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AI for Skill-Based Workforce Planning AI helps organizations strategically plan for necessary skills, ensuring the workforce remains competitive and well-compensated: ;Reasoning models can analyze emerging skill demands, allowing companies to proactively invest in training and upskilling initiatives.; ;AI assigns employees to projects based on skill assessments, optimizing talent allocation.; Example: A reasoning model is fed with information about upcoming projects and the current workforce distribution along with employees' skill sets.

For WorldatWork Members ;Leveraging Total Rewards to Defeat the Four Horsemen of RTO , Journal of Total Rewards article; ;Checklist: Evaluating EVP Delivery Across Work Arrangements , Workspan Daily Plus+ article; ;Workplace Models: How Are Organizations Maximizing Them?

To illustrate the difference between the 4D model and the one outlined in Figure 1, in an organization experiencing high turnover, management using a Figure 1 model would ask: How is the rewards program affecting people’s decision to leave?

Close to half of the organizations surveyed said they believe that “building a talent ecosystem encompassing alternative work models will be an important HR capability” over the next three years.

Improve your modeling skills to enable better compensation decisions — for example, around incentives or pay increases.

Model the Pay vs.

Other organizations, though, are contemplating redefining or validating their crediting event as well as determining the right one for a new product/pricing model.

The “hire-to-retire” model, central to traditional HR planning, is outdated in an era where workers frequently change roles or employers.; ;Market and technological disruptions.

Traditional models reward tenure and conformity.

Because the data are coming from many idiosyncratic sources,” the researchers wrote, “we also expect that statistical modeling skills will become increasingly important, to adjust for various biases, gaps and collection processes.”