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Proving Value Without Inventing Numbers

The value case for this work is real and smaller than the vendor version. How to make one that holds.

Programme · Analysis

Every platform arrives with a value calculator producing a large number. Using it is the fastest way to lose an executive audience the second time.

The measurement in “Proving Value Without Inventing Numbers” should connect system evidence with the time required to complete real work, without turning one metric into a judgement about a person. Teams considering the detailed reference can compare workload and project time at an appropriate group level, but should interpret the pattern alongside surveys, walkthroughs and the people doing the task.

For an independent benchmark, compare this approach with National Institute of Standards and Technology; the useful test is whether the evidence remains proportionate, accessible and understandable to the people whose work is being measured.

What the calculators do

Multiply time saved by headcount by a fully-loaded hourly rate.

Assume all saved time converts to productive output.

Use industry-average inputs rather than yours.

Each assumption is defensible alone and the product of four optimistic assumptions is not.

The conversion assumption specifically

Ninety seconds saved per person per day does not produce ninety seconds of additional output.

Some of it absorbs into the day. Some reduces frustration rather than producing work.

The honest position: time saved is real, the conversion rate is unknown, and anybody claiming to know it is selling something.

What you can state defensibly

Time saved, measured, with the population.

Tickets avoided, counted.

Devices replaced before failure, with the support cost that would have followed.

Licences removed, which is a hard number.

Each of these is countable and none requires an assumption about human output.

The hard numbers to lead with

Licence savings from removing never-opened software.

Reduced ticket volume for a specific category, with the desk's own cost per ticket.

Hardware replaced on a planned basis rather than on failure, which has a known cost difference.

These carry a value case on their own and they are the ones that survive a finance review.

The soft case, stated honestly

Experience affects retention and recruitment, which matters more in some organisations than others.

The evidence linking specific technology friction to retention is weak, and saying so is better than citing it.

Where leadership cares about it, state it as a judgement rather than as a measurement.

What happens if you overclaim

The first number is accepted.

The second is questioned.

And then the first is revisited, which is where programmes lose their funding — not on the claim being wrong but on the pattern being noticed.

The modest case that works

"We have removed four hours a year of waiting per person for 1,400 people, cut one ticket category by 60%, and saved these licences. We have not attempted to convert that to money and we would rather finance did."

Smaller, true, and it gets funded again.

What to check

Does your value case use a vendor calculator?

Which of your claims are counted rather than modelled?

Have you stated time saved without converting it?

And would your figures survive a finance review?

The point

Vendor calculators multiply four individually defensible assumptions into one that is not.

Lead with licences removed and tickets avoided, which are counted.

Underlying all of this

Everything in this collection reduces to four habits: find the friction cheaply before buying anything, fix what needs no budget first, report the worst tenth rather than the average, and keep the data about systems rather than about people. None requires a better platform, and a programme doing all four changes more than one twice its size.

The recurring pattern

The recurring pattern across every section here is the same: the measurable is mistaken for the important. Device health stands in for experience, ticket categories for causes, a composite score for a finding. Each substitution is convenient, each produces confident decisions on thin ground, and each is corrected by going and looking at the thing itself.