Data that enable a company to improve customer relations, streamline production or develop new products are providing future economic benefit and should be regarded as assets.
It is increasingly important that firms are able to account for their data. Firstly, regulatory and compliance initiatives are putting greater emphasis on the quality of data and resulting decision-making in the aftermath of the financial crisis. Secondly, for financial reasons, data that play an increasingly important role in value creation must be recognised if they are to be accorded appropriate priority by company decision-makers.
At economy level, valuing data would provide investors with better information on relative returns, allowing capital to be allocated to activities with the highest expected returns. More efficient allocation of capital within an economy would quicken the pace of economic progress.
Recognising the value of data is also vital in valuing national economies. Current national accounting methods do not capture the growing importance of software and information services – the relative size of the sector has been broadly stationary at around 5% over the last 10 years. This lack of awareness of the size and importance of data in modern economies may, in turn, be preventing governments from recognising growth industries and tailoring regulation and taxation regimes to support them.
Several features of data, however, make them difficult to value within a traditional balance-sheet accounting framework.
- Datasets are heterogeneous, meaning market valuation is not always appropriate.
- Estimations of the return on investment in data (the profit derived when firms invest in data and use them in their business) can be highly uncertain, as a range of other factors including the behaviour of competitors and customers, legal and regulatory conditions, technology and the human resources available to analyse data all influence the value a firm can draw from them.
- The costs of gathering and managing data may be difficult to distinguish from the costs of doing business and the non-rival nature of data (zero marginal cost to make more widely available) makes it difficult to attribute costs across users.
- Data does not have a physical presence and therefore may be considered to have an infinite life when compared alongside physical assets. However, data can depreciate quickly if it is readily outdated (e.g. unstructured social media and financial trading data).
- Some data has additive value, that is, the value of the original data increases as more data is accumulated (e.g. clinical, DNA and climate data).
- While the rate of depreciation tends to be high, there is value in the option to put the data to unforeseen commercial usages in the future, provided that they are well-maintained. But the valuation of such options is not straightforward either.
Other factors can also have a dramatic impact on the value of data
- The behaviour of competitors and consumers can change the value of data. In the highly-competitive soft-drinks market place, a company collecting data on consumer flavour preferences has an advantage, which can be eroded if a competitor gains access to similar data.
- Legal and regulatory conditions can affect the value of data. Legally-mandated access to public sector data can create an opportunity for other companies to create value. Information released by the Department for Transport in the UK, for example, is used to develop navigation apps. Changes in regulation can reduce the value of consumer data held by online retailers and used to generate advertising and transactions revenue.
- Data only have value if they can be accessed and analysed by current technologies. For large datasets or real-time analysis this may require investment in new data-infrastructure. Use of technology to consolidate data across a major retailer can release value by reducing the time taken to create personalised promotions.
- Human input and understanding is needed to ask questions of data, analyse it and devise responses to its insights. These skills are in short supply, and companies facing these limitations are increasingly training staff in house.
Nevertheless, data must be accounted for. Given the challenges in measuring the value of data, we suggest an integrated reporting framework, providing investors and other interested parties with a more comprehensive view of a company’s value by dealing with the factors and risks that can boost or depress the value of data.