The unique properties of data make assessing its value difficult when using the traditional approaches of intangible asset valuation. John Akred discusses a number of alternative approaches to valuing data within an organization for specific purposes, including informing decisions to purchase third-party data and monitoring data’s value internally to manage and increase that value over time.
Data is difficult to value in large part because, economically, it does not adhere to the three main conditions of a traditional market system. In addition, traditional valuation methods of intangible assets do not apply to data valuation.
While a traditional valuation of data may not be applicable, John explores data’s value in the context of specific uses and intentions within an organization, sharing several examples of how to use methods such as the value of information (VOI) framework and A/B testing to assess whether or not a third-party data source should be purchased or continue to be purchased and demonstrating how mutual information (MI) can be used to assess the value of a data source once it is in use within the organization.
John concludes by discussing the qualities that make data more valuable within an organization and provides a range of concrete and straightforward metrics that allow the value of data to be monitored internally to ensure that business decisions can be optimized to maximize that value over time.
With over 15 years in advanced analytical applications and architecture, John Akred is dedicated to helping organizations become more data driven. As CTO of Silicon Valley Data Science, John combines deep expertise in analytics and data science with business acumen and dynamic engineering leadership.
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