Guide to Developing a Strong Data Governance Framework

At a recent data and analytics summit, the focus shifted from the appeal of cutting-edge technology to the utilization of data and analytics for real business benefits. This shift reflects the maturation of the data industry, emphasizing the importance of practical methods to prepare data for AI and foster a data-informed culture among executives.

One of the key takeaways from the summit was the emphasis on storytelling as a crucial tool for chief data and analytics officers (CDAOs) and chief information officers (CIOs) to engage executive leadership in data-driven dialogues. This shift aims to move beyond technological fascination towards strategic business enhancement.

A new concept introduced at the summit by Distinguished VP Analyst Deb Logan and Gartner VP Analyst Ehtisham Zaidi is “collective intelligence.” This term signals a shift in data management towards “AI-ready data” and highlights the importance of robust governance to drive innovation in artificial intelligence. The focus on AI at the corporate level is becoming increasingly clear, with companies prioritizing AI as a strategic tool outperforming their peers and aligning AI strategies with business outcomes.

The importance of governance in preparing AI-ready data was underscored at the summit, with a call to action for leaders in data and analytics to enhance governance maturity for strategic business initiatives. The role of the future CDAO was also discussed, emphasizing the need for multifaceted leaders who drive culture change and foster data and AI literacy within organizations.

Upskilling and reskilling data, analytics, and AI employees was another key theme at the summit. The modern enterprise demands a workforce proficient not only in technical skills but also in business acumen and soft skills to foster a robust data-driven culture. Overcoming skill and staff shortages requires a systemic approach to skills development, culminating in a structured skills development portfolio aligned with business objectives.

Data governance was highlighted as a crucial enabler of business success, emphasizing the need to evolve traditional governance models towards ones focused on business outcomes. Modernizing governance requires a strategic and collaborative approach, benchmarking against best practices and pivoting to an adaptive governance model to drive digital advancement while aligning with business imperatives.

In conclusion, the summit emphasized the role of generative AI in delivering business value and the importance of alignment between business and technology. CIOs and CDAOs play a crucial role in shaping the corporate future by driving business change and delivering tangible business value. The focus is not just on technology but on driving meaningful business transformation.