Abstract
Decision and risk analysis helps organizations make decisions to maximize their utility in the presence of risk and uncertainty. It helps them make a risk-informed decision. The entire approach to developing alternative scenarios and evaluating them using tools and methods of decision analysis has undergone highly practical improvements in the last few decades.
These improvements have largely to do with the need to engage senior decision-makers directly. For the larger organizations, the approach is to maximize expected value, balancing rewards, and costs with uncertainty. Medium and smaller organizations may be risk averse. This means that they have a non-linear utility function, usually emphasizing avoiding negative outcomes, and maximizing expected utility.
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Notes
- 1.
Author notes—It will take some time for AI users to truly understand the architecture of AI systems. As its name implies, AI system is not so good at helping us with data or information. It would be better if we used these mechanisms to improve our knowledge and intelligence. Wisdom is still the field of human reasoning. But the time will come when we deal with truly wise machines and that will raise us to a new level of things understanding.
- 2.
Ver também: Leonard-Barton and Sensiper [5], que agregou à definição de Polanyi a seguinte frase: “We often know more than we realize” (Nós geralmente sabemos mais do que imaginamos).
- 3.
John Maynard Keynes (1883–1946) was an English economist and philosopher whose ideas fundamentally changed the theory and practice of macroeconomics and the economic policies of governments. Originally trained in mathematics, he built on and greatly refined earlier work on the causes of business cycles. One of the most influential economists of the twentieth century, he produced writings that are the basis for the school of thought known as Keynesian economics, and its various offshoots. His ideas, reformulated as New Keynesianism, are fundamental to mainstream macroeconomics.
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David Gleicher was a management consultant working mostly with Fortune 500 companies. After he retired he devoted his time to working for social and economic justice.
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Accountability—The obligation of persons or organizations to whom resources have been entrusted to assume the fiscal, managerial, and programmatic responsibilities conferred on them, and to inform society and those who have delegated these responsibilities about the fulfillment of objectives and goals and the performance achieved in the management of resources. It is also an obligation imposed on an audited person or organization to demonstrate that it has managed or controlled the resources entrusted to it in accordance with the terms under which they were entrusted to it.
References
Goldberg E (2005) The wisdom paradox: how your mind can grow stronger as your brain grows older. Penguin Group (Gothan Books)
Nonaka I, Takeuchi H (2007) The knowledge-creating company. Harv Bus Rev 85(7/8):162
Sveiby KE (1997) The new organizational wealth: managing and measuring knowledge-based assets. Berrett-Koehler Publishers, San Francisco
Polanyi M (1997) The tacit dimension. In: Prusak L (ed) Knowledge in organizations. Butterworth-Heinemann
Leonard-Barton D, Sensiper S (1998) The role of tacit knowledge in group innovation. Calif Manag Rev 40(3):114, Spring
Hammond JS, Keeney RL, Raiffa H (2015) Smart choices: a practical guide to making better decisions. Harvard Business Review Press
French S (1988) Planning under pressure: the strategic choice approach. Journal of the Operational Research Society, v. 39, n. 11, p. 1067–68
Burchell S, Clubb C, Hopwood A, Hughes J, Nahapiet J (1980) The roles of accounting in organizations and society. Accounting Organizations Society. Pergamon Press Ltd 5(1):5–21
Miettinen K, Salminen P (1999) Decision-aid for discrete multiple criteria decision-making problems with imprecise data. Eur J Oper Res 119(1):50–60
Kahane A (2012) Transformative scenario planning: working together to change the future. Berrett-Koehler
Malczewski J, Rinner C (2015) GIScience, spatial analysis, and decision support. Multicriteria decision analysis in geographic information science, pp 3–21
Diaz-Balteiro L, Romero C (2008) Making forestry decisions with multiple criteria: a review and an assessment. For Ecol Manag 255(8–9):3222–3241
Zeleny M (1994) In search of cognitive equilibrium: beauty, quality and harmony. J Multi-Criteria Decis Anal 3(1):3–13
Pounds WE (autumn 1969) The process of problem finding, industrial management review, pp. 1–19
Drucker PF (1954) The practice of management. Harper & Brothers, pp 351–354
Vanlehn K (1988) Problem solving and cognitive skill acquisition. Carnegie-Mellon, University Pittsburgh PA, Artificial Intelligence and Psychology Project
Simon HA, Newell A (1971) Human problem solving: the state of the theory in 1970. Am Psychol 26(2):145–159
Hayes JR, Simon HA (1976) The understanding process: problem isomorphs. Cognit Psychol 8:165–190. Reprinted in Simon HA (1979) Models of thought, Yale University Press
Chi MTH, Glaser R, Rees E (1982) Expertise in problem solving. In: Sternberg RJ (ed) Advances in the psychology of human intelligence. Erlbaum
Graham RTJ (1976) Problem and opportunity identification in management science. Interfaces 6(4):79–82
Schweiger DM, Finger PA (1984) The comparative effectiveness of dialectical inquiry and devil's advocacy: the impact of task biases on previous research findings. Strateg Manag J 5(4):335–350
Livingston JS (1971) Myth of the well-educated manager. Harvard Business Rev 49(1):79–89
Ackoff RL (1981) The art and science of mess management. Interfaces 11(1):20–26
Mitrotf II, Kilmann RH (1978) On integrating behavioral and philosophical systems: towards a unified theory of problem solving. Annu Ser Sociol 1:207–236
Senge P, Scharmer O (2001) Community action research. In: Reason P, Bradbury H (eds) Handbook of action research. Sage Publications
Johnson B (1992) Polarity management: identifying and managing unsolvable problems. Human Resource Development
de Groot AD. Thought and choice in chess. The Hague: Mouton Publishers, 2nd ed. 1978
Ernst GW, Newell A (1969) GPS: a case study in generality and problem solving. Academic Press
Schwenk C, Thomas H (1983) Formulating the mess: the role of decision aids in problem formulation. Omega 11(3):239–252
Phillips LD, Bana, Costa CA (2007) Transparent prioritization, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing. Ann Oper Res 154(1):51–68
Yager RR (2004) Uncertainty modeling and decision support. Reliabil Eng Syst Saf 85(1–3):341–354
YAGER R, LAMATA MT (1996). Aggregation of Nonnumeric Payoffs for Decision Making Under Uncertainty. In: Proceedings of IPMU 96, v. I, pp. 37–42, Granada, Spain.
Thierauf JR, Klekamp CR (1975) Decision making through operations research. John Willey and Sons
Hapke M, Slowinski R (1996) Fuzzy priority heuristics for project scheduling. Fuzzy Sets Syst 83(3):291–299
Marshall KT, Oliver RM (1995) Decision making and forecasting: with emphasis on model building and policy analysis, McGraw-Hill series in industrial engineering and management science. McGraw-Hill
Courtney H, Kirkland J, Viguerie P (November–December 1997) Strategy under uncertainty. Harvard Business Review. https://hbr.org/1997/11/strategy-under-uncertainty. Accessed 19 March 2023
Davenport TH, Harris JG (2007) Competing on analytics: the new science of winning. Harvard Business Publishing, Boston
Drucker PF (Spring, 1993) The rise of the knowledge society. Wilson Q 17(2):52–71
Drucker PF (2007) Management challenges for the 21st century. Routledge
Csikszentmihalyi M, Sawyer K (1995) In Sternberg RJ, Davidson JE (eds) The nature of insight. MIT Press, pp. 329–363
Taleb NN (2008) The black swan: the impact of the highly improbable. Penguin Books
Schwab K, Malleret T (2020) Covid-19: the great reset. Forum publishing, Geneva
Russo JE, Schoemaker PJH (2001) Winning decisions. Doubleday Publishing Co.
Janis I (1982) Groupthink: psychological studies of policy decisions and fiascos, 2nd edn. Houghton Mifflin
Schoemaker PJH, Day GS (2009) How to make sense of weak signals. MIT Sloan Manag Rev 50(3):81–89
Festinger L (1964) Conflict, decision and dissonance. Stanford University Press
Kelley HH, Michela JL (1980) Attribution theory and research. Annu Rev Psychol 31:457–501
Stoner JF, Freeman RE, Gilbert DR (1994) Management, 6th edn. Pearson
Daft RL (2021) Management. Cengage learning, 14th ed
Simon HA (1990) Bounded rationality. In Utility and probability. Palgrave Macmillan, pp. 15–18
Tversy T, Kahneman D (1974) Judgement under uncertainty: heuristics and biases. Science 18:1124–1131
Tversy T, Kahneman D (1973) Availability: a heuristic for judging frequency and probability. Cogn Psychol 5:207–232
Wind Y, Saaty TL (1980) Marketing applications of the analytic hierarchy process. Manag Sci 26(7):641–658
Forman EH, GASS SI (2001) The analytic hierarchy process—an exposition. Oper Res 49(4):469–486
Steuer RE (1989) The Tchebycheff procedure of interactive multiple objective programming. In Multiple criteria decision making and risk analysis using microcomputers. Springer Berlin Heidelberg, pp. 235–249
Tamiz M, Jones D, Romero C (1998) Goal programming for decision making: an overview of the current state-of-the-art. Eur J Oper Res 111(3):569–581
Romero C (2004) A general structure of achievement function for a goal programming model. Eur J Oper Res 153(3):675–686
Zeleny M (1973) Compromise programming, multiple criteria decision making, Cochrane JL, Zeleny M (eds)
Keeney R, Raiffa H (1993) Decisions with multiple objectives: preferences and value tradeoffs. Cambridge University Press
Zimmermann, H.-J. Fuzzy set theory—and its applications. Springer Science and Business Media, 2011
Stewart TJ (1996) Relationships between data envelopment analysis and multicriteria decision analysis. J Oper Res Soc 47(5):654–665
Paulus PB, Larey TS, Dzindolet MT (2014) Creativity in groups and teams. In Groups at work. Psychology Press, pp. 333–352
Klein G (2014) An overview of naturalistic decision-making applications. Naturalistic decision making, pp. 69–80
Pomerol J-C, Adam F (2008) Understanding human decision making—a fundamental step towards effective intelligent decision support. Intelligent decision making: an AI-based approach, pp. 3–40
Hwang C-L, Lai Y-J, Liu T-Y (1993) A new approach for multiple objective decision making. Comput Oper Res 20(8):889–899
Roy B (1991) The outranking approach and the foundations of ELECTRE methods. Theor Decis 31:49–73
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Sapiro, A. (2024). Decision and Risk Analysis. In: Strategic Management. Classroom Companion: Business. Springer, Cham. https://doi.org/10.1007/978-3-031-55669-2_7
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