Thirty years ago, a widely repeated joke was that CIO — the abbreviation for Chief Information Officer — really meant “career is over.” But as job tenures lengthened and the role became more institutionalized, the joke lost its relevance. Now, however, the most unstable C-suite job may be the Chief Data Officer, or CDO. Tenures are short, turnover is high, and as in the early days of the CIO role, many companies don’t seem to know exactly what they want from its incumbents.

But the CDO job doesn’t have to be so unstable. We believe there are ways that its value can be made more apparent, and for benefits to be delivered quickly enough to prolong job tenures. A clearer definition of the role and a focus on business rather than technology can also help. Conversations with the relatively few long-tenured CDOs have provided valuable insights for newer incumbents.

A Growing but Tenuous Role

The growth of the CDO role in large firms has surged in recent years. In the 2021 NewVantage Partners survey of large, data-intensive firms, 65% said they had a chief data officer in place. That’s rapid growth from 2002, when the role was first established by Capital One, and much higher than the 12% of firms with a CDO in the NewVantage 2012 survey. Financial services firms took the lead in naming CDOs, but now organizations in other industries with substantial data, including retail, healthcare, and even government, have appointed them.

In general, this trend reflects a recognition that data is an important business asset that is worthy of management by a senior executive. It’s also an acknowledgement that data and technology — the latter usually managed by a CIO or Chief Technology Officer — are not the same and need different management approaches. But that’s only part of the story.

Both the data and our experience suggest that the CDO role is a tenuous one. The average tenure, according to a Gartner survey and our own analysis, is between two and two-and-a-half years. Few CDOs have been in the role for more than three years. While most CDOs are championed upon their arrival, the honeymoon often ends sharply at about the 18-month period, when they are held accountable for achieving major transformational change — a quick timeline, given that data transformation is typically a multi-year process at a minimum for large, legacy organizations.

Even in financial services, where the role is more common, there is high turnover in the CDO job. Over the past two years, for example, there have been CDO departures (and some new hires) at JPMorgan Chase, Wells Fargo, Goldman SachsAmerican ExpressAIG, Travelers, Nationwide, Charles Schwab, USAA, TD Bank, Bank of Montreal,  MetLife, BNY Mellon, Freddie Mac, Prudential, TIAA, and Truist. Because they are in high demand, even CDOs who’ve left a company can usually get another job quickly. But most will encounter the same mix of high expectations and low ability to deliver value quickly at their next positions.

On top of all that, the CDO job is being pruned back as other new roles are created. In most organizations, the CDO job originally included data security. Now, however, Chief Information Security Officers attend to that issue in many firms. CDOs once owned data privacy, but some Chief Privacy Officers have taken it over. Some CDOs also owned the function of making sense of data with analytics and AI, but Chief Analytics Officer is now also a well-established role — though some firms have wisely, as we will argue, combined it with the CDO job as Chief Data and Analytics Officer (CDAO).

One might imagine that these are just teething pains for CDOs, and that with greater familiarity the role will stabilize. However, we’d argue that there are some inherent problems in how many organizations and incumbent CDOs have defined and focused the responsibilities of the job.

What’s the Problem?

Why is the CDO job so problematic? There are many reasons, unfortunately, but the most important one might be that the job is often poorly defined. Many organizations expect too much of their CDOs and have unclear priorities for them. They can’t create the ideal data environment within their companies, because legacy companies have legacy systems and data environments, and large-scale change in them is very expensive. Few companies have the appetite to throw them away and start from scratch. And this is all at a time when the volume of data increases enormously each year, and new technologies for managing it appear almost daily.

CDOs themselves may also find it difficult to sell their achievements to business audiences. Even when there are improvements in data, they are often relatively invisible to internal users, and very difficult to measure in business terms. And while CDOs may have data expertise, they typically lack C-suite experience and organizational leadership skills at the senior executive level. Their C-suite compensation levels plus their lack of C-suite history and lack of well-developed C-suite political savvy often makes them targets from day one.

In addition to improving the data environment, many organizations today are interested in changing the cultures of their firms in a more data-driven direction. Some CDOs we know, like Vipin Gopal at Eli Lilly and Mano Manoochar at Travelers, are leading cultural change initiatives for their firms. But others, with largely technical backgrounds, may find it challenging to undertake cultural change. One CDO told us, “I feel I am failing in my job because I am expected to carry out cultural change as well as implement a series of important technical changes. I am not experienced in change management and find the cultural change very difficult to achieve.” In any case, our surveys have shown little to no improvement over the past decade in the percentage of companies whose data executives say they are data-driven. Perhaps looking at CDOs and their companies that are data-driven can clarify how to make the role and the goal more feasible.

Learning from a Long-Tenured CDO

The next 5-10 years should see greater C-suite acceptance of the CDO role, and large companies should expect the role to continue to evolve in terms of expected skill sets (more business knowledge and expertise) and organizational mandate. However, CDOs wanting to survive in the shorter run might consider some of the advice below from Guy Peri, Chief Data and Analytics Officer at Procter & Gamble. He’s been in that job for over six years, was head of analytics for several more before that, and has been at P&G for almost 25 years. We would argue that one way to preserve your job as CDO is to have it include analytics and AI (as Peri’s does), since it is much easier to demonstrate value in those areas than in data management.

When we asked Peri how CDOs and CDAOs can improve the appreciation for what they do, he provided several ideas:

  • Start with a clear connection to business strategy with tangible examples of how data analytics can drive business outcomes (topline, bottom line, cash, stewardship).
  • Lead with 1-2 forward thinking business partners to demonstrate what is possible. Those partners become the change agents across the organization.

Peri argues, and we agree, that data strategies must be tied to — and advance — business unit strategies and goals. Once the goals are agreed upon, the CDO can help to build data assets, management approaches for them, and management skills to ensure that the unit can achieve the goals. An outcome of that process is a data platform to ingest, transform, and harmonize data to serve business unit prioritized use cases, and a democratized data environment using data services and business intelligence toolsets. P&G had such a platform and toolsets as early as 2013, as described in a Harvard Business School case study.

On the analytics side, Peri said that after building pilot projects, CDAOs should establish scalable and sustainable data /analytics products to accelerate time to value for business units. In our view, such products are key to showing value from data assets and analytical capabilities. In order to build these products, Peri has also attempted to attract and retain the best talents across data science, AI engineering, and data management. He tries to ensure they are working on the biggest challenges, have access to the latest tools and technologies to exercise their craft, and that they feel valued and part of a larger community of data/analytic professionals.

We concur that these are good strategies for success as a CD(A)O. Selecting a few high-value use cases for analytics and AI, and partnering with business leaders to understand their data and analytics needs and select and achieve initiatives, is particularly critical. Long tenures in the job can only be achieved by balancing quick wins with and for business partners, while undertaking longer-term data and analytics mandates and setting realistic expectations for how quickly they can be achieved.

Business knowledge, leadership and influence, communication, and organization change management skills are table stakes for todays’ CD(A)O. Without these skills the CDO role gets relegated to “back office” activities, much like traditional CIOs who focus solely on data center, infrastructure, and enterprise application deployments. We believe that future CIO, Chief Digital Officers, and even CEOs will be sourced from business savvy CDAOs. When executives ask Peri to describe his role he simply responds, “I’m a business leader who brings deep digital, data, and analytics expertise to help transform and grow our business.” When the data management and architecture component is primary and the business objectives secondary, that’s when CDOs struggle.

*This article was originally published in the Harvard Business Review on August 18, 2021