Lean in agriculture: less waste, more sustainable
In the food chain, waste isn't abstract. It's food in the bin. And nearly all of it is decided long before the supermarket.
Lean thinking — Toyota's recipe for eliminating waste — has been applied to food supply chains for over a decade.
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And there's one difference with industry that changes everything: here the waste isn't an abstract inefficiency. It's food that ends up in the bin.
Why it fits so well
The seven lean wastes have a direct, very physical translation in the field and in the cold chain:
| Lean waste | In the food chain |
|---|---|
| Transport | journeys that speed up ripening |
| Inventory | perishable product waiting in a chamber |
| Waiting | harvested fruit with no destination assigned |
| Overproduction | a crop with no buyer, lost |
| Defects | product rejected on size or looks |
| Over-processing | handling and packing nobody values |
| Motion | unnecessary movement around the warehouse |
But there's a particularity, and it's time.
In a metal parts factory, inventory waits and nothing happens to it. In food, every hour of waiting eats the product's shelf life. The cost of waiting isn't financial. It's biological. You can't negotiate it with anybody.
What showed up when the whole chain got looked at
For years the studies focused on separate stretches: the farm, the transport, the point of sale. The step forward came from analysing the complete chain, field to customer.
And then something turned up that only shows with that perspective: a good part of the waste that appears at the end was decided at the start.
A size specified in a contract leaves perfectly edible fruit lying in the field. A weak forecast produces a crop nobody is going to buy. And watch this, because it's the important bit: optimizing each link separately can actually make the whole worse.
The bridge to 2026
This is where I work today. And the change that matters most to me is called traceability.
At the Grupo Martinmar bakery, artificial intelligence closes the traceability of every pallet: composition, the checks it passed through, cold-chain temperatures, and an image of each of those moments. In seconds.
That started life as a certification requirement — paperwork, in other words — and ended up as a waste-reduction tool. Why? Because when you know exactly which batch has the problem, you don't have to pull the whole day's production.
And there's the point I find most interesting for the whole sector: the finer your traceability, the less healthy product you throw away as a precaution.
Because the alternative to knowing is throwing away too much. It always has been.