There's a lot of pressure in the modern workplace to be data driven, but you don't have to try too hard to find a salty data scientist who can tell you a story (or two or three) about a time that "product intuition" or "strategic bets" were used to justify a decision instead.
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While this is frustrating, insisting that every decision be purely quantitative also misses the point. It's almost as if people think performing the Sacred Ritual of A/B Testing protects them from being wrong, when the real goal of using data is being better than yesterday
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IMO, rather than attempting to predict the future, the most practical, scalable and immediately valuable use of data is to understand how the present compares to the past. This is the real reason why being data driven is worthwhile--it's a form of accountability.
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If you've ever budgeted to save money, or tracked your daily footsteps to become more active, congratulations! You've taken something it's easy to make excuses about and forced some objectivity into it. You're keeping yourself honest, which is what being data driven is all about.
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If you want to be data driven, pick a way to measure something, apply the measurement regularly, and keep all the measurements in the same place. Then look at the trend to see if the measurement is consistently moving in the direction you expect. That's really all it takes.
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Replying to @imightbemary
Usually the problem is those steps are taken care of in different functional groups. Need decent leadership to align steps. Ppl applying measurements very rarely have data warehouse knowledge for example.
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In my experience, this depends somewhat on company size, but you're absolutely right that alignment is key. If an engineer instrumenting a new feature doesn't know where the event logs are going or why they matter, the odds of them doing that instrumentation accurately are slim
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