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Data is one of the biggest assets a company has, worth up to 30% of market capitalization. Yet many companies are failing to manage their data properly, often ignoring it as an asset.

That was the message from data valuation expert Herman Heyns, CEO of Anmut, who recently presented to IFAC’s Professional Accountants in Business Committee. He explained why understanding and properly managing data is crucial for companies and their CFOs to create better outcomes for customers, employees, investors, society and other stakeholders.

A considerable amount of value sits outside of the balance sheet. For effective decision making across the capital investment chain, there needs to be greater understanding of what drives value and the long-term strategies for sustainable value creation. Assuming data is one of the biggest intangibles, increasing its visibility both within an organization and with investors is key to future success of organizations.

Data is an asset not a commodity

While there is data that can be bought and sold, much of the data a company owns holds enormous internal value to the business.

To understand this value, an organization first needs to identify what it is that drives value creation, then consider the datasets that support these value drivers. To be able to manage data an inventory of the data is needed, as well as mechanisms to measure it (see box for example methodologies).

Example value drivers in the pharma industry

  • Drug approval
  • Pipeline
  • M&A activity
  • Regulatory and legal compliance
  • Management/employees

Data valuation

Anmut uses various data valuation methodologies depending on the organization type and purpose:

  • Market-driven - used for publicly listed companies to identify overall data value at an enterprise level.
  • Market value of dataset – extension of the market-driven approach to assign value at a dataset level.
  • Initiative-driven – used to assess data value and readiness for digital transformation projects.
  • Stakeholder driven – calculates a value for each stakeholder and the datasets related to them.
  • Trading value – valuation certification method for tradeable data.

It is also important to consider:

  • What data should be protected (that is unique to the company)?
  • What data needs to be shared with the supply chain?
  • What data is a risk (and should be deleted)?
  • What data can be sold?

Valuing data in monetary terms may help shift perspectives within an organization to think about data as an asset, and can also increase visibility of its importance at the executive level. As with any other significant asset in a business, data requires appropriate stewardship, and needs to be owned and managed with appropriate authority at the board level.

To effectively manage data, companies need consistent governance structures to measure the quality and value of data. There also needs to be assigned data owners who are responsible for driving better business outcomes with data. If data is seen as an asset, it is about improving return on investment from that asset.

Considering data as a substantial asset raises the question as to whether it should be recognized on the balance sheet. The answer to this currently is no. Financial statements are prepared and audited in accordance with well-established, high-quality standards. The process for valuing data is not yet subject to the same level of rigor, but can give a high enough level of confidence for a board to make more informed decisions internally, and for investors to have confidence that a company is measuring and managing data.

Example: Understanding data as an asset provides the basis for better capital allocation and investment targeting where data can be used to improve decisions and enhance value creation to key stakeholders. Working from a stakeholder perspective, Herman gave an example of a highways agency looking to increase the capacity of its road network. Data provided the platform to increase capacity by optimizing traffic flow rather than building more transport infrastructure.

Leveraging the value of data requires investment in data before investment in technology

Companies know that data is important, but often don't know which data is important. Billions of dollars are spent on digital and analytics initiatives, but success rates of these can be low. Why? Because they start with the technology and not the business problem. Most initiatives have a high-profile proof of concept, such as improved customer experience or reduced costs, but, upon implementation, organizations realize that the data is not there to deliver the projected outcomes.

Investment in data is a fundamental governance responsibility that needs to be managed and owned at the board level. To be able to extract the value from data, boards need to understand their data portfolio, ensure data governance and management, and have in place a data strategy.

There is likely to be a link between investment in data and investment in technology. Therefore, the relationship between the CFO and the CIO/CDO is important. It is crucial to make sure that any technology implementation is viewed from the lens of driving business value and not through the lens of systems and processes. This will ensure no business-critical elements are cut during implementation.

What is the role of the CFO and finance team in leveraging the value of data as an asset?

Due to their direct access to the board and executive management team and their view across the organization, CFOs, with the support of their finance teams, are uniquely positioned to play a pivotal role in leveraging and managing data as an asset.

The PAIB Committee identified the following actions for the CFO and finance function to enhance their role in leveraging the value of data as an asset:

  • Advocate internally and externally on the value of data

○      Recognize the importance of data (prioritizing and funding)

○      Secure senior management buy-in

○      Raise awareness of the role of finance as an enabler across all business functions

○      Develop pilot programs to demonstrate value of data, e.g. product development from data

  • Build data governance, including ownership and accountability

○      Ensure effective management of data assets, including storage, access, and security

○      Establish business processes for data asset management

○      Drive data cleansing, ensuring quality and integrity of data

○      Establish KPIs for data use/investment

  • Educate and train

○      Invest in building talent and skills within the finance team focused on data and problem solving and analytical skills

○      Educate the wider organization on data management

  • Look beyond the organization for data valuation best practices
    • Identify benchmarks
    • Establish peer networks to share and exchange ideas
Laura Takamizawa
Laura Takamizawa

Principal, IFAC

Laura Takamizawa is a Principal in IFAC's thought leadership team, focusing on initiatives in support of finance and accounting professionals working in business and the public sector. She was previously an Audit Manager at Grant Thornton, specializing in public sector audit in the UK, and prior to that worked for the Audit Commission. She also spent a year on secondment to the International Integrated Reporting Council (IIRC), where she was responsible for managing their public sector and business network programs.

Laura is a member of the Chartered Institute of Public Finance and Accountancy (CIPFA), and holds a Bachelor of Science (Hons) degree in Mathematical Physics from the University of Nottingham (UK).