What is a chief data officer (CDO)?

Contributors: Gregg Lindemulder, Matthew Kosinski

When it was first formally established at the turn of the 21st century, the CDO role focused on data governance and compliance with emerging regulatory mandates such as the Sarbanes-Oxley Act.

Today, the CDO role is more strategic, seeking to use data-driven insights to fuel business outcomes.

CDOs work directly with C-suite leaders to drive digital transformation and launch data-driven initiatives that improve profitability. According to the IBM Chief Data Officer Study, most top-performing chief data officers report directly to the CEO.

In some organizations, a CDO might report to the chief operating officer (COO), chief financial officer (CFO), chief information officer (CIO) or another senior-level executive.

CDOs are important because they help organizations protect, share and optimize their data sets to improve decision-making.

The IBM Data Differentiator guide reports that 82% of enterprises are inhibited by data silos, and as much as 68% of organizational data never gets analyzed. CDOs can establish strategies, policies and capabilities to help organizations overcome these challenges.

For instance, to help build a data-driven culture across an organization, CDOs often begin by promoting data literacy. This effort involves educating stakeholders on the importance of data analytics and data-driven decisions.

CDOs can then implement policies for analyzing, sharing and acting on data-driven insights to help businesses:

• Improve the customer experience
• Increase productivity
• Reduce operational costs
• Use business intelligence to outperform competitors
• Take advantage of new opportunities
• Develop new products and services
• Mitigate risks

The skill set of a CDO is also important for organizations that use artificial intelligence (AI). They can help source and prepare the massive amounts of trusted, quality data that is required to train machine learning (ML) and large language models (LLMs).

CDOs also provide value by implementing controls that protect an organization’s data from cybersecurity threats and help ensure compliance with data privacy regulations such as the Payment Card Industry Data Security Standard (PCI DSS) and General Data Protection Regulation (GDPR).

The responsibilities of a chief data officer span the disciplines of both data management and business growth, including:

• Data governance
• Data security
• Data lifecycle management
• Data analytics
• Data strategy

Data governance focuses on the quality, security and availability of an organization’s data. The goal of data governance is to maintain safe, high-quality data that is easily accessible for data discovery and business intelligence initiatives.

A chief data officer is responsible for establishing, monitoring and updating an organization’s data governance framework. A CDO implements governance policies and processes that improve data quality, reduce data silos, help ensure compliance and security and distribute data access appropriately.

CDOs often collaborate with IT and legal executives to help ensure that data governance standards comply with the latest government regulations for protecting sensitive data. They also work with business unit heads to help ensure that data governance policies are applied consistently across the organization.

Protecting digital information from unauthorized access, corruption or theft throughout its lifecycle is a priority for CDOs. According to the IBM CDO Study, 52% of CDOs say that data security is their most critical responsibility.

CDOs can implement various measures to protect data such as encryption, data backups, firewalls, authentication and authorization, identity and access management (IAM), antivirus and antimalware tools, data loss prevention (DLP) tools and intrusion detection systems (IDS).

CDOs often work closely with chief information security officers (CISOs) to assess cybersecurity threats, and they help ensure that data security policies are enforced across the organization.

Data lifecycle management (DLM) is an approach to managing data through every stage of its lifecycle, from data collection, processing, storage, sharing and usage to archival and deletion.

CDOs are responsible for creating targeted policies that maximize the value and use of data at each stage of its lifecycle. For example, before data is shared and used, it must be properly prepared and validated to help ensure quality and accuracy.

Policies also determine if and when data are deleted, according to legal requirements and the needs of the business.

These policies become increasingly important as the volume of data that is incorporated into business workstreams grows. CDOs often seek to reduce costs, improve data accessibility and optimize data storage as part of data lifecycle management.

Data analytics use data science to extract actionable insights from an organization’s data. CDOs are responsible for helping data scientists uncover these insights, and for sharing the insights with business users so they can make data-driven decisions.

CDOs provide data scientists with the tools and guidance that they need to understand datasets, develop algorithms and build models that generate insights. CDOs then work with business teams to integrate the data insights into their workflows, planning and decision-making processes.

Ultimately, a CDO’s goal is to align an organization’s data analytics capabilities with its business objectives. When that is successful, data analytics can provide game-changing benefits across sales, marketing, product development, operations, customer experience and other business functions.

In some organizations, a chief analytics officer (CAO) might oversee data analytics instead of a CDO. There are also instances where one person holds both titles and is known as a chief data and analytics officer (CDAO).

While many CDOs have a master’s degree in data science or information technology, they must also possess a sophisticated knowledge of business. CDOs are responsible for creating and guiding an organization’s data strategy, which is a roadmap for using data assets to create business value.

A CDO’s data strategy outlines how data policies drive business growth. The plan often includes the promotion of data literacy, so business teams know how to use data to make better decisions. The plan might also communicate how data is used as a strategic asset to improve products and services, identify market opportunities and outperform competitors.

To help evaluate the performance of their data initiatives, CDOs often include key performance indicators (KPIs) as part of their data strategies. Some common KPIs for CDOs are revenue growth, customer retention, customer satisfaction, website traffic and conversion rates.

The IBM CDO Study identifies four things that set the data strategies of top-performing CDOs apart from others:

1. They define a clear line of sight from data to business value: They maintain focus on both the data function and the return on investment it generates.
   
   
2. Their data investments accelerate business growth: They tie data initiatives to broader digital investments for quicker business benefits.
   
   
3. Data is a central element of their business model innovation: They emphasize innovation as much as they do data protection and compliance.
   
   
4. They have extremely engaged ecosystem partners: They get buy-in and collaborate with transparency and visibility.

The difference between a chief information officer (CIO) and a CDO is that a CIO is responsible for the technology infrastructure that processes data, and a CDO is responsible for how that data will be used to create business value.

CIOs and CDOs work closely together to help ensure software, hardware and data strategies work together to achieve business objectives.

As advanced technologies such as generative AI and machine learning become the norm, CDOs may find themselves playing a new role in the organizations they serve.

Training the large language models (LLMs) that power gen AI requires massive volumes of high-quality, trusted data. As AI-driven insights transform the workplace, more data than ever before will need to be collected and properly managed.

CDOs will need to balance the evolving demands of data-driven AI with traditional safeguards such as data privacy, data protection and regulatory compliance. In a future where data and AI become the primary drivers of automation and business, some believe the role of CDO will eventually become that of a chief data, analytics and AI officer (CDAIO).