Perspectives and lessons learned on Data, AI and organizational transformation.
Strategy
Technology is rarely the root cause of failure. Framing, governance, alignment and adoption weigh far more heavily on the final outcome.
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AI
Not every problem deserves AI. Five criteria separate a value-creating use case from a showcase project: business value, feasibility, data, risk and adoption.
Transformation
The POC that never becomes a product is the most widespread symptom in Data programs. Scaling up requires a change in the nature of the project, not just its size.
Migration
A successful data migration is invisible: everything just works on Monday morning. A look back at the costliest mistakes seen on CRM and ERP migrations, and the practices that prevent them.
Governance
AI amplifies everything you feed it — including the mess. Without data governance, AI initiatives stall at pilot stage or produce results no one can explain or defend.
