From all the data a WMS gathers in the execution of warehouse activities, it generates vital statistics on the resources used to perform any range of warehouse tasks – a role that no other system in your application park can play.
Although vital for management, understanding past productivity is not enough to properly plan the activities of a distribution center. Visibility into the upcoming workload is also crucial. Since the WMS is not the entry point of transactional data, such as sales and purchase orders, it is dependent on a host system, such as an ERP, to provide insights on upcoming workloads.
A WMS should allow for orders to be created within its data set without instantly turning them into warehouse tasks. For instance, a sales order planned to ship 3 days from now can exist within the WMS without triggering picking tasks or having an impact on inventory availability.
The combination of data on upcoming workload (Purchase Orders & Sales Orders) and historical production rates provides managers with the ability to forecast and plan upcoming resources requirements.
A well optimized WMS can help you provide the following:
- Dashboards that integrate historical productivity levels and anticipated workloads with which resource level decisions can be made
- At any point in the shift, information on how each resource is doing and when you can expect them to complete their task
- Labor projections and a comparison to a list of warehouse tasks, so a manager can identify whether or not the next shift will be able to complete the work due in time
Interested in learning more about resource planning within in a WMS? Download LIDD’s eBook Keys to a Successful Warehouse Management System.
