"We have fifteen things we could fund. Everyone has a favourite, every one of them has a business case, and none of the cases are comparable."
Existing streams, new products, market entries, partnerships and AI use cases. What is already on the list usually arrives with a business case attached, built on its own assumptions, so the first job is putting everything on one basis so it can be compared at all.
The more useful half is discovery. AI use cases in particular rarely arrive as proposals: they show up as manual effort somebody has stopped noticing, data that already exists and is not being used, or a workflow doing the job a system should. Those get surfaced and costed alongside the ones that were already being argued for.
Sizing, unit economics, feasibility and time to revenue, applied identically to every option. Unit economics at real volume rather than at pilot scale, because most options look similar until you run them forward. Feasibility gets tested against the constraint that actually binds. That is usually data, capability, or a stack that is not joined up.
Three or four options, sequenced with dependencies made explicit rather than assumed away. The rationale for what was deprioritised is written down alongside, because that is the part the exec group has to be able to defend six months later when a sponsor reopens it.
A prioritised shortlist with the economics attached to each, on one consistent basis, so the sequence is arguable on numbers rather than on who argued hardest.
The scoring model stays with you and can be re-run. Options do not stop arriving, and the question repeats every planning cycle.
Where the answer has to be taken to investors, the case gets built in a form that survives their scrutiny rather than only the board's, with the weakest parts of the story identified before diligence finds them.
The analysis is rarely the hard part. The hard part is the option somebody senior has already committed to publicly, which is why the deprioritisation rationale gets written down as carefully as the shortlist. A prioritisation that cannot survive its first challenge has not decided anything.
Fixed price, not a day rate. The scope is agreed up front and the price does not move with it. If the work takes longer than expected, that is my problem rather than yours, which is the right way round.
Quoted after a short call, once I understand what you are actually dealing with. Invoiced half on start and half on delivery.
Most engagements end at delivery. Some clients keep me on a light retainer afterwards to keep the model current and to be available when the board asks something new. That is agreed at the end, not the start.
Where AI does part of the work, I say which part. Some of the analysis and model building uses AI tooling. The judgement, the method and the conclusions are mine, and I will tell you which is which if you ask.
It rarely fits exactly, and that is normal. Worth a conversation rather than a form.
martin@scalepointpartners.com