Picking: Data paves the Way to Peak Performance

In the logistics sector, personnel costs in the area of order picking represent a significant factor that significantly influences overall profitability. A study by the Fraunhofer Institute for Material Flow and Logistics (IML) shows that manual picking processes account for around 60% of operational storage costs. This key figure shows that significant savings potential can be achieved by specifically reducing inefficiencies.

In recent years, technologies such as mobile assistance systems, including smart glasses, have proven that they can contribute to increasing efficiency. The same study by Fraunhofer IML shows that the use of such systems can increase the efficiency of picking by up to 29%. In addition to these systems, however, the focus is on another technology that in particular provides precise insights into the processes and movements of manual work processes and quantifies the true potential of such systems:
Motion Mining®.

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In this article, we show how Motion-Mining® is used in a targeted manner in order picking, what optimization potential results from this and what central role the technology already plays today in efficiency and ergonomics assessment and process optimization of manual work processes.

What is Motion-Mining®?

Motion-Mining® is an established method for automated analysis of manual work processes — completely without a stopwatch or permanent observation. Using sensors and algorithms, movement data is collected and evaluated anonymously — whether from employees on the shop floor or from vehicles in the warehouse and/or on the farm.

The result: an objective, data-based basis for well-founded decisions to improve processes.

How does Motion-Mining® work?

The underlying technology consists of two main components:

Hardware

Mobile sensors worn by employees and stationary Bluetooth beacons record movement and position data over a period of around two weeks — without disrupting the workflow. Vehicles can also be equipped with sensors to analyze routes, downtime and usage.

More about our hardware.

Software & Analysis

The collected data flows into the MotionMiners PROCESS INTELLIGENCE (MPI) analysis platform. There, machine learning algorithms recognize patterns and anomalies and translate this data into process indicators. A process expert now has the opportunity to interpret process indicators and identify optimization potential, both in terms of efficiency and ergonomics, and to derive measures.
Note: We also offer Motion-Mining® analyses as a full-service package and interpret the data for you, if required. The case described here relates to our licensing model: MotionMiners INSIGHTS

Benefits of Motion-Mining® in Order Picking

• Increasing efficiency by identifying unnecessary movements and waiting times

• Ergonomic improvement through recognition of physically demanding activities

• Cost reduction through targeted process optimization

• Objective basis for decision-making instead of subjective observations

• Quick results thanks to short recording periods and automated evaluation
  

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The analysis of movement and process data with Motion-Mining® makes it possible to make existing inefficiencies visible and to achieve concrete savings potential. On average, Motion-Mining® reveals a potential of 15 to 40% within commissioning. Optimizing pick routes, reducing unnecessary movements, overhauling ABC sorting and improving ergonomics enable companies to significantly reduce overall picking costs. This leads to leaner processes, more efficient use of working time and resources, and increased employee satisfaction, which can often be observed when ergonomic process improvements have been introduced because they usually help people stay healthy. What results we have been able to achieve with our customers so far with Motion-Mining® can be found in our customer success stories, in the section Case studies.

Implementation of a Motion-Mining® measurement: step by step

1. Goal Definition & Planing

Which processes should be analyzed? Where is my biggest pain point in the process? What hypotheses are currently on the table, and what specific questions are we aiming to address?

2. Technical Set-up

Placement of hardware in the warehouse, training of employees.

3. Data Collection & Analysis

Recording period of approx. two weeks, followed by evaluation in the analysis dashboard, the MPI.

4. Derive & implement Measures

Based on the analysis, introduce specific optimizations — e.g. route management, workplace design, vehicle use, evaluation of special processes.

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Thanks to the plug-and-play approach, the implementation of Motion-Mining® in processes is generally uncomplicated and quick, without the need for intervention in operational IT. This significantly simplifies implementation and minimizes potential disruptions during operation. In addition, an experienced customer success team is available to support companies every step of the way — from planning to analyzing the results. In this way, questions can be resolved promptly and optimal results can be achieved.

Do you have any questions or would you like further information about using Motion-Mining® in your picking process? Our team of experts is always available to help you. Please contact us via our website-form or arrange a short consultation-meeting with us.

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