School of Business Affairs - October -2017

34 OCTOBER 2017 | SCHOOL BUSINESS AFFAIRS asbointl.org EFFECTIVE DECISION MAKING by specific factors that were observ- able and seemingly exceptional. Some of these factors, such as a lack of motivation, may appear to be controllable and therefore eas- ily overcome. In fact, the work of Buehler, Griffin, and Peetz (2010) reveals that individuals interpret their own controllable delays as being unlikely to recur in future projects. Other obstacles might seem uncontrollable but exceptional. For example, you might attribute a sub- stantial delay during a prior renova- tion to the emergence of competing projects, which you do not antici- pate recurring. Buehler, Griffin, and Peetz sum- marize the three factors that hamper decision makers’ use of outside information to predict a project’s time to completion thusly: • The forward-looking nature of planning focuses decision makers on future actions rather than past experiences. • Decision makers often fail to recognize that the current task is similar to past tasks in structure and issues. • Decision makers attribute delays in prior practices to controllable rather than uncontrollable events, which they believe won’t be repeated. The result is that decision makers rarely consider outside informa- tion—that is, past experience—when estimating a project’s or task’s time to completion. A vast body of experimental and naturalistic studies also demon- strates that if decision makers focus on inside information only (i.e., information about the current task), they will tend to underestimate time to completion. Buehler, Griffin, and Peetz (2010) argue that one factor that contributes to this result is that decision makers fail to “appreciate the vast number of ways in which the future may unfold” (p. 19). For example, a renovation project will be completed “on time” only if there are no work stoppages, mate- rial supply chain issues, substantial change orders, weather issues, con- tingencies, and so on—a probability that experience tells us is unlikely even when you include slippage time (Flyvbjerg and Sunstein 2016). Although individually the prob- ability of each cause of delay might be low, the possibility that at least one such delay will occur is the sum of the possible events—a fact that eludes most decision makers’ intu- ition (Kruger and Evans 2004). Evidence also indicates that when asked to predict a project’s or task’s time to completion, decision mak- ers envision a preferred scenario without considering the implications of possible obstacles. As Buehler, Griffin, and Peetz note, “When indi- viduals are asked to predict based on best-guess scenarios, their forecasts are generally indistinguishable from those generated by best-case sce- narios” (p. 20). Overcoming the Planning Fallacy The key to understanding the plan- ning fallacy is not that decision mak- ers’ time-to-completion estimates are simply optimistic, but that the opti- mism occurs despite outside evidence to the contrary (Buehler, Griffin, and Peetz 2010). As with other decision-making errors, awareness of the bias is one step toward overcoming its effect on your decisions. A second step is to seek out and consider outside infor- mation. A third step is to consider purposively less optimistic, perhaps even pessimistic, accounts of how the project might unfold, thereby increasing your estimates of time to completion (Buehler, Griffith, and Ross 2002). A fourth step is to take a hyperfocused inside view of the task and “unpack” it into subtasks. After all, most tasks require the completion of smaller, subcompo- nents—better to estimate the time to complete each subtask rather than the task in full without carefully considering what obstacles might arise during each subtask (Kruger and Evans 2004). By adopting these approaches, school administrators can improve the accuracy of their forecasts, which will increase the effectiveness and efficiency of project planning across the district. References Buehler, R., D. Griffin, and J. Peetz. 2010. The planning fallacy: Cognitive, motiva- tional, and social origins. Advances in Ex- perimental Social Psychology 43: 1–62. Buehler, R., D. Griffin, and M. Ross. 2002. Inside the planning fallacy: The causes and consequences of optimistic time predictions. In Heuristics and biases: The psychology of intuitive judgment , edited by T. Gilovich, D. Griffin, and D. Kahneman, pp. 250–70. New York: Cam- bridge University Press. Flyvbjerg, B., and C. R. Sunstein. 2016. The principle of the malevolent hiding hand; or, the planning fallacy writ large. Social Research 83 (4): 979–1001. Kahneman, D., and A. Tversky. 1982. Intuitive prediction and corrective proce- dures. In Judgement under uncertainty: Heuristics and biases , edited by D. Kahn- eman, P. Slovic, and A. Tversky, pp. 414–21. New York: Cambridge University Press. Kruger, J., and M. Evans. 2004. If you don’t want to be late, enumerate: Unpack- ing reduces the planning fallacy. Journal of Experimental Social Psychology 40 (5): 586–98. Brian O. Brent, Ph.D., Karen J. DeAnge- lis, Ph.D., and Nathan F. Harris. M.Ed. , are professors in the Warner Graduate School, University of Rochester. You may direct comments to bbrent@war- ner.rochester.edu .

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