What is a chief data and analytics officer, and why do you need one?

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Not too long ago, data and analytics were considered just ordinary parts of larger information-related roles. That’s all changed, though: data and analytics are now table stakes for ensuring competitiveness and innovation. Accordingly, the data and analytics role has been elevated to the C-suite, giving it the prominence it deserves to ensure the success of the executive team and the organization as a whole.

In this article, I describe the role of the chief data and analytics officer (CDAO) in today’s business world. I define the role, contrast it to similar ones in the organization, and explain its context in the C-suite. I then discuss the benefits of having a CDAO in the organization, the roles and responsibilities of a CDAO, and best practices for establishing and staffing the position.

What is a chief data and analytics officer?

The name itself tells much of the story: the CDAO is a senior executive role responsible for leading all of the organization’s data and analytics efforts. This includes establishing and leading the vision for how the company gathers and stores data and transforms it into actionable intelligence. 

The CDAO plays a pivotal role in creating and evolving the corporate “data culture” and ensuring that everyone in the organization is focused on using data and analytics to foster innovation and drive profit. The CDAO is also heavily involved in technology efforts, working with the CTO, CIO, and other executives to implement tools and technologies such as AI, machine learning, cloud computing, business intelligence, and much more.

While the CDAO role is still relatively new, it is being rapidly adopted by information-centric firms. Depending on the organization, the CDAO may report to the CEO, COO, chief strategy officer, executive VP, or another senior-level executive.

CDO vs. CAO vs. CDAO

The “alphabet soup” of the modern C-suite can be confusing, and that’s certainly the case when it comes to the data and analytics side. Let’s see if we can make sense of this jumble of acronyms.

The simplest place to start is by comparing the chief data officer (CDO) and chief analytics officer (CAO) roles. While data and analytics are closely related, these roles have important differences:

CDO: The chief data officer is primarily responsible for all the roles associated with managing the organization’s data. This includes establishing the organization’s overall data strategy, overseeing data-gathering activities, defining data quality standards, and establishing policies and procedures for the secure transmission and storage of data. 

CAO: While the CDO deals with data in its various forms, the chief analytics officer is responsible for leading organizational efforts to transform that data into information and intelligence to enable sound decision-making. The CAO sets up and manages data science and data analysis operations, working with other departments within the organization to discover and define opportunities for enhancing the business through data-driven analytics.

So, how does a chief data and analytics officer differ from a chief data officer or a chief analytics officer? Unfortunately, there’s no single clear answer to this. These terms may even be used interchangeably, which can be confusing; for example, the well-known research and consulting firm Gartner Group says that the CAO, CDO, and CDAO roles are “equivalent.” This is understandable, but as mentioned above, there are differences between the CDO and CAO functions. Accordingly, a more useful definition basically says that the CDAO role encompasses both the CDO and CAO functions, and that’s the one I use in this article. 

The idea of combining the two roles under the CDAO umbrella is to make clear that the CDO and CAO functions are different but work hand in hand. Having a single CDAO oversee both functions can help optimize the resources in each department, allowing the firm to exploit the obvious synergies between the data management and analytics functions. Merging the CDO and CAO roles can also be useful in other areas, such as enhancing regulatory compliance. In larger data-driven organizations, it’s also possible that there might be a separate CDO and CAO reporting to a CDAO.

Getting back to the “alphabet soup” issue mentioned earlier, be aware of the following:

  • CDO can also stand for “chief digital officer.” 
  • CAO may also mean “chief administrative officer.”
  • CDAO can also stand for “chief digital and artificial intelligence officer”; this is especially common in defense and military circles. 

While some of these functions are clearly related to the ones we’re discussing in this article, they are distinct roles.

Key business benefits of the CDAO role

Hiring a CDAO puts a champion for data and analytics at the highest levels of the corporate structure. Data by itself is useful, but to unlock its potential it must be applied to produce value. One of the most essential advantages of formalizing the data and analytics role is that it puts corporate emphasis on the transformation of data into information to drive action. 

Here are some other important potential benefits of the CDAO role:

  • Sending a clear signal to employees, customers, and suppliers that the company understands the importance of data and analytics
  • Helping to marshal funding for data-related projects and initiatives
  • Enhancing the quality of data
  • Driving innovation through the application of data-based insight
  • Improving the data literacy of the organization
  • Supporting the monetization of insights derived from data
  • Ensuring the efficient flow of data between organizations
  • Breaking down silos between computer systems and departments
  • Enhancing security by increasing understanding of the role of data and the importance of its safety

Key specific responsibilities

The duties of a chief data and analytics officer vary depending on how each organization defines and implements the role. However, while the details may differ, these individuals are all C-suite executives, which means a core part of their role is leading, not just managing. A CDAO must focus on establishing a vision related to data and analytics, inspiring the organization to take steps to achieve that vision, and revising it as the business changes.

Specific CDAO responsibilities generally span the range of tasks that a CDO and CAO must do, and may include any or all of the following:

  • Creating and implementing a general data strategy for the organization
  • Setting up data flows into, within, and out of the business
  • Managing the data lifecycle
  • Defining policies for organizing data
  • Analyzing data to generate insights
  • Working with other executives to support change management
  • Defining and upholding data quality standards through policies and specific initiatives
  • Creating mechanisms to assure the safety and trustworthiness of data
  • Assessing and improving user access to critical data sets
  • Identifying business opportunities based on the results of data analysis
  • Collaborating with other parts of the business to develop data insights
  • Designing, building, and maintaining data repositories
  • Crafting business intelligence systems
  • Documenting procedures to ensure compliance with data privacy regulations
  • Identifying and breaking down data silos
  • Supporting the creation of new products and services
  • Preparing to implement the CDAO role

CDAO success factors

The CDAO role is relatively new, and many companies are eager to jump into creating and staffing it. However, moving too fast can backfire. Without the right plan and infrastructure in place, the organization risks expending a great deal of time and money finding a great candidate, only to have the person quickly move on. 

This phenomenon is so widespread that Harvard Business Review published an article on the topic a couple of years ago; it focuses on CDOs, but the same concerns apply to the CDAO role. The study says that the number-one reason for problems is simply that the role is not properly defined. Organizations also often have unrealistic expectations of the person brought in or are unwilling to make the necessary organizational and cultural changes required for a CDO/CAO/CDAO to succeed and help the business. Other studies indicate that up to half of CDOs believe that the value of the role isn’t yet properly recognized among their C-suite peers.

It's clearly essential to “get your ducks in a row” before hiring. Here are some specific steps the organization can take in advance to ensure that a new CDAO thrives:

  • Define the role clearly, so everyone knows what its responsibilities are
  • Be sure everyone understands how the CDAO fits into the C-suite and its interfaces with other departments and functions
  • Clearly define, write down, and get buy-in on the goals and expectations for the role
  • Ensure that there’s an adequate support structure in place for the data and analytics function
  • Do a survey of the company’s culture. Is everyone ready for data and analytics to play a major role in the company? If not, how can that be addressed?
  • Assess the technological infrastructure. Be sure the technology stack is current enough to support modern data and analytics; if not, be prepared for the CDAO to work with the CIO, CTO, and other leaders to bring it up to speed
  • Set aside adequate funding for the data/analytics function

Staffing the CDAO position

Finding the right candidate for the CDAO is challenging due to the complexity of the role and the many areas of the business it touches. The ideal person for the CDAO position will have experience and aptitude in many areas, including the following:

  • Leadership
  • Organizational technology
  • Interpersonal relations
  • Data management and processing
  • Data science and analysis
  • Change management
  • People management
  • Problem-solving 
  • Interdepartmental collaboration

Here are a few specific tips for hiring a CDAO:

Properly define the scope and position of the role in the organization: I mentioned this before, but it’s important enough to warrant emphasizing.

Hire at the right time: Be sure the preparations discussed previously are all in place before starting to recruit. Beyond that, make sure that hiring into the role occurs when the company is in the right place in terms of its growth cycle.

Look for applicants with a balance of applicable skills: While obviously focused on data/analytics, this is more of a broad role than a narrowly focused one.

Consider applicants from non-technical backgrounds: Because of the many different skills required to be a good CDAO, it’s not always the case that a “techie” will be the right candidate; it’s worth keeping an open mind.

Consider an AI-enabled candidate matching platform like MojoHire. Finding the right person using conventional methods can be like finding a needle in a haystack. Let AI get you to the best candidate faster.

How iTalent can help

iTalent Digital’s Data Transformation and Business Intelligence Practice can support your enterprise CDAO role, from strategy to implementation. 

  • We can help you choose an optimal data analytics strategy to create an explicit link to value creation and business outcomes and guide you on designing, developing, implementing, and improving your existing data analytics landscape.

  • We can help turn that strategy into action by choosing the right D&A leader(s) who best fit(s) your organizational profile. 

  • With our flexible service approach, we can also bring in the right experts to carry out many of the same functions that a typical CDAO would do.

Contact us at itbi@italentdigital.com to explore how we can help you achieve your specific data management and transformation goals.

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