ARTIFICIAL INTELLIGENCE
A robust data strategy relies on a process engineering focus. It necessitates designing information flows and including the automation of data capture to ensure high-quality data by design. This foundational work builds the basis for real value.


The Digital Oil is Contaminated: Understanding Why Your Data Strategy Fails
The promise of a data-driven enterprise is often broken because organizations try to build AI refineries on a foundation of low-quality, non-integrated data. This failure stems from poor process design, where manual entry and system silos contaminate the "digital oil" needed for true IA (AI) success.
Achieving a robust data strategy requires a process engineering focus, including the automation of data capture, to build the foundation for value
Featured Insight
18/11/2025
Jose Cortinat - 2 min read
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Strategic Insights Compendium: Transforming Operations from Risk Mitigation to Value Maximization
IA
AI only generates value when the organization overcomes data contamination; it requires transforming process engineering to ensure a high-quality data flow through automation.
COST MANAGEMENT
Focuses on the company shifting operational areas from unpredictable cost centers to strategic investments, preventing significant value loss during project ramp-up, and ensuring a quantifiable return.
Demonstrates how Senior Leadership must transcend the "doing mode" to engage in strategic reflection, aligning the vision and ensuring key roles, like the PMO, orchestrate value for the business.
STRATEGY AND LEADERSHIP
PEOPLE AND ORGANIZATION PERFORMANCE
Highlights that operational excellence is anchored in the human factor and daily culture, emphasizing the crucial role of empowering middle managers as talent leaders and architects of team performance standards.
TRANSFORMATION
Describes the need for a structural paradigm shift in the organization, elevating Operational Readiness to an early value architecture and accelerating strategy implementation by committing leaders on the ground.
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