At a glance
- Company
- META-RegalbauMaker of shelving and racking systems
- Size
- Mid-market (250–999 employees) The publication that describes the case gives the company about 300 employees.
- Industry
- Manufacturing
- Where and when
- Germany. Published August 2021.
- Who produced the figures
- The company itselfThe figures are the company’s, published by Plattform Lernende Systeme, a German platform of AI experts, in a collection of cases from mid-sized firms.
What they did
META-Regalbau makes shelving systems, from simple shelf units to multi-storey racking. An order is made up of many separate parts. Staff collect them from different places in the warehouse, pack them and put them ready for dispatch. The company saw room to save time there. It was also about to move to a new plant and wanted the best layout for the new warehouse.
It worked with a start-up from its region. Small Bluetooth transmitters were fixed to the warehouse walls, and staff wore small sensors as they worked. This recorded the routes they walked and where they waited, for example for tools or at machines. AI analysis of the recordings then showed where time was being lost.
The works council, which represents employees, was informed from the beginning. So were the logistics managers and every employee. They were told the aim of the project and how the technology worked.
The numbers
- About €22,000 a year saved, from the new warehouse layout and from more efficient picking together.
- Paid back in 1 to 1.5 years. That is how long the saving took to cover the cost of working with the start-up.
What the case shows
- Here AI analysed the work and people changed it. Nothing was automated. The output was a better layout and a list of delays to remove.
- A modest result with a short payback. The saving is small for a company of 300. The cost was recovered in 1 to 1.5 years.
- Timing mattered. The analysis was done before a move, when the layout of the new warehouse was still open.
- Staff were told before they were tracked. Wearing sensors at work is sensitive. The company explained the purpose and the technology to everyone, and to the employees’ representatives, from the start.
What this says about the practices
Practices the company applied
- Protect psychological safety during an AI rollout From the start, logistics managers, the works council and all employees were told what the analysis was for and how the technology worked. Do first · Effort: medium (weeks, a few people)
- Start with one costly process, not a company-wide rollout The analysis covered one process: picking the many separate parts of an ordered shelving system in the warehouse. Do first · Effort: medium (weeks, a few people)
- Map tasks before deciding what to automate The steps of the picking process and the routes staff walked were recorded and analysed before the new warehouse layout was fixed. Do first · Effort: low (days, one person)
Sources
- Plattform Lernende Systeme (August 2021). KI im Mittelstand: Potenziale erkennen, Voraussetzungen schaffen, Transformation meistern. Report, in German, with a section on this company. acatech.de