Competitive strategy means creating unique value in a unique way, economist Michael Porter, Bishop William Lawrence University Professor at Harvard Business School, has said. It’s not enough to provide products or services that your customers can only get from your company. Your company also has to create those offerings in a way your rivals can’t easily copy.
In his classic 1996 Harvard Business Review article "What Is Strategy?,” Porter described this hard-to-copy way of creating value as a company’s "activity system." Activities are the processes a company carries out every day—the way it runs marketing campaigns, designs products, bundles offerings, provides support, manages risk, and protects patents. Every activity uses a combination of financial, skill-related, technology, information, or process resources.
Because information is the only resource both used and produced by every activity in a company, the digitization and datafication of more and more daily activities has a big impact on competitive strategy.
The good news for incumbents: The tools of data capital are available to all companies, not just to startups. In fact, enterprises have a distinct advantage in amassing stocks of data capital because of the volume of their interactions with customers, suppliers, and partners. Three principles show how to exploit this advantage:
The Data-Activity Connection
To drill down into Principle #1: From a data-production perspective, activities are like lands waiting to be discovered. Whoever gets there first and holds them gets their resources—in this case, their data riches. But not all that glitters is data gold; some activities are more valuable than others.
All activities produce information, but they don’t produce digital data unless they involve an application, device, or sensor. Companies that have been able to see and pursue this foregone data—the information rising off activities, places, and things like so much evaporating steam—have profited greatly from it. When Google deployed fleets of cars onto the world’s roads to capture imagery, distances, and wireless network IDs, and to associate all that information with GPS coordinates, few understood that the cars were amassing data capital that could be used to create search, navigation, and ad-placement services. Utilities installing smart meters, brokerages creating mobile advisory apps, travel sites recording all the offers visitors don’t click on—all of these are colonizing new data lands.
It’s difficult to know which activities will yield the most valuable data. The answer will vary from industry to industry and company to company. Naturally, a company should focus on activities that reinforce its competitive advantage, the things that make it unique. However, to make educated guesses, a company should look first to its biggest revenue and cost drivers, especially where it interacts with the outside world. Interactions with customers, suppliers, and partners are particularly crucial because rivals are probably looking at them, too. It’s imperative to digitize these activities before the competition does. The reason: If you’re not party to an activity when it happens, your chance to capture its data is lost forever.
For example, the Australian supermarket chain Coles is experimenting with a palm-sized kitchen device for making grocery lists. Scan a barcode or just tell it you want milk, and it adds the item to an online list. Through the device, Coles can gather data not just about the items customers want, but also about how and when customers make their shopping lists, opening new possibilities for targeted ads and improved service.
Digitizing activities means involving sensors or mobile apps in the activities in some way. Datafying activities means expanding the observations you capture about them. "Datification"—a term introduced by Kenneth Cukier and Viktor Mayer-Schönberger in Big Data: A Revolution That Will Transform How We Live, Work, and Think (Eamon Dolan/Mariner Books, 2014)—runs contrary to data-management orthodoxy, which tries to settle on the minimum dataset necessary.
For instance, an airplane manufacturer captures tens of millions of data points from every test flight of its latest passenger plane. Engineers use this data to speed up the delivery of safe planes, but what else will they do with all those observations of such a variety of flight characteristics? Not even the manufacturer knows yet. But the option value on potential uses of that data is likely greater than the cost to capture, store, and experiment with it.
This article is excerpted from our exclusive report, "The Rise of Data Capital." Read the full report to learn more about the other two data-capital principles—and how your organization can leverage its data assets for true competitive advantage.