Trusting Too Much in Data
In recent weeks I’ve run into multiple posts, articles, and discussions concerning some findings that employee morale does not equate to productivity. I’ve read a few of the discussions and a couple of the articles, and the subject and the reports prove to be an excellent example for discussion about how easily we can mislead ourselves with data.
By way of background, apparently some of the research groups and “better management” consulting firms have recently assembled some data analyses that refute the assumption that higher employee morale will drive higher employee productivity. Some of us immediately acknowledge that the findings merely state the obvious. Some of us immediately argue that the analyses could not have drawn an accurate conclusion. Some of us immediately demand to see the data and the analyses, suspicious that something obviously complex couldn’t possibly be summed up so simply.
Because of the diversity in response, and the probability that everyone is, at least in part, correct in taking their various sides of the arguments, I thought it would make a good focus for discussing some ways we allow ourselves to be misled. In particular, I want to discuss two major behavioral errors.
- To truly understand what the data means, we must understand the whole picture of the data, including how it was collected and analyzed
- Metrics do not necessarily make meaningful data – the truth may be far more complex
Herein, let’s focus on the first error. The second will make a good discussion for a second post.
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