What If We're Asking the Wrong Question About Food Waste?
Over the years, I've experienced periods where paying the bills took priority over buying the quality of food I wanted to eat.
When the choice is between financial survival and nutritional quality, survival wins.
That isn't because people don't care about eating well.
It's because reality sometimes forces difficult choices.
Most families facing financial pressure don't buy the food they'd ideally like to eat. They buy the food they can afford.
At the very same time, huge quantities of perfectly edible food never reach anyone's plate.
According to estimates, around 10 million tonnes of food is wasted across the UK every year.
That’s enough to fill Wembley Stadium around eight times.
Around 1.6 million tonnes (16%) of that is estimated to be lost on farms before it even enters the wider supply chain.
The older I get, the more interested I become in contradictions - situations where resources and unmet needs somehow manage to exist side by side. This felt like one of them.
In one of the world's largest economies, people struggle to afford nutritious food while farmers are unable to sell perfectly edible produce. At the same time, schools, hospitals, care homes and community organisations are all trying to stretch increasingly tight budgets.
How can these problems exist at the same time?
The Restaurant That Changed How I Think About Food
Many years ago, I worked in a restaurant that didn't operate from a fixed printed menu.
Instead, we had a blackboard, and the menu changed constantly.
If our wholesaler had an abundance of a particular ingredient at a good price, the chef designed dishes around it.
Customers loved it because there was always something different.
The restaurant benefited because it could buy excellent ingredients at sensible prices.
Looking back, I've often wondered why we don't apply that same principle more widely.
The chef didn't begin by asking, "What do I want to cook today?"
He began by asking, "What ingredients are we working with today?"
Everything else flowed from that simple question.
That flexibility has become less common. Independent restaurants like ours were far more common than they are today. As national chains expanded, consistency became a selling point. Customers expected the same meal whether they were in Liverpool or London. That consistency requires highly standardised procurement, leaving less room to adapt menus around whatever ingredients happen to be available.
However, that experience has stayed with me.
Why couldn't elements of that thinking work elsewhere now?
It's Been Done Before
During the Second World War, Britain faced an unprecedented challenge. Food imports were under constant threat, yet the country still had to feed millions of people.
The solution wasn't simply to produce more food.
It was to make better use of the food and land that already existed and coordinate the food system more effectively.
The Government encouraged people to grow their own food through the Dig for Victory campaign.
The Women's Land Army helped maintain agricultural production.
The Ministry of Food coordinated rationing, procurement and distribution.
County War Agricultural Executive Committees worked directly with farmers to increase production and make better use of available land.
School meals became increasingly important, and despite wartime shortages, nutrition became a national priority.
None of this was managed using computers.
It was achieved using paperwork, telephones and an enormous amount of human judgement.
Of course, wartime Britain was an extraordinary situation, and I'm certainly not suggesting we return to rationing or central planning.
But it does raise an interesting question.
If Britain could coordinate much of its food system using the technology available in the 1940s, what might be possible today?
Not through greater government control.
Not by replacing farmers, wholesalers, chefs or procurement professionals.
But by giving them access to better information.
Artificial intelligence can analyse millions of data points in seconds. It can identify patterns, predict demand and suggest solutions that would have taken teams of people days or weeks to calculate.
Perhaps the real opportunity isn't using AI to make decisions for us.
Perhaps it's using AI to help us coordinate resources more intelligently than we ever have before.
Artificial intelligence isn't the idea. Better coordination is. AI makes that coordination practical on a scale that wasn't previously possible.
The Conversation That Changed My Mind
When I recently shared a simplified version of this idea on LinkedIn, several people working in food resilience, farming, procurement and supply chains offered some fascinating insights.
One observation particularly changed my thinking.
Perhaps we shouldn't immediately describe unused edible food as food waste.
One contributor suggested thinking instead in terms of food excess.
Food that is still perfectly edible isn't waste.
It's simply food that hasn't yet found the right destination.
That feels like an important distinction.
Another point was equally valuable.
Receiving occasional surplus food isn't the same as having reliable access to nutritious food every week.
Continuity matters.
A system that occasionally distributes excess food isn't necessarily solving food insecurity.
It's helping, but it isn't addressing the underlying problem.
There was another observation that struck me.
Some people access surplus food because they're making an environmental choice. Others rely on it because they simply cannot afford alternatives. Those are very different situations.
If we're trying to design better systems, understanding those differences matters.
The comments didn't convince me the idea was wrong.
They made it better.
What If We Started Somewhere Else?
The more I considered the discussion, the more I found myself wondering whether we're asking the wrong question.
Rather than asking:
"How do we redistribute food waste?"
Perhaps we should be asking:
"How do we prevent perfectly edible food from becoming waste in the first place?"
Imagine regional digital food hubs covering the country. The exact boundaries are less important than ensuring each hub is large enough to connect producers, wholesalers and public services efficiently.
Farmers, growers, wholesalers and food producers could upload information about produce becoming available.
Not simply what is left over at the end of the week, but expected harvests, seasonal gluts, quality grades, shelf life, quantities and collection windows.
Schools, hospitals, care homes and community kitchens could upload their own information.
Expected meal numbers.
Dietary requirements.
Budgets.
Storage capacity.
Delivery windows.
Rather than every organisation operating independently, all of that information could exist within one intelligent system.
This Is Where AI Could Change Everything
Twenty years ago, coordinating something like this would probably have required an army of planners.
Today, artificial intelligence routinely solves problems of similar complexity.
Amazon uses AI to predict demand and position products before customers even place an order.
Supermarkets increasingly use AI to forecast stock levels and reduce waste.
Delivery companies constantly optimise transport routes.
Farmers are beginning to use AI to monitor crops, predict yields and improve irrigation.
The technology already exists.
The opportunity may simply be applying it differently.
Rather than waiting for food to become surplus, an AI-powered regional food hub could continuously analyse information from producers and purchasers across the region.
It could recommend where food should go before it risks being lost.
But I think it could go much further than simply moving food around.
The role of the AI needn't stop at matching food with buyers. It could also help catering teams make practical use of whatever was available.
Imagine the system knows that this week's available produce includes chicken, potatoes, carrots, onions, broccoli, apples, milk and wholemeal flour.
Rather than simply informing schools and care homes that those ingredients are available, it could suggest complete weekly menus designed around them.
Not random menus but menus that automatically meet nutritional standards, account for allergies and dietary requirements, remain within budget, maximise the use of locally available produce, and reduce unnecessary purchasing from elsewhere.
For example, the AI might recommend:
Monday - Roast chicken with herb potatoes and broccoli, followed by seasonal fruit.
Tuesday - Chicken and vegetable casserole with freshly baked wholemeal bread.
Wednesday - Cottage pie made with seasonal vegetables, followed by apple crumble.
Thursday - Homemade vegetable soup with bread rolls.
Friday - Vegetable pasta bake followed by baked apples.
Now imagine that on Tuesday morning a local grower reports an unexpected surplus of cauliflower.
Within minutes, the AI could recommend revised menus across dozens of schools, hospitals and care homes.
It could suggest replacing broccoli with cauliflower where appropriate, recalculate nutritional values, update shopping lists, adjust deliveries and reduce procurement costs.
All before procurement orders are placed.
The chefs still decide on the menu.
The catering managers still approve.
The AI simply performs in seconds what would otherwise take many hours of planning.
Looking further ahead, the system could become predictive rather than reactive.
It might advise a farmer that harvesting tomorrow rather than next Friday significantly increases the likelihood of a local sale. It could even identify likely demand months in advance, helping farmers make better-informed planting as well as harvesting decisions.
It might recommend that schools substitute one seasonal vegetable for another because it reduces costs while maintaining nutritional standards.
It could identify likely regional gluts weeks in advance, allowing menus to evolve naturally around produce that is already abundant.
The objective wouldn't be to replace farmers, chefs or procurement teams. In fact, better coordination could increase the value of human expertise by giving people better information on which to base their decisions.
Every week the system would become a little smarter. It would learn:
Which meals children enjoyed.
Which ingredients regularly remained unused.
Which producers consistently had excess supply.
Which transport routes proved most efficient.
Which menu choices generated the least food waste.
Like any good system, it would improve over time.
It's Not Really About Food
Stepping back, I began to realise that this is not just a food problem.
It's a systems problem.
Again and again we see situations where resources exist alongside unmet needs.
Surplus food alongside food poverty.
Labour shortages alongside unemployment.
Empty properties alongside homelessness.
People desperate for work while employers struggle to recruit.
Different sectors.
The same underlying pattern.
Existing resources.
Existing needs.
Weak connections between them.
Perhaps the greatest challenge of the twenty-first century isn't creating more resources. It's becoming better at connecting the resources we already have with the people who need them.
It isn’t a question of producing more. It’s a question of how to coordinate existing resources better.
Would It Work?
I honestly don't know.
There are procurement rules.
Commercial contracts.
Food safety regulations.
Transport costs.
Liability.
Seasonality.
Storage limitations.
Data sharing.
Commercial sensitivities.
None of those should be underestimated.
But equally, I don't think they should stop us asking the question.
Could an AI-coordinated regional food network reduce waste?
Could it support local farmers?
Could it lower costs for public services?
Could it improve access to fresh, nutritious food?
Could it strengthen local food resilience?
Could it become a model for connecting resources with needs in other areas of society?
I don't know the answers.
But I think they're questions worth exploring.
Because if there's one thing I've learned while writing The GOOD Method, it's that many of society's biggest challenges aren't always caused by a lack of resources.
Sometimes they're caused by the systems we use to connect those resources with the people who need them.
Perhaps AI won't solve food waste.
Perhaps it won't solve food poverty either.
But every generation inherits technologies that allow it to solve problems in ways previous generations couldn't.
Britain once coordinated a national food system using paper records, telephones and thousands of dedicated people.
Today we have tools capable of analysing millions of pieces of information in seconds.
The question isn't whether artificial intelligence has all the answers.
It's whether we're asking it the right questions.
If AI can help us connect farmers, schools, hospitals, care homes and communities more intelligently than we do today, we may waste less, spend less and feed more people with the food we're already producing.
One of the things writing The GOOD Method has taught me is that changing the question often changes the answer.
That's what systems thinking encourages us to do.
Rather than asking how one part can work harder, it asks whether the whole system could work smarter.
The biggest opportunity isn't producing more food; it's becoming better at connecting the food we already produce with the people who need it.
That means we've been asking the wrong question about food waste all along.