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HR metrics require much more than data
This article is part of the Business Information issue of August 2017, Vol. 5, No. 4
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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Features in this issue
Employers are trying health management, wellness and fitness apps, and other new HR tech tools to hold down healthcare costs and make employees happier.
Increased use of HR software for continuous feedback and goal setting gives companies more metrics to identify and nurture skills and improve employee performance.
AI is taking aim at the very people-oriented human resources profession. Expert Brandon Wirtz gives his take on why that's happening now and what it will mean for us all.
Important factors affect the adoption of mobile HR policies. Here are three key aspects to consider as employees access human resource features on mobile devices.
Columns in this issue
Data doesn't tell the whole story about employee performance and retention, but more companies plan to use workforce analytics tools to aid their staffing decisions.
Employing metrics and analytics to improve logistics, operations and forecasting is a good first step, but not enough. Your workforce is the most important resource to optimize.
What's a smaller needle in the haystack, finding the best job candidate or discovering what planet hosts intelligent life? A theory on the use of data is argued and debunked.