By Stephanie Simone
With every organization currently wondering if their data is sufficient for AI,closing the gap between data ambition and operational reality requires more than just a technical roadmap.It requires the strategic discipline to translate major pain points into a narrative leadership can fund.
Building a modern data foundation will support not only AI but a myriad of operational use cases. When backed by a resilient business case, the right technology can transform a company from being built around its silos to being built around its data.
DBTA recently held a webinar, From Silos to AI Readiness: Building a Winning Business Case for Your Data Foundation, with Monica Mullen, director, product marketing at Informatica from Salesforce and Alex Corman, CEO of Blue Mesa Consulting, who shared real world scenarios, industry examples, and core valuation frameworks to help secure funding for your data modernization projects.
According to Mullen, the question every executive is asking is: Is our data actually ready for AI? She cited several statistics including:
- 87% of AI projects fail not due to algorithms—but dirty, siloed data
- $12M-plus average annual cost of poor data quality per enterprise
- 6 weeks is the average time lost just to answer one customer analytics question in a silo environment
Mullen said data initiatives typically fail to get funded because:
- Technical teams speak in systems; executives speak in dollars
- ROI feels theoretical without real-world financial scenarios
- A ‘no’ at the C-suite stalls projects for 6–18 months
- Momentum lost = competitive disadvantage on AI readiness
There are several ways to change this outcome, she explained. This includes:
- Translating pain points into a narrative leadership can fund
- Creating conservative models across low, medium, and high scenarios
- Positioning data as the critical AI prerequisite—now
- Framing technical debt as an urgent business priority
The right platform removes the implementation risk that kills executive confidence, Mullen noted.
Corman explained that Blue Mesa Consulting’s goal is to help organizations make informed decisions about contemplated investments. He outlined the business case analysis process, which includes:
- Discovery: Have an initial team meeting, understand current workflows, and identify opportunities for value.
- Metrics gathering: From existing materials and form stakeholder interviews.
- Collaboration analysis: Create a preliminary model, present model for feedback, and review and iterate.
- Executive presentation: Have an executive walkthrough and then make final edits and ratifications.
The value of a strong data foundation is real, but diffuse—which makes it far harder to quantify than a typical technology investment.
“Our strategy is to build confidence and credibility at every stage,” Corman said.
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.