Is “dealing with data” oriented toward seeking opportunities or avoiding risk in your organization?
FedEx and Microsoft provide an example of the former, tying up to bring data-driven services for supply chain management to market. “Fedex Surround” was created by making a deal to jointly marshal data assets and analytics capabilities..
On the flipside, lately we spoke with an IT executive for whom data is more like “a big headache” than “the new oil.” In the absence of a company data strategy, he said: “I generate one terabyte of data every day. And I don’t know what to do with this. So every month, I throw this away, I just delete it.”
Wiping the slate clean is a sure-fire way to avoid compliance risks and reduce storage costs. But it will inexorably carry a larger and larger opportunity cost, because other companies figuring out valuable ways to use data will increase the potential value of their company’s data in the process.
This is because data is what economists call “non-rival.” Unlike a barrel of oil or an hour of human attention, data can be consumed simultaneously, without being diminished. Any number of firms, people, or algorithms can use it at the same time without reducing its availability to others.
This spins nested flywheels.
The first is a virtuous cycle within a firm. Products enriched through insights from user data get more compelling, attracting more users who generate more data. Netflix, for example, built a great content recommendation engine on user data, and now also uses insights derived from it to create compelling original content.
The second is the increasing odds of a valuable “match” between firms. T-Mobile aims to differentiate by knowing their customers “better than any company in our space,” in their CEO’s words. In much the same way that Netflix delighted us by surfacing shows we’d enjoy, T-Mobile promises to match customers with “free stuff and great deals from brands you love” on “T-Mo Tuesdays.”
Now, through a deal that makes sense between two companies that are committed to excellence at data-driven customer intimacy as a core value proposition, some T-Mobile subscribers can stream Netflix at no extra cost.
Looking ahead, every dataset (or insights derived from it) will have a greater likelihood of finding a valuable “mash up” with others.
The third flywheel is “more data expands what can be done with data.” This might include, for example, a new degree of accuracy in prediction or level of efficiency in optimization.
Fueling this, data exchanges are making a business facilitating access to aggregations that otherwise would not exist or would be off-limits due to regulation. Companies like Waymo are choosing to open datasets and offer prizes for innovation that may have not been possible within the firm’s boundaries.
Your company’s data culture and architecture must, of necessity, manage risk. But both should also embrace conviction that “dealing with data” will increasingly mean “making deals” to create shared value propositions, fill gaps, and make AI smarter than it otherwise would be.