Data Isn't Just for IT: Why Every Function Owns This Problem
A conversation happens, with reliable regularity, when a fashion or textiles organisation begins to take its DPP readiness seriously. Someone — usually in Sustainability, occasionally in IT — is asked to lead the work. They pull together what they can find. They discover gaps. They go looking for the data that should fill those gaps and find that nobody is quite sure who owns it, or whether it exists in a usable form, or why it was collected the way it was. They escalate.
And then the conversation becomes interesting. Because what emerges is not a missing system or a missing supplier. It is a missing understanding — shared across the organisation — of whose problem this actually is.
The assumption that data is primarily IT's concern is not unreasonable. IT manages the systems. IT owns the integrations. IT is the function people call when something doesn't work. But the DPP does not ask whether an organisation's systems are well-maintained. It asks whether an organisation knows its products — their composition, their provenance, their environmental footprint — well enough to make that knowledge verifiable and available on demand.
That is not a question IT can answer alone.
The relevant data does not originate in IT. It originates in the decisions made at every stage of a product's life — in the brief, in the sourcing negotiation, in the production facility, in the logistics chain, in the returns process. The functions involved in those decisions each hold a piece of the picture. None of them, in most organisations, has been asked to hold it deliberately.
That is partly a structural failure and partly a legacy one. When production moved offshore in the 1990s, the distance that kept costs down also eroded visibility. Brands knew what they ordered. They became progressively less certain about what they received — which materials were actually used, what was substituted mid-production, what the finished product contained at the level of detail a regulatory framework would one day require. The data gap that exists today is the accumulated cost of that trade. It was not paid then. It has to be paid now.
What makes that cost so easy to defer is that it is invisible in normal operations. Each function manages its own part of the problem. The organisation never sees the full cost of not managing it as a shared one. The sustainability report gets filed. The audit passes. The sourcing decision gets made with the information available. And the structural weakness — that no function has ever been given both the mandate and the visibility to own product data end to end — remains exactly as it was.
The DPP makes that weakness specific. It asks a question that crosses every functional boundary: can you account for this product, from materials to market, credibly and specifically? It asks that question in a form that permits none of the usual workarounds.
The organisations that discover this partway through a DPP implementation — rather than at the outset — tend to make the same observation. The technology was tractable. What stalled the project was the realisation that the data the system needed to hold had never been defined, owned, or maintained by anyone with the mandate to do it properly. Re-engaging functions after the architecture is built around assumptions about what each will contribute is possible. It is also significantly harder than engaging them at the beginning.
This is not a case for a data governance committee or a cross-functional steering group — though those have their place. It is something more basic: the recognition that data capability, in an organisation whose products move through complex global supply chains, is not a departmental function. It is an organisational one.
The question of who owns product data does not have a single answer. That is precisely the problem — and the starting point for addressing it. An organisation that has never asked which function is accountable for the accuracy of a material composition claim, or what happens when two functions are working from different versions of the same information, has not yet begun to answer it.
The data problem in fashion and textiles is not IT's problem to solve.
IT is one of many functions that has a stake in solving it.
Knowing the difference is where genuine readiness begins.
Michael Shea is a digital excellence advisor, non-executive director, and leadership coach working with organisations navigating the human and technical dimensions of digital transformation. He hosts The Aeolian Discourse and writes at The Aeolian.
Photo by Petr Magera on Unsplash