Map it. Measure it. Then decide what to automate.
An independent audit of how work actually flows through your organisation — with numbers attached. It is the cheapest project you will run this year, and it is the reason the next one succeeds.
Nobody in the building has the whole picture. That is normal.
Every organisation past a certain size runs on processes that no single person can describe end to end. Work gets done anyway, through workarounds, private spreadsheets and one or two people who simply know. That is fine until you try to scale it, automate it, certify it, sell the company, or replace the person who knows. Then the gap between the documented process and the real one becomes very expensive, very quickly.
The symptoms
Month-end takes a week. The same errors recur. Two departments give different answers to the same question. New hires take six months to be useful. Every automation attempt stalls halfway.
What we produce
A mapped process with real numbers against it: volume, cycle time, cost per case, error and rework rates, handoffs, and the specific points where value leaks out.
What you do with it
A ranked list of changes — delete, simplify, integrate, automate — with the expected return on each, so the next investment is defensible in front of a board.
Four to six weeks, mostly spent listening.
Audits fail when they are run from a conference room. Most of ours is spent with the people who actually do the work, because the real process lives in their heads.
Scope
Agree the boundary and the questions the audit has to answer. A vague audit produces a vague report nobody acts on.
Observe
Walk the process with the people who run it. Note the workarounds — they are not failures, they are evidence of where the system does not fit.
Quantify
Pull the numbers from the systems of record. Volume, timing, error and rework rates. Opinion becomes arithmetic.
Recommend
A ranked plan with effort, expected return and sequencing — including the things to stop doing, which are usually the cheapest wins.
What you get, in hand
A process map you can actually read, a data pack behind it, a ranked recommendations register with effort and return, and a short executive summary for the people who will fund the work. All of it yours, in editable formats, whether or not you engage us to do any of it.
Where AI fits, honestly
An audit is the only responsible starting point for automation or AI. It tells you which steps are stable enough to automate, which need judgement, and which should be deleted before anyone spends money on them. Roughly half of what people intend to automate should not be.
Automation that follows an auditQuestions we get asked
Will this feel like an inspection to our team?▼
It should not, and we work hard at that. We are documenting a system, not appraising people — and the workarounds staff have invented are usually the most valuable evidence in the whole audit. We say that to every team we sit with, on day one.
How much of our people's time does it take?▼
Typically two to four hours per role involved, spread across a few weeks, plus read-only access to the relevant systems for the numbers. We work around operational peaks rather than through them.
Are you going to recommend we buy your software?▼
We do not sell software licences, so there is no product we are steering you toward. A recurring outcome of these audits is 'stop doing this step' or 'change this policy', which bills nobody anything.
What if the audit says our current supplier is the problem?▼
Then that is what the report says. We are frequently engaged precisely because an independent read is needed on work somebody else delivered, and we do not soften findings to keep a future opportunity comfortable.
One free hour. No pitch, no obligation.
Bring the problem you are stuck on — an integration that keeps breaking, a cloud bill nobody can explain, an AI project that is all demo and no product, or a platform you are about to invest in. You will leave with a straight answer and a written summary, whether or not you ever work with us.
- Architecture and integration review
- AI feasibility — what will actually work, and what will not
- AWS, Azure and Google Cloud cost and design
- Business process audit and ISO readiness
- Technical due diligence before you invest or acquire