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> After that experience, my view of metrics-driven product development is that it's a way to offload the burden of thinking too hard or understanding where you'
by akiselev 5y ago
> After that experience, my view of metrics-driven product development is that it's a way to offload the burden of thinking too hard or understanding where you're going. When people talk about metrics-driven product development, I think of drivers who blindly follow their GPS' directions into a lake.
There's also the flip side - metrics-driven development used to keep other people from thinking too hard and scrutinizing work. At my last company, many product decisions were justified using a litany of metrics including AB tests, which people just swallowed because "the data speaks for itself!"
I once took a look at the app we were using to run the AB tests and not a single one had reached statistical significance. The company was basing its decisions on data considered garbage even by the AB app's naive p-value algorithm. I thought that after dozens of A/B tests at least one would be statistically significant just by dumb luck but no, not a single test had even the veneer of credibility.
- kqr 5y agoBut what you're describing is noise-driven development. It's not an actual metric value until you've somewhat ruled out noise as the explanation.
- akiselev 5y agoI believe that's a distinction without a difference. Most scientists have a hard enough time understanding statistical significance in well controlled experiments and they are (ostensibly) trained for it. There's so much noise in business data that it's like reading tea leaves, except no one can prove it because by the time they gather enough data they realize that the management and/or market dynamics have introduced even more noise so everyone keeps chugging along, blissfully unaware that they're indulging in statistical fantasies and reinforcing whatever beliefs they already hold.