Material flow and personnel flow are the core processes in a warehouse. The former is usually highly automated, the latter mostly not. Even companies that use personnel management, planning and time recording software rely on self-developed Excel tools for intralogistical processes. Warehouse processes are very dynamic and volatile. Even in a highly automated system, there are often unforeseen interruptions at short notice, e.g. delivery delays, sick leave or technical components cause errors and downtime. This leads to the need to redeploy staff at short notice in order to fulfil the orders of the day. In addition, there are also long-term events that need to be responded to adequately. These are the main reasons why large-scale human resource management systems are rarely used to operationally manage the flow of staff in warehouses. However, self-developed systems for staff scheduling and control are often based on empirical values and expert knowledge, are time-consuming (spreadsheets and mails are sent back and forth) and prone to errors because data is entered several times. This leads to information being lost, not being available in time and thus making planning more difficult. In addition, valuable data for (long-term) staff planning is lost and cannot be used for analyses (keyword: Big Data).
The project was therefore dedicated to the question of how companies currently plan operational staff deployment in the warehouse, how short-term events are taken into account and to what extent software-supported operational staff scheduling already takes place in the warehouse. From this it was derived to what extent companies have a need for software support in workforce management.