Data: value creation via marketable data-generation

Digital technologies enable the collection, storage and use of data, and also enable data to be gathered remotely and from a greater distance from the market than previously. Data can be gathered directly from users, consumers or other sources of information, or indirectly via third parties. Data can also be gathered through a range of transactional relationships with users, or based on other explicit or implicit forms of agreement with users. Companies collect data through different methods. These can be proactive, requesting or requiring users to provide data and using data analytics, or primarily reactive, with the quantity and nature of the information provided largely within the control of users e.g. social networking and cloud computing. Data gathered from various sources is often a primary input into the process of value creation in the digital economy. Leveraging data can create value for businesses in a variety of ways, including by allowing businesses to segment populations in order to tailor offerings, to improve the development of products and services, to better understand variability in performance, and to improve decision making. The expanding role of data raises questions about whether current nexus rules continue to be appropriate or whether any profits attributable to the remote gathering of data by an enterprise should be taxable in the State from which the data is gathered, as well as questions about whether data is being appropriately characterised and valued for tax purposes. As noted above, the issue of data collection is not new, although the ability to collect and categorise data has increased exponentially in large part due to computing power and the growth of the internet. As a result, addressing the growing role of data would require consideration of potential impact on more traditional business models as well.

While it is clear that many businesses have developed ways to collect, analyse, and ultimately monetise data, it may be challenging for purposes of an analysis of functions, assets, and risks, to assign an objective value to the raw data itself, as distinct from the processes used to collect, analyse, and use that data. For accounting purposes, the value of data collected by a business, like other self-created intangibles, would generally not appear on the balance sheet of the business, and would therefore not generally be relevant for determining profits for tax purposes. Although data purchased from another related or unrelated business would be treated as an asset in the hands of the buyer (and its subsequent sale would generate tax consequences), outright sale of data is only one of many ways in which collection and analysis of data can be monetised. For example, as with other user contributions, the value of data may be reflected in the value of the business itself, and may be monetised when the business is sold. Even where data itself is sold, the value of that data may vary widely depending on the capacity of the purchaser to analyse and make use of that data. The issue of valuing data as an asset is further complicated by existing legal questions about the ownership of personal data, and the ability of users to control whether businesses can access and utilise user data by using digital services anonymously, or by deleting data stored in local caches. Many jurisdictions have passed data protection and privacy legislation to ensure that the personal data of consumers is closely protected. Under most such legislation, this information is considered to be the property of the individual from which it is derived, rather than an asset owned by a company or a public good. Economic literature analysing intangibles, in contrast, has tended to embrace modern business realities and value also assets whose ownership may not be protected by legal rules.

The value of data, and the difficulties associated with determining that value, is also relevant for tax purposes in the cross-border context and triggers questions regarding whether the remote collection of data should give rise to nexus for tax purposes even in the absence of a physical presence, and if so what impact this would have on the application of transfer pricing and profit attribution principles, which in turn require an analysis of the functions performed, assets used and risks assumed. The fact that the value of data can impact tax results places pressure on the valuation of data. Further, the fact that the value of data can impact tax results if attributable to a PE or if held by a local subsidiary and sold to a foreign enterprise, but not if collected directly by a foreign enterprise with no PE, places pressure on the nexus issues and raises questions regarding the location of data collection. This distinction between the taxation of those with a PE and those without a PE was, of course, present in the traditional economy as well.

In addition, data, including location-specific data, may be collected from customers or devices in one country using technology developed in a second country. It may then be processed in the second country and used to improve product offerings or target advertisements to customers in the first country. Determining whether profit is attributable to each of these functions and the appropriate allocation of that profit between the first country and the second country raises tax challenges. These challenges may be exacerbated by the fact that in practice a range of data may be gathered from different sources and for different purposes by businesses and combined in various ways to create value, making tracing the source of data challenging. This data may be stored and processed using cloud computing, making the determination of the location where the processing takes place similarly challenging.

Additional challenges are presented by the increasing prominence in the digital economy of multi-sided business models. A key feature of two-sided business models is that the ability of a company to attract one group of customers often depends on the company’s ability to attract a second group of customers or users. For example, a company may develop valuable services, which it offers to companies and individuals for free or at a price below the cost of providing the service, in order to build a user base and to collect data from those companies and individuals. This data can then be used by the business to generate revenues by selling services to a second group of customers interested in the data itself or in access to the first group. For example, in the context of internet advertising data collected from a group of users or customers can be used to offer a second group of customers the opportunity to tailor advertisements based on those data. Where the two groups of customers are spread among multiple countries, challenges arise regarding the issue of nexus mentioned above and in determining the appropriate allocation of profits among those countries. Questions may also arise about the appropriate characterisation of transactions involving data, including assessing the extent to which data and transactions based on data exchange can be considered free goods or barter transactions, and how they should be treated for tax and accounting purposes. However, as discussed more generally above, the location of advertising customers and the location of users are frequently aligned in practice, such that the value of the user data is reflected in the advertising revenue generated in a country. The scale of this challenge may, in addition, be mitigated by the fact that advertising will frequently require a local presence to attract advertisers.

The changing relationship of businesses with users/customers in the digital economy may raise other challenges as well. The current tax rules for allocating income among different parts of the same MNE require an analysis of functions performed, assets used, and risks assumed. This raises questions in relation to some digital economy business models where part of the value creation may lie in the contributions of users or customers in a jurisdiction. As noted above, the increased importance of users/customers therefore relates to the core question of how to determine where economic activities are carried out and value is created for income tax purposes.