The U.S. sports world has been abuzz with “Linsanity” – hype about the excellent performance of Jeremy Lin, an NBA basketball player who came off the bench and immediately displayed stunning numbers.
Regular readers of my blog are likely asking, “Derek follows U.S. basketball?” No, not really. But I do follow research out of Cornerstone and Jason Corsello’s Human Capitalist blog.
Last week, Jason wrote about Jeremy Lin, pointing out that – based on his stats from college – Jeremy was predicted to be star. Yet he was very close to being released from his team, the New York Knicks, before getting his chance in the spotlight. In fact, two other NBA teams had already cut Lin.
That begs the question – why aren’t most companies analyzing their employee data to find the rising stars. One could argue that Jeremy Lin’s heritage (Chinese) and experience (Harvard) didn’t necessary sound the bell in an industry where pedigree and success looks very different. Every company must have many Jeremy Lin’s running around their offices. The answer, though, is most won’t be found (and likely lost) until performance focuses on the outcome instead of the process.”
How to find your own Jeremy Lin
I tend to think, however, there isn’t enough performance focus on the outcome OR the process. The essence of the challenge is simply not enough data points. I don’t need to hash through (again) the failures of the annual performance review as just one-time feedback from one point of view.
The question becomes, how do you build the data on your talent so you can find your Jeremy Lin’s? What’s the RSB40 score (a critical basketball stat) for your talent?
You need more data. A strategic employee recognition program can give it to you. When all employees are encouraged to praise their colleagues in very specific and detailed ways, you get far more data points on performance and therefore a much broader picture of your talent on both an individual and aggregate basis.
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Do you need your most innovative product designers for a huge new product development push? Simply parse the data to find which product designers – anywhere in your organization – have been recognized the most for innovation. If you structure your program properly for what matters most in your organization, you can turn your recognition data into your own form of “moneyball” for your hidden talent.
How do you make sure you’re not cutting your star talent before you even give them a chance to succeed?