Bad data costs more than the software you bought to fix it.
I find the money leaking through your data — and tell you exactly which field it’s leaking from. Chargebacks traced to their cause, deductions ranked by what’s recoverable, launches modeled before they eat your cash. You get a remediation plan your team executes without me.
Twenty-five years in operational data. Two decades running operations at an incentive-fulfillment company where I cut data errors 75% and architected $5M+ in platform implementations — including being the one employee retained post-acquisition to teach the buyer their own system. The methods on this site are how I’ve always worked. Now they’re available to your brand.
The Problems I Take Off Your Desk
Chargebacks you can’t trace
Retailer fines arrive coded and cryptic, and nobody can say which product-data field caused them. I audit the product master end to end — UPC/GTIN, GDSN, retailer requirements — and trace every chargeback to the specific field that triggered it, with the annualized cost and the fix.
Worked example: $458K/year in chargebacks, each traced to its causing field — Product Data Health Audit
Deductions aging past their dispute window
5–15% of gross sales leaks through deductions while net margins sit at 3–5%. I rank every deduction by dollar value, win likelihood, and days left to dispute — then hand your team the evidence checklist and the letters to file.
Worked example: $1.66M backlog, recoverable share moved from 16% to 65% — Trade Spend & Deduction Recovery
Trade spend nobody can account for
Promotions funded twice, deducted but never run, billed above the agreed rate. I match the promo plan to the deduction stream to the settlements — and rerank your retailers by what they actually return.
Worked example: $480K/year in operational trade waste — Trade Promotion Leakage Audit
A launch that could eat your cash
The retailer deal projects revenue; nobody models the cash trough. I score readiness across eight dimensions and model the launch month by month — before you sign.
Worked example: $499,200 in projected revenue, −$36,320 cash year — Retail Readiness & Launch
Data problems that keep coming back
An audit is a snapshot; defects are a flow. I build the validation layer — automated checks, item-setup preflight, exception protocols — so what flows into your systems is already right.
See the architecture — Validation Pipeline Build
Behind every engagement: audit pipelines in Python and R, decision tools your team actually uses, and validation engineering that runs without me. The capability list is on the Services page. The point is what it does to your P&L.
The Quiet Cost
The average specialty food brand spends 15–20% of revenue on trade promotions and cannot say which ones made money. Chargebacks run 5–15% of gross sales while net margins sit at 3–5%. Most of that loss traces to twelve product master fields that disagree across three systems — and nobody has audited them.
These problems don’t announce themselves. They compound in reports that are slightly off, reconciliations that don’t tie, and submissions that get kicked back. By the time someone notices, nine months of automatic deductions have already hit the P&L.
I work upstream — on the data layer between your raw records and the systems that depend on them. The goal is simple: what flows through is already right.
How I Work
Scoping Conversation
Thirty minutes. You describe the data problem; I tell you whether it's a fit and what a scoped engagement looks like.
Frame the Problem
We define the scope together — what data, what systems, what question needs answering. I send a written proposal with the deliverable, the timeline, and a fixed fee. No ambiguity about what you're getting.
Deliver
I do the work and hand you the deliverable — a written report, an interactive tool, a triage workbook, whatever the scope calls for. If the data needs ongoing attention, we talk about a retainer. If not, you have everything you need.
Concretely: a brand sends me twelve months of remittances; three weeks later they have a ranked list of every disputable deduction, the evidence to file each one, and the dollar value of what’s recoverable. That’s the shape of every engagement — your data in, a decision-ready deliverable out.
Not ready for a full engagement?
The Data Health Snapshot is the one-week version: send one dataset, get written findings with the annualized cost and a top-10 fix list. Fixed fee, credited toward a full audit within 60 days.
Learn more →Thirty minutes. No obligation.
Tell me about the data problem. I’ll tell you where the impact is hiding.
Get in Touch