CDO/CDAOs are failing to achieve their objectives

...to make their businesses Data Enabled and AI Powered, and as a result putting their businesses at risk of significant competitive disadvantage!

Recommendations and Call to Action

Strategic Importance of Data, Analytics, and AI (DAI) in Unlocking Competitive Advantage

Academic research demonstrates a strong correlation between investment in DAI capabilities and superior competitive performance.

A recent academic survey (conducted by the author, Aston University and DataLeaders) seeks to highlight the contribution of the DAI Leader (Chief Data Officer) in achieving that superior performance.?

However, instead the survey highlights that despite their potential, DAI Leaders

• are struggling to align their strategies with actual business needs. Only 36% of these leaders believe their businesses use data to drive key decisions, and just 30% think their organisations are data-driven.
• focus on technology rather than on the strategic framework needed to leverage data for competitive advantage. The technology itself is not a source of competitive advantage, as it is widely available and easily replicable.
• need a significant shift in their role and objectives to fully capitalise on the opportunities presented by AI, particularly Generative AI.

Critical Challenges and Strategic Imperatives

For CEOs, operating in a VUCA business environment, and with AI becoming increasingly critical, it is now both urgent and important to leverage DAI capabilities to create a competitive edge and drive new business opportunities.

?To make that happen:

• DAI Leaders need to hand over the ‘Data Tech’ and instead focus on embedding data-driven decision-making deeply within the organizational culture.
• DAI Leaders must effectively align with key stakeholders, such as CFOs and CXOs to demonstrate the value of data initiatives, and CTO/CIOS to ensure Data and AI platforms are delivered!
• CEOs must stop recruiting new ‘Tech’ DAI Leaders and instead focus on those who can truly embed Data and AI into the DNA of the business – Business Transformation Leaders!

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Executive Summary

In a recent global survey of approximately 100 Data, Analytics and AI (DAI) leaders, conducted as part of a DBA Research programme, the community note they are struggling to get the basics right, and in a world where Artificial Intelligence (AI) powered by Data is likely to be the key driver of competitive performance for the next decade, they are failing to move the dial in the business.

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• Strategic Contribution vs. Business Impact: Half of DAI leaders (50%) believe they are actively shaping business strategy. However, only 36% of these leaders think that their business counterparts are using data to drive key decisions, and just 30% believe that their organisations are truly data-driven.
• Data Utilisation in Identifying and Seizing Opportunities: While 49% of DAI leaders report that their businesses use data to identify customer needs, and 62% say data is used to drive new opportunities, a mere 32% of organisations utilise data to sense emerging opportunities. This is very concerning the Volatile, Uncertain, Complex and Ambiguous (VUCA) world we are operating within. Furthermore, only 50% leverage data to seize these opportunities, and just 33% use data to support organisational transformation.
• Core Data Practices: Foundational data practices remain a work in progress, with only 45% of respondents indicating that their organisations have effective data governance in place. Similarly, 46% believe that data is sufficiently democratised across their organisations, enabling broader access and use.

These findings highlight the urgent need for a fundamental transformation in the role and objectives of DAI leaders. Without a strategic shift to more effectively embed data-driven decision-making and AI capabilities within their organisations, businesses risk missing out on the full potential of AI-driven innovation and may struggle to maintain a competitive edge in the rapidly evolving landscape.

Background to the Research

With the advent of AI, and in particular Generative AI opens the door to businesses transforming to be fully data enabled and AI powered, to drive competitive performance and by that standards our survey shows that CDOs have a very long way to go!

To date despite two decades of articles and case studies in business journals such as Forbes, HBR (e.g. Davenport 3, 4) there is no manual for how to deliver Sustained and Sustainable performance using Data, Analytics and AI, or clarity of the role of the leader of the DAI function, the Chief Data Officer (Lee 5).? This is particularly important as we swing into a new wave of Data and AI hype, with Generative AI.?

As part of a multi-year Doctoral Research programme, the author (Eddie Short, who has been a global lead Consulting Partner and Chief Data & Analytics Officer for multiple international companies) has investigated how organisations can deliver sustained and sustainable competitive performance using Data, and Analytics (including AI).?

The leading research work has been completed in Europe by ?Prof Patrick Mikalef (6, 7, 8), and his work has shown strong positive correlations in investment in DAI capabilities and companies that outperform competitors.? The author has built his research on the pre-existing work of Mikalef and others, as well as his 30 years in the industry as a DAI Leader. ?His unique contribution is to build on the concept that DAI can deliver positive improvements in competitive performance and to specifically analyse the contribution of the DAI Leaders in enabling that performance.

?The academics who have done prior research have and focused on two business theories to help how you can deliver sustained competitive performance using DAI.

• ‘Resource Based Theory’ (RBT), which focuses on the capabilities that businesses and organisations use to create sustained competitive advantage.? If a business seeks to be competitively differentiated, it cannot realistically expect to be ‘world-class’ at everything.?RBT helps firms to identify and focus on internal resources that are best aligned with opportunities and threats from the external environment, to identify key combinations of internal capabilities that uniquely differentiate. RBT identifies truly differentiating capabilities if they are Valuable, Rare, Inimitable (difficult to copy) and organisationally embedded (VRIO).? (1, 2) If a resource or capability is valuable, rare, costly to imitate, and the firm is organised to capture its value, it can sustain a competitive advantage.

• ‘Dynamic Capabilities’ refer to a company's ability to continuously renew its competitive advantages in response to rapidly changing business environments.? This is critical in the Volatile, Complex, Uncertain and Ambiguous (VUCA) world we live in.? CEOs are not just facing the challenges of AI, but also squaring the circle between Financial Performance and their own and investor needs to deliver ‘sustainable’ (Net Zero) performance.? (9,10).?
• The Dynamic capabilities framework is built around three key actions: Sense, Seize, and Transform. 'Sense' involves identifying and assessing opportunities and threats in the external environment. 'Seize' is about mobilizing resources to capture value from those opportunities and mitigate threats. 'Transform' requires the firm to continuously renew and reconfigure its assets and organizational structure to maintain alignment with the changing business landscape. This approach empowers organizations to be proactive and adaptive.

Research Findings

The research was conducted by the author with the support of Data Leaders (www.dataleaders.net) a leading global community of DAI leaders.? Survey responses were received in late 2023 and early 2024.

Firstly, whilst many Data Leaders (50%) think they are critical to driving Strategy, but the question remains as to whether they are driving action?

• In terms of competitive performance, 50% of Data Leaders are shaping business strategy, but only 36% think leaders in their business use Data to drive key decisions, and only 30% believe they have a Data Driven Organisation. ?This is concerning given the VRIO points of Resource Theory, and to be truly differentiating a capability needs to Organisationally Embedded.
• 49% say that their company uses data to identify changing Customer Needs and 62% to identify new market Opportunities.

Secondly, some DAI Leaders believe they are delivering value, but the question remains whether they help to drive improved Executive Decisioning and Action:

• 38% think their companies outperform in Profit vs 21% who believe they are underperforming competitors;
• In terms of their investments, 44% believe they deliver Return on Investment vs 14% who believe they don’t;
• The most disturbing result is the largest percentage is those Leaders who have no idea on the contribution they make to company performance.

Thirdly, in the context of Dynamic Capabilities, which are essentially how companies, sense, seize and transform to respond to the VUCA world we are living in, DAI Leaders ?say they and their companies are not doing so well:

• Just over a third (35%) of organisations use Data to sense opportunities, which is quite concerning given the amount of external data available;
• On a more positive note, 52% use Data to seize opportunities, once they have been identified; and
• Only 34% use Data to support transformation.? Only 39% say their organisation can successfully adjust their business processes in response to shifts in our business priorities, and only 29% can successfully reconfigure business processes in order to come up with new productive assets.? This is very concerning – organisations are looking for more predictive and prescriptive insight to help them navigate change – it seems most are not getting that.

The research shows that DAI Leaders lack a framework with which to show how their strategy and plans contribute to the performance of the business; and is seeking to address that with Resource Based Theory and Dynamic Capabilities.?

?In the absence of a strategic framework, most are focused on the delivery of Data, Analytics and AI technology.? The problem is that the Technology in of itself cannot deliver competitive performance.? Why? Technology is very evenly distributed, especially with Cloud (for example most organisations have the same Office 365 applications or Salesforce CRM) and that includes AI (all have easy access to tools such as ChatGPT, Gemini or Claude) ergo the Technology of itself is neither Rare, nor Difficult to Copy and therefore not a source of competitive advantage.

?In terms of the basics CDOs are delivering almost 70% have established Data Governance and over 75% can bring data from multiple sources into a Data Lake and/or Enterprise Data Warehouse for customer and market analysis.? That said the core Data Tactics are still being worked on in many organisations:

• Only 42% think they have Good Data Governance and likewise only 44% have Democratised Data to make it fully available across the organization;
• Alignment with the business is positive with 59% agreeing that, but with the critical stakeholders in Finance and IT the situation is much worse.? Only 45% CDOs think they have strong alignment with their CFO, and only 27% think they have good alignment with IT.? Given the importance of these relationships, in terms of delivering Data capabilities and understanding the value they create, these numbers are very concerning; and
• This concerns us given again VRIO.? CDOs spend too much time on Technology which is neither Rare, nor difficult to copy, and hence not a source of competitive advantage, struggle to define Value (to the CFO) and are failing to get capabilities Organizationally embedded.

?In terms of Skills, tools and technologies, the survey shows a mixed bag of results, which could indicate that Data teams, whilst equipped to solve existing problems are poorly equipped to solve the problems that the business really faces in the VUCA world:

• The majority of CDOs think their teams (77%) have the right skills;
• 57% think their teams have access to the right tools and 49% use COTS over bespoke Data Tools; and
• That said this is at odds with the view that only 28% believe they have modern tools, whilst 47% think they have an Enterprise Architecture for Data.

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Additional Research Findings

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Other survey findings add to the overall challenge that CDO/CDAOs are facing:

• 43% have made significant progress with AI, Data Science and Machine Learning and only 36% think their projects are given sufficient time to deliver and achieve key objectives;
• 52% say the Board has recognized Data as a critical asset, but only 36% see their business leaders making most of their decisions based on data and only 33% see a business leader change a decision if the data contradicts their intuition or gut instinct.? Ultimately only 25% say they can acquire new and relevant knowledge;
• 30% think their organization is organized effectively to leverage data and similarly only 35% think their Data organization is at the right size and scale to service the organization;
• 33% have developed a Data Literacy and Culture programme to promote the value of data around the business;
• 32% use Data to drive external market sensing capabilities.? Only 45% use customer data to analyse whether product development is in line with customer needs;
• 39% think their Data and Analytics leader is a peer of other C-suite leaders in helping to determine how the business should allocate its resources;
• 52% see their CDO as able to advise the Board on Data and Analytical regulatory matters (in partnership with the Legal Counsel); and
• HR is only able to successfully use data to help the business in 28% of organisations.? HR can only effectively support the Data team in 37% of organisations and only 26% see Employee Engagement in the Data organisation on par with the rest of the business.?

Research References

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1.???? Barney, J. (1991). "Firm Resources and Sustained Competive Advantage." Jounral of Management17(1): 99-120.

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2.???? Barney, J. B., et al. (2011). "The Future of Resource-Based Theory." Journal of Management 37(5): 1299-1315.

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3.???? Davenport, T. H. (2006). "Competing on Analytics." Harvard Business Review.

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4.???? Davenport, T. B. R. (2020). "Are You Asking Too Much of Your Chief Data Officer?" Harvard Business Review: 2-7.

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5.???? Lee S., M. S., Wang R, Wang F,. Zhang H. (2014). "A Cubic Framework for the Chief Data Officer- Succeeding in a World of Big Data." MIS Quarterly Executive 13(March 2014).

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6.???? Mikalef, P., et al. (2019). "Big data analytics and firm performance: Findings from a mixed-method approach." Journal of Business Research 98: 261-276.

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7.???? Mikalef, P., et al. (2019). "Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment." British Journal of Management 30(2): 272-298.

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8.???? Mikalef, P., et al. (2020). "Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities." Information & Management 57(2).

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9.???? Teece, D. J. (2007). "Explicating dynamic capabilities: the nature and microfoundations of (sustainable) enterprise performance." Strategic Management Journal 28(13): 1319-1350.

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10.? Teece, D. J. (2014). "The Foundations of Enterprise Performance: Dynamic and Ordinary Capabilities in an (Economic) Theory of Firms." Academy of Management Perspectives 28(4): 328-352.

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