Explaining Decisions

Explanations of decisions are central to decision governance: before changing how decisions are made, you need to explain how they are made; you need to explain why they need to be changed; and, you need to explain how changes that governance brings should lead to better decisions. So the question is: What is a good explanation of a decision? Which leads to many others. How are decisions explained usually? What is wrong with such explanations? How can we improve them? How much do we need to invest to improve them until there’s no more benefit to continuing? And so on.

This text is part of the series on the design of decision governance. Decision Governance refers to values, principles, practices designed to improve the quality of decisions. Find all texts on decision governance here, including “What is Decision Governance?” here.

In another text, here, I related in a simple way outcomes to actions, actions to decisions, and wrote that there is always an explanation for a decision. The figure from that text is below, where the explanation, labeled with circle 6, is what we need to unpack.

Are there patterns in how people explain decisions?

There are well-documented patterns in how people explain decisions, and these patterns have been studied across psychology, behavioral economics, and decision science. Understanding these patterns is useful for decision governance as they suggest what to look for in explanations, and raise questions as to whether these are useful or not and therefore, if we need to target them through decision governance.

Table 1: Patterns in explanations of decisions
Pattern in decision explanations	Description of the pattern	References to supporting research	Example
Self-serving Bias	Individuals attribute successes to internal factors (e.g., skill) and failures to external factors (e.g., bad luck).	Zuckerman (1979)	A project leader credits strategic decision-making for a successful launch but blames poor market conditions for a failure.
Simplification and Reduction	People tend to simplify complex decisions, focusing on a few key factors.	Kahneman (2011)	A manager explains a cost-cutting decision as “improving efficiency,” ignoring potential long-term impacts on employee morale.
Temporal Proximity Bias	Individuals give more weight to immediate factors, underplaying long-term considerations.	Loewenstein & Prelec (1992)	A CEO emphasizes immediate cost savings from an acquisition but downplays the long-term integration challenges.
Cognitive Dissonance Reduction	People revise explanations to align actions with their beliefs and values, reducing internal conflict.	Festinger (1957)	An executive explains cutting sustainability programs as necessary for financial stability, despite advocating for sustainability.
Consensus Seeking in Group Decisions	People tailor explanations to align with group consensus, often avoiding conflict.	Janis (1982)	A board director supports a strategic shift, echoing the majority opinion, despite having personal reservations.
Post-Hoc Rationalization	Individuals construct explanations after a decision to rationalize intuitive or uninformed choices.	Haidt (2001)	A manager hires a candidate based on intuition but later justifies it with the candidate’s qualifications.
Counterfactual Thinking	People reflect on what could have happened if a different decision was made, especially after negative outcomes.	Roese (1997)	After a failed project, a manager says, “If only we had invested in better technology, the outcome would have been different.”

Illustration of the patterns on a single decision

Below is an example of a decision. How would you explain it in order to emphasize each of the patterns from Table 1? 

In The Iliad by Homer, Achilles, the Greek hero, decides to withdraw from battle after a dispute with Agamemnon, the leader of the Greek forces during the Trojan War. Agamemnon, having been forced to return his war prize, Chryseis, to appease the gods, demands Achilles’ prize, Briseis, as compensation. In response, Achilles, feeling dishonored and enraged by Agamemnon’s actions, chooses to withdraw himself and his troops from the fighting, despite the consequences for the Greek army.

Table 2 shows alternative explanations for Achilles’ decision to withdraw from battle, each emphasizing one of the patterns in Table 1.

Table 2: Explanations of the same decision to emphasize the explanation patterns in Table 1
Pattern in decision explanations	Explanation of Achilles’ decision
Self-serving Bias	Achilles explains his withdrawal as a necessary stand to protect his honor, framing it as a reflection of his strength and virtue. He blames the Greek army’s suffering on Agamemnon’s leadership failings, refusing to take responsibility for the consequences of his decision.
Simplification and Reduction	Achilles justifies his decision by simplifying the situation, stating that the only issue at hand is his personal honor, ignoring the broader impact on the war effort and the Greek army’s morale.
Temporal Proximity Bias	Achilles focuses on the immediate offense to his honor caused by Agamemnon’s demand for Briseis, disregarding the long-term consequences of his withdrawal on the Greek army’s chances in the war.
Cognitive Dissonance Reduction	Achilles revises his reasoning to maintain internal consistency, explaining that by withdrawing, he is not abandoning the Greek cause but rather upholding his principles, which he claims are more important than the war itself.
Consensus Seeking in Group Decisions	Achilles explains his decision by aligning with the sentiments of his loyal troops, who feel similarly dishonored by Agamemnon’s actions. He tailors his explanation to gain their approval, emphasizing the shared sense of injustice.
Post-Hoc Rationalization	After the decision to withdraw, Achilles constructs a justification, stating that his refusal to fight was part of a strategic move to teach Agamemnon and the Greeks the value of his contributions to the war, even though this was not his initial motivation.
Counterfactual Thinking	Achilles reflects on what might have happened if Agamemnon had shown him more respect, imagining that if only Agamemnon had refrained from taking Briseis, the Greek forces would have remained united, and the war might have progressed differently.

What is common across good explanations of decisions?

The characteristics of good explanations are well-supported by research in cognitive science, psychology, and decision theory. These characteristics ensure that explanations are clear, effective, and relevant to their audience, especially in decision-making contexts.

1. Causal Clarity: Good explanations clearly establish cause-and-effect relationships, allowing the audience to understand why an outcome occurred. This involves identifying the specific factors that led to the decision or outcome and linking actions to consequences. Research by Lagnado and Sloman (2006) emphasizes that people prefer explanations that trace a clear causal path from events to outcomes.
2. Simplicity: Good explanations are concise and avoid unnecessary complexity. Research by Lombrozo (2007) shows that simpler explanations, which minimize extraneous details while maintaining accuracy, are often preferred because they are easier to process and understand. This principle is related to Occam’s Razor, which suggests that the simplest explanation is often the best.
3. Coherence: A good explanation should logically fit with known facts and established beliefs, forming a consistent narrative. Thagard (1989) discusses how explanatory coherence enhances the acceptability of an explanation, as individuals are more likely to accept explanations that align with their prior knowledge.
4. Specificity: Effective explanations are detailed and specific, addressing the core elements of the issue at hand. Vague or general explanations are less satisfying. Research by Williams and Lombrozo (2013) indicates that explanations with more relevant details are perceived as more informative and useful for decision-making.
5. Pragmatic Value: Good explanations are practical and offer actionable insights. Keil (2006) argues that explanations should not only clarify what happened but also provide guidance for future action or decisions. This is particularly important in business and organizational settings, where explanations are used to improve decision-making processes.
6. Consistency with Evidence: Explanations grounded in empirical evidence or reliable data are considered more credible and trustworthy. Koehler (1991) found that explanations supported by factual information are rated as more convincing and are more likely to be accepted by others.
7. Counterfactual Plausibility: Good explanations often consider alternative scenarios—what could have happened if different decisions had been made. Roese (1997) highlights the importance of counterfactual thinking in evaluating decisions, as this helps people learn from mistakes and think critically about how different choices might have led to different outcomes.

These characteristics help ensure that explanations are not only understandable but also relevant and useful, especially in decision-making contexts where we want to achieve these properties of explanations through governance.

References and Further Reading

• Zuckerman, M. (1979). Attribution of success and failure revisited: Or, the motivational bias is alive and well in attribution theory. Journal of Personality, 47(2), 245-287.
• Kahneman, D. (2011). Thinking, Fast and Slow. Farrar, Straus and Giroux.
• Loewenstein, G., & Prelec, D. (1992). Anomalies in intertemporal choice: Evidence and an interpretation. Quarterly Journal of Economics, 107(2), 573-597.
• Festinger, L. (1957). A Theory of Cognitive Dissonance. Stanford University Press.
• Janis, I. L. (1982). Groupthink: Psychological Studies of Policy Decisions and Fiascoes. Houghton Mifflin.
• Haidt, J. (2001). The emotional dog and its rational tail: A social intuitionist approach to moral judgment. Psychological Review, 108(4), 814-834.
• Roese, N. J. (1997). Counterfactual thinking. Psychological Bulletin, 121(1), 133-148.
• Lagnado, D. A., & Sloman, S. A. (2006). Time as a guide to cause. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32(3), 451-460.
• Lombrozo, T. (2007). Simplicity and probability in causal explanation. Cognitive Psychology, 55(3), 232-257.
• Thagard, P. (1989). Explanatory coherence. Behavioral and Brain Sciences, 12(3), 435-467.
• Williams, J. J., & Lombrozo, T. (2013). Explanation and prior knowledge interact to guide learning. Cognitive Psychology, 66(1), 55-84.
• Keil, F. C. (2006). Explanation and understanding. Annual Review of Psychology, 57, 227-254.
• Koehler, D. J. (1991). Explanation, imagination, and confidence in judgment. Psychological Bulletin, 110(3), 499-519.