From gauging your personality and intelligence level, to anticipating click-through rates based on images, Big Data empowers decision makers with large statistical samples gathered in a moment’s notice to predict future outcomes. The contender to leverage this school of thought is a new HR application called Workday Talent Insight that uses a system based on Netflix’s movie recommendation algorithm to predict which employees are most likely to leave and how to retain them within the company.
The app was developed by a former Netflix data scientist named Mohammad Sabah while employed by a company called Identified, which ironically, was then acquired by Workday last February. To make its prediction, WTI examines years worth of HR data, including the interval of time between promotions, tenure at current job, and job functions, to estimate a level of “corporate restlessness” or turnover risk. It then cross-references the data with job posting data on sites such as Indeed.com, to determine the current supply-and-demand rate for that employee or his/her role within the company.
In addition, WTI may also make recommendations on what management needs to do in order to keep the employee interested, by suggesting alternative positions (either horizontal or vertical) that would be best suited for their specific skillset. Workday’s senior VP of Technology Products Dan Beck adds, “It’s not just a predictive model of what could happen next, but adding context, so you can then give something more prescriptive, like a recommendation.”
Applying the principle of Big Data toward human resource functions should come as no surprise, especially in light of Silicon Valley’s growing demand for skilled workers and its cutthroat approaches for acquiring them.
Source: Business Insider
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