The working record, in full.
A testimonial asserts quality. A record carries the number. If you have been burned before, one engagement documented properly is worth more than ten summarized.
Every number here traces to a documented catch.
The names are anonymized. The numbers are exact. Nothing on this page was written for this page.
A supplier overpayment, stopped before it left the account
Found by the reconciliation discipline itself rather than by somebody happening to notice. That distinction matters: a process caught it, so it would have been caught regardless of who was in the seat that week. A European appliance brand
A supplier refund chain, recovered on documentation
It worked because three things existed at once: the defect evidence, the PO record, and the payment trail. Most claims die because one of the three is missing. Documentation is a module in the build, not an accident. An 8-figure Amazon FBA brand
Unreconciled shipments swept into filed cases
Nobody had ever checked them. Contingency recovery firms do this one slice and keep 20 to 25 percent of what they find, permanently. In the build it happens once, and you keep all of it. An 8-figure Amazon FBA brand
Stock that already existed, invisible to planning
Sitting under a duplicate SKU name, hiding from a reorder decision that would otherwise have been sized as though it were not there. The forecasting software had all the underlying data. It never caught the mapping problem, because that is not what forecasting software is built to catch. A golf accessories brand
A just-placed PO, caught and stopped before it shipped
That catch only happens inside a live weekly review, where last week’s decisions get looked at again before this week’s get made. A one-off report nobody revisits does not find it. A golf accessories brand
From data access to a working multi-node master sheet
Every SKU, every node, combined inventory and demand. The client’s own words: “you did this in a day. Not four weeks.” A golf accessories brand
The three artifacts behind the method.
Each one is a real working file from a real engagement, not a diagram redrawn for a slide. They are what the build actually produces.
One catch, drawn to scale. A just-placed purchase order sat at roughly 400 days of coverage. The dashed line is day 90, the horizon the rest of this site plans around.
The actual master sheet
The combined inventory and demand view, built inside 72 hours of getting access to the data. Not a redrawn version for a slide. The working file, redacted. The client’s words afterward: “you did this in a day. Not four weeks.”
The actual sunset tab
The per-SKU discontinue-or-liquidate list, with the reason attached to every line. This is the artifact that caught a purchase order already in motion at roughly 400 days of coverage, before it shipped. The client’s words on this one specifically: “I love this... this is very accurate.”
The actual reimbursement case log
From a second, separately anonymized engagement. The real tracker: 280 shipments going in, 31 documented cases filed coming out the other side. Shown as a working file, not as a summary statistic on a slide.
The same modules, on your catalog
Each artifact ties back to a named module: the Master Sheet System, the Sunset Tab, the reconciliation sweep. The build runs those same modules against your own numbers.
The tab that stopped the order.
A purchase order at roughly 400 days of coverage is not obvious in a stock report. It is obvious here, because every line carries a tier, and every tier is a threshold somebody can check and argue with.
Tier 1 DEAD: SV L30 ≤ 0.10 and SV L90 ≤ 0.20 // thresholds are tunable per catalog| A | B | C | D | E | F | G | H | |
|---|---|---|---|---|---|---|---|---|
| 1 | Amazon SKU | Tier | SV L30 | SV L90 | Trend | DOC AVL | Units held | Action |
| 2 | CK-LID-05 | 1 · DEAD | 0.07 | 0.14 | 0.31 | > 999 | 3,180 | Liquidate |
| 3 | PT-BED-01 | 2 · SUNSET | 0.24 | 0.41 | 0.38 | 612 | 9,400 | Price move, then ads |
| 4 | PT-BED-09 | 2 · SUNSET | 0.29 | 0.46 | 0.47 | 548 | 2,610 | Price move |
| 5 | GR-MAT-02 | 3 · WATCH | 0.81 | 1.04 | 0.72 | 561 | 1,940 | Ad push, hold price |
| 6 | EM-SCT-11 | 3 · WATCH | 0.94 | 1.31 | 0.68 | 544 | 420 | Hold, re-check 30 d |
| 7 | CK-DUO-08 | — | 4.57 | 5.75 | 0.94 | 96 | 0 | Reorder normally |
Structure and thresholds are exactly what we deliver. SKUs and figures are illustrative: the real tab belongs to the client, and their numbers stay theirs.
The part most pages leave out.
Every catch above came from real engagements that built this method. None of them ran under this exact productized package at this exact price. That makes what you have just read a strong expectation built on a working record, not a completed track record of the product itself. We would rather state that plainly than let you discover it in month two.
No logos
Most of what we are proud of has not been cleared to name. Clients are never named publicly until they clear it themselves, which is also the policy that protects you if you become one.
No performance percentages
You will not find a forecast-accuracy figure or a stockout-reduction percentage anywhere on this site. We do not have verified ones, so we do not print them.
No quotes we wrote
Every quote on this page is verbatim from the platform record, unattributed because Upwork shows no client names. We do not paraphrase a client into a better sentence.
Upwork computes every one of these from completed contracts. Nothing is self-reported or rounded up. Twenty-one contracts completed, five running, sixteen five-star reviews and one four-star.
What clients actually wrote.
Thirteen clients left written reviews on the platform record. Five are here, in full or with an ellipsis where a sentence was cut. Upwork never shows client names on a public profile, so none are attributed, and we will not invent an attribution to make one look warmer.
“Hired him for a demand forecasting project, historical sales analysis, trend and seasonality identification, SKU-level projections, all built in Google Sheets. He came in fast, asked the right questions upfront, and the model he built was clean and actually usable by the team, not just impressive to look at. I first worked with him about a year ago on a similar scope and had a good experience. This confirmed it wasn’t a fluke. If you’re looking for someone who understands the operational side of inventory and purchasing, not just the spreadsheet mechanics, he’s worth the conversation.”
“Hamza has been a major lever in our business. He plays a critical role across supply chain operations, packaging development, dielines, and overall project management, while also effectively managing and coordinating the team. He brings structure to complex workflows, keeps projects moving forward, and consistently delivers under pressure … someone we trust with core parts of the business.”
“Hamza is really great with data, I personally like his way of understanding the system and going deep into it to find the gaps and then providing solutions for them. He is easy to work with and has a great sense of humour. I would definitely rehire him for my next project.”
“Great operational mindset. The recommendations were practical and clearly prioritized. Their coordination, focus, and ownership were outstanding. Each part of the work was handled by someone who clearly knew what they were doing, and communication was seamless.”
“Very good communication throughout the project. Helped find a reliable 3PL partner, negotiated effectively, and performed exceptionally well under pressure. Would definitely hire again.”
Talk it through against your catalog.
Thirty minutes on a free call. You almost certainly know which SKUs are tight already. The harder part is the order-by date sitting behind them, the cash that has quietly stopped moving, and where your three systems disagree. That’s the conversation.