Four steps, the same on every engagement. Scope is described in steps, not in hours, because I price the result.
I read the current state of the enterprise through four lenses.
Every finding carries its evidence. Opinions are labeled as opinions.
I test that state against your mission, vision and strategic plan, and against where your markets and customers are going. Three outputs answer the three questions.
At the end of this step the Board reads the findings and decides whether to commission the plan. If it stops here, it does not pay for the plan.
For every gap, options priced on the same cost lines: people, licenses, build, integration, maintenance, exit and risk. For each option, the two or three numbers that would change the answer. The result is an Actionable Plan: initiatives, owners, sequence, milestones, budget, the value each initiative targets, the risks, and the meeting rhythm for steering and for the Board. Sometimes buying is the right answer. Sometimes building is. Sometimes the right answer is to stop.
I come back at each milestone and test the result against the original numbers, using four rules.
Is a named person accountable, and can they state the number and the date?
Did spend, scope, access and data stay inside the approved limits?
Did a named approver review the result before it counted, and can they stop it?
Can the result be rebuilt from source records and does it match? For AI, was it tested with bad input, and do its guards fire?
Each milestone gets one status: Held, Slipping or Broken. A Broken finding goes to the Board sponsor in writing. I do not soften it to protect the relationship. These are management reviews against the plan. They are not audits and carry no assurance opinion.
Every client gets a dashboard of the agreed value metrics.
Revenue generation. Employee capacity and value. Cost reduction. Risk avoided. Working capital and cash. Valuation (using your own stated multiple, never an opinion of mine). Speed. Capital avoided. Retention. Alignment of initiatives with the plan.
Your data stays in your environment. Where a language model touches your data, it is only on a commercial-terms channel, a local model or your own approved AI tool, in a separate environment for your engagement that is deleted at the end with written confirmation. I name every AI vendor I use as a subprocessor.