Organizational Decision Making: Mapping Terrains on Different Planets
Abstract and Keywords
This article outlines major historical developments that have shaped organizational decision research and highlights themes focusing on organizational decision making. Several of the themes have been visible for many years; these raise questions about decision makers' rationality, their heuristics and simplifications, their political behaviors, and their interpretations of experience. Other themes, however, are nascent ones that promise to become more visible in the future; these deal with decision makers' expertise, intuitions, and emotions.
The Oxford Handbook of Organizational Decision Making comprises 30 chapters authored by leading social and behavioral scientists and scientist‐practitioners whose work addresses cutting edge issues in decision research in applied contexts. Targeted at professional decision researchers, management and organizational scientists, and reflective practitioners, the Handbook provides an authoritative overview of the main theoretical, methodological, and substantive developments in the analysis of decision making in organizations. The volume also offers insights for improving organizational decision making.
The Handbook's design expresses an underlying belief that research can often meet the twin imperatives of scholarly rigor and social usefulness. This philosophy is gaining momentum among behavioral and social scientists (Pettigrew 1997; Anderson et al. 2001; Dunbar and Starbuck 2006; Starbuck 2006; Van de Ven and Johnson 2006; Van de Ven 2007), although debate continues (Grey 2001; McKelvey 2006). The need for a volume that accords with this philosophy is all too evident from the various high profile decision fiascos that continue to dog public service and business organizations. From the Enron debacle to the multiagency mishandling of the 9/11 crisis and the recent floods of New Orleans, organizations have repeatedly failed to heed the lessons of similar cases. They adopt decision processes that perpetuate errors of judgment and miscommunication, leading them into inappropriate courses of action and escalating commitments to failing strategies (Staw 1981, 1997). Readers will recognize this tendency in the construction of many public works, where costs often spiral out of control.
The widely publicized space shuttle disasters of NASA illustrate the high costs of mismatches between decision‐making practices and their technological and organizational contexts. These events also illustrate the complexity of organizational and environmental influences on decision making and the difficulty of attributing specific consequences to specific decisions. NASA's official goals imply that the agency should pioneer new technologies, which inevitably entail risk, and NASA's technologies tend to be very complex ones in which many components can fail, so the risks are high (Starbuck and Stephenson 2005). History suggests that each launch has roughly a 2 percent probability of killing an astronaut (Whoriskey 2003), yet much of NASA's technology is many years out of date. NASA's political and mass communications environments have consistently emphasized the importance of meeting planned schedules for achieving various targets such as launch dates, which has pressured NASA to de‐emphasize technological progress and safety. NASA's political environment has demonstrated little enthusiasm for the agency's official goals and has loaded it with numerous additional “performance targets” that have tangential or no relationships to its official goals. In 2004, NASA claimed to be trying to achieve 211 distinct performance targets.
NASA's internal structure is also complex and mutually inconsistent. One result of the diverse performance targets is that NASA contains many subunits that are partially in conflict with each other. Furthermore, NASA's largest subunits have autonomous political support of their own, and the two largest centers have occasionally refused to comply with instructions from NASA's official headquarters. The centers use distinct rules for everyday activities such as travel to conferences and expense re‐imbursement. NASA's leaders have tried to manage the organization by specifying rules and procedures, in effect turning the agency into a mechanistic bureaucracy. Not only is mechanistic organization inconsistent with the agency's goal of technological development, but it contradicts the realities of subunits that conflict and does not recognize central authority.
NASA personnel include managers, engineers, and scientists who pursue different goals, espouse different values, and speak somewhat different languages (Vaughan 1996; Starbuck and Milliken 1988). These distinct cultures nurture intra‐organizational conflict and impede and distort communication. One of several persistent differences between these cultures has been that engineers have emphasized safety over cost or adherence to planned schedules, whereas managers have sought to keep costs within budgets and activities on schedule. One of NASA's senior leaders, Hans Mark, has said, “When I was working as Deputy Administrator, I don't think there was a single launch where there was some group of subsystem engineers that didn't get up and say ‘Don't fly.’ You always have arguments” (Bell and Esch 1987: 48).
Much of NASA's activity involves performing incremental experiments. Although these experiments may have laboratory precursors, the crucial experiments occur during space flights. Investigations of the 1986 Challenger disaster revealed that managers and engineers had drawn very different inferences from several years of flight experience (Starbuck and Milliken 1988). Some engineers at both NASA and Morton Thiokol had inferred that the Shuttle was becoming increasingly likely to have a catastrophic failure. They met in early 1986 to discuss the reasons for escalating evidence of burn damage to O‐rings in the solid rocket boosters (SRBs). Meanwhile, managers at NASA and Thiokol had been observing that the Shuttle had continued to fly successfully despite escalating evidence of burn damage to O‐rings, and they had inferred that the Shuttle was much more tolerant of problems than their engineering colleagues had said. As a result, the managers in charge of the SRBs had gradually lowered their standards for “acceptable” risk.
These differences led to several explicit disagreements between managers and engineers during the year before the fatal launch of Challenger. In the summer of 1985, engineers proposed that NASA ground the Shuttles for three years to wait for new SRBs. In August 1985, NASA held a meeting to discuss this proposal, which led to a decision to continue flying the Shuttles until new boosters became available. This meeting omitted some key personnel, including the astronauts and the top manager of the Shuttle program, and participants did not see some of the displays that engineers had produced about the O‐ring problems. Disagreements between engineers and managers arose at Thiokol during the fall of 1985, when a team of engineers was trying to study and produce a report about the O‐ring problems; these engineers complained that managers were giving them inadequate cooperation and financial resources. Disagreements between engineers and managers arose again on the afternoon before the fatal launch. Engineering managers from Marshall Space Flight Center met privately at a motel before their teleconference with engineers and managers from Thiokol. The Director of the Marshall Center had declared that his organization would never be responsible for a delayed launch, and it appears that the Director of the Marshall Center may have instructed his personnel to make sure that that this launch would occur as scheduled no matter what the people from Thiokol said. Thus, the teleconference placed pressure on the Thiokol managers to do what (p. 4) the NASA managers wanted to happen, and the Thiokol managers proceeded to construct a rationale for doing what their customer had demanded (Esser and Lindoerfer 1989). When Thiokol's Vice President for engineering expressed agreement with his engineers and reluctance to endorse the launch, the Chief Executive of Thiokol's operations told him, “Take off your engineering hat and put on your management hat” (Presidential Commission 1986: 108).
The Challenger disaster also illustrates the hazards of retrospective analyses of decisions. Just a few days before the disaster, engineers from NASA and Thiokol discussed 11 somewhat contradictory hypotheses about the causes of burn damage to the SRBs' O‐rings. The commission that investigated the disaster came up with two more hypotheses. Thus, at the time of the accident, there was no consensus about what might be wrong, and before the disaster there was no consensus that the burn damage had very serious implications. Yet, only a few months after the disaster, the press and academic analyses had developed a consensus about the causes of the disaster, and they had agreed that specific managers made the crucial errors. Such conversion of complexity, uncertainty, and ambiguity into simplicity, certainty, and clarity is typical of retrospective analyses (Fischhoff 1980). However, this distortion means that retrospective analyses generate deceptive guidance for future decisions, because the people who are making the future decisions will not possess certainty and clarity and they will not see simple situations. In order for analyses of past events to generate useful guidance for future decisions, analysts have to surmount their tendencies to know more than they could have known, and they must formulate prescriptions that help decision makers to operate effectively amid complexity, uncertainty, and ambiguity.
NASA and Thiokol reacted to the Challenger disaster by dismissing almost everyone who had participated in those events and by making numerous changes to rules and procedures. These changes created an impression within NASA that the agency was unlikely to repeat the errors associated with the Challenger disaster. Yet, 17 years later, the Space Shuttle Columbia suffered a catastrophic failure, and the decision processes preceding this second disaster had many similarities to those preceding the earlier one (Starbuck and Farjoun 2005). Again, years of successful launches had led NASA personnel to underestimate the risks posed by signs of damage&in this case damage to foam insulation on the large fuel tank. Pieces of foam had been coming off the fuel tank for 22 years. Engineers again showed more concern for safety than did managers, who again showed more concern for adherence to schedules. Again, managers paid little heed to protests and proposals from engineers. Of course, NASA's shuttles were still using much the same technology as in 1986, and NASA's political and public relations environments were still emphasizing low costs and conformity to plans and schedules.
We, the editors of this Handbook, draw two sets of inferences from stories such as the NASA one. Firstly, decision makers in practical situations can benefit from academic research. At a minimum, decision makers can gain insights by observing (p. 5) academic debates about how to interpret events. Decision makers may also find useful some of the prescriptions that academics have extracted from their observations. Secondly, academic researchers can benefit from considering the practical implications of their studies. Such reflections help researchers to identify contingencies that differentiate situations and to frame analyses in relation to variables that have practical meanings. Academic researchers may also be able to contribute to better decisions that produce a better world. Thus, this Handbook aims to meet “double hurdles,” providing both an up to the minute overview of theoretical and substantive advances and ongoing debates, and doing so in ways that will enable decision makers to benefit from these scientific endeavors (Pettigrew 1997).
The Past, Present, and Future of Organizational Decision Research
This introductory chapter outlines major historical developments that have shaped organizational decision research and highlights themes that surface in the chapters that follow. Several of the themes have been visible for many years; these raise questions about decision makers' rationality, their heuristics and simplifications, their political behaviors, and their interpretations of experience. Other themes, however, are nascent ones that promise to become more visible in the future; these deal with decision makers' expertise, intuitions, and emotions. The chapter concludes with an overview of the structure and contents of the Handbook as a whole.
Rational Decision Makers
People did not perceive organizations as making decisions until the late 1930s and 1940s. Before that time, talk and writing about organizations focused on their administrative hierarchies but people took for granted the activities that these hierarchies performed. Obviously, the hierarchies were making decisions but neither managers nor academics saw these decisions as worthy of discussion or study. In the late 1940s, Simon (1947) wrote the book, Administrative Behavior, in which he discussed decisions. He argued that observers could best understand (p. 6) administrative behaviors in terms of decision processes, that decision premises are the key factors in decision processes, and that decision premises and organizational structures influence each other. Simon also introduced a term that has had widespread influence: “bounded rationality.” People have bounded rationality, he said, because, “The capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real word” (Simon 1957: 198). Simon's formulations not only made decision making a focal point for understanding organizational behavior, they also placed organization theory amid the behavioral sciences, especially psychology.
Although Simon had pointed to mutual influence between decision premises and organizational structures, Administrative Behavior said little about organizations as systems. A decade later, March and Simon (1958) described organizations as complex interactive systems, and discussed how organizational activities modify the bounded rationality of individual decision makers, and vice versa. Still later, Cyert and March (1963) described how actual decision makers in department stores make routine decisions about prices and quantities to order. They showed that human decision makers adhere to very detailed rules of thumb. However, Cyert and March studied and described microscopic decisions that occurred repeatedly and routinely, not major strategic decisions that occur rarely.
Debates about decision makers' rationality have routinely displayed miscomprehension of the opposing viewpoints (Salgado et al. 2002). Both the proponents of rational theories and the critics of these theories agree that individual decision makers do not exhibit in their everyday behaviors the kind of rationality that microeconomic theories purport to assume. As observed by March (1997), rational theories commonly assume that every decision maker:
1. knows all the alternatives for action;
2. knows all the consequences of every alternative action, at least well enough to be able to state a probability distribution;
3. has a consistent preference ordering for alternative courses of action; and
4. uses decision rules that can select a single action to take.
March (1971) remarked that rational theories ignore the obvious fact that goals change over time, and they said people first specify preferences and then they choose actions, whereas people often discover their preferences through taking actions and experiencing the consequences. Thus, people need a technology of foolishness to supplement the technology of rationality. Sensible foolishness (or playfulness) enables people to experiment and discover but it requires a loosening of the requirement to behave consistently. March (1991) weighed the advantages and disadvantages of allocating resources to exploiting the knowledge an organization already has versus exploring the organization's environment in search of new knowledge. As an example, he cited choices between refining an existing technology versus inventing a new technology. Returns from such choices depend, he said, on their variability, timing, and external effects as well as on their expected values, and exploration generally entails consequences that are more variable, have longer time horizons, and exert weaker effects on other organizations.
Proponents of rational theories, who have been mainly economists, have said that these theories are not intended to describe either decision processes or choices in the short‐run. Economic theories of rational decision making are not about one person's behavior or one firm's behavior in the immediate future, but about industry level phenomena over the very long run. Economic theories of rational decision making focus narrowly on prices and quantities. Machlup (1946), for example, pointed out that empirical studies did not allow for the fact that the theory of the firm deals with expectations about the future rather than actual experiences, and that studies had assumed that business decision makers understand concepts such as marginal cost and elasticity of demand. Alchian (1950) argued that economists do not have to look at actual decision processes in order to predict the behaviors that survive in the long‐run. No matter what decision rules firms might use, they can survive only by earning positive profits: firms that lose money go out of business. In addition, firms that behave more optimally have higher probabilities of survival, he said. Friedman (1953) maintained that economic theory does not have to describe firms' actual behaviors as long as it helps economists to analyze firms' behaviors. That is, the appropriate frame of reference for analysis is that of the analysts, not that of the decision makers.
Throughout the 1950s, Carnegie hosted a never ending debate between Modigliani, who said that people are rational, and Simon, who said rationality has bounds. What Simon, Modigliani, and those who watched them did not see clearly was that they were debating two different topics. Simon was (p. 8) talking about the behavior one can observe when one watches one decision maker at a time or at least obtains data from individual decision makers. Modigliani, on the other hand, was talking about the behavior one can observe when one watches hundreds or thousands of decision makers who are responding to similar stimuli (e.g., financial markets). In a way, this debate continues today with similar non‐recognition of the fundamental differences due to aggregation. Economists' notions about rational expectations obviously make no sense when applied to individuals, who cannot know the future, yet these ideas have some predictive value when applied to large aggregates. Students of individual decisions are still criticizing economists for their blind disregard for the many factors that can influence choices and actions microscopically.
“Behavioral” Decision Makers
One subgroup of researchers that has applied economic rationality to individual people has been the behavioral decision theorists. However, behavioral decision theorists soon discovered that actual behavior deviates from what statistical models recommend as being “optimal.” For instance, Edwards (1954, 1961), who is usually regarded as the founder of behavioral decision theory, sought to describe human choice as maximizing “subjective expected utility.” However, even as early as 1961, Edwards was ready to say that maximizing subjective expected utility “does not fit the facts” (1961: 474). Hence, behavioral decision theorists have devoted themselves to finding ways in which human choice deviates from the maximization of subjective expected utility.
Researchers have identified a variety of rules of thumb, “heuristics,” that enable people to cut through the detailed information bombarding them (Kahneman et al. 1982; Payne et al. 1993; Gilovich et al. 2002). The “availability” heuristic says that the more easily people can recall past examples of events and outcomes, the more people will expect them to occur in the future. For example, recent media coverage of business failures would tend to increase the percentage of retail managers who predict that a major competitor will fail in the next year. The “representativeness” heuristic says an observer's estimate of the likelihood that an event will occur depends on that observer's generalizations about similar events, and an observer's estimate of the likelihood that a given person or object belongs to a particular category depends on that observer's generalizations about similar persons or objects. For example, if an employee's physical appearance closely resembles a manager's stereotypical image of a potential “high‐flyer” (e.g., smartly dressed and quick to offer forthright opinions in meetings), the manager will tend to classify the employee accordingly. Although use of heuristics reduces the information‐processing requirements of decision makers, their use may also yield poor judgments and choices.
Researchers have amassed much evidence about the relevance of behavioral decision theory (BDT) concepts for decisions and the design of interventions (Bazerman 1984; Schwenk 1984 1988; Bateman and Zeithaml 1989a, b; Das and (p. 9) Teng 1999; Hodgkinson et al. 1999; Highhouse 2001; Neale et al. 2006). Nonetheless, growing numbers of researchers have questioned BDT's adequacy on philosophical, theoretical, and methodological grounds. So far, BDT has made no significant contributions that take meaningful account of social interactions or organizational complexity.
Decision Makers With Simple Mental Models
Another enduring contribution of Simon is the computer metaphor of the human mind that has dominated the cognitive sciences over the past 50 years (Newell and Simon 1956; Newell et al. 1958). One legacy of this metaphor is the notion that decision makers develop simplified internal representations of problems that help them cope with their information‐processing limitations (Porac and Thomas 1989). The development of methods to probe more deeply organizational decision makers' mental representations has gathered pace over the past two decades, following the publication of Huff's (1990) influential volume and Walsh's (1995) landmark review. Unfortunately, from the late 1980s to the early 1990s, management and organizational scientists borrowed a plethora of terms from the basic cognitive sciences including “mental models” (Johnson Laird 1983); “schemata” (Bartlett 1932); “scripts” (Schank and Abelson 1977); and “cognitive maps” (Tolman 1932). Inconsistent usage of terms and concepts has likely impeded scientific progress. More recently, however, a number of conceptual and methodological refinements have advanced understanding of actors' mental representations; some of these contributions have focused on the sharing of mental models among members of single organizations (e.g., Daniels et al. 1994; Hodgkinson and Johnson 1994) and across industries (e.g., Porac et al. 1989; Porac et al. 1995). Furthermore, research about mental models has inspired the design of interventions to enhance decision processes. These design interventions seek to stimulate more effortful information processing and, where appropriate, requisite cognitive change (Eden and Ackermann 1998; Hodgkinson et al. 1999; van der Heijden et al. 2002).
Adaptive Decision Makers
Gigerenzer and colleagues (Gigerenzer 1991; Gigerenzer and Goldstein 1996) have criticized BDT as an incomplete portrayal of human cognitive abilities in that it pays insufficient attention to humans' adaptive capacities. Furthermore, Gigerenzer has maintained that many of the experimental studies central to the development and validation of BDT involve probabilistic reasoning and other forms of (p. 10) abstract judgment that are far removed from the real‐world environments to which humans have adapted (cf., Kahneman and Tversky 1996).
Predicated upon a fundamentally different conception of Simon's bounded rationality, ecological rationality, Gigerenzer and his colleagues have identified an alternative category of heuristics, fast and frugal heuristics, that they allege adaptively match the informational structure and demands of decision makers' environments. According to Gigerenzer and Todd (1999), people behave in an ecologically rational manner when they use heuristics that suit their environments. They maintain that Simon's notion of satisficing and fast and frugal heuristics suit the real‐life environments of decision makers and are thus ecologically valid. Gigerenzer and Todd claim that fast and frugal heuristics not only make minimal computational demands on decision makers, but they cause less error and bias than the heuristics identified by conventional BDT researchers. However, researchers attempting to identify and analyze fast and frugal heuristics in relation to organizationally relevant decisions have done so mainly in laboratory settings, or they have employed simulated data to compare the performance of fast and frugal heuristics with BDT counterparts (Hogarth and Karelaia 2005; Newell et al. 2003; Bryant 2007). The few studies of fast and frugal heuristics in natural settings (e.g., Astebro and Elhedhli 2006), have yielded mixed findings regarding the extent to which organizational decision makers actually rely on fast and frugal heuristics and with what consequences. There is a clear need, therefore, for further investigations in both controlled and organizational field settings, before researchers should draw definitive conclusions about the applicability of this notion to real‐world organizations.
Politically Aware Decision Makers
Miller and Wilson (2006: 471) observed,
Pettigrew's (1973, 1985) longitudinal analyses of decision processes in a British retail organization and the pharmaceutical and industrial chemicals giant, ICI, illustrate the potential contributions of a political perspective (see also Pfeffer and Salancik 1974, 1978; Pfeffer 1981; Wilson 1982). This body of work emphasizes the influence of multiple and contending stakeholders and of coalitions that assemble loosely on an issue‐by‐issue basis, each pursuing a distinct rationality (Cyert and March 1963).
In Simon's definition of the term, “bounded rationality” is largely the result of human and organizational constraints. Arguably, this view underplays the role of power and political behavior in setting those constraints. Many writers have pointed out that decision‐making may be seen more accurately as a game of power in which competing interest groups vie with each other for the control of scarce resources.
Cohen et al. (1972) pointed out that decision making often creates occasions in which heterogeneous problems, miscellaneous potential solutions, and diverse actors come together erratically. The authors described these occasions as resembling “garbage cans” into which people dump their preferences, technological alternatives, potential solutions, and participants, many of which have weak relations to the problems that gave rise to the occasions. Cohen et al. (1972: 1) observed,
As formulated, garbage‐can decision making is much more likely to occur during decision making by organizations than during decision making by individuals. Cohen et al. said that garbage‐can decision making is particularly prevalent and conspicuous in public, educational, and illegitimate organizations, although it may occur in any organization. Other researchers have observed garbage‐can decision making in business firms. The conditions that elicit garbage‐can decision making are ambiguity of goals, lack of clarity in technology, and transient participants. The decision processes of individuals may also look like garbage cans when they have ambiguous goals and unclear technological alternatives and their thinking mixes disparate issues and cherished solutions.
…organizations can be described for some purposes as collections of choices looking for problems, issues and feelings looking for decision situations in which they might be aired, solutions looking for issues to which they might be an answer, and decision makers looking for work.
Brunsson (2007) has contributed many case studies of rationality in political contexts such as local governments. Brunsson (1982, 1985) observed that the various activities that comprise “rational” decision making tend to lower the likelihood that decisions will lead to actions. When participants in a decision process become aware that a chosen action is only one of several alternatives, or when participants see that a chosen action may yield different consequences that are not entirely predictable, they may feel less commitment to that action. Actions become more likely when the people who carry them out do not see alternatives and expect only good results. Thus, irrational decisions are more likely to produce actions. At least in political contexts, said Brunsson (1989), decision making is a process of talking that participants engage in as a means of building rationales for action, creating visions of future states, and mobilizing resources. Because organizations have diverse goals and stakeholders that cannot all be satisfied simultaneously, organizational leaders have to espouse different visions at different times and support mutually inconsistent actions. Such hypocrisy helps organizations to make controversial decisions and to take forceful actions. Decision processes also create responsibility in that people hold to account those whom they perceive to have advocated actions or made decisions. The ways in which decision processes unfold create external perceptions of about the legitimacy of the decisions, the ensuing actions, and the deciding organization.
(p. 12) Decision Makers Who Process Information, Interpret, and Enact
Weick's (1969, 1979) much cited book, The Social Psychology of Organizing, challenged the idea that environments are stable, objective entities. He said people “enact” their environments when they make sense of their perceptions and experiences and act on these interpretations, and he portrayed organizations as operating in environments of human interpretation. The Social Psychology of Organizing was the first comprehensive analysis of organizations as information‐processing systems. March and Simon (1958) had devoted two chapters of Organizations to information processing, but they focused on a few propositions and did not attempt a comprehensive theory. Cyert and March (1963) had also offered general propositions, but they had concentrated on routinized decision making. Weick's book treated information processing as the essence of organized activity. Indeed, Weick argued that organizations are not static systems and that organizing is a never ending process so that organizations continuously evolve. This evolution occurs primarily in ideas, perceptions, data, beliefs, and communications, and people are endlessly choosing whether or not to follow standardized routines (recipes). Thus, organizations become interpretation systems (Daft and Weick 1984).
Weick's theorizing has reflected especially the ideas of Schutz (1932), who pointed out how interpretation was involved in selecting an experience out of one's stream of experience and how the meaning of action to an actor depends upon the actor's long‐run goals. Schutz argued that understanding conscious choice requires the knowledge of the perspective of the actor at the time of choice; an action that appears irrational after the fact might have appeared perfectly rational when the actor chose it. He also observed that actors learn through experience recipes and rules that guide their behavior.
For Weick (1995), sensemaking involves more than interpretation and wrestling with cognitive dissonances. Sensemaking encompasses: (a) changes in perceptions to render them mutually consistent (consonant); (b) changes in goals and expectations to render them consistent with perceptions; (c) changes in perceptions to render them consistent with actions that have already occurred; and (d) active efforts to manipulate environments to render them consistent with one's perceptions and desires. Even when performed by individuals, sensemaking is intrinsically social because it relies on words to define concepts and categories. Weick has studied sensemaking in various crises and hazardous situations, such as aircraft landings, forest fires, NASA space shuttles, and nuclear power plants. One persistent theme in his writings is the importance of maintaining the coherence of sensemaking; he has argued that situations go out of control when sensemaking breaks down. Another enduring theme is the sharing of perceptions and expectations that enables teams of workers to act coherently during crises. Weick has (p. 13) referred to the latter as “collective mind,” and he has argued that people (individually or collectively) must develop effective “mindfulness”—meaning useful categories and appropriate attention to different kinds of stimuli. An influential article by Weick and Roberts (1993) described the activities of flight operations crews on the decks of aircraft carriers, demonstrating that such crews cooperate effectively in turbulent situations without overt communication because they have rehearsed their activities until each person understands what the others are doing without anyone having to speak.
Theorists disagree about whether computational perspectives, such as BDT, and interpretive perspectives, exemplified by the work of Weick and his colleagues, describe complementary processes that coexist in a dynamic interplay or constitute irreconcilable accounts. Several commentators have advocated unification (Lant and Shapira 2001a, b; Hodgkinson and Sparrow 2002; Lant 2002; Hodgkinson and Healey 2008). Finkelstein and Hambrick (1996), for example, offered a model of strategic decision making in which selective attention and limited search processes by the organization's dominant coalition precede interpretation and choice. However, interpretive perspectives imply that much BDT research has been off‐target. Rather, as Miller and Wilson (2006) observed, interpretive perspectives call for frameworks and metaphors commensurate with sensemaking (Weick 1995), ones capable of supporting decision makers who confront ambiguity and indeterminacy.
Expert Decision Makers in Naturalistic Environments
Like Gigerenzer and his colleagues, researchers who study naturalistic decision making (NDM) reject the notion of equivalency between barren laboratories and the much richer, more complex settings in which organizational decision makers conduct their everyday affairs. These researchers have been seeking alternative concepts, theories, and methods that reflect specific decision contexts.
NDM originated in studies of domain experts making complex, high stakes, and ill‐structured decisions under time pressure, often in dangerous situations (Lipshitz et al. 2001). Klein's (1993) recognition primed decision making model epitomizes the NDM approach. It emphasizes the crucial role of pattern recognition in obviating the need for extensive deliberation about multiple alternatives. NDM applications in organizational contexts have been gathering momentum (Lipshitz et al. 2006), and this work demonstrates that expert decision makers in (p. 14) naturalistic settings are surprisingly adept at making rapid fire and largely error free decisions.
Intuitive Decision Makers
A further challenge to rational theories comes from research on the nature and role of intuition in organizational decision making. Intuition had received scant scholarly attention until recently, but advances in cognitive neuroscience (Lieberman 2007) and managerial and organizational cognition (Sinclair and Ashkanasy 2005; Dane and Pratt 2007) have rejuvenated the construct. Intuition now lies at the heart of a number of dual‐process theories of cognition (Chaiken and Trope 1999; Gilovich et al. 2002; Evans 2007, 2008) and has potential relevance across a range of domains of application, from education to management to health (Hodgkinson et al. 2008). Dual‐process theories assert that two modes of processing are necessary for many tasks: both automatic processing that is beyond conscious control and conscious, analytic processing. The former, automatic mode enables people to cut through vast quantities of information rapidly, while the latter, conscious mode entails detailed analysis. Substantial neuropsychological and psychometric evidence supports dual‐process conceptions, but researchers are currently debating the adequacy of these formulations (Hayes and Allinson 1994; Hayes et al. 2003; Hodgkinson and Sadler‐Smith 2003a, b; Sinclair and Ashkanasy 2005; Dane and Pratt 2007; Sadler‐Smith and Shefy 2007).
Emotional Decision Makers
Yet another challenge to rational theories comes from research on emotion and affect in organizations. Reflecting Mumby and Putnam's (1992) notion that people in organizations are constrained by “bounded emotionality,” Ashkanasy and Ashton‐James (2005: 221) have speculated, “Perhaps the reason scholars have been so reluctant to address the role of emotions in organizations is because of the inherent complexity and ambiguity surrounding emotion.” Again, advances in cognitive neuroscience (Phelps 2006) have been building useful bases for investigations that could elevate the relevance of emotion (cf., Fisher and Ashkanasy 2000; Brief and Weiss 2002). For example, such research may help to explain how emotional traits and states influence the extent to which decision makers rely on conscious or automatic processing (Daniels et al. 2004). Such research could also clarify how anticipated (fear, dread) and felt (anxiety, stress) emotions constrain behavior relating to difficult decisions. However, the time has come for conceptual advances that go beyond linear, single‐step analyses of affective influences on cognition or, conversely, of the cognitive determinants of affect (cf., Brief and Weiss 2002). (p. 15) Researchers need to consider recursive processes by which affectively informed appraisals produce discrete emotions, in turn shaping subsequent cognitions, both within discrete episodes and over time (Hodgkinson and Healey 2008).
With few exceptions, these nascent themes have been focusing on microscopic behaviors. They have said virtually nothing about macroscopic behaviors. However, developments in strategic management could be signaling a new orientation. Drawing on anthropology, economics, management, psychology, and sociology, researchers are attempting to enrich understanding of the dynamic interplay between the micro processes and practices of strategic actors and the macro sociological and economic contexts of those actors and their practices (Wilson and Jarzabkowski 2004; Hodgkinson and Wright 2006; Hodgkinson et al. 2006; Whittington 2006; Jarzabkowski et al. 2007). Suitably developed, this new line of inquiry has the potential to advance the study of organizational decision making beyond an impasse that has limited scholarly and practical progress over much of the past 50 years.
Overview of the Handbook
The Handbook comprises five sections that focus variously on the context and content of decision making, decision making during crises and hazardous situations, decision making processes, the consequences of decisions, and efforts to make decisions more effectively. Although the table of contents divides the chapters into sections with such titles, the sections are not distinct. The chapters under context and content also discuss decision processes, consequences, and ways to make decisions more effectively. Similarly, the chapters under decision processes also discuss context, content, and consequences and they offer suggestions for improving decision making, while the chapters under consequences of decision making also discuss context, content, and decision processes.
Within sections, chapters with more similar topics are closer together. However, there are many ways to describe each chapter and consequently many ways to classify and sequence them. For example, some chapters talk mainly about decision making by individual people, others about group decisions, and others about the behaviors of organizations or other large collectivities. A number of the chapters discuss rationality—its meaning, existence, nature, implications, and usefulness. These chapters surface repeatedly the underlying tensions discussed above concerning the relative merits of the computational and interpretive approaches to the analysis of decision making. The four chapters about consequences of decision making all talk about non‐obvious or deceptive consequences.
Part I: The Context and Content of Decision Making
Boom and Bust Behavior: On the Persistence of Strategic Decision Biases, by Michael Shayne Gary, Giovanni Dosi, and Dan Lovallo (Chapter 2), points to several cognitive and behavioral factors that drive boom and bust dynamics that are widespread and persistent. Firms react to economic booms by trying to expand their capacities, but these expansions rely on too‐simple mental models and imperfect forecasts, and firms implement their decisions slowly so they tend to overexpand or overcontract. Furthermore, firms do not learn to avoid the errors they made in previous cycles. In concluding, the authors argue that firms could improve their decision making by using schemata of logistic demand growth when they manage product lifecycles and by paying attention to historical time data about capacity building.
In Information Overload Revisited (Chapter 3), Kathleen Sutcliffe and Karl Weick question some of the effects observers have attributed to “information overload.” It has been widely accepted that distractions, large amounts of noisy information, excessive task demands, and time pressure lead people to overlook relevant information. The authors propose that overload depends on people's abilities to interpret information and situations, and hence on their prior learning. As well, overload is a transitory condition that fluctuates over time. One effect of overload is that it changes how people infer what they need to interpret, which tells them what they need to decide. That is, interpretation dominates deciding.
Decision Making with Inaccurate, Unreliable Data, by John Mezias and William Starbuck (Chapter 4), looks at consequences of inaccurate, unreliable data. Such data may arise from social construction, from subjective extrapolations of sparse objective data, from noisy collection and transmission processes, or from forecasting errors. The authors propose that when decision makers recognize that they have unreliable data, they seek more data, collapse probability distributions into certainties, revert to ideology, act incrementally, and play to their audiences. Noisy, unreliable data present the challenges of how to design organizations that act effectively despite such data and how better to educate and inform decision makers.
Terri Griffith, Gregory Northcraft, and Mark Fuller ask, “Borgs in the Org?” Organizational Decision Making and Technology (Chapter 5). The authors point out that decision‐aiding technologies can facilitate searches for information, uses of information, and interactions among group members. Decision‐aiding technologies can also undermine decision making, and empirical studies have shown that technologies have mixed effects. In particular, such technologies reflect the human limitations of their designers. Searches for information and uses of it depend on how designers characterize and classify information, so technologies can at best make rationality less bounded. Technologies to support group processes (p. 17) have revealed some unexpected effects. Thus, decision‐aiding technologies are works in progress.
In Making the Decision to Monitor in the Workplace: Cybernetic Models and the Illusion of Control (Chapter 6), David Zweig, Jane Webster, and Kristyn Scott evaluate the trend toward electronic surveillance and monitoring in the workplace. The authors argue that cybernetic models of control that underpin the decisions of many organizations to adopt surveillance practices yield illusory consequences that can generate a repetitive spiral of increased control at the expense of employees' trust and respect. The authors advise leaders to entrust employees with responsibility for decision making and to intervene only when essential. Building on cognitively oriented leadership theory, the authors assert that such behavior by leaders should yield better consequences than the use of electronic monitoring.
Jacques Rojot's chapter, Culture and Decision Making (Chapter 7), describes ways that cultural assumptions influence decision makers. For instance, differences in the traditions of France and Germany appear to influence wages, hierarchical control, and the content of work assignments. However, because prevalent ideas about cultures are vague and inconsistent, they make unreliable foundations for discussions of decision making. Rojot argues that people can understand cultures' effects more usefully as limitations on rationality. For example, national traditions, occupational customs, and organizational systems limit the options that decision makers perceive. This approach to cultural effects has the advantage of drawing upon theories that have grounding in research.
Part II: Decision Making During Crises and Hazardous Situations
Facing the Threat of Disaster: Decision Making When the Stakes are High, by Michal Tamuz and Eleanor Lewis (Chapter 8), considers effects of extreme potential consequences such as accidents or disasters. High stakes decisions occur in diverse settings such as natural disasters, industrial accidents, military planning, and medical treatment. This chapter examines decision making under the threat of disaster, in the midst of disaster, and during post‐disaster investigations. It also points out that organizations have developed decision‐making practices to avert or mitigate disasters. Organizations collect and analyze data about small failures and near misses, mobilize support from other organizations in their environment, and draw on local expertise to generate and test hypotheses about how to recognize and remove hazards.
In The Fit Between Crisis Types and Management Attributes as a Determinant of Crisis Consequences (Chapter 9), Teri Jane Ursacki‐Bryant, Carolyne Smart, and Ilan Vertinsky discuss the consequences of “fit” between decision processes and (p. 18) different types of crises. They propose that various properties of a crisis require good performance on corresponding dimensions, and they identify organizational properties that support good performance on each of these dimensions. Weakness of the appropriate organizational properties causes organizations to respond pathologically.
Karlene Roberts, Kuo Frank Yu, Vinit Desai, and Peter Madsen's chapter, Employing Adaptive Structuring as a Cognitive Decision Aid in High Reliability Organizations (Chapter 10), reviews research about high reliability organizations. These organizations seek to meet stringent requirements for safety and performance in hazardous environments that spawn crises. The authors present three contrasting case studies that illustrate structural and cognitive mechanisms that support rapid and effective decision making in crises. The authors infer that those organizations that achieve high reliability use structural properties to augment the capabilities of individual decision makers.
In Expertise and Naturalistic Decision Making in Organizations: Mechanisms of Effective Decision Making (Chapter 11), Michael Rosen, Eduardo Salas, Rebecca Lyons, and Stephen Fiore review the growing body of research about how expert decision makers handle “naturalistic” decision situations. This work has investigated decision makers in real world settings that entail complexity, high stakes, and time pressure, such as military battle fields and emergency control rooms. The authors identify mechanisms that enable expert decision makers to make rapid and largely error‐free decisions in such situations.
Part III: Decision‐Making Processes
In Cognitively Skilled Organizational Decision Making: Making Sense of Deciding (Chapter 12), Julia Balogun, Annie Pye, and Gerard Hodgkinson offer a sociological perspective on decision‐making skills. They suggest that decision makers with different agendas and personal interests use their differing power resources to influence and shape meaning, leading to particular definitions of the situations at particular moments in time. This chapter highlights the importance of understanding conversational and social practices through which people negotiate and renegotiate their worlds. It points out that people not only make sense of their situations but also influence the sensemaking or those around them. Thus, one power of skillful decision makers arises from molding perceptions and interpretations.
In Linking Rationality, Politics, and Routines in Organizational Decision Making (Chapter 13), Isabelle Royer and Ann Langley explore the roles of decision routines in altering the relative influence of socio‐political and procedurally rational elements of organizational decision making. They suggest that generalization from a single period or a global characterization of decision making as entirely rational or political is likely erroneous. The complex influence of routines on (p. 19) decision making implies a need for longitudinal and multilevel research. Moreover, people naturally favor decision‐making patterns in which procedural rationality and socio‐political processes are more symbiotic than contingent.
Jerker Denrell's chapter, Superstitious Behavior as a Byproduct of Intelligent Adaptation (Chapter 14), offers a perspective as to why organizations often fail to learn from their past decisions. Denrell argues that the requirement of obtaining excellent results prevents managers from experimenting with actions that they expect to produce inferior results. Limited experimentation leads to superstitious routines; in other words, to behavior performed repeatedly despite the absence of clear evidence about causal connections between actions and consequences. Denrell's analysis suggests why managers should limit experimentation and why superstitious routines constitute intelligent responses. He says organizational learning only eliminates practices having direct and severely negative consequences. When practices do not have such negative consequences, organizations avoid experimenting with alternatives, with the result that some behavior is superstitious.
Zur Shapira's chapter, On the Implications of Behavioral Decision Theory for Managerial Decision Making: Contributions and Challenges (Chapter 15), reviews the origins and major developments in BDT and considers its implications for managerial decisions in organizations. According to Shapira, research on BDT and organizational decision making have few similarities and many differences, notwithstanding the fact that the two traditions share common roots and have pursued similar research agendas for over 50 years. One reason, as observed above, is that BDT has relied on lab experiments with simple decision problems involving statistical reasoning, and researchers who study organizational decision making have doubts about the realism and relevance of such experiments; studies of organizational decision making, in contrast, have emphasized longitudinal analyses of sensemaking and social construction.
Eugene Sadler‐Smith and Paul Sparrow examine implications of Intuition in Organizational Decision Making (Chapter 16). Recent theorizing portrays intuition as an expression of tacit knowledge in which cognitive and affective processes interact below the level of conscious awareness. BDT researchers have portrayed intuitive judgments based upon heuristics as being both useful and error prone. Drawing on the insights of this body of work, this chapter argues intuition and rational analysis are different facets of information processing that may operate in parallel and interact contingently, depending on the person's expertise, the task, and the social setting.
Kevin Daniels' chapter, Affect and Information Processing (Chapter 17), considers the influence of cognitions on emotions and moods, and vice versa. Daniels describes affect as having independent negative and positive dimensions; negative affect varies from relaxation to anger, whereas positive affect varies from boredom to enthusiasm. Affect reflects social contagion and situational influences, and individual people exhibit affective traits. Research studies lead Daniels to infer (p. 20) that affect is both a major determinant and consequence of cognition and individual level decision making, and a factor in effectiveness and well‐being.
In Individual Differences and Decision Making (Chapter 18), Emma Soane and Nigel Nicholson survey the range of individual differences that affect decision making. In line with the aforementioned dual‐process conceptions of decision making, the authors argue that many decisions reflect automatic processing whereas others involve conscious, effortful information processing, and that individual difference variables influence the thresholds between these two modes as well as behaviors within each mode. In particular, people exhibit systematic and consistent preferences and traits. The authors develop a person‐situation framework that portrays decisions as both causes and effects of individual differences.
Group Composition and Decision Making, by Elizabeth George and Prithviraj Chattopadhyay (Chapter 19), discusses the effects of group diversity on decision making. Diversity has been increasing due to globalization, the creation of cross‐functional teams, and the employment and promotion of more women, people of differing ethnicities, older workers, and workers with more education. This chapter considers the influence of diversity on access to information, information‐processing biases, and commitment to group decisions. The authors surmise that diversity can be beneficial but its benefits are uncertain and subject to complex influences.
Part IV: Consequences Produced by Decisions
Making Sense of Real Options Reasoning: An Engine of Choice that Backfires? by Michael Barnett and Roger Dunbar (Chapter 20), discusses a proposed strategy for managing risk and uncertainty by generating future opportunities. Real‐options reasoning allocates a proportion of the organization's current resources to support the exploration of potential future actions, thus gaining information while postponing major commitments. However, this strategy can inadvertently create future obligations that foreclose future choices, and attempts to avert escalation of commitment can render real‐option positions incapable of generating a wedge capable of holding open future decision‐making opportunities in the face of rivalry. Barnett and Dunbar's analysis offers a number of insights into the question of when and how decisions makers might find real‐options reasoning more or less appropriate.
In The Social Construction of Rationality in Organizational Decision Making (Chapter 21), Laure Cabantous, Jean‐Pascal Gond, and Michael Johnson‐Cramer focus on the divergent perspectives of economists and organization theorists. As observed earlier, whereas economists have prescribed a normative model for rational decision making, organization theorists have rejected the hypotheses of (p. 21) this normative model, disputed the model's explanatory power, and rejected the idea that humans can behave as prescribed. The authors argue that managers attempt to follow the dictates of the normative model by using its concepts and compatible analytic tools and that the tools compensate for decision makers' biases and limitations. The results include “rituals” of rationality and markets for rationality—as exemplified by demand for courses, tools, and advice from consultants.
In a chapter entitled When “Decision Outcomes” are not the Outcomes of Decisions (Chapter 22), Bénédicte Vidaillet points out that “so‐called decision outcomes” are often not the consequences of decisions because consequences also depend upon actions. Vidaillet remarks that both rational and political concepts of decision making incorporate similar assumptions—that different decision making processes lead to different decisions, that different decisions lead to different actions, and that different actions lead to different consequences. Prescriptions usually focus on decision processes as if consequences follow automatically from decisions, and analyses usually attribute consequences to decisions. According to Vidaillet, actions influence consequences at least as decisions, and are driven by their own dynamics. Moreover, consequences result from interactions of multiple issues that mobilize the organization's attention rather than from specific and identifiable decisions.
What Lies Behind Organizational Façades and How Organizational Façades Lie: An Untold Story of Organizational Decision Making (Chapter 23) proposes that decision processes are not what they seem to be. Eric Abrahamson and Philippe Baumard argue that three types of façades pervade organizational decisions—rational, progressive, and reputation. Rational facades give the impression that decisions are creating technically efficient means toward important financial ends. Progressive façades convey the impression that decisions mirror the norms of progress, in line with management fashions and fads. Reputation facades enhance organizations' legitimacy by painting positive images of activities and accomplishments. The chapter shows that façades play positive roles in decision making that go beyond the obfuscation of organizational deficiencies.
Part V: Toward More Effective Decision Making
In designing this Handbook, as noted above, we, the editors, sought not only a comprehensive survey of scholarly developments but also state of the art guidance for practical applications. Trying to identify useful implications encourages authors and researchers to define operational variables and to consider contingencies. Evidently, the authors of the Handbook chapters accepted these premises, for nearly all the chapters offer prescriptions or point to some practical implications. However, the seven chapters in Part V evaluate explicitly practices that purport to enhance decision making.
Gerald Smith discusses his insights and experiences while Teaching Decision Making (Chapter 24). He argues that logical calculation is appropriate for some situations and intuitive “gut feel” appropriate for other situations, and mistakes occur when decision makers adopt the wrong mode. Smith develops a broader account of decision‐making rationality, one that seeks to do justice to the human capacity for reflective thought. Rejecting dual‐process conceptions as bases for developing decision‐making skills and capabilities, he construes reflective thought as forming a middle ground between intuition and logical calculation, and he says it is potentially decision makers' most valuable resource. One implication of this analysis is that curricula should put less emphasis on the rational model and should incorporate concepts, heuristics, and methods pertaining to functional parts of decision processes such as problem definition or diagnosis.
In Facilitating Serious Play (Chapter 25), Matt Statler and David Oliver give an account of their work at the Imagination Lab (I‐Lab), a charitable foundation that conducts research on “play,” “imagination,” and “emergence” in organizing and strategizing. In conjunction with academic and business collaborators, research staff in I‐Lab have developed an approach to facilitation in the context of strategy making, organizational development, team dynamics, and leadership initiatives. The authors reflect critically on the practices that have emerged through these collaborations and extract lessons about the effectiveness of different practices.
Alfred Kieser and Benjamin Wellstein ask, Do Activities of Consultants and Management Scientists Affect Decision Making by Managers? (Chapter 26). The authors analyze the proposition that the activities of consultants and management scientists can enhance the processes or consequences of decision making through collaborative working, and their analysis leaves them highly skeptical. They challenge the notion that organizations can bridge the widely documented communication gap between academics and managers through joint activities or by hiring consultants. According to their analysis, managers, academics, and consultants inhabit separate self‐referential systems, each characterized by its own goals, values, norms, and interests. They say the idea of applied science contains fundamental flaws because neither consultants' knowledge nor academic knowledge integrates well with managerial knowledge and managerial problems.
John Maule provides a state of the art overview of research on Risk Communication in Organizations (Chapter 27). The central message emanating from Maule's review is that the effective communication of risk requires far more than merely passing on formal risk assessments. Risk managers have given inadequate attention to recipients' acceptance of assumptions underlying risk assessments, to their interpretations of such assessments, and to whether recipients act in accordance with these assessments. Skillful risk communicators need to take account of a broad range of individual and social processes that attenuate or amplify perceptions of risk; they also need to consider whether their communications ought to inform or persuade.
In Structuring the Decision Process: An Evaluation of Methods (Chapter 28), George Wright and Paul Goodwin describe and assess various formal methods that purport to enhance decision making. They identify a number of “best practices” at both individual and group levels and conclude that formal methods can be helpful but users need to match them to specific decision situations.
In Strategy Workshops and “Away‐Days” as Ritual (Chapter 29), Nicole Bourque and Gerry Johnson consider the effectiveness of strategy workshops, the practice of taking time out from day to day routines to plan the longer‐term direction of organizations. Drawing on anthropological theories about ritual, the authors argue that many of these events have designs that assure failure. The very act of removal from everyday work contexts generates outputs (chiefly, ideas and feelings) that are less likely to transfer readily from the ritualized contexts in which many of these workshops and away‐days occur to normal workplaces. The authors offer suggestions for how designers of these events could engineer them to improve the chances of attaining the required transfer.
Finally, in Troubling Futures: Scenarios and Scenario Planning for Organizational Decision Making (Chapter 30), Mark Healey and Gerard Hodgkinson review research about the effects of scenario thinking on judgment and choice, pointing to both benefits and potential liabilities. One widespread claim in popular management literature is that analyzing multiple scenarios leads people to perceive wider ranges of possible futures, but this chapter shows that unskillful use of scenarios can anchor and confine thinking because people who construct scenarios build assumptions into them. Scenarios may also decrease or increase decision makers' confidence, thus creating excessive optimism, excessive pessimism, or rigid adherence to chosen courses of action. The authors propose that scenario users can mitigate these undesirable effects by providing decision makers with continuous feedback on the accuracy of predictions and by encouraging reflective thought about ideas that arise from discussing scenarios.
In sum, the study of organizational decision making is a vibrant, multidisciplinary endeavor. Intentionally varied in style and purpose, and drawing upon fields as diverse as anthropology, business and management studies, economics, psychology, and sociology, the above chapters reveal the richness and variety of theoretical and methodological approaches that characterize this eclectic domain. With contributions from leading researchers from around the globe, The Oxford Handbook of Organizational Decision Making provides a comprehensive overview of developments at the forefront of the field.
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(*) The financial support of the UK ESRC/EPSRC Advanced Institute of Management (AIM) Research in the preparation of this chapter, under grant number RES‐331–25‐0028 (Hodgkinson), is gratefully acknowledged.