There is a common misconception, largely based on outdated accounting standards, that it is not possible to value data. However, with intangible assets such as data, content, brands and software now driving over 87% of all company value and virtually all earnings growth, new methodologies have been developed that can provide senior management teams and Boards with a robust, defensible, business-focused valuation of what the Economist called “the world’s most valuable resource: data.
Until recently valuation methodologies focused almost entirely on assessing the value of a company based on its balance sheet and earnings performance. This was largely driven by the fact that accounting standards such as GAAP and IFRS almost completely ignore intangible assets. They are either off the balance sheet entirely, lumped under the amorphous term “good will” or recorded solely at cost. This was acceptable in the 1970’s when intangible assets only accounted for 17% of company value and tangible assets did all the world. Today with that ratio inverted, this will no longer suffice.
Failing to account…
Failing to account for the value of intangible assets such as data has revealed a growing disconnect between company accounts and reporting and the reality of what is really driving value, growth and risk within an organization.
To drive this point home, you only need to look at the world’s five most valuable companies (Apple, Amazon, Alphabet, Microsoft, and Facebook). According to a recent report from the UK Treasury, these companies are together worth £3.5 trillion, yet their balance sheets report just £172 billion of tangible assets. The other £3.3 trillion of value (their intangible assets) is well, missing in action.
Sticking with these companies for a moment, a commonality between all of them is the way in which they have managed to capture and monetize data (and other intangible assets) to create sustainable, high growth, high margin revenue – the Holy Grail for many companies.
Yet not all data is created equal
Before like so many companies you rush off to monetize the “highly valuable” data you own it’s worth keeping a few items in mind. To begin, value is intrinsically related to scarcity. Based on estimates by Cisco, more than 847 zettabytes of data will be generated in 2021 – that’s a lot of data, it’s hardly scarce.
While some of this data will help drive significant revenue streams for savvy companies, it is important to note that not all data is created equal or even valuable. For a start much of this data lacks inherent value. Furthermore, even “good data” without context, has no value. Data needs to be applied in some way to create an economic return either for its owner or third parties to generate value. Interpreted incorrectly or mismanaged, data can actually do more harm than good – witness the numerous hacks of custodial data that occur every week leading to massive costs, regulatory penalties and brand damage This is why it is critical to stop and assess the potential return, value and risk of data monetization before rushing down a path to monetize
So how can you determine if your data is “worth it”?
Returns from data monetization will be heavily context, cost and risk dependent, which is why it is critical that companies start this journey by first building a viable business case prior to spending money on the technical challenges associated with data monetization. This is basic business common sense.
Think about it, if your company owned a vacant plot of land, no-one in their right mind would decide to develop the land (monetize the asset) without first working out what the potential return was, the costs involved in the development and the risks involved. Data is no different yet many companies fail this basic step and charge off to monetize their data without even understanding basic issues such as “what is this data likely to be worth?”
Understanding what your data is worth
In order to make the business case for monetizing data, companies first need to understand the value of the data they own. There is a common misconception that you can’t accurately value data. This is incorrect. You absolutely can value data – it just requires a different methodology as it needs to take into account a much broader range of factors than are included in a traditional physical asset or business valuation.
Traditional valuation methods such as cost-basis analysis or discounted cash flow (DCF) that work well for fixed assets or mature companies simply don’t work (cost basis), or are subject to major accuracy and defensibility challenges when applied to data and other intangible assets.
When it comes to valuing data, there is often no correlation between the cost of the data and the potential revenue that can be generated from it. Likewise, a data set in the hands of a small operating business might be worth (on a discounted cashflow basis) a relatively small amount, but in the hands of a much larger business could be worth a vastly larger sum.
For example, we worked with a small financial services provider. The owners were exiting the business and had been told by the investment bank managing the transaction that, based on industry standards, the business was worth approximately 4x EBITDA. Not satisfied that this reflected the company’s true worth, the client approached us for a second opinion. Upon analysis of the company’s intangible assets, we identified highly valuable data sets that were completely off balance sheet and not recognized in the sale process.
We suggested a very different approach to the sale. First, we focused heavily on the data and ensured that buyers understood just how valuable it and outlined the potential end use cases for the data. This was critical because the data was off balance sheet and did not feature as a standalone line item in the P&L). Second, we targeted buyers who wanted to buy data, not an operating company, as these companies had a much larger cheque book.
The result: the company was sold to a strategic buyer for the data for 32x EBITDA – an 800% increased return to the owner. Cue one very happy business owner.
Monetized effectively, data has the potential to become one of a company’s greatest assets. However, the first step in this process is to understand the various business end use cases for your data, as it is these end uses cases that will determine the potential economic returns and risks associated with leveraging your data.
A key aspect of the process is building an accurate valuation of the end use cases. This is not only possible, but with the right advice entirely viable. It does however require an understanding of how to assess data using a different set of factors and techniques that have previously been used in traditional asset valuations.
 A zettabyte is 1,000,000,000,000,000,000,000 bytes.