the health strategist
institute for strategic health transformation
& digital technology
Joaquim Cardoso MSc.
Chief Research and Strategy Officer (CRSO),
Chief Editor and Senior Advisor
October 25, 2023
One page summary
What is the message?
Data is the lifeblood of modern organizations, and the role of Chief Data Officers (CDOs) is evolving rapidly to harness the potential of generative AI.
This report delves into the shifting landscape for CDOs, highlighting the importance of creating visible value, exploring the potential of generative AI, overcoming roadblocks, and emphasizing data strategy, culture, and governance as pivotal elements in the journey toward data-driven success.
What are the key points?
Creating Visible Value:
CDOs are primarily focused on achieving business objectives (44%) rather than technical accomplishments. Analytics and AI are pivotal in delivering this value, and they adopt approaches like literacy training, use case-driven data management, and data product management.
Generative AI Enthusiasm:
CDOs are excited about the potential of generative AI, with 80% believing it will transform their organizations. However, they are cautious and not ready to abandon existing data-related initiatives for generative AI.
Roadblocks to Generative AI:
Data quality (46%) and identifying the right use cases are the two main challenges for realizing the potential of generative AI. CDOs also emphasize the importance of responsible AI, data security, and privacy.
Crucial Data Strategy:
While 57% of CDOs haven’t made changes to their data strategies to support generative AI, 93% acknowledge the significance of data strategy in unlocking generative AI’s value.
Cultural Transformation:
Culture is pivotal to effective data utilization, and CDOs are focusing on initiatives like data literacy programs and change management to foster a data-driven culture.
Data Governance Strategies:
CDOs are increasingly involved in data governance activities (63%), focusing on enabling the right use of data and establishing common data platforms.
Team-Oriented Transformation:
Successful CDOs see their role as making internal clients successful in achieving their objectives, emphasizing the importance of building coalitions.
Examples
- CDOs prioritize value creation by incorporating analytics and AI, using approaches like literacy training and data product management.
- Generative AI holds immense potential, but CDOs are cautious about transitioning completely from existing data initiatives.
- Data quality and identifying suitable use cases are major roadblocks in unleashing the potential of generative AI.
- CDOs stress the need for a robust data strategy to support generative AI success.
- Cultural transformation is a priority with initiatives like data literacy programs and change management.
- Data governance activities have increased, with an emphasis on enabling the right use of data.
- Successful CDOs focus on building coalitions to help their organizations succeed.
Statistics
- 44% of CDOs define success as achieving business objectives, not technical accomplishments.
- 80% of CDOs believe generative AI will eventually transform their organizations.
- 46% of CDOs identify data quality and finding the right use cases as the biggest roadblocks to generative AI.
- 57% of CDOs have not made changes to their data strategies to support generative AI.
- 63% of CDOs are spending a substantial amount of time on data governance activities.
Conclusion
As organizations strive for data-driven success, CDOs play a pivotal role in navigating the data and generative AI frontiers.
A well-crafted data strategy, experimentation, and a gradual cultural shift are essential elements for success in this rapidly evolving role.
This report provides ten key insights to help CDOs succeed in this dynamic landscape.
DEEP DIVE [excerpt of the report]
CDO Agenda 2024: Navigating Data and Generative AI Frontiers [excerpt]
AWS FOR DATA
Thomas H. Davenport, Randy Bean, and Richard Wang
Executive summary
Collecting data, transforming it, and putting it to use is essential to remain competitive today. Virtually every organization is actively pursuing the goal of becoming more data-centric, enabling them to swiftly uncover and respond to valuable insights. With generative AI, the power and potential of organizational data is bigger than ever before.
Organizations often appoint chief data officers (CDOs) to lead them toward data-driven success. In the summer of 2023, we conducted a global study to understand how this role is evolving, what the key priorities and roadblocks are for CDOs, and how they tackle generative AI.
This is the second annual report on CDOs, chief analytics officers, chief AI officers, or some combination of these titles or equivalent (hereafter described as CDOs).
This is one of the largest CDO studies in the market, with a survey of 334 respondents with CDO or equivalent titles and level positions. It includes qualitative interviews with 12 leading CDOs.
One of the key findings from our study is that CDOs need to show a visible value for their efforts—in part by emphasizing analytics and AI. As a relatively new C-level role, CDOs have more topics than ever to focus on, which makes it difficult to standardize the job description.
We found that CDOs also need to be flexible and agile to change their charter with changing technologies, such as generative AI.
CDOs are excited about the possibilities of generative AI, even though their companies are mostly experimenting with it. They feel that data and data strategy will be critical to success with generative AI, and they are in the early stages of that transformation.
Other topics that are a top priority for CDOs include data governance and cultural change toward a data-driven organization.
The savviest CDOs are prioritizing change management, communication, and evangelism, and they consider making other executives successful as critical to their success in the role.
This research report comprises key insights from our study and conversations with esteemed CDOs on how they’re setting themselves up for success in the new generative AI era.
Key learnings
1.Creating visible value is still a key focus for many CDOs
Forty-four percent of CDOs still define success as achieving business objectives, as opposed to technical accomplishments (only 3 percent), and mark analytics and AI as keys to providing value. Other approaches include literacy training, councils across the organization, approaching data management use case by use case, and the data product management approach.
2.CDOs are enthusiastic about the potential of generative AI
Generative AI dominated the discussion. The majority of CDOs (80 percent) agreed that it would eventually transform their organization’s business environment, but they don’t want to abandon existing data-related initiatives in favor of generative AI yet.
3.The biggest roadblocks to generative AI—data quality and finding the right use cases
A large portion of CDOs (46 percent) rank data quality and finding the right use cases as the two biggest challenges for realizing the potential of generative AI, followed by (creating) guardrails around responsible AI, security, and privacy of data.
Customer operation, such as customer support and chatbots, was the top generative AI use case (44 percent), followed by overall personal productivity (40 percent), and software code generation (36 percent).
4.Data strategy is crucial to generative AI success
More than half (57 percent) had not yet made necessary changes to their company’s data strategies to support generative AI, but a majority (93 percent) of CDOs agreed that data strategy is crucial for getting value out of generative AI.
A quarter of CDOs are pursuing data integration and cleaning, while nearly one-fifth are surveying data to understand what might support generative AI use cases.
5.Culture comes first, but challenges persist
Culture is increasingly critical to effective data use, but CDOs are taking a “slow and steady” approach to changing it.
Culture initiatives are a major focus for over half of the CDOs surveyed, including data literacy programs and change management.
6.CDOs embrace new data governance strategies
Similar to last year, CDOs spend a substantial part of their time focusing on data governance activities (63 percent in 2023 vs. 44 percent in 2022).
The new methods of establishing governance include an “enablement” focus—making it easier to do the right thing with data—and common data platforms.
7.Data-driven transformation is a team sport
Successful CDOs see their role as making their internal clients more successful in achieving their objectives.
They don’t focus so much on their own performance alone but on building coalitions to help their organizations succeed.
In conclusion
The chief data officer role—increasingly combined with analytics and AI—is one of the most rapidly-changing jobs in business. As companies move toward digital transformation and data-driven decisions, it’s also one of the most central roles in that transformation. It is apparent from both the large survey of CDOs and our interviews that adding generative AI to the mix of an organization’s capabilities will be one of the most pressing tasks of the next several years.
A well-crafted data strategy—often listed as CDOs’ primary responsibility—is the foundation of generative AI success. CDOs will need to encourage experimentation, start with the right use cases, and treat organizational data responsibly to showcase visible business value with generative AI.
Ten keys to succeeding as a CDO
- Constantly look for ways to add visible value to your organization.
- Add analytics and AI to the CDO portfolio whenever possible.
- Try to build coalitions and make other people successful in achieving their objectives.
- Encourage experimentation with generative AI, but try also to find strategic use cases for the technology.
- Don’t abandon existing data, analytics, and AI initiatives in favor of generative AI, but add it to the mix.
- Begin transforming and curating data, both structured and unstructured, to make it easier to succeed with generative AI.
- Adopt a common platform for data, analytics, and machine learning features for the organization to employ in its decision-making.
- Employ an “enablement” approach to achieving the data-related behaviors you desire, not a “governance” one.
- Take a use case by use case approach to improving data management.
- Strive to create a data-driven culture, but don’t force changes, and take them slowly.
About the Authors
Tom Davenport is a Distinguished Professor of Information Technology and Management at Babson College, Fellow of the MIT Initiative on the Digital Economy, and Senior Advisor to Deloitte’s AI practice. He’s published 23 books and over 300 articles for Harvard Business Review and many other publications. He has been named among the world’s Top 25 Consultants, the top three business/technology analysts, the 100 most influential people in the IT industry, and the top fifty business school professors in the world. He’s worked with many of the world’s leading companies on data, analytics, and AI strategies.
Richard Wang is the Founder and Executive Director of the Chief Data Officer and Information Quality Symposium and the CDO Certification Program. He has served as the Chief Data Quality Officer and Deputy CDO of the US Army, Pentagon, and the first CDO at the State of Arkansas. Dr. Wang is an internationally renowned pioneer in the field of Information Quality. He is a professor at the University of Arkansas at Little Rock; before that he served as a professor at MIT for almost a decade.
Randy Bean has been an advisor to Fortune 1000 organizations on data leadership for over 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 contributor to Forbes, Harvard Business Review, and MIT Sloan Management Review. Randy was founder and CEO of NewVantage Partners (NVP), a data strategy advisory firm that he ran for 20 years prior to its acquisition by Paris-based global consultancy, Wavestone, in December 2021. He currently serves as Innovation Fellow, Data Strategy at Wavestone.
Originally published at https://d1.awsstatic.com/psc-digital/2023/gc-600/cdo-agenda-2024/cdo-agenda-2024.pdf
