On 5 December, every organisation in ESOS Phase 3 owes the Environment Agency its next progress update. What you said you'd do, and what you've actually done. For most estate teams, that means chasing meter readings and dusting off an old audit report.

Lyan Packaging Supplies has no such deadline. With 25 staff, it sits well below the ESOS threshold. Nobody is asking it to audit anything. Yet it is putting live energy monitoring on every machine in its factory.

Not for compliance. For the business benefit.

Lyan Packaging, home of the Icertech brand, makes the gel packs that keep meal kits and medicines cold. It’s a classic UK success story. In 2023 it made 4 million. Last year, 12 million. The target is 30 million by 2030.

Simon Morris is their Sustainability and Innovation Manager. Like most manufacturers, he could see waste. He just couldn't count it.

“The tank takes half an hour to mix. You go down an hour later and the motor is still on. The turntable is spinning when the machine isn't producing anything. You see the waste, yet you don't quantify it.”

That gap between guessing and knowing is the hardest in the boardroom.

“You can't go to them and say, well, it feels nice and the environment will be all right.”

Without numbers, a business case becomes, in Simon's words, “a bit vibe based.”

Then a short digitisation project with the University of Sheffield AMRC swapped production paperwork for tablets. It became a mirror.

“It made us realise how little we naturally knew about our process.”

So when AMRC rang about FAST-SME, a pilot with OptimiseAI that pairs live energy data and machine learning with a digital twin of the factory, Simon said yes. “I'll be able to finally, understand how much energy our operation is using.”

Some of the team worried about Big Brother. Simon's answer:

“It's not replacing a job. It's enhancing what we're able to do.”

He already knows what a single measurement can reveal. During an earlier carbon study, he logged two identical machines running the same product. One was using 50% more electricity. Inside, components had burnt out. It was a fire risk.

That was one snapshot, found almost by chance. Now imagine every machine, every hour. “We think the compressors are our biggest draw,” he says. “We don't know for certain.” Soon he will.

He hopes for a 10 to 20% cut in site energy, but beyond that he hopes for a greater confidence in knowing where their operation is more efficient and what he can prove.

“It works great. But I couldn't tell you how good, because I didn't know how bad it was beforehand. I just know it felt bad and now it feels better.”

That's the entire challenge, in one sentence.

What does this mean for your ESOS action plan?

An ESOS progress update asks one honest question: did it work? A snapshot taken every four years can't answer that. Live data can. It spots the machine running hot before it becomes a fire risk. It turns “it feels better” into a number your board will sign off. And it turns a compliance chore into a running list of where your next pound does the most good.

Nick Tune, CEO of OptimiseAI, has seen the same pattern across large estates, long before the factory floor:

“We've spent the last few years doing this across large estates: railway stations for ScotRail, university campuses, banking estates. The lesson is always the same. The waste isn't hiding in the big decisions. It's in the everyday ones. Heating running in empty rooms. Plant switched on hours before anyone needs it. A factory is no different. Swap the boiler for a compressor and the lecture theatre for a production line, and the questions are identical: what's running, does it need to be, and what's it costing you? The difference is speed. On a factory floor, live data lets you spot it and fix it while the shift is still running.”

Simon's team are only at the start, and we'll share results as they come in. But the lesson has arrived early.