The growth of data assets for public companies has skyrocketed over the past decade. 90% of the data in the world today has been created in the last two years alone. Many publicly listed companies have been at the forefront of the new data frontier (think Google, Facebook, Amazon and others). In many cases, revenue, profit and market capitalisation is either substantially or totally based on the data that these companies collect. In contrast, the value associated with data on the balance sheets remains relatively low, usually recorded as part of intangibles and goodwill.
Current methodologies of associating a dollar value to data are typically based on revenue or earnings-based techniques that simply do not reflect the complexity of data’s role in commercial models or the market is clearly putting on data-based assets. There is clearly a gap emerging between traditional valuation techniques for data assets and market-driven prices reflected in market capitalisations.
Data assets have unique characteristics that diminish the effectiveness of traditional valuation methodologies. As such, there is a growing need for data valuation methodologies that can more accurately reflect the true value of a company’s data assets.
To address this growing need, Aurum Data has spent several years in R&D, blending traditional asset valuation methodologies with data science, AI and ML techniques to create a bespoke valuation methodology for data assets that is now available to the holders of data assets or investors seeking an insight into the value of data.
Our research team has conducted deep dive reviews into the data assets of thousands of public companies from exchanges around the world. For each company, the team has recorded more than 100 attributes about each data set that impact the value of data assets. The machine learning algorithm then allocates weightings to apply to each characteristic based on targets identified.
For data holders and investors, data assets will play a critical role in future valuations. Aurum Data’s valuation reports provide critical insights, including valuation ranges for assessed data and guidance on the value drivers and value drags using explainable AI technology. For investors in the 2020s, such insights provide critical points of difference in a relatively immature part of the market research space.