Long-Range Staff Planner Using Simulated Employees
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Solution Overview
Problem
Current workforce management systems are unable to accurately plan for long-range staffing needs, typically only scheduling employees for a week or two based on expected demand, which is inadequate for meeting future business requirements.
Innovation Solution
A staff planner system that calculates long-range staff plans over six months to fifteen months by determining the timing and jobs needed to meet future labor demand, and suggests hiring or cross-training existing employees to effectively cover labor needs, using a combination of existing employees and simulated new hires to optimize labor distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If current workforce management systems schedule employees only for a week or two based on expected demand, then short-term scheduling flexibility is maintained, but long-range staffing planning accuracy deteriorates
Solution Approach 1:
The scheduling system is divided into two distinct modules: a long-range staff planner that handles strategic planning for future periods, and a traditional short-term scheduler that manages immediate scheduling needs. This segmentation allows each module to specialize in its time horizon, with the long-range planner focusing on accuracy and the short-term scheduler maintaining flexibility, thereby resolving the contradiction between long-range accuracy and system complexity.
2Reliability
If the system plans for long-range periods, then future labor demand coverage is improved, but the complexity of calculations and data processing increases
Solution Approach 1:
The long-range staff planner performs preliminary calculations and generates staffing recommendations in advance for future time periods. By conducting these calculations ahead of time, the system prepares detailed staffing plans that guide subsequent short-term scheduling decisions, thereby improving future labor demand coverage while managing calculation complexity through advance processing.
3Adaptability or versatility
If existing employees are allowed to work additional jobs or be cross-trained, then labor distribution flexibility is improved, but training and implementation time increases
Solution Approach 1:
The system changes the skill parameter of employees dynamically by identifying cross-training opportunities and recommending specific skill acquisitions. By systematically analyzing skill gaps and recommending targeted cross-training, the system improves labor distribution flexibility while minimizing training time through focused, data-driven recommendations rather than broad, untargeted training programs.
Data Source
AI summary
A system and method are disclosed for determining long-range staff planning. Embodiments include determining a baseline measurement of labor needs over a time period of one or more employees at one or more entities and modifying the baseline measurement of the labor needs over the time period based on one or more constraints that allow the one or more employees to work additional types of labor needs at the one or more entities. Embodiments further include determining working times and job assignments of the one or more employees based on one or more simulated employees that represent potential employees to the modified baseline measurement of the labor needs over the time period and storing the determined working times and job assignments in the database for the one or more employees at the one or more entities.