Trusted data is now a business requirement, not a technical nice-to-have.
It underpins operational decisions, supplier performance, customer experience, reporting accuracy, and increasingly AI outputs. Yet in many organisations, nobody is clearly accountable for whether the data is actually fit for purpose.
Most companies have people who use the data, people who fix the data, and people who complain about the data. Far fewer have someone who is formally responsible for its quality, consistency, and usability across the business.
That gap matters.
Ask a simple question in most organisations: who owns product, customer, or supplier data quality?
The answer is often vague.
Sometimes it is IT. Sometimes it is operations. Sometimes it is “the data team.” Sometimes it is everyone, which usually means no one. And when ownership is unclear, quality becomes reactive rather than managed.
That is why trusted data keeps breaking down in the same places:
– New records are created badly.
– Existing records are corrected in spreadsheets instead of at source.
– Teams work around bad data rather than fixing root causes.
– No one is measured on the outcome.
The result is not just poor quality. It is organisational drift.
The stakes are higher now than they were even a few years ago.
As organisations adopt AI, automate more decisions, and depend on data across connected systems, poor data quality stops being an inconvenience and becomes a risk multiplier. If the underlying data is wrong, incomplete, inconsistent, or poorly governed, the outputs built on top of it will be too.
Trusted data is therefore not just a data management issue. It is a leadership issue.
If your CEO asked today who owns trusted data quality for the business, who would answer?
Would that person have:
– A clear mandate.
– A budget.
– Measurable objectives.
– The authority to require change upstream.
If not, the organisation may have a data problem, but it is also likely to have an accountability problem.
In the next post in this series, we are going to make a provocation: that poor data quality is, at its heart, a leadership failure — not a technology failure. We expect some pushback. Good. That is the point.