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It’s exciting to watch advances in predictive and prescriptive employee solutions. Workday recently announced the release of an application enabling employers to “identify which employee is likely to quit, and what options need to be considered to retain that person”.

Workday is not the first to announce Flight Risk Scores of current employees. Many top Talent Management solutions have made similar announcements in the past several months. It’s a step in the right direction.

As exciting as these announcements sound, I wanted to tease apart some of what we have learned that matters to businesses and their employee decisions. Perhaps frame how to interpret current innovations coming from the Talent Management industry.

Is “Focusing Only on a Small Subset of Top Performers the Right Focus?”
Businesses and their Talent Management vendors seem to be obsessed about a small subset of top performers they are afraid of losing. Meanwhile thousands of bottom performers are hired, weigh down our organizations, turnover quickly and cost our businesses millions.

Of course businesses need to attack the problem from both sides. The most costly expense to mid to large businesses are frequently high volume, high turnover roles where thousands of employees are hired only to leave quickly or be a bottom performer. In both instances these new employees incur a massive cost to the business before providing any value to the employer.

Flight Risk Scores for Current Employees is Too Late
They are already hired. They are on-boarded. They are costing the organization without delivering value. A better approach would be to predict how long a job candidate will stay, before you hire them avoiding hiring those with a high flight risk altogether.

Figure 1: Turnover Prediction is a Process not a Single Score Employee-Cost-and-Performance-Curves-Talent-Analytics-300x225

Flight Risk is not a Single Score
Employees in a specific role have different flight risks at certain times. Like saying the probability of machine failure is 78%. There is a missing piece of important context, which is “time”.

For a machine the probability of failure might be 32% at 6 months, 51% at 1 year and 78% at 2 years and so on.  This Survival Curve gives the most accurate view of Flight Risk and enables the organization to be more sophisticated about their decisions.

Understanding that flight risk is a curve instead of a single point in time allows the organization to pinpoint when intervention is optimal and can save the most employees and the most money.

1Greta_PhotoThis is a guest article by Greta Roberts, the CEO of Talent Analytics, CorpGreta is an influential pioneer of the emerging field of predictive workforce analytics where she continues to help bridge the gap and generate dialogue between the predictive analytics and workforce communities. Since co-founding Talent Analytics in 2001, CEO Greta has successfully established the firm as the recognized employee predictions leader, both pre- and post-hire, on the strength of its powerful predictive analytics approach and innovative Advisor software platform designed to solve complex attrition and performance challenges. Follow Greta on twitter @gretaroberts.