Ah, Data!


For some of us that’s as boring a word as ever there was. It’s also a word full of critical information for making good decisions (and combating the dreaded assumptions we tend to make.) Yea, right…that’s obvious, you say! But I can’t tell you the number of times I’ve found myself in situations where the answer was in the data – but the data was just about the last thing anyone was considering.

Let me give you a couple of examples:

Example 1: Company A was experiencing a lot of turnover in one division. Thinking a contributing factor to dissatisaction was the environment, management upgraded everyone’s chairs. The problem continued. So, management then decided the problem was a lack of employee commitment to the work and the company. They brought in a motivational program. The turnover problem continued. Finally (after considerable time and money), they really dug into and examined the turnover data more carefully. They discovered that management was bringing in people based mainly on recommendations from current employees – with the result that the people they hired were not necessarily qualified, did not understand the work, and were certainly not committed to the company. Had they looked at the data concerning employment practices first, rather than making assumptions about the cause of the turnover, the problem could have been successfully addressed by improving the employee selection practices much earlier.

Example 2: When a new manager was hired in another workplace, she noticed that the staff seemed to make an awful lot of mistakes. She concluded there was a lack of skill, standards and monitoring.  So, she provided training, set exacting performance standards, and carefully reviewed the work. Still, mistakes did not appreciably decrease. Finally, she brought someone in to look at what was going on. After an analysis, it was brought to her attention that the same employees who were expected to pay close attention to detail were constantly being interrupted by the phone and by people at the counter, as well as being expected to immediately answer e-mails from the public. Once work was re-distributed to minimize interruptions for any one person at any one time, mistakes decreased dramatically.

In both of these examples, managers who knew and understood the work assumed they knew what was wrong without examining the data. They assumed that what they “knew,” rather than any data, was all they needed to solve the problem – and they were absolutely wrong. So, before you assume you know the answer, look at the data. Ask the questions. Talk to the people who are actually doing the work and those who are hiring them. If needed, get an outsider to look at the problem from a neutral perspective. Then, address the real issues based on your discoveries, on the data – not on your assumptions.

How have you successfully used data to address issues in your workplace? Tell us! ~ Daphne Schneider

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