Two of your systems disagree.
We find out which number is right.

Reporting that keeps the numbers true, and checks that find where two systems stopped agreeing.

For companies of 10 to 1,000 people Three public datasets, measured — not claimed Every price published
Write, with the questions filled in
oleksii@slippagehq.com

Two lines by email · no obligation · answered by the person who would do the work

Three
public datasets measured with the same script we run for clients — linked, so you can rerun them yourself
Five
demos you can watch before writing to anyone, including the one that refuses to print a number
Same day
a straight answer, including “this is not something we would help with” when that is the honest one
What comes back

Two kinds of output, both shown before you ask

Reporting: the definitions, written down first

MetricOne readingThe otherGap
Net revenueReturns in the month of saleMonth they arrive3–8%
MarginFulfilment and fees includedFees in overhead5–15pp
On-timeAgainst the customer promiseInternal cut-off2–10pp

Both readings are defensible. The build starts by choosing one and writing it down. What a build contains →

Checks: the console output, warnings included

Key match on mature paid orders: 93% ✓ key looks right ============================================ Mature paid orders in flow: 404 A. Paid, no shipment anywhere 25 $4,088 B. Fulfilled, warehouse blank 4 $623 E. Cancelled, shipped anyway 3 $285 ------------------------------------------ MONEY AT RISK 32 $4,996 Share of flow 7.92% ============================================ [!] Above 5% is more often a data problem than a leak of that size.

Sample files, not client data — the same script that runs on real exports. The full run →

Free, and it needs nothing from us

Three things you can do right now without writing to anyone

Run the check on your own export

Orders against shipments, in your browser tab. Nothing uploaded, no account, no email asked — and the list of paid orders with no shipment is yours whether or not we ever speak. Run it →

Watch a check argue with its own result

Five demos on sample files, including the one that refuses to print a number when the key match is too low. That refusal is the part worth watching. See one run →

Download what you would actually receive

The findings file from a check, and the definitions sheet from a reporting build. Real columns, sample data, no form in front of them. Definitions sheet →

Money

Published prices, fixed scope

Free
$0
the browser check, on your own data
  • Runs locally, nothing uploaded
  • Paid orders with no shipment against them
  • The output is yours to keep
Data work
from $1,500$750 for the first three
one report automated, definitions written down
  • Full reporting build from $6,500, typically $6,500–12,000
  • A one-off analysis, one question answered: $1,800
  • What moves the band is published, not discovered later
Checks
from $1,200$600 for the first three
a seam checked end to end
  • Three months of data, not a sample
  • Line-by-line findings with amounts
  • Written method, so it's repeatable without us
Ongoing
from $600
per month, whichever we built kept alive
  • Checks run every morning, exceptions in your inbox
  • Reporting kept current as definitions change
  • Month to month, no lock-in

Invoice and deduction work is priced on what comes back. For 3PL invoice audits and retailer deductions we take a share of what's actually recovered. Nothing recovered, nothing owed — details on the pricing page.

While there is nothing to show

The first three pieces of work are half price, and you pay after delivery.

Not a launch promotion. A trade: we need work we are allowed to describe, you need a reason to go first. Both sides of it are written below, including the part that is our problem.

Half price on the first piece

One report, done properly: $1,500 → $750. Any single check: $1,200–1,600 → half of it. Everything afterwards is at the published price — there is no introductory rate that quietly expires.

Nothing upfront, and nothing owed if it is wrong

You pay when the output is in your hands and it is what was agreed in writing. If it is not, you do not pay. At $750 that is also small enough to approve without asking anyone, which is the real obstacle more often than the money.

What we get: permission to describe it

With your name or anonymised — your choice — and you read and approve the text before it goes anywhere. The agreement is to describe the work honestly, not to praise it: if the finding was “the leak was tiny and not worth chasing”, that is what gets written.

Three places, and none of them taken yet. Stated plainly rather than dressed up as a countdown. Three is the honest number: at that price it is roughly a month of capacity, and pretending otherwise would be the sort of number this whole site exists to argue against.

Evidence

One hour, 43 orders, 42 of them never shipped

One public dataset shows both sides of the seam at once — a retailer’s orders against what the warehouse shipped. We measured it rather than guessing.

0.64%

of orders vanished between the two systems — paid for, never shipped, never flagged

42 / 43

orders in the worst hour, across 42 different products. Stock doesn't run out on 42 products in the same hour

34%

of order lines in a real warehouse export where two internal systems wrote the same shoe size as 105 and 10.5

We don’t have client logos. We have measurements. The first two come from Mendeley Data, “E-Commerce Dataset” — 50,231 mature orders from a real retailer, both sides of the seam visible, measured with the same script we run on client files. The third comes from a footwear manufacturer’s WMS export, 122,370 order lines against 215,192 picking records. Open either one and check us. How we measured, in full →

The reporting side has nothing equivalent to measure, and we won’t invent it. No public dataset holds one company’s two conflicting definitions of the same metric. What we publish instead is the artefact itself — a definitions sheet you can download — and the typical size of the disagreement: 3–8% on net revenue, 5–15pp on margin.

The obvious objection

“You have no client list.”

Correct, and a logo wall would be the easiest thing on this site to fake. It would also be the first untrue thing in a relationship that runs entirely on whether you can trust a number we hand you.

So the honest question is what you can inspect instead, before paying anything. Four things, all of them on this site right now.

If you would rather not be early with a supplier, that is a reasonable position and worth saying now rather than in week three.

  • The method, written out. Including the exact cases where the tooling refuses to produce a number at all. Read it and decide whether it is what you would have done.
  • Three public datasets, measured. Same script we run on client files, sources linked so you can rerun them and check us. The working.
  • Five demos on sample files — including the one that shows the check refusing to answer when the key is bad, which is the part nobody puts on a website.
  • The money moved to our side. Price fixed in writing before the start; if the data turns out not to answer the question we stop in week one and refund the balance; you own the output either way. All of it.
How the work runs

Two shapes. What changes is inside them.

Neither is improvised. What differs company to company is named up front and agreed in writing before anything starts — not discovered in week three.

A reporting build

Two to three weeks. What differs: how many sources, how many metrics, and whether the definitions already exist.

The definitions get decided first

Which orders count as fulfilled, when a return lands, which source wins when two disagree. One written line each — the artefact that ends the meeting argument.

The model is built on what you already pay for

Power BI, Looker Studio, Metabase, a warehouse you have, or scheduled exports. No new licences, your conventions, your team reviews it.

It refreshes, and the logic stays readable

Before the working day, failing loudly rather than returning a wrong slice quietly. Recorded handover, so it outlives whoever built it — including us.

A check

What differs: which two files, which shared reference joins them, and what has to be excluded before the number means anything.

You export two files

Orders and shipments, system stock and counted stock, invoices and the rate card, deductions and your ASN. Producing them is the easy part.

The match runs event by event, not total by total

Totals tell you a gap exists. Events carry a timestamp, so the divergence gets a day, a type and a size — which is the difference between “we are 1,284 units short” and “this started on 3 February, on purchase orders closed late, and has recurred since”.

You get a list, with the evidence attached

Line by line: what each side says, the difference, the money, and — where it applies — the contract clause or deduction code to quote.

Every exclusion and every case where we refuse to produce a number is written out on the method page.

Honesty

When not to hire us

  • Your stack is genuinely clean. The free check tells you that in fifteen minutes, and that’s a fine outcome.
  • Everything lives in one system. No seam, no gap, nothing to find.
  • The data underneath is wrong. Reporting on it faster spreads the error with more confidence — we will say so rather than take the larger job.
  • Under roughly $2M and doing it all yourself. The gap is real at your size too, but a few hundred dollars a month doesn’t pay for the work.
How to start

Two lines by email. There is no form and no calendar link.

Which two systems, roughly what size, what you have already tried. The button fills those three in; two lines of answer is enough. Then fifteen minutes on your screen, then scope and price in writing — the prices are already published, so that step confirms rather than negotiates.

Write, with the questions filled in
oleksii@slippagehq.com

Two lines by email · no obligation · answered by the person who would do the work