Advisory for distributors and manufacturers
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
Two closing reports produced by the method, one for a distributor and one for a manufacturer, on sample data. Timing across purchase order, receipt and invoice. Cost changes. Duplicate items. The exceptions ranked by what they are worth, so you read the 6 that matter and not the 4,000 that do not.
How it works
Anyone can ask AI a question. This is a workflow designed end to end, from the raw exports to the decision: the same steps, the same rules and the same checks every time, so the result can be repeated, compared month to month, and defended.
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, then about 30 minutes reading the result.
This is how I run a diagnostic, with my own workflow, to get you the answer. Building a workflow 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 inventory line, every month, so each figure traces back to the transactions behind it, and month 6 compares cleanly with month 1. That turns the close into a position of strength: better terms from a lender, a shorter diligence, a board that moves on to the next question.
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 30-minute readout. Sample 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.
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: Inventory month-end close with Claude
The framework to learn and run in-house: the closing Skill, the data map, the thresholds and the report template.
Sharon 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 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, TaiwanShe has great ability in distilling complex subject into practical workflow and application.
Her coaching style encourages critical thinking, problem-solving, and genuine understanding rather than reliance on prescribed answers. She creates an engaging learning environment that consistently challenges and inspires students to reach a higher level.
Sharon is an excellent hands-on instructor. Her coaching is amazing and her AI skills are incredible.
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