Forget ghosts and goblins this Halloween. The Big Data Apocalypse approaches. Boo!

Children may be obsessed with the supernatural right now, but for corporate executives, the scarier specter is the advent of Big Data - a world in which data is so voluminous that it overwhelms our ability to store, manage, and use it.

No fantasy here, right? After all, pundits, consultants, even our collective common sense tell us it must be so.

Well, no, actually. Like ghosts and goblins, the Big Data Apocalypse makes for good entertainment but doesn’t have much grounding in reality. Sure, the world is awash with bits and bytes, and we’re creating more of them by the microsecond. But most of that data goes unrecognised or ignored, and that’s OK.

Here’s a useful analogy. Consider how we humans think about the universe. We accept that it is unimaginably vast. We acknowledge that it contains countless stars - trillions and trillions of them. Yet we spend precious little energy thinking about most of those stars. Instead, we learn to recognise a few of the most important ones, the ones that have directly impacted human history. Like the sun. Or the North Star. To them, we accord an appropriate amount of communal consideration. To the rest - the trillions that have had little or no impact on human life - we give almost no consideration. We have always seemed to know, intuitively, that any time and effort we spend on those parts of the universe that do not directly affect our lives are, for most of us, time and effort stolen from more fruitful endeavors.

That’s how we need to approach Big Data. Executives sometimes argue that if you give them all the raw data that’s available, they can create wisdom and insight. In our view, that almost never works. First, they have to figure out what questions they’re trying to answer. Only then can they truly make a difference for the business. Only then can they make magic happen.

We have argued in prior columns that the most successful companies of tomorrow will navigate the Big Data hype with a high degree of focus, constructing strategic information ecosystems that provide them with a distinct competitive advantage. We have further suggested that these ecosystems will be so valuable they will warrant constant stewardship from someone in a newly created position, the chief strategic information officer (CSIO).

But what will a strategic information ecosystem look like?

For starters, it will utilise three types of data: data that already resides inside the company, data obtained from a myriad of external sources, and data created as needed in real time. It will focus on increasing the value of the enterprise in a very specific area: accelerating new product introductions, improving operational efficiencies, penetrating new and existing markets, perhaps increasing customer satisfaction. It will be proactive. In many cases, it will require the building and sourcing of a new data environment before analytics can begin.

To make the concept more concrete, consider a simplified example involving a pharmaceutical company’s attempts to create more revenue from its existing lineup of products. At its core, the company does this by increasing prescription volume, maximising prices, and optimising product mix—a formula common to many other industries. The CSIO who understands the specific information needs of this formula, sources that information, and then properly analyses it will win the day.

How might he or she do that? Let’s look at one aspect of the revenue formula, increasing prescription volume. Doing this efficiently would require the company to focus its efforts on three groups of doctors: those who primarily prescribe the company’s products already, those who prescribe the most pharmaceuticals of all kinds, and those who would prescribe the company’s products if they had better information about them. Building or sourcing an ecosystem that can provide the information needed to improve this effort could be challenging, especially because the company’s distributors will probably cloud the line of sight to the prescription data. However, someone will figure it out, and that company’s shareholders will be richly rewarded.

As is probably obvious, most companies will need multiple strategic information ecosystems. Extending the example above, one could envision a pharmaceutical company with an R&D ecosystem, an operations ecosystem, and perhaps several sub-ecosystems within the operations ecosystem.

As mentioned earlier, strategic information ecosystems will focus on maximising enterprise value. Accordingly, they should not be limited to a single functional area of the organisation. They can, and should, span multiple functions. In the pharmaceutical industry, product safety offers a good example. Pharmaceutical firms must report to regulatory agencies any adverse events experienced by patients using their products, and it is important that those reports be filed on time and accurately.

However, it is equally important, from an enterprise-value perspective, that companies understand what caused each adverse event and whether it was specific to certain types of patients, involved interactions with other drugs, or had implications for similar drugs in development. Strategic information ecosystems can enable this sort of analysis - a high-value benefit that is possible only in organisations willing to create information ecosystems at the value-chain level as well as the functional level.

So no, there really is no Big Data Apocalypse lurking in the shadows this Halloween. But there are companies already starting to build strategic information ecosystems that will facilitate their ascent to the top of their industries. If any of them happen to be your competitors, explaining to your C-suite colleagues why your organisation hasn’t done the same could be a frightful experience.

Mike Cooke is a partner in Booz & Company’s strategy and IT practices. Christopher Perrigo is a senior executive advisor at Booz & Company.

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