The post-COVID work environment has seen unprecedented shifts in employee preferences. They require more flexibility in the ways they do their work, and they also demand this work to be more intellectually stimulating. This poses additional challenges for MISO’s succession planning and allocation of employees brought on by retirements and employee turnover. MISO is therefore interested in finding new approaches to the areas of employee retention and talent acquisition.
In this Challenge, MISO is looking for methods and tools of predictive analytics to improve employee retention and talent acquisition. MISO is requesting a comprehensive review of the field of predictive analytics tools applied to human resources. MISO is also asking for specific suggestions on how these tools could be put into practice to achieve its goals.
The post-COVID work environment has seen unprecedented shifts in employee preferences. They require more flexibility in the ways they do their work as hybrid work arrangements become common. Employees also demand their work to be more intellectually and emotionally stimulating. All this happens against the background of a higher-than-usual number of employees who leave or retire earlier than usual. This poses additional challenges for MISO’s succession planning, and MISO is interested in finding innovative, data-driven approaches to the areas of employee retention and talent acquisition.
In this Challenge, MISO is looking for methods and tools of predictive analytics to improve employee retention and talent acquisition. An “ideal” solution to this Challenge will consist of two parts. First, Solvers will compose a comprehensive review of the field of predictive analytics tools applied to business human resources. Second, Solvers will formulate specific suggestions on how identified tools could be put into practice to improve employee retention and talent acquisition.
Awards:- $15000 USD
Deadline:- 31-10-2022
