Accurately measuring enterprise value (EV) has never been more important or challenging. Even more so because firms are confronted by growing volumes of data, and the stakes implied in misinterpreting the value of that data have risen to new heights.
Data is no longer the domain of tech companies or IT departments — it is fast becoming a centerpiece of corporate value creation more generally. Today most organizations are data-driven to one degree or another. Data contributes not only to brand equity, but to what constitutes product and service delivery in globally connected and hyper-competitive markets. Failure to accurately quantify the enterprise value of data (EvD) may therefore woefully undervalue the importance of cyber-security investments, as well as the face values typically applied to cyber insurance policies.
Definitions for what constitutes EvD, and methodologies to calculate its value, remain in their infancy. The closest proxy for EvD is to look at a firm’s intangible value, however, this will still fall short of fully estimating the value and therefore the risk inherent in data-laden enterprises. Many attempts to do so have proven to be flawed — even for some of the largest and best known firms in the world.
For example, at the end of its 2015 fiscal year, Apple’s balance sheet stated tangible assets of $290 billion as a contribution to its annual revenues, with approximately $141 billion worth of intangible assets — a combination of intellectual capital, brand equity, and (investor and consumer) goodwill. Using the same formula, Apple’s intangible assets in 2014 were $280 billion — or almost twice the value of its 2015 calculation. By its own estimation, Apple had lost 50% of its intangible value over the previous 12 months, revealing the limits of using a simple intangible value calculation.
The challenge is to quantify the precise value of data to a firm so that economic value can be ascribed to this asset class over time.
