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August 2017, Vol. 5, No. 4

HR metrics require much more than data

A Business Information reader recently reached out to me with an observation about something that impacts the way people interpret and use predictive analytics data in every corner of the world, from politics to human resources -- bias. In the February issue, I wrote about the role predictive analytics played in last year's U.S. presidential election, especially in forming the candidates' campaign strategies and swaying the analysis of pollsters. The reader aptly pointed out that bias was the likely culprit and led analysts to see only what they wanted to see in the data. "The black swan is almost always visible early on," he wrote. "The problem is that we do not want to admit it when we see it. Because then we would have to admit that our model is wrong. We have our ego invested in our data model." The reader went on to explain that he's involved with health analytics, and he's seen plenty of projects that start with preconceived biases on controversial topics like the Affordable Care Act and immunizations as well as ...

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