Your data strategy is probably following advice that doesn't work.
After 25 years building data strategies—first running his own program, then consulting for hundreds of organizations across every major industry—Kevin Lewis discovered something: nearly everyone having challenges with their data strategy is making the same fundamental mistakes.
They're trying to build business cases disconnected from the real enterprise priorities. They're creating "foundations" that are severely underutilized. They're swinging between extremes of centralization and decentralization. And they're wondering why their significant investments aren't delivering results. All this while faithfully following widely-repeated expert guidance.
It's time to reconsider the conventional wisdom driving these strategies.
In Data Strategy Reconsidered, Lewis shares seven counterintuitive principles that actually work in the messy reality of large organizations:
Target Business Initiatives, Not Direct Business Value
Stop competing for attention and become an enabler of what matters most
Build for Change, Not All Possible Requirements
Create extensible solutions without over-engineering
Balance Responsibility, Don't Polarize
Find the sweet spot between centralization and decentralization
Build Coherent Architecture, Not Monolithic Data Stores or Splintered Data Products
Enable true cross-domain integration when business demands it
Focus on the Future, Not on Rewriting Legacy
Deliver value immediately while gradually retiring old systems
Plan the Program, Not Just Individual Solutions
Ensure every project contributes to a larger vision
Embed Data Strategy, Don't Isolate It
Make good data practices a permanent organizational capability
What makes this book different:
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