However, this approach presents logistical challenges with extracting and reloading updates, and what to do with data that changes in the system during the cleansing process.
Data quality solutions that last
Far better is an approach to data quality management that builds quality into the heart of an organization’s processes and operations, including rigorous ongoing monitoring. There are plenty of cost-effective tools that can be deployed within MAP and CRM systems to monitor, correct, and prevent data quality issues (recognizing that neither the issues nor the solutions are entirely technical). In our recent LinkedIn Live B2B Marketing Leaders 2023 Planning webinar, I talked about the need to put a data steward in place to take responsibility for these measures.
Adopting an “always on” data quality management ethos is a longer-term play that may lack the one-off satisfaction of a quick clean-up. Certainly, data quality rules and algorithms require maintenance, nurturing, and oversight long after the initial “gift” of deployment. “Always on” data quality management delivers operational effectiveness, agility, and efficiency benefits, and it enables rapid and flexible campaign execution, accurate analytics, and robust compliance controls. As with that dog your family falls in love with, data quality is a gift that keeps on giving.
Data quality – like a dog – is for life not just for the Holidays