Operational data matching shows: Grid boxes extend picking time by 30% and increase ergonomic load by 20%. The combination of WMS data and Motion-Mining® creates new transparency for logistics teams.
Modern logistics centers collect millions of data points every day, many of which remain hidden in separate systems. Only the combination of movement data and WMS data provides a complete picture of how manual processes actually work and which factors influence them.
A practical example impressively shows how great this potential is: In the order picking of machine parts, the use of certain load carriers resulted in a 30% longer lead time and a 20.6% higher ergonomic load. These relationships only became visible when Motion-Mining® sensor data and WMS charge carrier data were linked together — an analysis that would hardly have been possible using traditional methods.
Operational data matching combines movement-based sensor data with operational system data, for example from WMS, TMS or ERP systems.
As a result, variables such as
be directly linked to measurable effects on picking times, distances, load and efficiency.
The result: Invisible patterns become visible, hypotheses become measurable and decisions become more reliable.
The company in question orders machine parts for its own production. Direct suppliers use different types of load carriers. The respective type is documented in the WMS.
This diversity is typical of inbound processes. However, it has not yet been possible to clearly prove whether and how they affect picking time, ergonomic load and ultimately costs.
MotionMining® recognizes the movements and activities of people or objects and locates them. In combination with WMS data, the result is a complete picture of the process.
The analysis shows a clear pattern: lattice boxes increase ergonomically demanding time by 20.6%.
The stressful postures include in particular:
On an eight-hour shift, this is equivalent to:
1 hour and 12 minutes of additional workload per employee
Extrapolated over weeks and several employees, there is a relevant risk factor for:
What was previously considered “burdensome but common” can now be measurably quantified and thus addressed in a targeted manner.
The process indicators also speak a clear language:
What initially seems like a small deviation can become a significant cost factor when picking volumes are high. For the manufacturing company, this means that lattice boxes slow down productivity. And that every day with every pick.
1. Conduct supplier negotiations based on data
If a load carrier demonstrably causes higher costs, it can:
2. Repackaging upon receipt of goods
If the supplier is unable to make the switch:
3. Redefine charge carrier strategy
Well-founded container logic reduces variance and process fluctuations. Technical solutions can help with this, such as:
The analysis shows that the load carrier is a process lever and not a detail.
By integrating WMS data and Motion‑Mining®, relationships that were previously only suspected can be precisely quantified. The result is a new level of process transparency: from hypothesis to well-founded insight, from black box to data-based decision.
Companies can now:
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