The most important decisions now happen before the program begins
Four takeaways on Phase 0 in a post-AI world, including why pre-implementation now has two objectives and why the data will never be ready.
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Perspectives
Writing on enterprise planning, the office of the CFO, and what AI changes in finance. Each piece links to the original on LinkedIn.
If your default is that AI can't automate this, you're right
A utility client never automated its actuals load because every objection was legitimate. Years later the copy and paste continues.
Read on LinkedInHumility is an operating requirement for critical thinking
Part three of the critical thinking series. Why 'I was wrong' is the most avoided sentence in corporate life, and what saying it does for trust.
Read on LinkedInScenario analysis the way meteorologists do it
Three independent LLMs run the same scenario against a copy of the model, and the spread between them becomes the confidence score. Agreement is not accuracy.
Read on LinkedInThe modern RFP tells you how the project will go
AI writes the RFP, AI writes the responses, AI scores them, and a human decides over lunch. Why selection should be rebuilt around prototypes.
Read on LinkedInPlanning level of detail is always an issue
Dozens of implementations, and never once have consultants and client agreed on the planning grain. A 2x2 diagnostic for finding the disagreement early.
Read on LinkedInClaude as the orchestration layer for corporate planning
An account catalog, a design file, and a folder structure are enough for Claude Code to build the model, run auditable scenarios, and write its own manual. Where a gap in experience still shows.
Read on LinkedInYou prepared for your last meeting by focusing on what you wanted to say
That's the mistake, and almost everyone makes it. Part two of the critical thinking series, on seeing the room through the audience's eyes.
Read on LinkedInThree AI models, one financial model, three different answers
Leading AI models given the same model to build. All three balanced the balance sheet, then disagreed on what matters. A passing check is not a correct model.
Read on LinkedInWhat's the problem we're trying to solve?
Part one of the critical thinking series, with a hand-drawn double diamond and a steering committee that spent a whole meeting making the wrong thing faster.
Read on LinkedInAI is the hot topic at the top of the org chart. Finance isn't deploying it.
Most finance teams aren't deploying it, and many aren't especially interested. Five reasons why, and a question about which one applies to yours.
Read on LinkedInFive steps to a self-improving forecast
Close and compare, split the variance, learn from what's left, run it forward, repeat. Part three of the machine learning series.
Read on LinkedInA model should only learn from mistakes it owns
When actuals arrive, the miss splits into exceptional events, human decisions, and true model error. Only the last one retrains the model. Part two.
Read on LinkedInMachine learning and the model do two different jobs
ML predicts the drivers. The model calculates everything that follows. A model should never guess a number a formula can compute exactly. Part one.
Read on LinkedInTwo stories, one project
A client and a consultant describe the same program and both are telling the truth. On the gap between delivered scope and delivered value.
Read on LinkedInHire problem-solvers, not AI specialists
A recruiter asked whether I'd rather hire finance people who know AI or AI people who know finance. Neither. The gap is problem-solving.
Read on LinkedInImagine this interview for a corporate planning role
An empty office, a laptop, every LLM available, and a public company. Build a driver-based forecast the CFO can run scenarios on, live. You have 60 minutes. How would you do?
Read on LinkedInEating my own words: the four-hour forecast
I said Claude shouldn't be used to balance a balance sheet. Then I built a three-statement forecast in four hours and ran the integrity check. Every statement tied.
Read on LinkedInName one program that finished on time, on budget, and delivered its business case
Take your time. The list is short, and faster AI delivery makes it shorter unless partners are chosen on their ability to execute.
Read on LinkedInPrivately owned businesses plan in generations
A ranch and a steakhouse on summer vacation, both run by families thinking decades out. What long-lived private businesses know about planning.
Read on LinkedInI. Don't. Know.
A prospect asked a question I couldn't answer, so I said so. On the most honest thing a consultant can say in a first meeting.
Read on LinkedInA pulse check on the culture of your project
Find the last missed milestone and listen to how people reacted. Nothing sounds toxic, and that's the point.
Read on LinkedInBudgeting is not forecasting
An old friend challenged my decision to run the firm with no budget, ever. How to give investors a projection, and how to hold people accountable to something other than an outdated target.
Read on LinkedInCheck out this chat I just had with Claude
Q1 closes. In under two minutes the actuals are validated, the forecast and 10-year plan are refreshed, and a 1,000-path Monte Carlo hands the CFO an EPS distribution. Nobody opens a spreadsheet.
Read on LinkedInThe platform question is becoming irrelevant
For as long as I can remember, planning transformations have started with the same question: which platform? Why that question no longer comes first.
Read on LinkedInThe technology is the easy part
After the kickoff, the sponsors leave and the team designs a future it was never incentivized to reach. Why 'nobody ever got fired for buying IBM' is an admission, not a compliment.
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