Rotational onboarding involves matching multiple employees looking to switch teams with multiple teams looking to add team members with specific skills and experience. Computational approaches that provide optimal one-to-one employee-team pairs cannot easily match each employee with several varied teams while load balancing the distribution across teams. This disclosure describes techniques to map a rotational onboarding pool of employees and team proposals as a network structure that enables the application of the Min Cost Network Flow algorithm to generate optimally varied one-to-many matches balanced across teams. When mapping the rotational onboarding task in the form of a network structure, the algorithm can incorporate various relevant required and optional constraints, inputs, and input conditions. The Min Cost Network Flow algorithm can be applied to obtain the optimal one-to-many employee-team proposal matches. Implementation of the techniques can provide employees with more varied options for switching teams, thus enhancing employee agency and improving employee satisfaction with career development choices. By avoiding hotspotting, the approach can distribute fitting human resources optimally across the various teams.
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Halabi, Kareem, "Generating Optimal One-to-Many Employee-Proposal Matches for Rotational Onboarding", Technical Disclosure Commons, (September 06, 2023)