Abstract
This paper intends to assume a comprehensive and far-sighted enough perspective on the pillar themes of the Conference. Data Science (DS), Decision Theory (DT) and Strategic Management (SM) are three relevant and interrelated fields that have undergone substantive changes in recent years. The purpose of the paper is, first, to examine the revolution that occurred in DS, DT and MS and, then, to discuss the leap that happened in the process data are linked to decisions and these, in turn, to strategies. In short, data moved from a situation of scarcity, fragmentation and poor quality to a situation of abundance, structure and extreme richness; Decision Theory moved from Olympic rationality and certainty to bounded rationality, uncertainty and cognitive biases; Strategic Management moved from clear and straightforward course of action to an open, incremental and “many best ways” process. So, once upon a time, (few) data were the input for decisions based on sound criteria and led to a definite route to be followed by the organization. Nowadays, a multitude of data are available to decision-makers who are more or less aware of the flaws affecting their behavior with the whole process ending in simple claims of strategic agility and flexibility. Finally, some reflections are introduced about the consequences of such changes, the challenges digital technology poses to companies and society in the coming years and about a tentative logic to cope with such complexity.
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References
Ariely D, Jones S (2008) Predictably irrational. Harper Audio, New York
Baccarani C (2005) Diario di viaggio sul treno che non va in nessun posto: riflessioni per chi vive l’impresa. Giappichelli, Torino
Borgmann A (2000) The moral complexion of consumption. J Consum Res 26(4):418–422
Crawford K (2013) The hidden biases in big data. Harv Bus Rev 1(4):814
Cukier K, Mayer-Schönberger V (2013) The dictatorship of data. MIT Technol Rev
Damasio AR (1994) Descartes’ error: emotion, reason, and the human brain. Putnam, New York
Eiser JR, van der Pligt J (2015) Attitudes and decisions. Psychology Press, New York
Kelly K (2010) What technology wants. Penguin, New York
LeDoux J (2005) Le cerveau des émotions. Odile Jacob
Lindstrom M (2016) Small data: the tiny clues that uncover huge trends. St. Martin’s Press
Mintzberg H, Waters JA (1985) Of strategies, deliberate and emergent. Strat Manag J 6(3):257–272
Muller JZ (2018) The tyranny of metrics. Princeton University Press, Princeton
O’Neil C (2016) Weapons of math destruction: how big data increases inequality and threatens democracy. Broadway Books, New York
Pfeffer J, Salancik JR (1978) The external control of organizations: a resource dependence perspective. New York
Porter TM (1996) Trust in numbers: the pursuit of objectivity in science and public life. Princeton University Press, Princeton
Quinn JB (1980) An incremental approach to strategic change. McKinsey Q 16(4):34–52
Simon HA (2013) Administrative behavior. Simon and Schuster, New York
Todd PM, Gigerenzer GE (2012) Ecological rationality: intelligence in the world. Oxford University Press, Oxford
Wang T (2013) Big data needs thick data. Ethn Matter 13
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Brunetti, F. (2021). Data Science, Decision Theory and Strategic Management: A Tale of Disruption and Some Thoughts About What Could Come Next. In: Sinha, B.K., Bagchi, S.B. (eds) Strategic Management, Decision Theory, and Decision Science. Springer, Singapore. https://doi.org/10.1007/978-981-16-1368-5_17
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DOI: https://doi.org/10.1007/978-981-16-1368-5_17
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