This post introduces a data economic valuation process that uses an organization’s key business initiatives as this basis for establishing prudent value.
[Note: I have been trying to write this blog for several years. But instead of trying to perfect the concept, perhaps the best approach is to simply put the idea out there and let it percolate amongst my readers. My University of San Francisco Big Data MBA students will get a chance to test and refine the approach outlined in this blog.]
Data is an unusual currency. Most currencies exhibit a one-to-one transactional relationship. For example, the quantifiable value of a dollar is considered to be finite – it can only be used to buy one item or service at a time, or a person can only do one paid job at a time. But measuring the value of data is not constrained by those transactional limitations. In fact, data currency exhibits a network effect, where data can be used at the same time across multiple use cases thereby increasing its value to the organization. This makes data a powerful currency in which to invest.
Nonetheless, we struggle to assign economic value to an intangible asset like data. Being able to attach economic value to data is key if we want organizations to truly manage data as a corporate asset. However, accounting already has a mechanism for quantifying the value of an intangible asset like data. It’s called goodwill. In the accounting vernacular:
Goodwill is an accounting concept [attaching] value [to] an entity over and above the value of its assets. The term was originally used in accounting to express the intangible but quantifiable “prudent value” of an ongoing business beyond its assets.
From this definition of goodwill, it seems that being able to express the intangible but quantifiable “prudent value” of data should be possible.