Talent Intelligence could be a key lever in today’s hyper-competitive world. Talent Intelligence is the capture, aggregation, analysis, and timely reporting of talent data to inform decision making for improved organizational strategic planning and operations.
In 2012, “big data” was mentioned in 2.2M tweets by 980,000+ authors, at a peak rate of 3,070 times per hour!
However, as is often the case with relatively new and nebulous concepts, there is quite a bit of confusion surrounding big data and Moneyball and how they can be applied to HR and recruiting, as evidenced by the obviously incorrect usage of the terms in many cases. It’s also nearly impossible to stay on top of all of the content being generated on the subject (although I am trying my best!).
This is precisely why I’m going to take the opportunity to clear up any confusion by concisely explaining the concepts of big data, analytics, and Moneyball as it relates to HR and recruiting, as well as illustrate some obviously incorrect references to these concepts in recent articles, including those from the Wall Street Journal, Forbes, The Economist, The New York Times, and more.
Let’s talk about the future of predicting job success and why the world’s biggest evangelist for pre-hire assessments thinks tests are in danger of becoming extinct (and is OK with it).
There are a number of emerging trends in hiring right now that center around the currency of the new millennium: data. The impact of our ability to collect, organize, and interpret data is rapidly changing all areas of the economy. Should employment be any different? There are three ways in which data is slowly killing the employment test as we know it.
Turnover is a huge problem in any company. So what if you could predict, with reasonable accuracy, which of your team members were most likely to quit?