This algorithm can predict when workers are about to quit—here's how. (via CNBCMakeIt)
, Professors Brooks Holtom of Georgetown University and David Allen of Texas Christian University describe the results of their latest research. Using big data and machine-learning algorithms, the two developed a real-time indicator to measure two main indicators that an employee is about to quit.
When put to the test, the algorithm identified that those marked as "most likely" to be receptive to a new opportunity were, in fact, 63% more likely to be in a new job by the end of the three-month study period.Knowing that HR can use this information to determine who's a flight risk might feel like an overstep. There's a financial benefit to re-engaging dissatisfied employees rather than having to hire someone new.
By using available data, "The potential benefit to employees is that, over time, sophisticated managers and employers learn more about what their people really value — not just say they value — and are able to create a more positive and perhaps more personalized work environment," Allen says."My major concerns are around privacy boundaries," Holtom says.
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