Unlocking data’s future value: A new role for CFOs

An emerging financial model is allowing businesses to monetise the current and future value of data as an asset that can be securitised and traded.

According to market intelligence firm International Data Corporation, the amount of data created, captured, and consumed globally is increasing by a compound growth rate of 23%. By 2025, global data creation is projected to almost triple from 2020 to more than 175 zettabytes (one zettabyte is equal to a billion terabytes). Today, almost every event or interaction has a digital footprint. However, only a small percentage of the potential value of data is being realised.

Much of the data within an organisation is either discarded, trapped, or retained in an unusable format. Despite years of investment in data warehouses, data lakes, and other tools, rapid access to clean, accurate, and timely data for use internally remains a significant challenge, never mind creating data products that have value in the external marketplace.

Revealing the potential

Advances in data management, falling storage costs, and the emergence of artificial intelligence (including machine learning), data science, big data, and cognitive computing are opening new ways to extract value from data. This is done by unlocking trapped data, providing structure and organisation, and finding patterns within data that can produce insights and create value. It creates opportunities for CFOs to unlock the value of data for the enterprise — both for internal use and increasingly for sale externally.

McKinsey & Co. estimates that the economic value from the broad adoption of financial open-data ecosystems could range from about 1%–1.5% of GDP by 2030 in the EU, the UK, and the US, and as much as 4%–5% in India.

CFOs have long understood the potential value of data and have always played a key role in data stewardship. Over time this role has expanded to embrace both market and operational data as well as financial data. Today, many companies share anonymised data for little or no value to other organisations that then profit from it. Retailers provide sales data to aggregators that then sell the data to consumer products companies and marketers. Physicians and hospitals give up medical data that is resold for research and development purposes, and airlines, insurance companies, banks, and others freely disclose pricing data on comparison sites in the hope of generating new business. But what if the value of that data could be realised by the organisation itself?

A new model

A new financial model is emerging that allows organisations to monetise the current and future value of data. A useful reference point is the deal musician David Bowie struck in 1997 to sell a bond backed by his future royalties. In effect, he received cash then in return for giving up his rights to future royalty streams from his music.

This model has exploded in recent years as artists from Bob Dylan to Bruce Springsteen cash in on the future value of their music rights. When this model is applied to data, an organisation can still own the data but sell the rights to future revenue streams derived from the data in return for payment today. Data becomes a more tangible asset with a fair market value that can be securitised, traded, or borrowed against. Valuing data is becoming increasingly practical as marketplaces emerge that establish a price for data that is categorised and packaged. Revenue streams from subscriptions, licensing, and royalties provide the inputs to a model for forecasting the future value of data.

The process of creating value from data is analogous to that of extracting value from natural resources. Raw data can be processed or refined to create products of differing value. This can involve subjecting data to aggregation, concatenation, categorisation, extrapolation, and analysis.

For example, sales data could be grouped by product or geography to create a product. This could be sold or subjected to further processing to create another product. The product and geographic sales data could, for example, be combined with weather data to show how sales vary under different weather conditions. Much like the refining of crude oil, where products can be created at each stage of the process, data is a resource that can be refined into multiple products, each of which has economic value to someone. And both oil and data are benefiting from technology advances that have dramatically improved the efficiency of exploration, extraction, refining, and use.

Types of data value

From a CFO’s perspective there are three primary sources of value:


Data can be used to initiate and process transactions. Examples include execution based upon a set of predefined criteria being met; inventory replenishment triggered by usage, events, or algorithms; or validating transactions based upon the existence of required metadata such as customer identifiers. Selling access to large streams of transaction data can allow others to derive intelligence and insight that can guide innovation, research, financing, and product development.


Data can be aggregated and concatenated to provide information about a series of events or transactions such as measuring activity levels, comparing to different bases (eg, prior periods, plans, targets, or statistical value and trends), or evaluating past actions or decisions.

Organisations that accumulate rich data that can be grouped around different attributes can create data products that have value to others. For example, information on traffic flows from municipal traffic management systems can guide the planning of infrastructure investments; hospital data on patient outcomes can help refine insurance coverage and pricing.


By applying rules, statistical formulas, data science, and AI, including machine learning, or other analytical frameworks, data can be interrogated to explain current or past outcomes or predict future outcomes and events. Financial institutions can create analytics that track spending behaviour by income level and geography, which can be used to hone marketing campaigns and product assortment strategies.

Each of these uses can deliver internal value in the form of better decision-making, but they also have value as commercial data products available for sale to others.

The journey to value

There is already an emerging group of technology service providers, financiers, insurers, advisers, and data asset company operators willing to partner with CFOs to convert enterprise data into assets that can be traded and securitised.

This ecosystem can ensure that an organisation’s data is fit for reuse, can be replicated or combined with other data to create new data, and can be safely transferred and used by others. These service providers can also ensure provenance, veracity, and accuracy; validate aggregation and calculation routines; provide secure access and governance; and mitigate risk.

The biggest barrier to unlocking the value of data is not technical. High-profile data breaches, both accidental and through hacking, have created an atmosphere of fear about the financial, regulatory, and reputational risks of exposing sensitive data. For many boards and executive teams this has engendered a very cautious approach to leveraging the value of data.

Data protection legislation, such as the EU’s GDPR, has further reduced the appetite to embark upon any data-related activity that exposes an organisation to risk. Many of these concerns can be addressed by effective anonymising of data, adopting advanced cybersecurity protocols, and the judicious use of insurance and other risk mitigation techniques.

For a CFO, job one remains ensuring the integrity of financial data, and job two focuses on ensuring that the organisation extracts maximum internal value from data. However, an attractive third job is emerging — developing a financial construct to unlock the future value of an organisation’s data in the marketplace. Proceed with caution, but don’t discount what could be a potent new source of tangible financial value.

David A. J. Axson is a former partner with Accenture, co-founder of The Hackett Group, and former head of corporate planning at Bank of America. He currently serves as part-time CFO of To comment on this article or to suggest an idea for another article, contact Oliver Rowe at


Making the Case for Data Analytics

Learn the foundations of data analytics and how it can transform an organisation and close data analytics skills gaps for future success.

Find this course in the AICPA Store and in the CGMA Store.


Getting Started with Data Analytics

Learn how you can conduct data analytics projects in your organisation. Learning outcomes include recognising how data analytics can be used to achieve a competitive advantage and create opportunities for innovation.

Find this course in the AICPA Store and in the CGMA Store.


Cybersecurity and Digital Transformation

The course lays out market trends in digital transformation and their impact on cybersecurity.

Find this course in the AICPA Store and in the CGMA Store.