Abstract: Examples provide a system for budget-driven labor demand allocation to roles and/or tasks associated with a selected location. A labor demand splitter analyzes a budget plan for a role and live metric data, including weekly delivery schedules and predicted foot traffic, using a set of per-role configuration criteria, forecast metrics, and per-role metric weights. A month splitter and/or a week splitter allocates hours to each day based on the analysis. An intra-day splitter spreads the hours across a set of time-segments for a selected day based on a selected forecast spreading routine, such as an end-points spreading routine or a mid-point spreading routine. The labor demand splitter performs rounding, smoothing, edge-filling and/or coverage fill to generate a set of per-role allocation hours for each day during a selected time-period. The per-role allocation hours are output if it conforms with the goal hours specified by the budget plan.

Abstract: Exemplary embodiments are provided for generating a metric based on current information and future needs. Historical payroll metrics are determined for a job title, and future payroll metrics are estimated for the job title. Forecasted workforce metrics are estimated for the job title, and preferred workforce metrics are determined for a specified period of time for the job title. It is determined whether a low-point is expected within the specified period. The forecasted workforce metrics and the preferred workforce metrics are compared to estimate an employee-hour deficit in the workforce. A hiring recommendation is generated based on the employee-hour deficit and open requisitions, and an employee status is assigned to the recommendation based on the low-point.