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In our employee retention challenge, we would prefer to obtain an estimate of the probability that a person will leave the organization rather than just a prediction of whether they will do so within a given time frame. According to the likelihood that an employee will leave, we would rank them, and the highest probability cases would receive majority of a constrained incentive budget.

Consider the case of employee turnover, where Human Resources treats a n employee because they believe they will leave the company in a month, but the worker stays. This result is erroneous. Although this error could be costly, inconvenient, and time-consuming for both Human Resources and the employee, it is a smart investment for the development of interpersonal relationships.

Compare this miscalculation with the one that occurs when human resources ignore to recognize or reward employees, resulting in their resignation. This kind of mistake is more costly because the business lost an employee, which could result in serious setbacks and cost more to hire back. Different charges are considered based on these faults and the kind of employee being dealt with. Would we need a more expensive sort of treatment, for instance, if it was a high-paid employee? What if the worker makes a low salary? Each inaccuracy has a different cost, which should be considered.

Solution 1:

• We can rank employees by their probability of leaving, then allocate a limited incentive budget to the highest probability instances.

• We can allocate our incentive budget to the instances with the highest expected loss, for which we'll need the probability of turnover.

Solution 2: Develop learning programs for managers. Then use analytics to gauge their performance and measure progress. Some advice:

• Be a good coach

• Empower the team and do not micromanage

• Express interest for team member success

• Have clear vision / strategy for team

• Help team with career development