These standard analyses enable the person in charge of a distribution center or warehouse to calculate the rough workload for the next few days. The analyses can be used, for example, for planning how many staff workers are required, for creating wave picks, or for statistical evaluations.
Using these analyses it is possible to display an overview of the workload either per day or per warehouse.
The workload data update is based on SAP documents:
Purchase order and corresponding shipping notification
Stock transport order
Rough goods receipt (only in retail systems)
Sales order
Delivery
Returns to vendor, customer returns and store returns (only in retail systems)
The system updates the quantity, weight, volume, and the number of document items or stock allocations from these documents. Alternatively, processing times can be determined by using Customizing tables.
The rough workload forecast is a standard analysis in the Logistics Information System (LIS).
All functions of the LO Logistics Information System are available for analysis of the workload data, for example:
Early warning system
Dual classification
Classification
Hit lists and ABC analysis
Arbitrary aggregation and disaggregation options
You can also use the planning function to incorporate planned data into analyses, rather than analyzing only actual data.
Implementation of Lean WM (as a minimum) is necessary to perform rough workload estimation. Rough workload estimation is naturally also possible using the complete WM function.
For information on Customizing, refer to the IMG for Warehouse Management,
Rough Workload Estimate
section.
The following five analyses are provided for the rough workload estimate:
Total overview
Goods receipt / putaway
Picking / goods issue
Customer/stores returns (stores returns only in retail systems)
Returns to vendor
With analysis 1, you can determine the entire workload for the distribution center / warehouse for all warehouse processes.
With analyses 2 through 5, you can determine workload for specific warehouse processes.