Blog: Jill Dyche

« Selling MDM to Executives. Or Not. | Main | Highlights from TDWI Vegas »

Don't Pull a Dunbar: The Catch 22 of Data Quality

In which Jill muses that--in the war on bad data--reluctant soldiers can either hunker down, or arm themselves with the tools to fix their data, and bolster their companies' competitive readiness in the bargain.

In Joseph Heller’s classic American novel Catch-22, a character named Dunbar spends his days lying on a cot musing on his own state of boredom. Dunbar’s theory goes that the more bored a person is, the slower time passes, effectively making life seem longer. The obvious irony here is: who wants to lead a long-but-boring life?

(Coincidentally, this is a question I usually ask aloud right before ordering the cheesecake.)

We could ask ourselves a version of that question when it comes to using customer data. Who wants to settle for summary data, missing information, or inaccurate values when we could be enriching our data and, by extension, driving additional revenues? I mean, it’s pretty clear by now that the better our data, the more meaningful our customer interactions. But many of us are still sitting around in a state of complacency.

As with Dunbar, our inertia has consequences. Maybe we’re afraid to make the pitch for better data to executives with other things on their minds. Fussy shareholders? Crabby customers? Perturbed partners? Bet you can fix some of those issues with better data deployed faster for improved business action.

I know. It sounds like so much motherhood. But we recently watched a specialty retailer implement coupon-on-demand capabilities based on who the customer was and what she bought. The quality of the retailer’s customer data was abysmal, but executives in the IT department understood they needed to deal with poor customer addresses before launching the new coupon program. We helped an international materials conglomerate waive delivery fees to the customers in the top decile. Again, they needed to clean and reconcile their data first. And a major bank is now recognizing customers at the time of interaction with its new CDI hub. Again, poor data quality was initially a barrier, but not anymore.

None of these successes was immediate. They all involved the cleansing, matching, merging, and reconciliation of customer data. It’s a work in progress—but in all cases it’s already driven bottom-line improvements.

So, if you’re bored, don’t pull a Dunbar. Consider the strategic programs on your company’s radar and start talking to vendors about data cleansing and reconciliation. It may or may not be fun, but it will definitely make life more interesting.

Technorati Tags: customer data integration, master data management, customer relationship management

Share: