From balance sheets to data streams - Comparing the CDO and CFO in the modern enterprise

Summary comparison

Divergent origins but converging importance

The CFO role has existed for decades, forged by regulatory compliance, fiscal discipline and strategic stewardship. By contrast, the CDO is a product of the digital age – a response to the exponential growth of data volume, complexity and opportunities.

CFOs have historically been the custodians of “hard” value (money, assets) while CDOs focus is on m

ore intangible elements such as data, insights and information-driven opportunities.

Despite different starting points both roles now operate as strategic advisors to the CEO. The CFO ensures financial sustainability and stakeholder confidence while the CDO delivers data reliability and organisational agility. Each drives enterprise value – one via capital, the other using information.

Evolving financial leadership

Today’s CFO is often a digital-aware strategist. With financial planning and risk management increasingly dependent on predictive modelling, scenario analysis and right-time information flows, CFOs lean heavily on data ecosystems. They need clean, reliable and timely data for operational intelligence as well as more traditional reporting.

Evolving data exploitation

The CDO role is often mistakenly viewed as purely technical or an exercise in managing risks and costs. More often, successful CDOs operate between the organisation, its information and transformation. Their remit includes improving data literacy; identifying and exploiting data monetisation initiatives; and helping the organisation differentiate itself through the way it manages and provides value through data. As an example, consider the successful Apple strategy to emphasise privacy first with its implied critique of those who seek to profit from manipulation of personal data.

Perhaps most importantly, the CDO is there to provide decision comfort – providing necessary and sufficient information to stakeholders whether internal (staff, governance bodies, processes) or external (clients, regulators, partners) that enables them to be comfortable about the decisions they are making.

The CDO role is still evolving and is much less well understood than that of the CFO – it is perhaps because the role is often ill-defined that a 2023 IBM study into CDOs found that the expectation gap is the main reason why many CDO tenures are much shorter than their C-suite colleagues.

Synergies and strategic overlaps

As data exploitation and digital transformation becomes ever more important, there are increasing areas of common ground between CFOs and CDOs.

Reporting requirements now extend beyond traditional financial accounting data into supply chain, modern slavery, environmental and social data meaning the CFO is more reliant on the data generated within the CDO’s jurisdiction than purely within the finance function. A CFO without trustworthy cross-functional data cannot model financial risk accurately or delivery timely insight to investors and other stakeholders.

Building trust in financial data is something that CFOs have extensive experience of. While non-financial data sources are typically less mature, building trust in the should be approached in much the same way:

• By having processes - a great place to start is the DAMA Data Management Book of Knowledge (DMBOK). This codifies the experiences of hundreds of data leaders to provide specific processes.
• Quality metrics – the UK government has a great definition of data quality.
• Regulatory requirements and standards – where to start? GDPR, PECR and MPS are just three regulations looking at data more broadly. There are frameworks such as ISO27001 (Information Management Security Framework); the National Cyber Security Centre defined Cyber Essentials; and SOC 2 reports looking at Systems and Organisational Controls.
• Internal and external audits – compliance with all of the frameworks mentioned above can be certified by independent auditors to provide assurance.
• Ownership – for financial measures this would typically be a budget holder, for data more broadly these are often called data stewards. The role is essentially the same – a budget holder is accountable for deploying the financial resources allocated to achieve agreed outcomes while a data steward is accountable for ensuring the data resources in their area of accountability are fit for purpose and will enable the organisation to achieve its agreed outcomes. Controls can be similar to – a budget holder has to remain within tolerance by not spending in excess of budget while a data steward has to remain within tolerance by ensuring data quality is at an appropriate level. Variances for both can be investigated and resolved.
• Professional scepticism – just as accountants are trained to be sceptical and act with objectivity when dealing with financial information, so should the same apply with non-financial data.

Planning and budgeting for data transformations requires both roles to interact. The CDO identifies the value while the CFO scrutinises this, ensuring the investment is justified and measurable.

Both roles are guardians of trust. CFOs ensure financial integrity while CDOs ensure data integrity. Together they form a complementary assurance layer vital to governance and stakeholder confidence, including regulatory scrutiny.

On the other hand, does this mean that CFOs and finance teams should embed and merge data talent into their roles? Finance teams are already great sources of data talent when you look at what they do on a daily basis:

1. Manage the quality of financial data by reconciling accounts and implementing governance techniques such as budget holders
2. Identify patterns in the financial data through analysis
3. Extract/transform/load data – often using Excel to turn transaction system data into reports (see next question)
4. Interpret the financial data by storytelling via financial statements, investor calls etc
5. Think logically and critically about the information they are working with

The finance team may not have the same depth of technical knowledge as a centralised insight team, but they have the key soft skills. There is an implicit assumption here that embedding data talent within a finance team or to use a centralised insight team are mutually exclusive   options. With the right organisational design they do not need to be.

A more sophisticated approach that can work very successfully is to place analysts in finance, or any other organisational function, with reporting line to management within that function. They can spend 80% of their time/expertise/experience anticipating and answering the questions for that function and 20% of their time managing the data and their analytical competencies. How do they do the latter? Give the analysts a dotted line to the central insight team for training, required skillset definition and a community for mutual support

Friction points and organisational challenges

Despite these overlapping interests, tensions can arise. Budget allocation for data initiatives is one common area – CFO policy often requires early ROI while CDOs can identify innovation opportunities and platform investments offering long-term strategic value.

CDO metrics such as data quality can be hard to directly tie to CFO metrics such as ROI and profit, especially as they are usually part of a wider change initiative. For example, an investment in improving customer and prospect data quality could result in lower regulatory risk, happier customers, increased conversion rates and less time spent by support teams sorting out issues, but may not directly lead to tangible financial ROI. The fact that the financial benefits of CDO investments are often felt indirectly, makes the value of those investments much harder to quantify and measure.

Not integrating data and financial risk perspectives may leave gaps in enterprise risk assessments. BNFL incurred over £100m in costs in 1999 and suffered a global reputation loss when it was found that staff had been falsifying quality control data relating to nuclear fuel pellets for some considerable time.

More recently, Volkswagen admitted to installing software in diesel engines to cheat emissions tests, affecting approximately 11 million vehicles worldwide. This deliberate manipulation of data to meet regulatory standards exposed significant flaws in the company's risk management and ethical oversight. The scandal resulted in over $30 billion in fines and settlements, along with lasting reputational harm. It underscored the critical need for alignment between data management and financial reporting to ensure compliance and ethical integrity.

Culture can also be a hurdle – finance functions are traditionally risk averse and compliance driven; many elements of data functions are experimental and innovation-oriented. Both cultures have a role to play but establishing trust across the divide can be tricky without appropriate sponsorship.

Furthermore, getting executives or the board to buy in to the value of good data may also be a challenge. A useful technique is to ask everyone in the board or exec meeting to raise their hands if they have all the information they need to make decisions and, if any of them do, to keep their hands up if they get it when they need it to orient themselves, decide what to do and then act in a timely basis (refer to the OODA cycle, a decision-making framework).

It's very unusual any hands go up to the first questions, even rarer for any hands to stay up after the second but, just in case they do, the final question to ask is can they rely on that data and confirm it matches the underlying detailed systems?

If hands stay up please consider writing a case study for the Data Analytics Community!

It can also be helpful to abstract the discussion to something unrelated to their accountabilities as this avoids any defensive reaction, conscious or subconscious. Asking simple questions such as “If a pilot had 80% confidence in the altitude reading, would you still board the plane?” or “If while driving your car the view through your windscreen only updated once a month how far would you feel safe driving?”.

You can then relate these back to organisational risks and specific examples.

Conclusion – a partnership for the modern enterprise

In a modern enterprise, the CFO and CDO form an essential complementary relationship. As financial success becomes increasingly data dependent and as data-driven strategies seek financial justification the synergy between the two roles becomes imperative, not just desirable.

In a world shaped by analytics, automation, algorithmic insight and AI how the two roles interact will play a material role in determining how well an organisation performs.