For distributors and manufacturers, $20M to $200M in sales
The close went through. Everything reconciled. And margin still moved, and nobody can say why. A number that reconciles on the financial report is not automatically a number that is correct.
A month-end number that matches what actually happened, and an explanation for every move in it.
What you get
A month-end inventory number that matches the warehouse and the costing logic behind it.
Margin that can be walked through line by line, and every move in it accounted for.
The board pack, the lender review, the buyer's diligence. Every figure traceable to the transactions behind it.
Why this works
A medical consumables company reconciled its inventory every month for 2 years. The reports balanced, margin looked stable, and the same unexplained adjustments came back every month. Purchase orders, supplier invoices and warehouse receipts each ran on their own timing, so cost kept landing in the wrong month. The timing was aligned across all 3. The adjustments stopped, and margin could be trusted before the next capital commitment. “We had reconciled those numbers every month for two years. Nobody had ever mapped the timing across all three.”
This pattern, opened up on a worked example: the adjustment every month, the shipments behind it, the fix and the result. Open the month-end dashboard
Try it yourself
Try it on your own numbers first, free, in your browser. Nothing is sent and nothing is stored. Then see the whole method run on a worked example. Client files stay confidential.
Is the month-end adjustment noise, or a pattern? 12 numbers in, the verdict and the fix out.
Free, your own figuresTry itWhy does it take an adjustment to close inventory every month, and what is it doing to margin?
Worked exampleOpen itWhat does the month look like when every line is checked, and only the exceptions that matter reach the CFO?
Worked exampleOpen itHow it works
Not a question typed into AI. A workflow designed end to end, from the raw exports to the decision, with the same steps and checks every time, so the result repeats, compares month to month, and holds.
Nothing about the close changes. The usual inventory export is all it takes.
It takes the inventory export and tests every line: timing across purchase order, receipt and invoice, cost changes, duplicate items, reserves. It compares the result with last month, ranks what moved by dollars, and drafts the month's report. The same tests, in the same order, every month.
Cost in the wrong period, a costing method that changed, reserves resting on last year's demand. Found early, while each one is a small fix.
Time from the team: The usual export. The result arrives ready to read.
This is how the diagnostic runs, on my workflow. Building one inside your own business is the AI workflow implementation below.
Why now
A lender, a buyer or a board asks one thing: where did this number come from. An AI workflow runs the same tests on every line, every month, so each figure traces to the transactions behind it and month 6 compares with month 1. The close becomes a position of strength: better terms, a shorter diligence, a board that moves on.
Ways to work on it
Pick the one that fits. Its price, scope and timeline open underneath.
Written findings: Focused Diagnostic
The business provides its month-end data. The work is the design of the output: an AI closing report built on that data, as provided. What moved the inventory number this month. How much cash sits in it. What in the data cannot be trusted yet, rated by severity. The 3 actions that matter, each with its dollar impact. Plus a readout. Example reports: a distributor and a manufacturer.
US$1,500 is the report itself. Not included: collecting or cleaning the data, fixing what the report finds, changes to the closing process, a second month. Each is quoted separately.
How it runs
What it takes
Messy data is the normal starting point. The work runs on the data as provided, screenshots included, and the report states what any gap does to the answer. The data is used for this work only, never shared, never used as an example, and deleted on request.
Built and handed over: AI workflow implementation
One deliverable: a working AI workflow inside the business, run by its own team. One workflow, named at the start.
Scope and timeline
In scope: one workflow, named at the start, such as the inventory close, the buying review or the monthly report, plus the handoffs it depends on. Anything beyond that workflow gets its own quote. Most of the 3 months goes to mapping how the work really gets done, with your people, so the AI fits reality.
Coached: AI workflow build sessions
Live coaching while the team builds, on its own data, in its own Claude. One session unblocks one thing. 4 sessions build the whole workflow.
Self-paced: The 30-Day Inventory AI Challenge
The IOP method learned hands-on: 30 AI workouts on one distributor's files, then on the business's own exports. Every workout ends on a number that must match.
She reads financial reports quickly and spots patterns, opportunities, and potential issues that others might miss, turning insights into actionable strategies. Her ability to notice hidden details and identify root causes instead of just surface issues makes her invaluable.
Charles TuCEO, technology manufacturer, TaiwanSharon is an insightful, kind, and hyper-detailed analyst. She quickly recognizes core issues and provides a clear path to the answer ... she has developed a powerful intuition and sense of clarity in a very difficult subject matter: cash and inventory optimization.
Mark LuptonCFO and advisor to 8-figure companies. Founder, Greenhouse Business AdvisorsShe doesn't critique outputs, she diagnoses the system behind them: backtesting, train/test splits, auditability. That's the rigor senior finance professionals actually need.
Albert LeeFounder, FP&A advisory practice. FCPAShe has great ability in distilling complex subject into practical workflow and application.
Emily MooreSenior finance and FP&A leader. CPA, PMPSharon is knowledgeable and approaches a situation from a real-world perspective.
Public reviews from senior finance people who have worked with Sharon. Roles are their own.
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