The dirty secret of data analytics: Culture of honest inquiry required

For far too many organizations, analysis has been corrupted by a culture of tweaking parameters to support desired outcomes. Here’s how to establish an honest path to data-driven decisions.

Data analytics’ dirty secret: Culture of honest inquiry required

In the beginning there should have been a culture of honest inquiry.

Instead there was the internal rate of return (IRR) — a polynomial formula for computing return on investment that only trained accountants could master. IRR defined business value in a single dimension of analysis: cash flows. The gods of accounting looked on it with favor, and so it was, theologically speaking, good.

Then Dan Bricklin invented the electronic spreadsheet. Like Prometheus bringing fire to we mere mortals, Bricklin and his spreadsheet let all humanity calculate IRRs for ourselves — and once anyone could compute IRRs for themselves, they did.

The problem? Managers quickly figured out how to do more than compute it. They learned to adjust their assumptions — poking, prodding, and tweaking parameters — until their IRR generators infallibly arrived at the answer they wanted.

The result? Cultures across corporate America in which data lakes, data marts, data warehouses, and analytics software have become little more than platforms for managerial parameter tweaking. They’re used, not for illumination, but as ammunition by those who start with the decision they want and work backward to find the filters and parameters needed to support it. And this is the dirty secret that is sinking your analytics strategy.

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