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How we calculate what automation saves

Every number the calculator on this site shows you comes from five inputs and four sums. Here they are, plus what they don't tell you.

Five blocks of different sizes feeding along a channel into an open hopper, with one much smaller block coming out underneath, and a separate tall block whose upper third is an empty wireframe outline.

Umer Ejaz Chaudhry, Cadral AI ·

The ROI calculator on this site doesn’t call a model, doesn’t guess, and doesn’t hide its working behind a “contact us for your custom report” form. It multiplies five numbers you give it. This is exactly what it does with them.

The arithmetic

weekly cost

= hours the job takes a week x people who do it x their hourly cost

cost across a year

= weekly cost x 46 working weeks

recovered once it runs

= cost across a year x the share of the job that goes away

pays for itself after

= what the build cost ÷ (recovered ÷ 12)

year one, net

= recovered - what the build cost

Three assumptions, and why they sit where they do

46 working weeks, not 52

Fifty two assumes nobody takes a day off all year. Forty six removes bank holidays and normal leave before the first pound is counted. Using 52 would inflate every annual figure by about 13 percent before anyone has looked at the job.

Seventy percent, not a hundred

Few jobs automate fully. The routine cases run themselves; the unusual customer, the missing field and the judgement call still need a person. Seventy percent is the starting point because that second group never disappears. Move it to match how routine your job is.

Hourly cost, not salary

Divide salary by hours worked and the result is too small: it leaves out employer National Insurance, pension, software seats and the desk. Enter what an hour of their time costs the business, not the payslip figure. Undercount it and everything downstream undercounts too.

A worked example, using nothing you can’t check

Open the calculator and enter these five numbers: six hours a week, two people, £28 an hour, a £2,500 build, seventy percent recovered.

That gives a weekly cost of £336, a yearly cost of £15,456, and £10,819 recovered once the build is running. The build pays for itself in 2.8 months, and year one nets £8,319 after paying for itself.

Every one of those figures is reproducible: open the tool, enter the same five numbers, and read the same results back.

The same job, half as optimistic

Now halve the optimism. Drag that same job down to 40 percent recovered instead of 70, and the picture changes: £6,182 comes back in a year instead of £10,819, and the £2,500 build takes 4.9 months to pay for itself instead of 2.8.

The arithmetic hasn’t moved. Only the one input you’re least certain about has, which is exactly why it’s worth arguing with your own number before you believe it.

What this does not prove

This shows what a plausible number looks like once you trust the three inputs above. Whether seventy percent is right for your version of the job depends on how routine it is, and a real look at the work settles that.

It is arithmetic, not a measurement. The calculator works from the numbers you give it, not from a stopwatch on anyone’s week. Treat the output as the start of a scoping conversation, not the end of one.

Run it yourself, change every slider, and see where your own week lands.

Read something here you want running in your business? Send us the brief and we will come back with a fixed price, or book twenty minutes and talk it through.

Tell us the job. We will tell you the price.

Twenty minutes and a fixed quote in writing. You bring the brief and the brand. Everything after that is us.

Not ready to talk? Run your own numbers on fifteen free tools, no email asked.

Umar has brought real value to LP Exchange by helping us utilise AI effectively across the business. He has strong technical knowledge, but importantly, he understands how to apply it in a practical and commercially useful way. His work has supported improvements across data cleansing, process automation, marketing and sales reporting, helping us turn complex information into clearer insights and more efficient ways of working.

James DonohueManaging Director, LP Exchange · 21 September 2026