Why Data Teams Fail to Deliver ROI (And How to Fix It)
Most data teams are overworked and underdelivering. Learn why—and how to align data work to ROI using the Value vs Complexity Matrix.
Ali Z.
𝄪
CEO @ aztela
Table of Contents
The $2M Data Black Hole
A few weeks ago, I spoke with a CEO who spent over $2M on data last year.
Their team was buried in dashboards, pipelines, tools, and “AI readiness.”
When I asked what ROI they saw?
“Honestly? Nothing I can point to.”
That hit hard. But it’s not rare.
Why Most Data Teams Are Busy but Useless
Every day, their team woke up to Slack PTSD:
“Can you add this metric?”
“Pull this from Salesforce?”
“Fix the BI dashboard before QBR?”
It never ends.
The result? Weeks spent fixing reports, debating definitions, and wiring pipelines—but none of it moves the business forward.
The missing ingredient? Strategy.
Code Means Nothing Without ROI
You can write the cleanest dbt model or the best Airflow DAG.
But if you can’t walk into a meeting and say:
“This saved the company $X.”
“This feature grew NRR by Y%.”
…then none of it matters.
The Fix: The Value vs Complexity Matrix
Before writing a single line of code, plot every initiative against:
Business impact: revenue, cost, or risk reduction.
Complexity: data quality, tools, team effort.
Then:
Focus only on high-value, low-complexity projects.
Make those your 1–3 quarterly priorities.
Cut or delay the rest.
This is how you turn chaos into a roadmap that actually matters.
For more on prioritizing initiatives, see our data strategy framework.
Think Like a Product Team, Not a Service Team
The best data teams don’t just “fulfill requests.” They think like product teams:
1. Strategy — Who’s the user? What decision does this enable? Why now?
2. Build — Ship a fast MVP. Just enough to prove value.
3. Iterate — Collect feedback, improve, drive adoption.
This mindset shifts your team from reactive → revenue-driving.
Real Tip: Less Meetings, More Deep Work
AI work requires focus. Most meetings are noise.
The only ones that matter? User feedback sessions.
Everything else should be async.
Blunt Bottom Line
Most data teams are overworked and deliver nothing.
The fix isn’t more dashboards or headcount—it’s strategic focus, ruthless prioritization, and product thinking.
If you want your data team to move from cost center to ROI driver, Book a Data Strategy Assessment.
