Takeaways from a Thrilling 17th Annual Chief Data Officer (CDOIQ) Symposium

Image caption: CDO Magazine CEO Steve Wanamaker (standing right) and Global Editor Camille Prado (standing left) enjoy gathering with some Global Editorial Board members from its CDO Forum communities in Boston, Chicago, Israel, Latin America, New York, Tennessee, Texas, Toronto and Washington, DC, at the CDOIQ Symposium on July 18, 2023.

Left to right are: Chevron Chief Data Officer Ellen Nielsen; Bureau of the Fiscal Service Chief Data Officer, Deputy Asst. Commissioner Justin Marsico; Delek US Holdings EVP, Chief Information & Data Officer Ido Biger; CDO Magazine CDO Ambassador for Canada Della Shea; Sanofi Chief Data Officer R&D, Data and Data Sciences Raj Nimmagadda (standing); West Monroe Innovation Fellow, Data & Analytics Strategy Doug Laney; SGI Canada Insurance Chief Data Officer Cal Rosen (standing); Mizuho Financial Group Managing Director & Chief Data Officer JC Lionti; Stanley Black & Decker Sr. Director, Data & Advanced Analytics Kishore Aradhya; TDECU VP, Engineering, Architecture & Analytics Devshree Golecha; Health Care Service Corporation Head, Strategic Partnerships, Enterprise Data & Analytics Phanii Pydimarri; Mars Wrigley Global Head, One Demand Data & Analytics Solutions Deepak Jose; and Grupo Intercorp Chief Data Officer Ivan Herrero.

Perhaps it is the energy and excitement over Generative AI. Or the recognition that, in spite of decades of encountering and overcoming impediments to transformation and success, organizations continue to struggle to deliver business value from their data, analytics, and AI investments. Afterall, only 23.9% claim to be data-driven and just 20.6% say they have established a data culture. 

Could it be the ongoing cycle of test and learn, failing fast and learning faster that data and analytics leaders embrace day to day? Or the perpetual development, introduction, repackaging, renaming, and repositioning of data, analytics, and AI capabilities that excites and confuses business leaders?  

Might it be the tenuous nature of the Chief Data & Analytics Officer (CDAO) role? Even with 82.6% of companies claiming to have appointed a CDAO, 35.5% say the role is well established within their organization, and 40.5% say it is well understood. The average CDAO tenure has been two years, and recent turnover has been unusually high.  

Or, is it the realization that we are truly living in the data, analytics, and AI moment? Enthusiasm is high, and the stakes are great.

Whatever the reasons, the 17th gathering of the CDOIQ Symposium (long known as MIT CDOIQ) held last week in Boston was by general consensus the most energized, exciting, well attended, and influential CDOIQ event in the program's long and illustrious history. 

The data tells the story. The CDOIQ team under the direction of CDOIQ Founder and Executive Director Richard Wang report these stats:

• 2,700 attendees representing 77 countries

• 752 in-person attendees

• 1,459 companies and organizations represented

• Nearly half of attendees were CDAOs or their companies’ data leaders -- 1,285 CDAOs or companies’ data leaders (218 with the CDAO title)

• 37% in management/leadership roles; 31% in IT roles

• 129 sessions over 3 days.

Click on the picture to enlarge.

The energy was palpable throughout. The presentation takeaways were countless.

Following the session “The Data Leadership Imperative: How Leading CDAOs Overcome Cultural Obstacles to Deliver Business Value from Data Investments,” panelist Raj Nimmagadda, Sanofi Chief Data Officer R&D, noted what makes CDOs successful:

• The CDO is a high attrition role ... the successful ones focus on delivering rapid business value, building the right alignment in the organization, and upskilling their teams.

• The CDO is a coalition-builder, with high EQ and self-awareness.

• Successful CDOs align their strategy to the company strategy vs. building their own from scratch.

• Speed of delivery is critical – CDOs “think big, start small, scale fast.”

In his session, “Chief Data Officers and the Quest for Visible Value,” Babson College Professor Tom Davenport identified eight major success factors to drive the most value out of data transformation:

1. Foster Data Enablement (Governance)

2. Build an effective self-service data infrastructure

3. Embrace Data Products & Data Product Owner

4. Form a Supply & Demand dependency for Analytics

5. Focus on a few, but impactful use cases

6. Show visible demonstration results

7. Build relationships and connect with business peers

8. Create a Data-Driven Culture at all levels.

As a CDOIQ participant, Mizuho Americas Managing Director and CDO JC Lionti summarized his key takeaways:

1. Value, value and value again. Link everything to business strategic outcomes. If you can’t … don’t do it. Monetization and ROI must be key elements of your strategy.

2. AI is inevitable but not for anything, not by anyone and not at any cost. Since everyone agrees that you need solid data quality management to really enable your AI aspirations, why don’t we start by using AI to establish a scalable, robust and sustainable data quality management practice?

3. For those who still had doubts, data without good metadata is useless. And refer to point #2 (using AI and models) to enable DQ and observability at scale with it.

For those unable to attend, or seeking to deepen their learning and engagement with the global CDAO community, CDOIQ has extended their programs globally with upcoming events in Switzerland (September 2023), Finland (February 2024), Brazil (March 2024), Taiwan (May 2024), Singapore (May 2024), and South Africa (June 2024).

For those hungering for the next CDO events in North America, CDO Magazine is hosting its hallmark CDO Magazine Summit on September 12 in Cincinnati – one of the largest gatherings of CDOs and senior data, analytics and AI leaders in North America, and its inaugural CDO Magazine Toronto Summit on October 30 in Toronto. The engagement and learning continues.

About the Author

Randy Bean has been an advisor to Fortune 1000 organizations on data leadership for more than three decades. He is the author of the bestselling Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, and a current contributor to Forbes, Harvard Business Review, and MIT Sloan Management Review. Bean serves as Innovation Fellow, Data Strategy for Paris-based consultancy Wavestone.