The data capability problem in most fashion organisations is not a shortage of understanding. It is a surplus of partial understandings that never add up to a shared one. Every function has a piece. But the pieces don't connect.

This is not a collaboration failure in the conventional sense. The meetings happen. The cross-functional projects are stood up. The willingness, in most organisations, is genuine. What tends to be absent is something more fundamental — a shared understanding of what the data is actually for, and who is accountable when it falls short.

A version of the supplier data problem is familiar to most brands. The data comes back incomplete. Fields are estimated rather than measured. Certifications cover a material category rather than the specific input used in a specific product. The figures submitted this season look suspiciously similar to the figures submitted last season, regardless of what actually changed in the supply chain.

The diagnosis is almost always the same: the supplier isn't capable, or isn't trying. The response is more pressure — tighter requirements, harder deadlines. And the data quality stays roughly where it was.

Nobody has told her that the difference matters.

The platform is live. The data fields are populated. And a product manager is copying last season's material composition figures into this season's record because gathering them fresh would take three days she doesn't have.