THE DATA HIERARCHY: factors influencing the adoption and implementation of data-driven decision making

Stefan Sleep (), John Hulland () and Richard A. Gooner ()
Additional contact information
Stefan Sleep: Georgia Gwinnett College
John Hulland: University of Georgia
Richard A. Gooner: University of Georgia

AMS Review, 2019, vol. 9, issue 3, No 6, 230-248

Abstract: Abstract Marketing practitioners have access to a rapidly increasing quantity and variety of data from customers and other stakeholders. Managers use the term “Big Data” to describe this avalanche of information, which many view as critical to providing a better understanding of customers and markets. This research uses interviews with managers to examine the marketing function’s perspective on data-driven decision making within the firm. Based on informant responses, we develop a hierarchy of data-oriented decision making, describe the drivers that influence where a firm falls within this hierarchy, and detail several transition capabilities for marketing managers interested in becoming more data-driven. The key factors that influence the level of data driven decision making are: 1) firm environment; 2), competition, 3) executive commitment, 4) interdepartmental dynamics, and 5) organizational structure. This framework guides marketing managers both in evaluating the firm’s data capabilities and facilitating change.

Keywords: Data-driven decision making; Big data; Big data hierarchy; Grounded theory (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s13162-019-00146-8

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