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Capacity and Workforce Planning

The W2MO Digital Twin of your warehouse provides an overview of the capacity situation in your warehouse and enables more effektive workforce planning.

Strategic planning and operational use

Online productivity control

Online load preview per department, team, and shift

also available on mobile devices makes time-specific and dynamic bottlenecks visible

Scenario calculation

for the optimization of working time models and employee deployment

Demand-oriented deployment of personnel

based on current/planned orders

Minimization of the organizational effort

for reassignments

Holiday planning

based on the expected order volume and the resulting workload

Strategic Capacity Planning

  • Optimization of work time models, staff number, and teams
  • Development of operational recommendations to handle sudden changes in demand
  • Optimization of buffer capacity for load peaks
  • Scenario calculations, e.g. changes in working schedules, change in order schemes of customers, mix of full time and part-time workers
  • Budget planning
Strategic Capacity Planning

As part of strategic capacity planning, the required workforce is determined, budgets are planned, and various scenarios are considered. Using a true-to-scale model and adaptable standard times and time studies, realistic process times can be detected in the digital twin. Based on the simulated storage tasks, the necessary personnel for each process in the logistic sequence can be realistically identified. This makes it possible to determine in the long term which workforce and shift model is suitable in which situations. Load peaks can be simulated and, allowing for the examination of a mix of regular and temporary employees. Different work time models can be evaluated as well.

Mid-term Capacity Planning

  • Extrapolation of past scenarios and order pools for future periods
  • Volume planning, applying of alternative scenarios
  • Automatic identification of efficiency for estimating future staff demands
  • Holiday planning in cooperation with administrative systems
  • Shift scheduling
  • Prediction of the staffing requirements based on automatic scaling from comparable past periods
Mid-term Capacity Planning

For medium-term planning, future demand is estimated based on expected demand. The objective is to make the most accurate planning possible based on information from the past. At the same time, the expected workforce needs are automatically calculated considering the forecasted sales volumes and order structures. From this, holiday planning can be generated, which is based on holiday requests from higher-level management systems. Approval is then granted on the basis of the expected capacity requirements. A similar procedure is used for foresighted shift planning. The shift structure and numbers are determined for a mid-term period.

Operational Workforce Planning (Online Productivity Control)

  • Bottleneck avoidance through constant, current load evaluation in the digital twin
  • Optimization of the available workload through automatic redistribution of employees between work areas
  • Consideration of, among other things, current orders, warehouse assignment, current staff availability and/or relocations, changes in allocation, and failure of system components
  • On-time delivery by determining the expected end dates of the orders
  • Re-prioritization of orders and relocation of staff in case of imminent delay
  • Balancing the capacity workload of the employees
Operational Workforce Planning (Online Productivity Control)

One of the key elements in operative workforce scheduling is current load balancing in the digital twin. Based on current orders and, if necessary, short-term forecasts, the expected workload is simulated over the day. This results in a division of employees according to their abilities in the work areas. The expected completion date for each order is constantly monitored, so if a delivery is in danger of being delayed, it is possible to react in time by re-prioritizing orders and reallocating employees. In the event of newly arising circumstances, such as system failures, a reallocation can be initiated at any time. This can be done automatically. The constant transparency of the workload and the reduction of unused resources lead to an increase in productivity in the overall process productivity.