Abstract

With the increase in volume of data and the ability to harness it, organizations are becoming more data-driven, but decision makers are paradoxically becoming further removed from the origins of the data on which they rely. As data travel greater organizational distances, the contextual knowledge about data—its provenance—often weakens or becomes obscured. Data provenance (DP), that is information about the origin, transformation, and handling of data, has been studied extensively in technical literature, primarily from a top-down perspective. However, its sociotechnical dimensions, that is, how different organizational actors understand and value DP, remain underexplored. We draw on interviews with 21 professionals working in banking and finance or with banks as clients. Using a grounded theory approach, we develop a substantive model tracing how DP evolves as data move from upstream source systems to downstream consumption contexts. We identify four modes of adaptation – embedded DP, DP routinization, DP substitution, and DP dissolution – capturing a progressive weakening of the coupling between data and its provenance. Our findings advance the understanding of DP as a phenomenon, revealing the uneven distribution of data-centric knowing. Furthermore, we highlight the potential for DP to be mobilized as an organizational resource.

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