Is data-driven decision-making driven only by data? When cognition meets data

Zaitsava, Maryia

First

;Marku, Elona

Second

;Di Guardo, Maria Chiara

Last

2022-01-01

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Abstract

This paper aims in the context of data-driven decision making (DDDM) at investigating how biases related to the intuitive and rational types of human reasoning interact and how the trust in data changes applying the parallelcompetitive theory. Using ethnographic research based on participatory observations, we explore the case of a traditional transportation firm in the northern UK and its earliest use of data to inform strategic decisions. We found that biases are grouped into what we called cognition trap, data trap, and trap recognition zones. We further observed three facets of trust in data as decision makers were falling into the three trap zones. These findings contribute to the parallel-competitive theory by unveiling the intriguing synergy of the intuitive and rational types of reasoning in DDDM and providing fine-grained insights related to biases and trust changes. The study also enlarges our understanding of the inception and nature of cognitive and data biases in the DDDM context. Managerial implications are also highlighted and further discussed.