The Best (and Worst) Question to Ask About Your Data

By Bryan Kirschner, Vice President, Strategy at DataStax

Helpful advice from companies that were purposely built to be data-driven permeates our daily lives.

Recommendations for new music and movies I might enjoy from Spotify and Netflix, respectively, are like old friends. My Fitbit reminds me when I need to get moving in order to meet my daily step goal. Our Peloton offers up a “for your usual” and a “for something different” workout without being asked.

We’ve started to take it for granted from other quarters as well. For example, we expect the apps and websites of any number of brick-and-mortar retailers to deliver us digital coupons that are intelligently selected based on our purchase history.

When I asked Marshall Van Alstyne and Geoffrey Parker about “The Secret Weapon for a Data-Driven Enterprise,” they emphasized that the bridge between big aspirations and successful execution starts with asking the right question.

The question “To whom can we sell our data?” isn’t the right one. Rather, the journey toward differentiation starts with asking “What data about their interactions with us might our customers find valuable?”

“The items you’re about to buy might make you or someone in your household ill” was one example that fits the bill. If online shoppers voluntarily added food allergy and intolerance information to their profiles, one retailer automatically provides a warning if those ingredients are present in items in their shopping cart. That struck me as a win in more ways than one. It’s helpful advice that saves a customer time (to safely check ingredient lists), money (assuming they discard an inadvertently purchased off-limits item), and possibly a fair bit of discomfort (if the wrong person happens to eat the wrong thing).

A fireside chat between Geoffrey and Jes Staley, the CEO of Barclays, crystallized for me how powerful it can be to lean in to how data might be used to save customers the trinity of “time, money, and grief” as part and parcel of doing business.

Staley explained that with 8,000,000 retail banking customers growing by double digits every month, “we think we might have more data than any other entity in the United Kingdom.”

But historically the company had been organized by products such as credit cards, mortgages, and investment advice. Data was siloed, so much so that, in his words, “if you banked broadly with Barclays…god forbid if you got into financial difficulties…you’d be bombarded.”

The credit card, mortgage, and checking account overdraft product groups all had collections departments that did not talk to each other—so they might all be calling the customer demanding repayment. This was not just a needless source of grief—it was also a big missed opportunity. Barclays likely had the best data available with which to tailor repayment plans that would lead to the highest probability of customers getting back on their feet.

Barclays made a commitment to creating a complete data-driven view of the customer that unlocked this possibility. As part of this, functions like “collections” were reorganized into services to which all product lines turned.

Consumers not only got a single point of contact, but also they got a partner equipped with unparalleled data with which to recommend the best win-win plan for their situation.

“What does data from my interactions with you tell me about how to ‘get well soon’ during a rough patch?” is every bit as valuable to a customer of a financial institution as “what does data from my interactions with you tell me about the probability of achieving my retirement goals?”

Leading data-driven enterprises don’t stop asking how to make data valuable to customers, and don’t let the old way of doing things stand in the way of making it happen.

Read about taking a discovery-driven approach to transformation here.

About Bryan Kirschner:

Bryan is Vice President, Strategy at DataStax. For more than 20 years he has helped large organizations build and execute strategy when they are seeking new ways forward and a future materially different from their past. He specializes in removing fear, uncertainty, and doubt from strategic decision-making through empirical data and market sensing.