Valuing Companies' Data – The State of the Art and the Effects of Uncertainty

However, such sharing is rendered more difficult by uncertainty as to how the companies involved assess the value of the data to be shared. A survey among 1,051 companies in Germany reveals that a variety of valuation methods are being used, none of which can be identified as the leading method of choice among either sellers or buyers of data. Data can be valued on the basis of cost, market price or benefit, and often a mix of these methods is used. A fee is payable for approximately one in four data transactions, but half of all companies find it not easy to set an appropriate price. There are, however, ways in which companies can make data valuation easier. First of all, they can prepare themselves generally for the data economy by storing more data digitally, processing it in a more effective and standardised way, and exploiting it in a wider range of applications. Doubts about how transaction partners have valued their data can be overcome by trust-building signals such as sellers providing buyers with sample data sets. In addition, Gaia-X, the European secure data initiative, can be used as an indirect indicator of data quality. Sellers can use screening mechanisms such as contracting a share in the buyer's profits or making licencing arrangements to resolve uncertainty about the buyer's data valuation. Effective tools are thus available that, when used appropriately, mitigate the risks of uncertain valuations and so facilitate mutually beneficial sharing of business data.