Employee retention is absolutely essential for running a successful organization. Keeping the crew engaged, happy, and productive is tricky and relies on a complex host of factors. Executives need to plan ahead, and that includes figuring out who is likely to stay and who is likely to bolt. How to plan?
Interplay® has applications ready for HR teams, with AI predictive analytics that can take an employee’s working history, age, gender, etc., and predict that employee’s likelihood to leave the company within a given time frame. Traditionally, the contributing factors for this were too varied and complex for standard regression analysis. However, advanced AI engines such as those available via Interplay can now make predictive analysis with a high degree of confidence.
With a core baseline of employee demographic data, this Interplay application can run through series of machine learning epics to calculate the mathematical probabilities of each contributing factor that might determine an employee's likelihood of staying or going. The demographic data can be loaded with a simple spreadsheet or tabbed text. Output can be routed to wherever best suits the organization.
With Interplay’s low-code platform, these predictive models can be connected to a myriad of HR point solutions to the degree that SaaS providers are available via https://en.wikipedia.org/wiki/API. Applications can be rapidly prototyped and then run in production environments all within the Interplay platform.
Client:
Confidential
Goal:
Reduce employee turnover
Development Time:
6 weeks
Deployment:
Undisclosed