Big Data Strategy: Datafication

Datafication of everything enables new ways of creating value and becoming more competitive. Oracle Big Data Strategist Paul Sonderegger explains.

By Paul Sonderegger, June 4, 2014

Big data’s true name is the datafication of everything – the capture and use of more data in more daily activities. This is such a fact of life that T-shirts in America’s favorite gambling city now say, “What happens in Las Vegas stays on Facebook and YouTube forever.”

What Happens in Vegas Stays on YouTube and Facebook forever Michael Porter, the world’s leading authority on competitive strategy, says strategy is choosing to create a unique value in a unique way.The first part of this definition means that to set your price at a profitable level, you need to offer something your competition can’t. But it’s the second part – creating that unique value in a unique way – that’s the key to sustaining profitability. And here’s where big data makes such a big difference.

The datafication of everything enables entirely new ways of creating value. Take Google, for example. One of Google’s early insights was that a link between two Web pages is the datafication of a human editorial judgment – “to find out more about this, go here.” Analyzing the network of links among pages datafies the wisdom of the crowd about what should point to what.

But that’s just a narrow set of activities. And any single thing a company does can be copied. But to mimic a group of interconnected activities, a rival has to copy the whole system.

This means that in a big data world, strategy is a question of capturing and using data across a system of activities in ways your rivals can’t copy.

This is why Google continues to datafy more and more activities, capturing data from one and using it in another. Take your interactions with Google’s search results. The company collects extensive data on how you interact with the results its engine serves up. This includes which links you click on, as well as which ones you don’t. The data exhaust from this interaction becomes input to the way the engine handles the next person’s search on the same terms. Google is busily extending its network of interconnected activities across all of its other services including Gmail, Google Now, Maps, and more.

Using the data exhaust of a particular activity to improve its own performance spins up a kind of big data flywheel where each activity contributes another piece of information to an overall collection that’s more useful the bigger it gets. But true big data competitive advantage comes from spinning up multiple flywheels that mutually reinforce each other.

So, if you weren’t born with the Google spoon in your mouth, what do you do? First, think in terms of data market share. Look for value-creating activities in your industry and focus on the share of those interactions you conduct. If you spot important interactions with customers, partners or suppliers that are still analog, that’s a land-grab opportunity. Datafy them before the competition does.

Second, spice up your proprietary data assets with third-party data. For example, you can buy a data feed of tweets about your rivals’ products. And your rivals can do the same for tweets about your products. But don’t think these tit-for-tat actions cancel each other out. Combining that feed with proprietary data about your customers gives you a proprietary view of your competition’s performance among your customer base. You now see the broader market in a way your rivals can’t, which is crucial because they’re probably creating their own different, proprietary view.

Paul Sonderegger Finally, conduct experiments to figure out where your new proprietary data assets can improve a key activity and, in the process, create more data to fuel future improvements. Because the datafication of everything has changed more than just Las Vegas. It’s changed the basis of competitive advantage – forever.

Paul Sonderegger is Oracle’s Big Data Strategist. Prior to joining Oracle, he was Chief Strategist at Endeca, a discovery analytics company. Before Endeca, Paul was a Principal Analyst at Forrester Research, specializing in search and user experience design. Paul has a BA degree from Wake Forest University.

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