Across our data & AI engagement, I've observed a repeating challenge: C-lelel leaders struggle to see business value early and when visibilty is low, confidence drops.
C-suites speak in revenue, risk, and ROI, while data teams speak in pipelines, models, and dashboards.
This “translation gap” kills funding, momentum, and trust.
Data projects don’t fail because of tech, they fail because of storytelling.

Instead of “data cleansing 80% done,” say:
“Before, finance spent two days reconciling numbers across systems. Now they can trust a single figure in one click.”
Instead of “Data model complete,” say:
“We’ve consolidated 12 customer systems, now sales can see a single customer view for the first time.”

I am currently working on a Value Visibility Framework.
No buzzwords. No over-engineering.
Just clearer communication, clearer milestones, and clearer value.

If we can solve this problem as an industry, even partially,
we’ll reduce transformation leakage, strengthen trust,
and finally bridge the gap between data delivered and value realised.
I’d love to hear from other leaders on this:
How do you make business value visible during long, complex data programs?
It’s a challenge worth tackling together.

(PS: it's another AI-generated video. 😁 )