Ask a data team what they delivered last quarter and you'll usually get a list: pipelines built, dashboards shipped, models trained, tickets closed. Ask the CFO what value the data team delivered last quarter and you'll often get a shrug.
This gap — between what data teams do and what the business perceives — is one of the most persistent problems in the industry. It drives under-investment, misaligned priorities, and talented people leaving frustrated. And in most cases, it's entirely fixable.
The output trap
Data teams default to measuring output because output is easy to count. Pipelines, queries, features, models. These things are real and they matter, but they're not value — they're the means to value. A pipeline no one uses has zero business value, regardless of how well it's engineered.
The shift required is from reporting activity to reporting impact. That means tracing a line from a data team's work to a decision that was made better, faster, or more confidently as a result. Not always easy — but always worth attempting.
A framework for thinking about value
There are broadly three ways data teams create business value:
Revenue impact — Did a model, analysis, or insight directly enable more revenue? Personalisation, pricing optimisation, churn prediction, lead scoring. These have a clear financial story if you're willing to do the attribution work.
Cost avoidance — Did better data prevent a bad decision? Avoided a costly marketing campaign targeting the wrong segment, caught a fraud pattern early, identified a supplier risk before it became a crisis. These are harder to measure but often significant.
Decision velocity — Did self-serve analytics mean a decision happened in a day instead of a week? Compressing decision cycles has real economic value, even when it doesn't show up cleanly in the P&L.
Having the conversation
The conversation about value has to happen proactively — it won't be asked for. Data leaders need to build the habit of connecting their team's work to business outcomes in every stakeholder interaction, not just at annual review time.
That means partnering with business stakeholders before the work begins — agreeing on what a good outcome looks like and how you'd know if you achieved it. It means tracking decisions, not just deliverables. And it means being willing to say "this initiative didn't move the needle" when that's true, so that the times when it did are more credible.
Data teams that can articulate their value don't just get more budget. They get better briefs, more meaningful work, and a seat at the table when strategy is being shaped. That's worth the effort.