Bewegungsdaten

What is movement data?

Movement data is generated whenever a goods item or storage unit changes its status, location or owner. Typical triggers include goods receipt postings, transfers between storage locations, picking operations, dispatch postings and returns registration. Unlike master data – which describes the fixed, fundamental properties of an article or storage location – movement data is transaction-based and time-dependent: each record is assigned to a specific event and a timestamp.

Typical contents of a movement data record include: date and time of the event, quantities and units affected, source and destination storage location, the Handling Units (HU) or SSCC numbers involved, the triggering order, and the responsible user or executing system. These data points are generally generated automatically through posting processes in ERP, WMS or TMS systems.

How does movement data work in practice?

In modern warehouse systems, movement data is generated continuously: a scan at a data capture terminal, a confirmation in the warehouse management system, or an automatic posting by a conveyor system each creates a new record. The quality of this data depends heavily on how seamlessly the capture points are covered throughout the process. If mandatory scans are missing at critical points – such as during the handover between goods receipt and put-away – gaps arise that can lead to inventory discrepancies or time-consuming searches.

For evaluation purposes, movement data is typically used in three areas of application: firstly for operational transparency, meaning current knowledge of where which goods are located; secondly for KPI reporting and process analysis, such as throughput times, picking performance or error rates; and thirdly for proof and audit processes, for example when documenting delivery quantities to clients or authorities.

In procurement and vendor management, movement data serves as the basis for performance verification within the framework of SLAs, as well as for vendor evaluation and process cost accounting.

What matters when planning and implementing?

When designing a movement data concept, you should clarify the following questions:

• Which types of movements are fully captured, and where do intentional or unintentional gaps exist?
• How is data quality ensured – for example through mandatory scans, plausibility checks or dual-control principles?
• How long is movement data retained, and what legal or contractual requirements apply to archiving?
• How is the data made available across systems – for example through API interfaces between ERP and WMS?

A common practical problem is data volume: in large warehouses, millions of movement records are generated every day. Without a clear data architecture and suitable analysis tools, this potential goes untapped. At the same time, data quality depends on the vendor and the process – blanket statements about completeness or accuracy should therefore be treated with caution.