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The opinions expressed are my own and do not represent those of my employer.
Last week, the former Sr. Brand Director of Nike published a rare deep dive into a marketing blunder four years in the making. As a firm believer in taking inspiration from analogous domains, I think there is a great lesson here for Product and UX to take away.
Why do I think it’s relevant? Just tell me this doesn’t sound familiar:
“Nike invested billions into something that was less effective but easier to be measured vs something that was more effective but less easy to be measured.”
On the advice of McKinsey, Nike’s new CEO John Donahoe decided to pivot to a “data-driven” approach, reorganizing the company towards digital direct-to-consumer sales and eliminating the former model centered on distinct categories. The allure is easy to recognize, and it’s the same trap that Boeing and other companies fell into over the preceding years.
Coming up with new ideas is difficult and requires specialist knowledge. Moreover, it requires specialist knowledge to understand what those specialists are doing and therefore manage them.
Meanwhile, slashing costs works the same way across every industry. And so Nike squared up to eliminate duplicate processes, streamline operations, improve efficiency, and increase productivity — all those phrases that are meant to say “whatever it is you do — do it harder.”
This kind of strategy was already a punchline in 1997 (Bellwether, Connie Willis)
How well did it work? Well, that depends on what the intent behind the strategy was. If Donahoe intended to lose $25B in market cap and tank the stock price 32%, it was a smashing success. For those of us who don’t think that’s what he meant to do, it bears reflecting on where he went wrong.
It is wrong to suppose that if you can’t measure it, you can’t manage it — a costly myth. — W. Edwards Deming
Data isn’t worthless. Data is really, really valuable for telling you what has happened in the past. Great expense has gone into producing data that can tell you what’s going on in the present. But as the 7- and 8-figure salaries of quantitative analysts at hedge funds show us, using data to extrapolate what will happen in the future is one of the most challenging things you can try to do with it.
Typically, the way one would do that is by harvesting what’s called warm data — the qualitative data that gives the numbers their meaning — and then using that to tell a story about where the numbers are going.