The Function That Was Handed the Problem Without the Mandate
A conversation happens with reliable regularity when a fashion or textiles organisation begins a data-related implementation. The scope is defined. The system is selected. The project plan is approved. And then, partway through, the implementation team discovers that the data the system needs to hold has never been properly defined — that two functions are working from different versions of the same information, and that the governance questions the project assumed had been answered were never asked.
At that point, the project lands on IT. Not because IT created the problem. Because IT is the function holding the system that makes the problem visible.
The data problem in fashion and textiles organisations is not primarily a technology problem. Earlier articles in this series have made that argument from multiple angles. But the argument looks different from IT's position — because no function experiences the gap between that argument and organisational reality more directly than the one expected to implement the technology.
A system can store and retrieve data. It can enforce formats and flag inconsistencies. What it cannot do is decide what data means, determine who is responsible for its accuracy, or resolve a version conflict that two functions cannot settle between themselves. Those are human decisions. They require organisational clarity — shared definitions, assigned accountability, agreed processes for maintaining data when circumstances change. In most fashion organisations, that clarity does not exist. And in the absence of anyone else to hold it, it lands on IT.
This is the mandate gap. IT is handed asset responsibility — for the integrity and availability of product data — without the organisational conditions that would make exercising it possible. The result is a function that manages data technically while the decisions that determine data quality are made, or not made, everywhere else.
The distinction between data management and data governance is where the gap concentrates. Data management is what IT does — maintaining systems, ensuring data is stored correctly and retrievable on demand. Data governance is what the organisation needs to do — deciding what data means, who owns it, and what happens when it falls short of the standard. The two are related but not the same. A well-managed system holding poorly governed data produces a database that is technically sound and practically unreliable.
Most fashion organisations have invested in data management. Few have invested in data governance. The gap between those two things is where the DPP implementation will stall — not because the technology fails, but because the technology arrives at decisions the organisation has not made. Which product attributes are mandatory fields and which are optional? Who signs off on a material composition figure before it populates a passport data field? What is the process when a supplier changes an input mid-season and the passport needs to reflect that change? Those questions have to be answered before the system can be configured to enforce them. They are not IT's questions to answer alone.
What IT understands intuitively — and rarely has the organisational language to argue upward — is that data infrastructure, properly governed, compounds in value. Each well-structured data product makes the next easier to build. Shared definitions established for DPP compliance become the foundation for demand forecasting and circularity operations — uses that were not anticipated when the governance decisions were first made. The investment made once, in getting the data right, compounds across every subsequent use.
The inverse is equally true, and IT lives it most directly. Each implementation built around data that was never properly defined requires another implementation when the requirements change. The system built to satisfy the 2027 minimum will need to be rebuilt — partially or wholly — for the 2031 requirements, and again for the circular economy framework beyond that. Not because the technology is wrong. Because the governance that should have preceded the technology was deferred.
IT is the function best positioned to make that argument — not as a complaint about mandate, but as a strategic observation about where the investment actually needs to go. The organisations that will navigate the full DPP trajectory without rebuilding at each phase are the ones whose IT function was empowered to insist on governance before configuration, on shared definitions before system design.
That empowerment does not arrive by itself. It requires leadership to understand that the data capability question is not primarily a technology question — and to resource the governance work that precedes any useful technology implementation accordingly. IT cannot mandate that understanding from below. But it can make the case for it clearly, with the evidence that only IT can see: the accumulated cost of implementations built on unresolved governance questions, and the rebuild cycles that follow each new regulatory requirement.
The function handed the problem without the mandate is also the function with the clearest view of what solving it actually requires. That is not a paradox to be managed. It is an argument to be made.
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.