Manufacturing
Cost to make, yield and OEE joined to what you actually sold.
Production data and commercial data rarely meet, so nobody can say which lines make money. Shop-floor systems know output, finance knows revenue, and the cost of a unit is an estimate everybody privately doubts. We connect them.
The numbers that matter here
What we'd connect here
Whatever it is and however it exposes itself — API, database, nightly file, or a spreadsheet somebody maintains by hand. We only ever need read access, with personal data excluded.
What we do about it
Where it hurts
- Standard costs stale, so product profitability is a guess
- Yield and scrap reported weekly, decided daily
- Downtime causes recorded but never analysed
- Production and sales data never reconciled
What Acta builds
- Actual cost to make per unit, updated as inputs move
- Yield, scrap and downtime joined to shift, line and product
- Order-to-despatch timeline across production and commercial
- Product-level profitability the commercial team trusts
What you get
A clear answer on which products and lines are worth running.
Live in months rather than years, from £5k a month, on your own Google environment — handed over to you, or run by us.
Inside a manufacturing engagement
Production data and commercial data rarely meet. The shop-floor systems know output, yield and downtime, the ERP carries a standard cost that went stale months ago, and finance knows revenue — so the actual cost to make a unit is an estimate everybody privately doubts, and nobody can say with confidence which lines make money. Yield and scrap are reported weekly but decided daily, and downtime causes are recorded and then never analysed.
We land the shop-floor and commercial events together in your own BigQuery and build an order-to-despatch timeline across both, with an actual cost to make per unit that updates as inputs move rather than once a year. The line that usually surprises people is one with strong OEE and disappointing margin, because the scrap rate and input cost eating it were never joined to the product it affected. Yield, scrap and downtime tied to shift, line and product turn a weekly report into something you can act on the same day.
Once it is live the commercial team has product-level profitability it actually trusts, and the answer to which products and lines are worth running stops being a matter of opinion. OEE, yield, scrap rate, cost per unit and on-time-in-full all read from the same events, so an operational fix on the floor and its effect on margin are visible in one place.
You don't need to be a tech company. You need to see your own numbers.
Builders merchants. Wholesalers. Distributors. Plant hire. Family manufacturers. Serious turnover on thin margin, where the person who really understands the numbers is the owner, a long-serving manager, and a shared drive. If that is you, this is more for you than it is for the tech companies — because you are the one still doing it by hand.
Cash sitting on a shelf nobody has counted since March
The only copy, and it leaves when Dave does
Gross margin, so the branch that eats the deliveries still looks fine
Nobody knows the win rate, or which quotes went cold and why
Two versions in circulation, and the trade counter has the old one
Cost to serve per drop, which is where the margin actually goes
Set once, three years ago, on a customer who has since doubled
Rebate thresholds you hit or miss without noticing until the quarter ends
Every one of those is a question the business already asks every week. None of them talk to each other, none of them have any history, and all of them depend on somebody remembering to update them.
Which customers actually make you money
Not gross margin — margin after the deliveries, the returns, the credit you carry and the time your team spends on them. Most merchants find a handful of their biggest accounts are their worst.
What is dead on the shelf
Every line, how long since it moved, and what that cash would be worth doing something else. Along with the lines you keep running out of, which is the same question from the other side.
Which branch, van or rep is carrying the others
The same numbers for every part of the business, worked out the same way — so the comparison is an argument about what to do rather than about whose spreadsheet is right.
You are not too small for this. You are the size where it pays back fastest.
In a large corporate, doing this properly is a multi-year programme with a steering committee. In a business of forty or a hundred people it is a few months, because the whole operation genuinely fits in one layer — one stock system, one finance system, one CRM if you are lucky, and the spreadsheets in between.
And the payback is not a nicer report. It is one dead product line cleared, one bad account repriced, one rebate threshold hit that you would otherwise have missed. At £60k a year for a single area, that arithmetic tends to work out quickly — or start with the £15k map and see the numbers before you commit to anything.
Common questions
Can you tell us the real cost to make a unit?
Yes. We build actual cost to make per unit, updated as inputs move, rather than the stale standard cost most product profitability rests on. Joined to what you sold, it gives the commercial team a product-level profitability number they can actually trust.
Our shop-floor and finance systems don't talk — can you connect them?
That join is the core of the work. Shop-floor systems know output, finance knows revenue, and the two rarely meet. We land both in your own BigQuery and build an order-to-despatch timeline across production and commercial, so which lines make money stops being an argument.
How do you handle yield, scrap and downtime?
We join yield, scrap and downtime to shift, line and product, so causes recorded but never analysed finally get analysed. Reported weekly but decided daily becomes a live operational view, which is where OEE improvement actually comes from.
Which manufacturing systems do you connect to?
Whatever you already run — it makes no difference whether a system exposes an API, a database view, a nightly file or a spreadsheet somebody maintains by hand. In manufacturing that usually means: ERP and MRP; Shop-floor MES; SCADA and PLC historians; Quality and non-conformance; Maintenance (CMMS); In-house SQL and Access databases. We only ever need read access with personal data excluded, and the layer is built in your own Google environment rather than ours.
Other sectors
Bring one decision your data should be helping you make.
30 minutes, no deck. We'll tell you on the call whether we're the right partner, and exactly what we'd ship in the first 30 days.