Too Much or Too Little: Tackling Food Waste with Smarter Planning

Walk into any supermarket and the shelves are usually full—fruit glistening under bright lights, salad leaves crisp in refrigerated aisles. Behind that picture of abundance is a complex system trying to match supply with demand, day after day.

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But too often, it gets it wrong.

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According to the World Food Programme, one-fifth of the food produced for human consumption is lost or wasted each year, at a cost of roughly $1 trillion. Sometimes there's too much of one product and not enough of another. Sometimes crops are harvested and never sold. And sometimes, deliveries arrive too late—or too early—to be used in time.

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This isn’t just a waste of food. It’s a waste of the water, energy, labour, and land that went into producing it. It’s also a huge economic loss across the entire food supply chain. Fortunately, predictive analytics is helping us shift from reactive to proactive—and turn this waste into opportunity.

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Where Things Go Wrong

Food waste happens when supply and demand fall out of sync. A sudden glut of lettuce, for example, can flood the market and cause prices to crash—forcing growers to leave fields unharvested. Meanwhile, if a bakery runs short of wheat due to an unexpected drop in supply, it may have to scale back production or absorb higher costs.

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These issues can be hard to avoid when decision-makers are flying blind. Without reliable forecasts, producers and retailers are left making educated guesses. And in a system where timing is everything, even a small error can lead to spoilage or shortages.

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Seeing the Signals Early

That’s where predictive analytics makes the difference.

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At Agrimetrics, we’re using AI and satellite data to build accurate models of crop performance. By predicting yields weeks or even months in advance, we can help food businesses adjust purchasing, logistics, and storage plans before problems occur.

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Take our work on the Environmental Land Management Scheme(ELMS) for example. We’re combining satellite imagery from Sentinel-1 and Sentinel-2 with machine learning to forecast wheat and oilseed rape yields.These models help flag over- or under-supply before harvest, giving stakeholders across the food chain time to adapt.

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The result? Better planning. Less waste. And more efficient use of resources.

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ThePower of Planning Ahead

Imagine this:

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A logistics company sees a forecast for a bumper onion harvest and scales up distribution capacity in advance.

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A food manufacturer anticipates a shortfall in oilseed rape and adjusts sourcing plans before prices spike.

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A retailer aligns promotional offers with predicted supply, moving surplus products faster and reducing spoilage.

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These aren’t future scenarios—they’re real opportunities being unlocked by data that’s already available. All it takes is the right tools to interpret it.

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A Smarter, More Sustainable Food Chain

Food waste isn’t inevitable. With smarter planning, informed by predictive insights, we can dramatically reduce it—helping businesses improve margins while also benefiting the environment.

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At Agrimetrics, our mission is to make complex data accessible and actionable. That means turning satellite images and soil conditions into simple answers: Will the yield be up or down? Should we store more, transport faster, or buy elsewhere?

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When we get the answers right, we all win.