An algorithm based on Netflix's movie recommendation system has just been repurposed to let employers know if they're about to lose their most talented and productive workers.

A former Netflix data scientist, Mohammad Sabah, has used an algorithm to develop a predictive system. He has packaged it into a new app called Workday Talent Insights (WTI), which comes from Human Resources software creator, Workday.

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At its base, WTI uses Netflix's movie recommending algorithm that lets users know what movies they might like from their existing picks.

The app then uses sets of different data to predict the hard-won or hard-nurtured departure of certain staff members.

To make its prediction, WTI examines years of human resources data, the interval time between promotions, tenure at the current job, and job functions.

These are then used to estimate the turnover risk of an employee.

The data is revealed by cross-matching this information with job postings. In turn, this determines the supply and demand of the market in relation to the workers functions in the company.

Dan Beck, Workday's senior VP of Technology Products, says WTI isn't just a predictive model that lets people know what could happen next. Instead, WTI adds context, allowing space for something prescriptive like a recommendation on the matter.

Thus, WTI can act as more than just an alarm that goes off when an employee is about to leave a company.

It can offer employers so much more such what management needs to do or offer to keep the employee interested, and suggestions of alternative positions best suited to the person's skillset.

The application of the Netflix algorithm and WTI to human resources comes as no surprise, especially with the Silicon Valley boom that brings in a steady demand for skilled workers.

Tagsnetflix, employees, Algorithm, Mohammad Sabah, Workday Talent Insights, WTI