Welcome back to Connecting.The.Dots.
During a recent fireside chat a few days ago, a statement made me think:
"People will trust you when they see you in action."
Not when you present frameworks. Not when you share strategies. When you show what actually works.
After the first editions of Connecting.The.Dots exploring frameworks and concepts, it's time to move from theory to action and share concrete examples of my frameworks in operation.
My last 2 weeks have been highly focused on moving to action on an exciting new digital journey ahead in 2026. So it's only fair that I start sharing why I believe my framework works with concrete, real-life examples.
This edition of Connecting.The.Dots is about a very special project that I've had the pleasure of leading at Danone over the past 2 years: VAULT — A Multi-layer Fraud Prevention Security Model for Vendor Management. More importantly, it's proof that the frameworks we've explored aren't theoretical constructs. They're operational requirements for building sustainable competitive advantage in Global Business Services.
So let's unpack this first case study. Here's what data foundation work actually delivers when you commit to doing it right.
The Question Everyone Asks
After my recent keynotes on data readiness for AI, the most common question isn't about frameworks. It's simpler and more honest: "Does this actually work?"
Behind that question sits exhaustion with transformation presentations, framework launches, and strategic pivots that never materialize.
So let me answer directly: Yes. But not the way most organizations attempt it.
What is Vault?
Vault is our multi-layer fraud prevention security model. It protects against payment fraud, bank account manipulation, and vendor impersonation across global operations.
The industry recognizes it as an operating model demonstrating what becomes possible when you get data readiness right.
But here's what makes Vault interesting: it didn't start as a fraud prevention project. It started as foundation work on master data that nobody wanted to build.
The Foundation Work Nobody Wanted
Years ago, we faced the problem every GBS organization faces: fragmented vendor and bank account data across multiple systems.
No one wanted to work on this. Master data management is the broccoli of business transformation—everyone knows it's good for you, but nobody gets excited about it.
We made a choice. Build the cipher key properly. Clean vendor master data. Validated bank account information. Mapped data flows. Established clear ownership and governance.
This foundation work took years. Master data global governance. Centralized operations. The unglamorous infrastructure that nobody applauds.
And during those years, executives asked: "Why aren't we implementing AI yet?"
Because you can't AI your way out of a data problem.
Getting to "Good Data" in the Good, Bad, and Ugly framework for data readiness requires commitment to foundation work that delivers no immediate wins. Most organizations aren't willing to make that commitment.
But here's what happened once that foundation was solid: Vault deployed in short, continuous waves. Rapid activation. Quick iteration. New capabilities are launching monthly instead of yearly.
The foundation took years. The capability deployment took months.
That's the acceleration paradox: you move fastest when you build on solid ground.
The Virtuoso Dynamic Model in Action
Here's how the foundation enabled sustainable value:
Data Quality (The Cipher Key):
- Clean vendor master data, providing the translation layer
- Validated bank account information across systems
- Mapped data flows showing exactly where information moves
- Clear ownership ensuring accountability
Process Excellence (The Structure):
- Multi-layer verification protocols
- Automated exception handling
- Escalation pathways for complex cases
- Continuous improvement loops
Technology Capability (The Amplifier):
- Data-powered fraud detection
- Real-time risk scoring
- Automated vendor validation
- Integrated alert systems
None of these layers works in isolation. Technology fails without data quality. Process excellence can't scale without technology. Data quality provides no value without processes to leverage it.
The VDM isn't a framework to implement. It's a reality to orchestrate.
What Actually Made Vault Work
Let me be specific about what enabled Vault's success:
We Trimmed the Data Hedges:
Multiple systems held vendor and bank account data. Each spoke a different dialect. We didn't eliminate the systems—we created translation mechanisms. The hedges stayed, but we maintained clear sight lines across them.
This is why most digital twin initiatives fail. You can't create a complete picture of your processes when data hedges fragment your view. AI needs to see the whole picture, not disconnected fragments.
We Built on the White Canvas:
We didn't try to "fix" existing fraud detection processes. We asked: "If we designed fraud prevention from scratch today with AI capabilities, what would it look like?"
That white canvas thinking allowed us to design something genuinely new rather than automating broken processes faster.
We Made the Cipher Key Work:
Every fraud detection layer relies on knowing: "Is this the real vendor? Is this their actual bank account?"
Master data became the foundation that made every other layer possible. Without it, even the most sophisticated AI generates false positives because it can't distinguish signal from noise.
We Accepted the Long Game:
Foundation work takes time. Years of master data governance and centralized operations created the platform. But once that foundation was solid, we could move fast—deploying Vault capabilities in continuous short waves, iterating monthly instead of annually.
The patience required is in building the foundation, not in deploying capabilities. Organizations rushing to implement AI on weak foundations spend years debugging. Organizations that invest in foundations first deploy capabilities in months.
Three Insights That Transfer
If you're building GBS x.0 capabilities, three lessons from Vault transfer directly:
1. Foundation Work Isn't Optional
Clean master data. Mapped data flows. Clear ownership. These aren't "nice to have"—they're prerequisites for everything else.
The organizations racing to implement GenAI without data readiness will spend years debugging hallucinations. The organizations building foundations first will unlock genuine intelligence amplification.
2. Frameworks Work When Orchestrated
The Intelligence Triad, Virtuoso Dynamic Model, Data Hedges, White Canvas thinking—these aren't competing ideas. They're interconnected realities you must orchestrate simultaneously.
Vault works because all these elements align. Remove any one, and the whole structure weakens.
3. Foundation First, Then Accelerate
The paradox: organizations that invest years in data foundations deploy capabilities in months. Organizations that skip foundations spend years stuck in pilots.
Vault's rapid deployment only happened because master data governance and centralized operations were already solid. We moved fast precisely because we'd been patient with the foundation.
The organizations building deliberate foundations today will accelerate past competitors tomorrow—and sustain that advantage because their capabilities rest on solid ground.
What Comes Next?
Here's where the acceleration advantage becomes visible in real-time.
The foundation we built didn't just enable Vault's deployment. It created the platform for continuous evolution.
Vault—the safe space for vendor and bank account master data—is actively evolving into V.A.U.L.T.: Vigilant Anti Fraud Unit Leveraging Technology.
This isn't a rebrand. It's a capability transformation happening now.
The original Vault established trust through clean master data and validated processes. V.A.U.L.T. leverages that foundation to deploy AI-powered vigilance—predictive fraud detection, real-time threat intelligence, and adaptive risk scoring that learns from every transaction.
The evolution happens in continuous short waves because the cipher key is solid. AI can now detect patterns we never imagined, predict threats before they materialize, and adapt faster than fraud tactics evolve.
This is white canvas thinking in operation. We're not automating Vault's processes—we're reimagining what becomes possible when the Intelligence Triad orchestrates on a foundation built for scale.
The organizations that built solid foundations are evolving monthly. The organizations that skipped foundation work remain stuck debugging their pilots. You can see this immediately by the length of their deployment plans, years with no foundation, and months when the foundation is strong.
That's the acceleration advantage: you move fastest when you've built properly.
But here's an important reality: working on foundations for years isn't a luxury we have anymore. The pace of AI evolution means we need to step-change the speed at which we build those foundations.
I believe AI will play a critical role here as well—not just as the capability we're building toward, but as the accelerator for foundation work itself. How organizations leverage AI to rapidly achieve data readiness while AI capabilities simultaneously advance is a challenge we'll explore in upcoming editions.
What This Means for You
You don't need to build Vault. You need to build your version—the capability your organization needs that requires proper foundations.
Ask yourself:
What strategic capability would transform our operations if we got the foundations right?
Not "What AI tool should we buy?" but "What becomes possible when we crack our data code?"
For us, it was fraud prevention. For you, it might be:
- Predictive supply chain optimization
- Intelligent customer experience
- Automated compliance monitoring
- Real-time financial intelligence
The domain doesn't matter. The approach does.
Build the cipher key. Orchestrate Human, Process, and Artificial Intelligence. Apply VDM thinking. Embrace the white canvas design. Trim your data hedges.
Then watch what becomes possible.
The Bottom Line
Vault proves that foundation work delivers both capability and speed when done properly.
Years invested in master data governance and centralized operations enabled rapid deployment of sophisticated capabilities in continuous short waves. The acceleration paradox in action: patient foundation work creates the conditions for fast capability deployment.
The organizations that understand this will build advantages their competitors can't replicate—not just better capabilities, but the ability to deploy new capabilities faster than anyone rushing AI implementations on weak foundations.
Stay tuned. Keep Connecting. the.Dots.
Disclaimer: This content is based on the author's independent reflections and thoughts and is not associated with any company or organisation.