Archives

Zero-day close as a direction, what a continuous close actually is, who is talking about it, why the forecast is the point, and why a finance team can now build one: writing the code got cheap, owning it did not.

One FP&A month, old way and new: a contract that reaches the forecast in week six or on the morning of the 8th, which numbers can close early, which must wait, and the chain from purchase order to accrual that decides it.

The architecture of a continuous close: small processes orchestrated centrally, one append-only log, people at the gates, approvals in Slack or email, and a console that is only a view over the log.

Questions I kept asking while designing the continuous close, with the answers I settled on: where the forecast lives, the two closes, why actuals load nightly against a monthly budget, exception queues, estimates, idempotency. A page that grows.

Companion to the continuous FP&A essay: the nightly load in detail, model-against-code benchmarks, question-box rules, access, failure modes and a go-live gate.

A three-part series: what a continuous (zero-day) close is and why to aim at one, one FP&A month worked old way and new, and how to build it with mainstream AI tools.

The agentic loop explained for finance people: what an AI agent is, how it differs from a chat, and the ten-line algorithm underneath, with real runs.

A free, open-source review of your Anaplan estate from the metadata exports: 42 defined tests, an action plan of the five most impactful things to do, a change-impact explorer and the evidence behind every finding. A walkthrough on the fictional Caldergate estate, then how to run it on your own models.

I completed Anthropic's courses on Claude for AWS Bedrock and Google Cloud Vertex AI. A refused first request sent me into the paperwork, with a few lessons for client work.

Why is freight over budget? The model shows the variance; the three sentences for the pack still take the morning. Where the work around an Anaplan implementation actually sits, which of it is plain automation, and where AI has to interpret evidence.

The spreadsheet moved the ceiling on how much finance work one person could do, and we forgot it was ever automation. AI is moving the ceiling again. Nine things it already does inside finance teams, with pictures, a place to start, and a test for telling a good build from a dangerous one.

I rebuilt a clinical-stage biotech's month-end around Anaplan and scheduled data loads, and the close went from 12 working days to under 8 hours. The list of what moved it is mostly boring. That's the lesson.

What is verifiable AI? The difference between a citation and a verification, why AI arithmetic needs a calculator, and the four controls a finance team should demand.

Engineering teams have shown how to build company knowledge bases. Finance needs a different animal. Seven organs, what each one is for, and how I built them.

The entire pitch for what I built, asterisk included: why the board pack questions that cost an afternoon stop getting asked, what changed this year, and how I'd test any AI that says it's fixed that, including mine.

Is it safe to put company data in ChatGPT? A working protocol for finance teams: what to paste where, how to anonymise a question properly, and how to get IT to yes.

I published an exam for finance AI: 34 realistic documents, 25 questions, a deterministic grader, answer key included. The frontier models got most answers right. Proving them right was a different story.

It's the question every finance leader asks, and it deserves a straight answer, including the cases where a chatbot genuinely is the right tool.

The four ways an AI agent can search your files (keyword, vector, file system, graph), each mapped to how you already find things, and why spreadsheets break the most popular one.

The word finance people hear in every vendor call, explained through their own day: how actuals move between NetSuite, Anaplan, SAP and Workday, what a key is, and why IT's questions are your own posting-access discipline.

What happens to our runway if the Phase 3 runs a year long? How Grounded's advisory mode answers a board-level question in three tiers: facts, assumptions, analysis.

Two of your own documents disagree about R&D spend by $2.1 million. Which one is right, and how long would it take your team to find out? A walkthrough on a synthetic biotech reporting pack.

Variance analysis has four steps. Only one of them is analysis. A look at where an FP&A analyst's time actually goes, and which steps a machine should be doing.

Every finance team knows the out-of-nowhere question that lands at the worst moment. It isn't an interruption. It's a tax. Here's what it actually costs, and why you'll never get headcount to fix it.