UK manufacturers see one energy number a month. They cannot see which product, process or shift actually made the cost. Here is how product-level energy intelligence protects margin on every line.
On one of your largest controllable costs, a few per cent is margin kept on every unit. (Carbon Trust)
Energy is one of the biggest costs a manufacturer can actually control. Materials are set by suppliers and labour by the market, but how much energy each line, asset and product consumes is within your influence. The problem is that most manufacturers cannot see it. The site meter gives finance one number a month. What it does not show is where that cost is really made: which product, which process, which machine, which shift.
For an Operations Director, that blind spot means the lines and assets quietly wasting the most energy stay hidden. For a CFO, it means energy sits in the accounts as a site overhead instead of a cost you can attribute to product margin. With UK industrial energy prices among the highest of any major economy, that is a lot of controllable cost left unmanaged.
Because the data that would answer the question lives in different systems that were never designed to talk to each other.
Each system is accurate on its own. None of them, on their own, can tell you the energy cost of a single batch or product run. Joining them up by hand means exporting to spreadsheets, matching timestamps and reconciling definitions that differ from one site to the next. By the time the analysis is done, the production run is long finished and the moment to act has passed.
It moves energy from a site-level overhead to a cost you can read at the level where decisions are made:
Once energy is visible at product and process level, it stops being a number finance explains after the event and becomes something operations can manage during the run.
On one of your largest controllable costs, even a few per cent is margin you keep on every unit you make, not a one-off saving. The commercial case does not stop at the energy bill. Product-level energy data also sharpens quoting and pricing, because you finally know the true energy cost of what you sell. And it gives you the granular evidence that carbon reporting and customer sustainability questions increasingly demand.
Because it is a data problem before it is an energy problem. The data already exists. It is just trapped in plant systems, held in local spreadsheets and described differently at every site. So every attempt to see energy by product turns into a bespoke engineering exercise that is hard to repeat and harder to scale. Fix the data foundation and the energy insight follows. Skip it, and you are back to a single number on a meter at the end of the month.
The practical route is to bring metering and IoT, production and ERP data together on one modern data platform, model it once, and serve it to finance and operations from a single trusted source. The right tools depend on your environment, not a vendor preference. We build this across the modern data stack and choose what fits the data you already hold and the skills in your team. For example, that often means pulling meter, IoT and MES data in with Fivetran or Talend, landing and modelling it on Snowflake or Databricks with dbt, and serving energy cost per product in Qlik.
The results are practical, not theoretical. Bonfiglioli cut its data loading and extraction times sharply after moving its manufacturing data onto a modern cloud data platform, which is what makes near-real-time energy analysis possible rather than a month-end report. tesa brought 7,000 products onto a single source of truth, giving it product-level insight across the whole range instead of site-by-site guesswork.
Energy is too big a cost to manage from a single meter reading. Seeing it by product, process and asset is how you protect margin on every line, not just the site P&L.
Ten questions, a score out of ten, and a sense of how you compare with the sector. Or read the full report the energy use case sits inside.