In a food production plant there is a supply chain almost no one talks about. It is not about raw materials, ingredients or packaging, but about something that involves hundreds or thousands of people every day: workwear.
Every day thousands of garments are handed out, worn, returned, sent to the laundry, processed and put back into circulation. It is a continuous flow, yet it is rarely planned with the same rigour reserved for the other resources of production. And when it is, the results are surprising: in a real case we will look at later, the number of garments in circulation was cut by 60% while improving, not worsening, the service.
We would be glad to talk it through with you at CFIA Toulouse, from 22 to 24 September 2026 (MEETT), an event dedicated precisely to those who face the complexity of food production every day: efficiency, operational continuity, automation, quality, people and use of resources.
Is there a supply chain without a forecast?
No production manager would plan raw materials without knowing at least three variables: demand, lead times and safety stock. In workwear management, however, this information is often far less precise.
You know the number of employees, the total garments purchased and, sometimes, the theoretical number of sets assigned to each operator. But none of this tells you what the real demand is. How many size-L trousers are actually used each week? Which departments generate the most rotation? How long passes between a garment being returned and becoming available again? How much stock is really needed to absorb production peaks, new hires or variations in laundry times?
These are obvious questions in any supply chain. Applied to workwear, they suddenly become difficult.
What does the need for workwear really depend on?
Not only on the number of operators. It depends on the relationship between three factors.
Demand varies by department, garment type, size, shift and season: two departments with the same headcount can have completely different needs.
Lead time matters because a returned garment is not immediately available. It has to be collected, transported, washed, checked, handed back and put into circulation again; the length of this cycle directly affects the number of garments needed.
The buffer absorbs the inevitable variability: turnover, absences, temporary production increases, logistical delays. The problem arises when the buffer becomes the main tool for compensating a lack of information.
Why doesn’t more stock mean more service?
If real consumption is unknown, increasing stock seems the most prudent choice. In the short term it often is. But piling up garments does not automatically improve the service level, and sometimes worsens it.
A plant can have plenty of workwear available and still suffer localised shortages: some sizes sitting idle, others always in use; items abundant in the system, but not where they are needed. The problem is not the absolute quantity, it is the alignment with demand. The same rule that applies to raw materials applies here: availability does not mean quantity, it means the right resource, in the right place, at the right time.
Workwear has its own service level?
In supply chain terms we talk about the service level: the ability to meet demand when it arises. Workwear has one too. If the operator always finds the right garment in the right size, the system works; if they have to look for it, wait, ask someone or fall back on an alternative, the service level drops.
This changes the objective. It is not about having the largest possible number of garments, but about ensuring availability with the most appropriate stock level. A tiny difference in wording, an enormous one in management.
How do you make an invisible supply chain measurable?
To improve a system you first have to be able to observe it. RFID technology makes it possible to identify each garment and record its events, from distribution to return. But traceability is not the finish line: the value comes when the data describes the behaviour of the system.
How much is actually distributed? Which items rotate the most? How often is a given size needed? How long does a garment stay out of available stock? Where do imbalances form? With a solid data foundation, workwear stops being simple inventory and becomes a flow to be governed.
The laundry is part of the supply chain too
In this model the laundry is not an external supplier, but an actor in the cycle. The turnaround time of garments directly conditions the amount of workwear needed: a change in lead time raises or lowers the stock requirement.
The reverse is also true. More accurate consumption data lets the laundry prepare what is really needed, instead of working on estimates, occasional requests or standard stock. The relationship evolves: from supplying garments to jointly managing a flow.
The Agristo case: redesigning the flow, not just automating it
That is exactly what Agristo did, an international producer of frozen potato specialities. Introducing an automated distribution and return system was only part of the change; the decisive step was using real data to understand consumption and reorganise the relationship with the laundry.
The result: garments in circulation cut by about 60%, administrative activity made of phone calls and e-mails reduced by about 90%.
It is not proof that fewer garments are enough, but that a better-informed supply chain can be both more efficient and more controllable.
From stock to resilience
Resilience is not about hoarding resources without limit, it is about continuing to function when conditions change. For workwear that means absorbing variations in demand without needlessly inflating stock, knowing where to keep safety margins and where surpluses are hiding instead, reacting to shift changes, seasonality, turnover or laundry times with better information. In a word, moving from reactive management to informed management.
See you at CFIA Toulouse, from 22 to 24 September 2026
This is the conversation we want to bring to the MEETT. Not just to show a machine, but to show what happens when distribution, return and data become parts of the same process.
At the stand you will be able to try White C Evo and White Box, see real cases developed in industry and food production, and follow a demo of ONE, the ABG software that turns the data collected by the systems into useful information on usage, availability and needs. It will also be a chance to discuss concrete situations: stock sizing, laundry times, distribution by size and department, peak management and replenishment planning.
Every plant has its own workwear supply chain, the difference is how well it knows it. If you want to analyse yours, book an appointment with the ABG team at CFIA Toulouse: we will start from your data, your flows and your real needs.
