What do most companies do wrong when they use data to make decisions? originally appeared on Quora - the knowledge sharing network where compelling questions are answered by people with unique insights.
Analysis paralysis. We're victims of it too at Mixpanel on occasion. There is a moment where you just need to place a bet or make the best possible decision given time constraints and information at hand. Often there will be no perfect answer or the results will be a bit deflating because it turns out things are inconclusive. Either way, make a decision and realize that you can probably course correct or further de-risk a decision and test if things don't go to plan. More optimistically, at least you empathize with the President, who probably makes harder calls.
Sometimes the team doesn't actually trust the data, which makes making decisions very challenging. It's important to buy the team into how you defined the metrics and that the definition is well thought out. Keep in mind: perfect is the enemy of good here. You can get really sophisticated with how you define metrics to the point where nobody actually understands what the definition is anymore, thereby causing people to lose trust again (including you).
Or there's a chance they're looking at biased data. There are many situations where selection bias can occur and that you are improperly concluding something.
People don't freak out enough when things aren't going well in the numbers. You should freak out! Why? Because the alternative is that things are really broken and it's an existential risk to your company. Jeff Jordan wrote aon this recently.
Don't silo the data analysis to just managers. One thing we do at Mixpanel is that various teams review metrics for their organization at a recurring cadence. That causes people in the company to quickly highlight major sustained declines in conversion rates or anomalies that we can go learn about. Let people in your company be a part of the process by which you discover and solve problems.
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