Monetizing Your Big Data: A Grand Dream, A Constrained Reality

Big Data Evangelist, IBM

Everybody these days wants to monetize their big data—and why not? You know that on some level your data is valuable. If it weren’t, you wouldn’t be investing so much in the acquisition and analysis of it all.

currency.jpgBut is big data truly monetizable? This utopian vision can break your heart if you let it stray too far from practical reality. On one level, saying you want to monetize data is tantamount to asserting that it’s a form of common currency. In fact, some pundits are fond of claiming that data is the new currency of the digital economy. According to this logic, monetization is simply the procedural equivalent of panning, mining and minting coinage from raw materials floating in your big-data stream.

That’s a grand vision, but it’s rarely clear whether the dreamers are speaking metaphorically or literally. For the sake of argument, I’m going to construe it literally.

For something to be regarded as common currency, it must have purchasing power with respect to a broad range of goods and services within the wider economy. However, if data—like almost any resource you can name—may only be bartered ad-hoc for other things of value, it’s not currency. Consequently, according to this strict definition, data is not currency. And, in fact, I have never seen any good or service in the larger economy that’s priced in data bits (the much-ballyhooed digital currencies, such as Bitcoins, are artificial constructs designed to emulate traditional monies, but they’re not, strictly speaking, content-bearing data).

There is another, weaker sense of “monetizable,” and it’s simply that data can drive business activities that generate actual currency. By that definition, almost every factor of production—land, labor, physical plant, intellectual property, entire businesses, etc.—is monetizable. Therefore, stating that yet another business asset—data—is monetizable is a trivial point that may simply be assumed.

Where monetization is concerned, it’s more meaningful to ask yourself the following strategic questions:

  • Can our business data be sold in raw, aggregated, refined and other forms?
  • Can our business data drive outcomes that generate cash flow?
  • Can data-driven business activities increase the market valuation of our company as a whole?

These thoughts came to me as I was reading a recent article on “objective-based data monetization.” As near as I can tell, the article only addresses the third of these senses of “data monetization” (i.e., the loosest possible sense of the term). As such, it sketches out an approach that could just as easily be dubbed “value-driven data science,” given that it primarily focuses on how a savvy data-science operation—not just the data itself—can boost a business’ bottom line. There’s no discussion of identifying data that may itself be sold, nor does the author pay any attention to which data-driven business initiatives might contribute the most to cash flow.

When it comes right down to it, the core traditional business uses of data science—marketing, customer retention, upsell, next best offer and the like—would appear to have the most direct impact on cash flow. But, when you think about it, the data that drives these activities is only indirectly monetizable.

I guarantee that you’ll never see currency spontaneously spring forth from your big-data clusters without the assistance of data scientists wielding analytics tools and leveraging a substantial data management infrastructure.

Only rarely is any of this data directly monetizable.

Few businesses have a realistic opportunity to sell off their core operational data. And it’s for the obvious reason: it’s a key strategic asset that’s usually protected by privacy and security mandates. Unless you’ve decided to enter the data marketplace business or have non-strategic data not constrained by privacy mandates, you won’t directly monetize—in other words, sell off—the data you’ve collected.

If you attempt to monetize the big data that you’ve gathered through crowdsourcing, you may have another issue to consider: intellectual-property rights (IPR) and equitable distribution of the fruits of data monetization. In this respect, I recommend that you consider the provocative viewpoint of computer-science pioneer Jaron Lanier. Though he doesn’t discuss IPR issues, Lanier argues that Internet giants such as Google and Facebook should return to users some of the money that was made from the valuable data that had effectively been crowdsourced from them.

Whether or not you agree with that point of view, you have to admit that there’s an interesting principle underlying it. As online newspapers (e.g., New York Times, Washington Post) start to monetize their content behind “paywalls,” why shouldn’t individuals erect their own personal “paywalls” as a condition of participating in online communities where someone else—the data aggregator—is profiting?

Clearly, monetization is potentially a two-edged sword in online data-sharing initiatives. If your customers, in their capacity as crowdsourced data feeds, feel that they’re being denied their fair share of the money pie, they may push back hard.

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