No matter how much human beings strive to make strictly rational choices, they are incapable of doing so because human knowledge is limited and suffers the influence of psychological aspects. This paper aims to demonstrate how the use of foresight methods has contributed to minimize problems inherent to human rationality through a qualitative descriptive study of the case of the Brazilian Agricultural Research Corporation – Embrapa.
This paper collected primary and secondary data through document analysis and interviews with managers of the Embrapa’s strategic intelligence system (SIS), Agropensa (a recognized success case of strategic intelligence (SI)/futures studies in Brazilian public administration).
The results show that it was possible to strengthen corporate behavior in the long term, minimize biases inherent to the decision-making process and bring relevant information into the management of the organization. Foresight methods and tools have made it possible to mitigate problems arising from bounded rationality (BR) in the Embrapa’s decision-making processes. The change in company’s culture potentiated long-term views and access to future-bearing information. Embrapa’s SIS contributes to mitigate difficulties inherent to human nature by bringing uncertainty into managerial discussions.
Taking in consideration all the advances in the future studies/SI approach, this paper realizes that this particular practical case can contribute to scientific community deepening the understanding of how a structure dedicated to run future studies/SI can diminish BR impacts on the company’s decision-making process.
Authors thank Dr Hércules Antonio do Prado (Catholic University of Brasilia) for reviewing the article and for his rich contributions.
Torres, L.A. and Pena Jr, M.A.G. (2021), "Foresight as decision-making support within bounded rationality in individuals and organizations – Embrapa’s strategic intelligence system – Agropensa’s case", Foresight, Vol. 23 No. 4, pp. 477-495. https://doi.org/10.1108/FS-07-2020-0072
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