Uncertainty in Crisis Management

  • Thomas W. HaaseEmail author
Living reference work entry
DOI: https://doi.org/10.1007/978-3-319-31816-5_2922-1



Uncertainty is a sense of doubt that inhibits a decision-maker from acting.


A crisis is an event that poses a “serious threat to the basic structure or the fundamental values and norms of a system, which under time pressures and highly uncertain circumstances necessitates making critical decisions” (Rosenthal et al. 1989, 10). During such events, public administrators must be aware of, and seek to reduce or manage, the uncertainties present in their operational environment. While the meaning of uncertainty has been explored in fields such as mathematics, economics, statistics, and philosophy, decision-making and organizational theorists define uncertainty as a sense of doubt that blocks or delays action (Lipshitz and Strauss 1997). This definition frames the subsequent discussion of uncertainty.

To ensure clarity, a distinction must be made between the concepts of uncertainty and complexity. Complexity relates to the characteristics of a system and its components and subcomponents. By way of example, complexity can refer to the number of actors in a system, the way these actors are organized, and the number and nature of the interactions exchanged among these actors. In contrast, uncertainty does not relate to a system’s characteristics or behavior but, rather, to a specific level or state of knowledge.

The sections that follow begin with an overview of the sources of uncertainty, which can stem from the characteristics of the problem under consideration, the availability and characteristics of the information connected to the problem, or both. The focus then shifts to the types (or dimensions) of uncertainty that exist in a decision-making environment: objective uncertainty and perceived uncertainty. Finally, references will be made to the rational and naturalistic decision-making literatures, which provide insights into how decision-makers might manage uncertainty.

Sources of Uncertainty

The presence of uncertainty in decision-making situations is often attributed to problems of information quantity and quality. Lipshitz and Strauss (1997) identified three specific information problems that can constrain decision-makers. One problem is the lack of information. This constraint occurs when a decision-maker does not have any information or when a decision-maker has incomplete information. The two other problems relate to issues of information quality. For instance, the information possessed by a decision-maker could be ambiguous. This ambiguity means that a decision-maker has information, but the information causes the decision-maker to become overwhelmed by the “abundance of conflicting meanings that [the information] conveys” (Lipshitz and Strauss 1997, 151). Alternatively, a decision-maker could hesitate to act because the available information has created a conflict. In such instances, the uncertainty is not caused by the presence of multiple meanings, but rather, by the presence of information that provides the decision-maker with multiple, and equally attractive or unattractive, alternatives (Lipshitz and Strauss 1997, 151). The uncertainties caused by problems of information quantity and quality can inhibit decision-makers from taking action, whether as individuals, as managers of an organization, or as members of an organizational network.

Types of Uncertainty

A separate line of inquiry considers the types, or dimensions, of uncertainty that occur in decision-making situations. Scholars involved in this line of inquiry suggest that there are two categories of uncertainty, objective and perceived, both of which relate to a decision-maker’s relationship with the operational environment. Scholars who focus on objective uncertainty consider uncertainty to be an intrinsic property of the operational environment. Robert Duncan (1972, 317), for example, suggests that environmental uncertainty can be conceptualized as three different problems. The first problem is that decision-makers are not able to predict the outcome of a certain event. The second problem is that decision-makers do not have sufficient information to generate conclusions about cause and effect relationships. The third problem is that decision-makers cannot assign probabilities to events that will happen in the future. Although they approach the problem of uncertainty differently, these conceptualizations are unified in that the source of the uncertainty is both objective and outside the direct control of the decision-maker.

The second category of uncertainty is called perceived environmental uncertainty. Scholars who fall into this category consider environmental uncertainty to be contextual, meaning that uncertainty is a result of the subjective perceptions of individual decision-makers. Frances Milliken (1987) suggests that a decision-maker can experience three types of perceived environmental uncertainty. The first is state uncertainty, which occurs when a decision-maker perceives some part of the operational environment to be uncertain. This situation can occur when a decision-maker does not understand the actions taken by others or, more broadly, when a decision-maker does not understand that the operational environment has begun to shift from one state to another. The second is effect uncertainty, which refers to a decision-maker’s inability to predict how an event or shift in the environment will affect his own organization. As suggested by Milliken (1987, 137), while one might know that a hurricane is approaching his home, this does not mean that he knows exactly how that hurricane will affect his specific home. The third is response uncertainty, which Milliken (1987, 137) refers to as “a lack of knowledge of response operations and/or an inability to predict the likely consequences of a response choice.” In such cases, a decision-maker may not understand what should be done during a crisis, or they may not understand the “value or utility” of the available response options.

The preceding discussion focused on decision-making and perceived uncertainty at the individual and organizational levels. There also scholars who investigate decision-making and perceived uncertainty in networked systems. In a networked system, decision-makers can adopt different frames of reference as they work, both individually and collectively, to interpret and respond to problems. Joop Koppenjan and Erik-Hans Klijn (2004, 37) argue that the emergence of such divergent frames of reference is the result of “an excess of ambiguity.” This ambiguity can become problematic for decision-makers who must address wicked social problems, which are problems that are complex, technically complicated, and cross-jurisdictional and sectoral boundaries. For example, in a crisis management or disaster response system, which is comprised of a collection of decision-makers who have to operate as a networked system that crosses jurisdictional boundaries, an excess of ambiguity can create uncertainties that inhibit or constrain collective action. In such circumstances, decision-makers may disagree about the nature of a problem, the means that are available to solve a problem, and their desired or expected outcomes. Regardless of how a problem is framed, decision-makers can also deviate from each other in terms of how they perceive the status or adequacy of the information and knowledge that is generated about a problem. When a network of individual decision-makers encounter ambiguities such as these, they can end up participating in a never-ending series of asymmetric debates about a problem’s source, nature, and solution (Koppenjan and Klijn 2004, 37).

The distinction between objective and perceived environmental uncertainty enables decision-makers to understand the source of doubt that has blocked or delayed their action. By extension, this distinction also suggests that decision-makers may be able to manage or avoid some types of uncertainty, especially during periods of stability. This distinction, however, provides decision-makers with little insight into how they might manage uncertainty.

Management of Uncertainty

In the crisis management context, decision-makers must protect the structures, values, and norms of the system that has come under threat. Whether acting individually or collectively, decision-makers must not only recognize that uncertainties may exist, they must also take steps to reduce or eliminate the uncertainties that might block or delay their ability to act. To this end, scholars have explored the strategies that decision-makers use to manage conditions of uncertainty. Although the strategies discussed below are directed toward the sources of uncertainty, they may also be instructive for the management of both objective and perceived environmental uncertainty.

The Rational Model

Decision makers could use the rational model of decision. Making to manage uncertain conditions during a crisis situation. The rational model of decision-making suggests that an appropriate decision can be reached by those who follow a sequence of established steps. These steps include identifying the problem, collecting all relevant information, establishing a decision criterion, developing a comprehensive set of alternatives, and choosing the alternative that maximizes utility (Lindblom 1959). Despite being the touchstone for the analysis of economic and social problems, the utility of the rational model of decision-making has been called into question.

Herbert Simon, a prominent critic of the rational model of decision-making, argued that the rational model has three limitations. According to Simon (1997, 93–97), the model was built upon the assumption that decision-makers operate in conditions where information is complete and attainable. Simon further noted that the model assumes that decision-makers will be able to develop a comprehensive set of alternatives and that decision-makers will be able to accurately anticipate their future preferences and the consequences of their choices. Recognizing that the assumptions of the rational model would be difficult, if not impossible, to meet in the real world, Simon maintained that decision-makers operate according to the principles of bounded rationality, meaning their decision-making processes are bounded by their cognitive limitations and the constraints present in the decision-making environment. In making this argument, Simon does not suggest that decision-makers make irrational decisions, but rather, they satisfice (Decision-makers that satisfice take into consideration only those factors that are relevant and crucial to the problem at hand and then select the best of the available alternatives (Simon 1997, 119)) by selecting a course of action that is “good enough” for the circumstances (Simon 1997, 119).

Naturalistic Models

Building upon Herbert Simon’s insights, other scholars developed naturalistic models of decision-making, which describe how decisions are made in real-world contexts. The naturalistic models of decision-making have been used to explore the decision-making processes of individuals (Klein 1998), teams (Weick 1993), organizations (Weick and Sutcliffe 2001), and systems (Hutchins 1995). While the naturalistic models differ in terms of their specific areas of attention, they are unified in that they seek to specify how decision-makers navigate uncertain and high-risk situations.

As an illustration, Lipshitz and Strauss (1997, 156–157) indicate that decision-makers use five strategies to cope with uncertainty. These strategies are employed by decision-makers in response to the type of uncertainty that is encountered. For instance, if the uncertainty relates to a lack of information, decision-makers use assumption-based reasoning and rely on their mental models about the situation, which can evolve after a shift in assumptions or the discovery of new information. If the uncertainty relates to the lack of understanding, decisions-makers reduce the uncertainty by searching for new information, soliciting advice, or following standard operational procedures. If the uncertainty relates to a conflict among alternatives, decision-makers weigh the pros and cons of their potential decision, seeking to evaluate the gains and losses connected to a course of action. In response to all three types of uncertainties, decision-makers may also choose to use forestalling or suppression strategies. To forestall uncertainty, a decision-maker will delay action until additional information clarifies the situation. To suppress uncertainty, decision-makers will ignore the uncertainty, act on intuition, or gamble that their choice of action is the correct choice. While not comprehensive, these five strategies may provide decision-makers who encounter uncertainty the ability to overcome the sense of doubt that can block or delay action.


The decision-makers responsible for the management of a crisis event must have the capacity to take the rapid and effective action that is needed to save lives, protect critical infrastructure, and bring the crisis to an acceptable resolution. The ability of decision-makers to take such actions, however, can be blocked or delayed by uncertainty (Lipshitz and Strauss 1997). The uncertainties that occur during crisis management situations can come from a variety of sources, including the lack of information, ambiguous information, the inability to predict outcomes, the inability to generate conclusions about cause and effect relationships, and perceptional disagreements about social problems and information adequacy.

During a crisis, a decision-maker should neither ignore these sources of uncertainty nor succumb to the consequences of uncertainty. Rather, a decision-maker should face the uncertainty that exists within their operational environment and, by extension, take steps to eliminate or manage this uncertainty. As an initial step, a decision-maker must improve their awareness of the situation by identifying the source and type of the uncertainty that inhibits their ability to act. Once the source and type of uncertainty are identified, a decision-maker can then adopt a strategy that will help them to manage the uncertainty. These strategies can include satisficing, the reduction of uncertainty, the acknowledgment of uncertainty, and the suppression of uncertainty. The use of these strategies does not guarantee that all uncertainty will be eliminated or that a crisis will be brought to an acceptable resolution. What these strategies can do, however, is help a decision-maker involved in the management of a crisis to overcome, or at least reduce, the sense of doubt that can block or delay their ability to act when their actions are needed most.

Cross References


  1. Duncan RB (1972) Characteristics of organizational environments and perceived environmental uncertainty. Adm Sci Q 17:313–327CrossRefGoogle Scholar
  2. Hutchins E (1995) Cognition in the wild. MIT Press, Cambridge, MAGoogle Scholar
  3. Klein G (1998) Sources of power: how people make decisions. MIT Press, Cambridge, MAGoogle Scholar
  4. Koppenjan J, Klijn E (2004) Managing uncertainties in networks. Routledge, New YorkGoogle Scholar
  5. Lindblom CE (1959) The science of ‘muddling through’. Public Adm Rev 19(2):79–88CrossRefGoogle Scholar
  6. Lipshitz R, Strauss O (1997) Coping with uncertainty. Organ Behav Hum Decis Process 69(2):149–163CrossRefGoogle Scholar
  7. Milliken F (1987) Three types of perceived uncertainty about the environment: state, effect, and response uncertainty. Acad Manag Rev 12(1):133–143Google Scholar
  8. Rosenthal U, Charles MT, & ‘t Hart, P. (Eds). (1989). Coping with crises: the management of disasters, riots and terrorism. Springfield: Charles C. Thomas.Google Scholar
  9. Simon HA (1997) Administrative behavior: a study of decision-making processes in administrative organizations, 4th edn. Free Press, New YorkGoogle Scholar
  10. Weick KE (1993) The collapse of sensemaking in organizations: the Mann Gulch disaster. Adm Sci Q 3:628–652CrossRefGoogle Scholar
  11. Weick KE, Sutcliffe KM (2001) Managing the unexpected: assuring high performance in an age of complexity. Jossey-Bass, San FranciscoGoogle Scholar

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Political ScienceSam Houston State UniversityHuntsvilleUSA