See where AI creates value
across your business — and where to start.
Most teams know AI matters. Few know where it actually pays off in their own business — so pilots scatter and stall. I give you a map: your business read from the outside in, the one place value concentrates, and a clear answer to what to build first.
Outside-in & preliminary — a starting point for discussion, sharpened with your own knowledge.
AI is everywhere. Where it pays off in your business isn’t obvious.
The risk isn’t that you do nothing — it’s that you spread effort thinly across a dozen places and prove value in none. The hard question is not “should we use AI?” It’s “of everything we could do, which one place is worth building first?”
Pilots scatter
A dozen small experiments, none owned by the place where a wrong answer is actually expensive. Motion without movement.
Value leaks at the seams
Effort lands on what’s easy to automate, not on the node that decides the result — so the gains never reach the bottom line.
No way to compare
Without a shared yardstick, the loudest idea wins — not the one with the best value for the lowest cost to build.
The fix is a map, not more pilots. Read the whole business once, find the one node where value concentrates, and name where to start. That’s what this does.
An outside-in value map — and the one place to start.
I read your whole business as a single value line, from customer demand to cash, and find the crux — the one node where value concentrates. The result is a map you can put in front of a board: where value sits, and where to point AI first.
demand
& commit
concentrates
& supply
& serve
(cash)
A fast, structured start
Built from public information and experience — so you get a sharp first read without handing over any data to begin.
One place to start
Not a list of twenty ideas — the single node worth building first, so effort stops scattering.
An honest reliability read
It tells you where AI can carry real weight, and where it can only assist — so you don’t over-invest where it can only guess.
Behind the read is a method refined over 17 years and engineered for reliability — how each node is scored and ranked stays with me. The engine stays with me; the result is yours.
Two steps: an outside-in map, then your inside view.
The first read is deliberately preliminary — a sharp hypothesis to react to, not a verdict. It becomes a decision when your knowledge sharpens it. You always know your business better, and your view overrides mine every time.
The outside-in map
Your value line, the likely crux, and where to start — built from the outside, fast, and ready to challenge.
Calibration with your inside view
We sharpen the map with your real numbers and your team’s judgement — turning the hypothesis into a decision you can act on.
A complement, not a replacement. Your internal team pushes AI broadly — this takes the few high-stakes places where a wrong answer is expensive, and gives them a ranked map to act on.
Proven on machines. The organisation-level read is the adaptation.
World-leading manufacturers like ebm-papst already run physics-based digital twins of their machines — a live model that simulates, predicts, and improves decisions before anything changes in the real world. Reading an entire organisation as its own twin — demand to cash — is my adaptation of that proven idea. The lens is borrowed from engineering; applying it to where AI creates value across a company is the new part.
One map. One place to start. One clear next build.
A read you can put in front of a board — and act on the same week.
Your business read as one demand-to-cash line — with an honest view of where AI can carry weight and where it can only assist.
The single node where value concentrates — plus any engine that can be built once and used in more than one place.
What to build first — the biggest prize you can build for the lowest cost — ready to become a working tool.
Map where AI pays off in your business.
A short conversation. Bring your business and one hard place you suspect AI could help. Leave with an honest, outside-in read on where value concentrates — and a clear sense of the first step worth taking.