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| Say hello to big data! |
Population Health Blog readers may recall the Facebook kerfuffle when it was revealed that the company had been "experimenting" on its users. While this is another timely reminder that Facebook users are not customers but a product, what's far more interesting is how the company used its vast utilization data to monetize the changes of a hundredth of single percent in its users' behavior.
These weenie changes can add up to additional ad revenue. Ditto for the techy Google's search, Amazon's placements and Facebook's ads which, according to Schumpeter, are getting a return on investment from "every pixel" of the monitor screen you're using to read this blog.
Unfortunately, says The Economist, this big data approach has been more difficult for the for the traditional "bricks and mortar" businesses, which have traditionally been fixated on traditional accounting measures. But, as these businesses tether their infrastructure increasingly to information technology, they're getting there: UPS is monitoring 60,000 delivery vans, retailers are assessing how in-store placements generate the most revenue and businesses are measuring how the mix of different types of employees relates to productivity.
The PHB would rate most health care providers as being in the bricks and mortar category than in the technology space. They have a way to go.
Two lessons:
1) Big data doesn't replace traditional business monitoring of revenue and expense, balance sheets, averages and standard deviations, it adds to it. And yes, that ceaseless tinkering adds cost that - in the right hands - should have a return on investment.
2) The "tinkering" has its share of failures in addition to successes. While The Economist can point to some wins, the landscape is probably littered with losses.
Speaking of the right hands and minimizing losses from big data, the PHB is proud to link this article appearing in the NACD Directorship Magazine. While a password is necessary, the bottom line is that corporate boards can do ten things to help their companies successfully achieve a big data return on investment:
1. Provide analytic leeway;
2. Be clear on who is responsible;
3. Set realistic budgets;
4. Assess how big data is fitting into the pre-existing culture;
5. Be skeptical;
6. Link it to Enterprise Risk Management;
7. Task the Audit Committee with some oversight;
8. Assure privacy;
9. Reduce inappropriate incentives;
10. Get a big data expert on the Board.
Image from Wikipedia
