Determining the value of data is on this year’s research agenda of the CC CDQ. In the course of three workshops, members and guests of the CC CDQ discussed the economic value of data assets in breakout sessions. The attendants agreed that there was a growing need for organizations to treat data assets with the same attention and care “traditional” (i.e. tangible) assets are treated. To do so, data intangibles need to be managed efficiently. While quality oriented management of data is largely considered by current DQM reference models, the management of data assets in terms of their financial value is still insufficient. Although it is widely agreed that “you can't manage what you can't measure”, a broadly accepted method for determining the economic value of data assets is still missing.
To close this gap, a work report entitled “Assessing the Economic Value of Data Assets” (authored by Andreas Zechmann) presents two data asset valuation methods. Differing in the conceptual design, both methods consider data quality as a key determinant of the value of data assets. The first method uses a cost-based approach, considering data reproduction cost as a measure for determining the value of data. The second method takes a use-based approach to determine the economic benefit / damage resulting from the use of high-quality / poor-quality data in specific use contexts. The work report presents the conceptual design of the two methods and provides guidance for applying them. A central message of the report is that data valuation should not be considered an end in itself. Instead, organizations should use data valuation as a starting point to implement “data asset performance management” at the interface between DQM and finance.