I commit the money · The Buyer

You committed the budget in March. You find out in September.

You commit open-to-buy in March against a spreadsheet and a feeling. Your supplier's forecast is a sales target wearing a forecast's clothes. You negotiate hard on margin in January and hand it all back in markdown in September, and everybody calls that the cost of doing business. Your supplier brings an analyst to that meeting. What do you bring?

The promise

What changes on Tuesday.

A forecast that thinks: seasonality, trend, paydays, promotions, and a lead time for every product and supplier rather than one number for the lot. Cannibalization modeled before you commit, not discovered in the post-mortem. A lifecycle profile, so you know the shape of the curve before you buy the top of it.

The proof: Every order shows the lead time it was sized to and where that number came from: the product, the supplier or your default. Measuring what each supplier actually delivers against what they promise is in build.

For you: You walk into the supplier meeting knowing the lead time every order was sized to, and what it would take to move the inventory you are both looking at.

See it on your own data.

Twelve weeks, one category, anonymized by you. A ten-minute job, not a project. Send it Thursday and you'll have the findings the following Wednesday.

  1. 1 · The extract"Twelve weeks, one category, anonymized by you." A ten-minute job, not a project. No NDA drama, no IT ticket, nothing to approve.
  2. 2 · The findings"Here is what it found in your data." The engine has never met a real dataset it did not find something embarrassing in. Evidence about you, not persuasion.
  3. 3 · Run-alongside"Eight weeks. It doesn't touch anything." Zero operational risk; your own scorecard.
  4. 4 · The agreement"Terms in writing, implementation as a fixed number." By then you have your own proof, so the decision is an easy one.
Send the extract

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