In previous articles, we have outlined drivers that make data an ever more important factor for business success, the associated need to audit data (including the processes involved to collect, store and analyze data) and how financial auditing methods can be translated to fit this purpose.
Company accounts are crucial for the allocation of assets in a free market environment. Business success is reflected in the P&L account and can be related to the assets required to run the company and associated financing costs through the balance sheet. Rankings and evaluations of historical successes place limited demands on company accounts beyond being accurate and reasonably comparable. For analyzing prospects of future success, however, resolution and nuance at the start is paramount. In this article, we argue that the introduction of data as a new asset class on company balance sheets, has the potential to benefit investment returns and asset allocation.
We have established that data increasingly affects, or even determines, business outcomes and that appropriate auditing methods can be implemented to verify the existence and quality of such data. From this perspective, data is similar to other types of intangible assets. Like with patents, trademarks and goodwill, the inclusion of data as an asset on the balance sheet, brings additional information on a key factor for differentiation and competitive advantages
Data differo from other intangible assets in several ways with implications for both inclusion criteria and valuation. To qualify data for inclusion as a new asset class in company accounts, a new accounting framework would need to be introduced that outlineo the principles. Examples of such aspects include:
- Asset life. While this will depend on the type of data (i.e. data from a clinical trial vs customer data for direct marketing), data is typically likely to have a shorter asset life than assets like trademarks and patents.
- Value volatility. Valuable data can rapidly turn in Click here to enter text.to a critical liability if not properly managed and protected. Although trademarks and patents need to be protected as infringements can otherwise reduce their values, leaking of sensitive personal data can rapidly put a company out of business. A suitable auditing framework will clearly need to recognize such risks.
- Valuation. The real values of assets like trademarks and patents, frequently appear under the catch all heading “goodwill” which in simple terms reflects that a buyer placed a higher value on the combined assets than their book value. In many cases, this is likely to be true also for data. Due to the nature of data, we believe there is potential to develop robust methods that allow more specific values to be assigned to data sets and processes.
The absence of a key asset class such as data from a company’s balance sheet has negative effects on the relevance of company accounts in terms of meaningful analysis and forecast. In addition, investments in processes to collect, process and store data are likely to be restrained by the absence of an adapted auditing framework. This is especially true regarding methods for advanced statistical analysis and machine learning. In future articles, we will investigate some of the characteristics that enable such methods to generate significant values AND to both verify and quantify these values.
