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The evolution of the chief data officer role

Chief data officers are taking on additional responsibilities beyond data management as they strive to transform organizations' data culture and focus on value creation.

While only joining the organizational hierarchy two decades ago, the CDO role is already evolving from a CIO Mini-Me to a full-blown equal on the CEO executive leadership team.

It's time for the next evolution of the CDO: leading organizational efforts to utilize data and analytics to power the business. This means championing the application of data and analytics to help the organization optimize key business processes, mitigate compliance and regulatory risks, generate net new revenue streams, derive value from data and create distinct customer and stakeholder experiences.

The next generation of CDOs has to adapt due to the following five ways the role has changed since its inception, as explored in the 2022 IDC study "Driving Business Value from Data in the Face of Fragmentation and Complexity.''

Nurturing the organization's data and analytics maturity

The next-generation CDO role is evolving from a reactive data management role to a proactive, value creation one.

"Data leadership levels of maturity" provide a roadmap for advancing the organization's data and analytics capabilities to power the business, states the IDC report.

The following four levels of data and analytics maturity are identified in the report:

  • Reactive organizations are overwhelmed by data fragmentation and operational complexity.
  • Opportunistic organizations are more proactive, but are not repeating success in complex operational environments.
  • Repeatable organizations leverage data successfully, but data fragmentation inhibits progress and scale.
  • Optimized organizations are the most mature and successful at managing data fragmentation and operational complexity.

One area where optimized organizations are excelling is in operational AI. Optimized organizations are five times more likely to use AI to increase operational innovation and generate higher levels of business value. Optimized organizations also take advantage of advanced analytics to create semi-autonomous capabilities that continuously learn, adapt and scale with minimal human intervention.

Moving beyond digital transformation to cultural transformation

CDOs must think beyond just digital transformation. They must become the catalyst for cultural transformation because operationalizing AI is not a technology issue, it's a cultural one.

Data and analytics cultural transformation occurs when organizations create a data and AI-literate culture that understands where and how to use data and analytics to drive more accurate, more relevant decisions. The culture should also empower employees to identify new areas of the business where data and analytics can drive new sources of customer and operational value.

Evolving from optimization to reinvention

AI and machine learning excel at optimizing business processes based upon the customer, product, service and operational insights -- predictive behavioral and performance propensities that already exist in the data.

CDOs must become the catalyst for cultural transformation because operationalizing AI is not a technology issue, it's a cultural issue.

However, the CDO's charter cannot stop at just "optimizing today's cow path" with AI and ML. CDOs must drive organizational AI literacy to fuel strategies about where and how data and AI can transform the customer experience and operational excellence.

CDOs should seek to empower empathy, experimentation, methodical failure and continuous learning to reinvent key business and operational processes. They can cultivate an environment where everyone thinks like a data scientist by democratizing data and AI ideation, instilling a culture of experimentation and learning through analyzing purposeful failure.

Shifting to the hub-and-spoke data model

The data and analytics industry is struggling between centralized versus decentralized data and analytics structures. Researchers from IDC advocate for centralizing everything, with market concepts like the data mesh, data virtualization and federated learning pushing enterprises in the decentralized direction.

The answer is the hub-and-spoke model, which achieves the following:

  • centralize (hub) responsibilities such as data governance, master data management and the engineering of reusable data and analytic assets by instilling organization-wide data and analytics objectives and standards; and
  • decentralize (business unit spokes) responsibilities such as data management, data quality and data stewardship.

Data products represent one of the best of the hub-and-spoke organizational structures. Data products are a category of domain-infused, AI-powered apps designed to help non-technical users manage data-intensive operations to achieve specific business outcomes.

Data apps use AI to mine a diverse set of customer and operational data, identify patterns, trends and relationships buried in the data, and make timely predictions and recommendations. Data apps track the effectiveness of those recommendations to continuously refine AI model effectiveness.

Becoming value-centric, not data-centric

Organizations are failing to become data driven, according to a 2022 NewVantage Partners big data and AI leadership survey. While many business leaders believe that data is the catalyst to drive economic growth in the 21st century, companies' ability to become data driven is regressing.

CDOs are leading the charge in becoming value-driven through data. CDOs should champion a value engineering framework that drives cross-organizational collaboration to identify and validate how the organization creates value, and the KPIs and metrics against which the organization measures that value creation effectiveness.

The role of the CDO is evolving. To be successful, the modern CDO not only needs to master data and data management, but also champion value creation by empowering everyone in the organization with data ideation. This includes allowing them to give input on how data and analytics can drive new sources of customer, product, service and operational value.

As the evolution of the CDO role continues, the successful CDOs may realize it's more about cultural transformation and empowerment than it is about digital transformation and data management.

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