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Survey details data officers’ priorities, challenges for 2023

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What’s on the minds of chief data officers as they head into 2023? The need to balance data safety with new data initiatives, deliver business value, and change company culture around data.

These are a few of the findings from a 2022 survey of more than 350 data professionals who attended the MIT Chief Data Officer and Information Quality Symposium. The survey included more than 260 respondents in a chief data officer type of role, and 25 CDOs were interviewed in depth.

The survey was sponsored by Amazon Web Services, and the research summary was written by Thomas H. Davenport, a Babson University professor and fellow at the MIT Initiative on the Digital Economy.

Here are some key insights from the survey.

1. Data governance heads the list of CDO responsibilities.

Chief data officers have a large set of responsibilities, Davenport writes. When survey respondents were asked to specify their responsibilities as a chief data officer, their answers were as follows:

  • Establishing clear and effective data governance (51%)
  • Improving data quality (48%)
  • Building and maintaining advanced analytics capabilities (42%)
  • Building and maintaining business intelligence capabilities (36%)
  • Data monetization capabilities (21%)
  • Data, analytics, and AI ethics (21%)

Data governance also ranked highest when chief data officers were asked to rank their top three priorities, with 45% citing clear and effective data governance as a top concern.

“In our view, data governance initiatives require a more strategic focus across the organization, as governance is a shared responsibility and a difficult way to add value as a CDO,” Davenport writes, adding that governance involves changing the behavior of data users and getting business functions and units to take responsibility for data management.

2. Data-driven culture is a goal — and a challenge.

70%

Nearly 70% of survey respondents said they devote 20% or more of their attention to data-driven culture initiatives.

Nearly 70% of survey respondents said they devote 20% or more of their attention to data-driven culture initiatives. This was followed by data governance initiatives (66%); enabling new business initiatives based on data, analytics, and AI (64%); and producing insights based on analytics or artificial intelligence for the organization (48%).  

And when data professionals were asked to name their three biggest challenges, issues related to organizational culture topped the list. More than 62% cited difficulty in changing organizational behaviors or attitudes, followed by the absence of a data-driven culture or data-driven decision-making (55%). About 52% of CDOs said they have insufficient resources to accomplish goals, and about 47% said a lack of data literacy or understanding is a challenge at their organization.

3. CDOs must tackle both data defense and data offense.

Originally, the CDO position was focused on “data defense,” Davenport writes. This means focusing on cybersecurity and taking protective measures such as preventing major problems with data, avoiding data breaches and hacks, and ensuring regulatory compliance.

Although data defense is still a critical part of the job, data offense activities are growing in importance. Those include increasing revenues and profits through enhanced operations; improving customer relationships and marketing; and enabling new products and services, processes, business models, and strategies.

Data offense activities give CDOs the ability to quickly demonstrate value — something that isn’t always true for defensive data maneuvers, Davenport notes.

4. Success means creating value from data.

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Creating value is an imperative for most CDOs, but there are different ways to accomplish that. When asked to select three initiatives they are pursuing to create value for their organizations, about 44% said establishing clear data governance responsibilities across the organization, followed by adopting a data product management orientation with product managers (38%). Data product managers “help to ensure that all aspects of an analytics or AI initiative, from conception to deployment and ongoing maintenance, are effectively managed,” Davenport writes.

Other ways of creating value include focusing on a small set of analytics and AI projects (36%) and improving data infrastructure with each analytics or AI case (34%).

5. Remember the 10 keys to succeeding as CDO.

Davenport ended with 10 keys to success gleaned from the survey.

  1. Add analytics and AI to your portfolio of responsibilities.
  2. Adopt a “data product” and “analytics/AI” product orientation.
  3. Show success early by building and successfully deploying a few high-value use cases.
  4. Don’t boil the ocean: Modernize the data environment to support key use cases, including building analytics and AI solutions.
  5. Drive more value from data governance initiatives by focusing on easing data consumption and access rather than maintaining walled gardens.
  6. Build allies within function and line-of-business owners in the organization.
  7. Develop more extensive and varied initiatives to move toward a data-driven culture.
  8. Focus on creating tangible business value for your organization at all times.
  9. Measure the value and impact of data initiatives and communicate them widely.
  10. Over time, focus on building reusable data sets, data markets, analytics/AI models, and feature stores.

Read next: Data literacy for leaders

For more info Sara Brown Senior News Editor and Writer