EDO 816 Module 6 Decision Making Under Uncertainty Example

Eleven Months to Decide on Price: Decision Making Under Uncertainty at a Small College, and a Faster Way That Is Not Reckless

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Doctor of Education Program, Aspen University

EDO 816: Leading in Highly Uncertain and Rapidly Changing Environments

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Month Day, Year

Eleven Months to Decide on Price: Decision Making Under Uncertainty at a Small College, and a Faster Way That Is Not Reckless

In September 2024, Halden College's vice president for enrollment proposed that the college cut its published tuition from $48,000 to about $31,000 while reducing institutional aid, so that the average price students actually paid stayed roughly the same. Several peer colleges had made similar moves, and some reported more applications as families stopped dismissing them on sticker price alone. Others saw little change. Halden's cabinet decided to proceed the following August, eleven months later and too late to apply the new price to the next entering class. This paper reconstructs that process and compares it with research on strategic decision making under uncertainty. The college, its people and the figures are invented for this course.

The Shape of Unstructured Decisions

Mintzberg et al. (1976) studied twenty-five strategic decision processes in a range of organizations and described their structure. Decisions moved through three central phases: identification, recognizing the need for a decision and diagnosing it; development, searching for ready-made alternatives or designing custom ones; and selection, screening, evaluating and authorizing a choice. The phases rarely ran in order. Processes were interrupted by new information and opposition, delayed by timing and scheduling, sped up or slowed by the decision makers, and they looped back as problems were rediagnosed. Development, especially when a custom solution was designed, consumed most of the time.

Reconstructing Halden's Decision

What Fast Decision Makers Do

Eisenhardt (1989) studied strategic decision making in eight microcomputer firms operating in high-velocity environments, where demand, competitors and technology changed rapidly. She found, contrary to the expectation that speed requires shortcuts, that the quickest teams drew on a larger volume of information than the slow ones, though of a particular kind: real-time information about current operations and markets rather than forecasts and planning studies. They considered several alternatives at the same time, which sped comparison and gave them fallback positions. They relied on experienced counselors for advice, resolved conflict through consensus with qualification, in which the top executive decided if consensus failed, and integrated each decision with other decisions and plans. Fast decisions, in her study, were associated with better performance.

Halden's process did the opposite. It sought forecasts and studies rather than real-time information, such as what admitted students said about price in conversations that week. It considered one alternative, the reset, against the status quo, rather than several together, such as a partial reset or a guaranteed price for four years. It sought no counselor who had made the decision before. And with no rule for resolving disagreement, each objection produced another study.

Whose Intuition to Trust

Leaders at Halden held strong intuitions. The enrollment vice president was confident families would respond; the president was confident donors would be upset. Kahneman and Klein (2009) addressed when such intuitions deserve trust. Reconciling their once-opposed research programs, they agreed that intuitive judgments can reflect real expertise when two conditions hold: the environment has regularities stable enough to be learned, and the person has had extensive practice with timely, clear feedback. Where those conditions are missing, confident intuitions may be no better than guesses, and subjective confidence is not a reliable guide to accuracy.

By that standard, the enrollment vice president's intuition deserved considerable weight. She had set prices and aid offers for fifteen years and seen each year's yield within months. The president's intuition about donors did not meet the conditions: no one at Halden had ever reset tuition, so there was no feedback from which to learn how donors would respond. Weighing the two intuitions equally, as the cabinet did, treated rank as a substitute for valid expertise.

What the Delay Cost

The eleven months were not free. Because the decision came after the next class's prices had been published, the reset could take effect only for students entering more than a year later. If the consultant's lower estimate of a 6% gain in applications was right, the delay cost Halden roughly 150 applications and, at its usual yield, perhaps twenty enrolled students, worth about $400,000 a year in net tuition over four years each. The cabinet treated waiting as the safe choice, but under uncertainty, delay is itself a decision with a price, a point Eisenhardt's fast decision makers seemed to grasp.

A Decision Protocol

Conclusion

Halden spent eleven months on a decision that needed three, because each study opened a new question in the development phase and the cabinet weighed all intuitions alike. Mintzberg, Raisinghani and Théorêt explain the stalled phases, Eisenhardt shows that fast and effective decision makers use real-time information, several alternatives and experienced counsel, and Kahneman and Klein show how to decide whose intuition to trust. A ninety-day protocol with those features can make Halden's next decision faster without making it careless.

References

Eisenhardt, K. M. (1989). Making fast strategic decisions in high-velocity environments. Academy of Management Journal, 32(3), 543-576. https://doi.org/10.5465/256434

Kahneman, D., & Klein, G. (2009). Conditions for intuitive expertise: A failure to disagree. American Psychologist, 64(6), 515-526. https://doi.org/10.1037/a0016755

Mintzberg, H., Raisinghani, D., & Théorêt, A. (1976). The structure of "unstructured" decision processes. Administrative Science Quarterly, 21(2), 246-275. https://doi.org/10.2307/2392045