Technical excellence alone rarely secures investment, influence, or recognition. A central data team in a large travel group learned this the hard way: they were historically underinvested, had low reputation and morale, and were told that out of 16 divisions only two would receive funding.
Despite having a solid strategy, cutting-edge architecture and clear cost-saving ideas, the turning point came from reframing the message. Instead of talking about cloud migration or data ingestion, the team led with one powerful truth: the company does not own the products it sells; it depends entirely on data about supply and demand. If that data is not managed well, there is no business. That sentence captured executive attention and unlocked a multi-year transformation investment.
The workshop emphasizes that data and AI leaders must first focus on what the business cares about, then align data capabilities to those priorities. The challenge is less about intelligence or preparation and more about language and framing.
Common frustrations are shared:
These experiences often stem from communication anti-patterns and limiting beliefs—such as assuming “the value speaks for itself” or that executives are interested in the same details as data professionals.
The session is structured in three “episodes”:
Identify Anti-Patterns
Participants surface where communication goes wrong and which beliefs hold them back from being heard.
Think and Act as Credible Business Partners
The focus shifts to adopting the mindset and language of the business, so data teams are seen as value drivers, not cost centers.
Craft and Share a Great Value Story
Finally, attendees apply these ideas to build concise, impactful stories that connect data and AI work to strategic outcomes and recognition.