The process of collecting, aggregating and analysing data for the purpose of successful
operation is nothing new for companies. However, the amount and variety of data they use
has increased dramatically in recent years. In fact, data have often become a central
element in business models, posing fresh challenges to researchers and policymakers alike.
In this paper, we investigate how the economic value of data can be conceptualised and
measured from a business perspective. We first discuss data monetisation as a strategy for
developing new business models, as well as enhancing “traditional” business models.
Secondly, we review taxonomies for data and propose a new taxonomy with a specific focus
on measuring the business value of data. Here our discussion is centred on four stylised
‘data monetisation strategies’ that are commonly used by companies to generate new
streams of revenue, or to improve current business processes or products. We also discuss
how different data characteristics and types affect economic value. Next, we examine the
role of cross-border data flows as a key enabler of our global economy. We discuss how
and why businesses transfer data across borders, as well as the broad scale and value of
cross-border data flows. To do so we present the concept of a ‘global data value chain’,
based on the idea that digitalisation enables the physical detachment of data collection,
analysis, storage and monetisation. Finally, we summarise and discuss the most promising
avenues for measuring the economic value of data and consider their feasibility in the short
and long-term.

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