Fashion
A size was there. The size they wanted wasn't.
Fashion demand fails at a level your systems never record: the size, the fit, the colour a customer asked for and walked out without. Orkestra captures that, per store, and turns it into allocation.
Orkestra in fashion
Fashion doesn't have a forecasting problem. It has a capture problem.
- 01 · Capture
Pulse on the floor
- 02 · Unify
StoreDNA per door
- 03 · Act
Cockpit rebalances
From the floor
What fashion demand actually looks like.
Live from the floor: what was asked for, what was on hand, and the move Orkestra recommends.
StoreDNA · size curve
Store 22 · Milan
WOOL-COAT-BLK-38
demand vs on hand
36
38
40
42
44
46
Orkestra recommends
Move 38 and 40 in from Store 09 before the weekend
2 sizes refused this week
Recoverable
€41k
The invisible gap
A broken size curve looks like a slow seller.
When 38 and 40 sell out in week two, the store carries a rail of 44s for six weeks and the report reads: this reference underperformed here. It didn't. It sold out of the sizes that mattered and was never replenished. The next buy repeats the error, because the buy is trained on the sale that happened, not the one that was refused.
How Orkestra runs it
Capture, unify, act, in this category's own language.
Step 01
Pulse on the floor
Advisors log the refused request in seconds, size, colour, fit note, inside the sale, not after it.
Step 02
StoreDNA per door
Real size curves per store and market: what this door would sell, not the chain average.
Step 03
Cockpit rebalances
38s sitting in a slow door move to the door that's asking, before markdown makes it academic.
A decision, not a dashboard
What lands in front of your team.
Executive decision required
97% confidence
Decision window expires in 14:32
- Action
- Transfer 60 units
- Reference
- FW26-KNT-0421-NVY-38
- Route
- Store 22 → Store 9
Calculated logic
- · Store 9 has 4 days of cover left on its top-selling size
- · Pulse logged 11 requests for this reference in the last 7 days
- · Store 22 is three weeks from markdown risk on the same reference
What changes
The measurable difference.
Size curves per door
Allocation follows the demand shape of each store rather than a national grade.
Fewer bestseller gaps
The references that carry the season stay on the floor through the season.
Sharper next buy
Buying decisions trained on refused demand, not only on realised sales.
Less end-of-season residue
Broken curves get rebalanced early instead of being marked down late.
Fashion doesn't have a forecasting problem. It has a capture problem.
See Orkestra on your own fashion stores.
Your first agent runs within 48 hours of kickoff, no re-platforming.