One of the mantras that has guided Google through so many of its product development routines is the fact that the data matters. If you can show that there is data to support a decision, it is more likely to be well received than one based on the experience, instinct, or hunches of any person.
Often in the past I wished that the companies I worked for had operated in a similar manner. Many times I've had managers decide to pursue some course of action based on something other than data. At times I've even had managers ask if we could rework queries or reports to support their position. It wasn't entirely unreasonable to question the queries we had written as we may not have approached the problem in the best way, but asking for evidence to support a pre-determined result felt wrong to me.
Companies spend thousands, or millions, of dollars every year on all sorts of resources to collect, manage, and analyze an ever growing set of data points. Many of us find our jobs revolving around data, looking for new ways to analyze data and drive better decisions. At the same time, many companies struggle with decision makers that trust their own instincts more than the data reports they review.
There isn't a lot we can do as data professionals, other than continue to refine the models we build and work more closely to convince managers to tune our models, using the actual data before and after the decisions to analyze the results. We can also champion the ideas that the data is more objective, and should be a significant part of the decision process, while allowing for some input by the people that have a wealth of experience in our particular industry. We want their gut feel, but we don't want to ignore the data.
As with most things in business, communication and compromise help to drive us forward to better decisions in the future.
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