Performance in Planning: Processes, Requirements ... - SAGE Journals

Copyright 2001 by the Educational Publishing Foundation 1089-2680/01/S5.00 DOI: 10.1037//1089-2680.5.3.213

Review of General Psychology 2001, Vol. 5, No. 3, 213-240

Performance in Planning: Processes, Requirements, and Errors Michael D. Mumford, Rosemary A. Schultz, and Judy R. Van Doom

This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

University of Oklahoma Planning is not only an aspect of our day-to-day lives, it represents a critical aspect of performance on many high-level tasks. Although few of us would dispute the need for planning, the psychology of planning remains relatively undeveloped. With this point in mind, the intent in the present article was to review the available literature on planning. The authors begin by examining alternative models of planning and delineating their implications for performance. Subsequently, the findings obtained in various studies of planning are reviewed with respect to 8 key questions ranging from when planning is useful to how errors in planning should be minimized. The implications of current answers to these questions are discussed in terms of research needs and development of a more comprehensive theoretical understanding of performance in planning.

Few other activities have as much impact on our lives as planning. People must plan their day-to-day chores (Agre & Chapman, 1990). Organizations must plan new product introductions (Castrogiovani, 1996). Surgeons must plan how operations will be conducted (Kuipers, Moskowitz, & Kassinger, 1988). Although planning represents a crucial aspect of performance on many complex, real-world tasks, psychology has not, historically, invested much effort in studies of planning. Recognizing the importance of planning as a psychological phenomenon, R. M. Berger, Guilford, and Christensen (1957) and G. A. Miller, Galanter, and Pribram (1960) initiated the first systematic studies of planning some 40 years ago. Over the intervening years, research on the psychological mechanisms underlying planning has proceeded in fits and starts (Gaerling, 1996). Nonetheless, the research conducted to date indicates that planning can, at least at times, have a pervasive impact on performance, influencing not only the

Michael D. Mumford, Rosemary A. Schultz, and Judy R. Van Doom, Department of Psychology, University of Oklahoma. Parts of this work were sponsored by a series of grants from the United States Department of Defense. We would like to thank Shane Connelly, Holly Thompson, Juan Benevidez, and Tommy Mobbs for their contributions to the present effort. Correspondence concerning this article should be addressed to Michael D. Mumford, Department of Psychology, University of Oklahoma, Norman, Oklahoma 73019. Electronic mail may be sent to [email protected].

course of action pursued but also other, more subtle aspects of performance such as learning (Kops & Belmont, 1985), motivation (Smith, Locke, & Barry, 1990), and teamwork (Weldon, Jehn, & Pradhan, 1991). Given this apparent impact of planning on performance, we must ask exactly why it has received so little attention. One answer to this question may be found in our stereotypic conceptions of planning. Mention the word planning, and images are called to mind of a robot executing a prespecified action sequence that provides little room for the adaptive flexibility that seems to characterize most high-level performance (Sternberg & Lubart, 1996a, 1996b). In the present article, however, we argue that planning is, in fact, an inherently adaptive activity, one more likely to promote than inhibit flexible reactions to a changing environment (e.g., Keane, 1996). Along related lines, we carry with us, as a field, a conception of planning that may be traced to the behaviorist models that dominated studies of human performance throughout the 1950s and 1960s. Within this framework, planning was conceived of as a somewhat rote assembly of predefined action sequences or scripts (G. A. Miller et al., 1960; Wilensky, 1983). We would not dispute the fact that response assembly represents one aspect of planning. By the same token, however, we argue here that it is not response assembly per se but, rather, cognitive operations that allow one to identify and 213


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construct viable response options that represent the core of planning. Planning in this sense can be described as the mental simulation of actions and their outcomes. These simulations, however, represent projections, projections that must take into account the complexity and dynamism of the environment in which the individual will act. Accordingly, we examine the kinds of cognitive capacities that make it possible for people to generate viable mental simulations, such as, goal identification, environmental analysis, specification of causes and consequences, and forecasting, all of which appear to play a role in planning. In addition, we present a model describing how the cognitive capacities operate together in an integrated planning effort. When planning is conceived of as the mental simulation of actions in a dynamic environment, a host of new questions about the nature and implications of planning come to fore. For example, the construction of these mental simulations is likely to be a demanding, resourceintensive activity. Thus, one might ask exactly what conditions require people to invest scarce cognitive resources in planning. The complex, tentative nature of plans as mental simulations, moreover, implies that planning performance is not assured and that errors will occur in planning. Thus, those of us interested in planning must ask the following: What makes planning performance possible? What errors are likely to occur in planning? And when is planning likely to prove useful? After examining available evidence on the cognitive capacities involved in planning, we turn to a series of questions about planning that might be subsumed under four broad rubrics. We begin by examining general parameters shaping planning performance, considering the characteristics of effective plans and the behaviors characteristic of successful planners. Next, we examine the characteristics of individuals as they influence planning performance and the effects of planning on individual performance capabilities. We then consider the kinds of situations that call for planning and the situational factors that influence performance in planning. Finally, we consider the kinds of errors people make in planning, along with available techniques for remediating these errors.

Planning Definitions Like many other complex phenomena, planning has been defined in different ways by different investigators. Read (1987), for example, defined planning as the selection and organization of actions to attain certain goals. Also stressing the importance of goal attainment, Simons and Galotti (1992) viewed planning as a process of mentally simulating potential methods of goal attainment, coupled with subsequent refinement of these simulations to minimize conflict among competing goals. In contrast to these goal-oriented views, McDermott (1978) conceived of planning as a problem-solving activity involving the identification and organization of subtasks, or performance components, to execute a problem solution. A similar conception of planning was presented by Chaiklin (1984), who defined planning as a set of instructions guiding problem solving. Although these two competing types of definitions differ in the emphasis placed on problem solving vis-a-vis goal attainment, they stress a common element: seeing planning as involving the mental simulation of actions (Heppner & Krauskopf, 1987). Recognition of this point led Hayes-Roth and Hayes-Roth (1979) to define planning quite simply as the predetermination of a course of action. In fact, most recent definitions of planning follow the Hayes-Roth and Hayes-Roth (1979) conception, holding that planning involves the active, conscious construction or mental simulation of future action sequences intended to direct action and optimize the attainment of certain outcomes (e.g., Anzai, 1984; C. R. Berger, Karol, & Jordan, 1989; Patalano & Seifert, 1997).

Models The notion that planning involves the mental simulation of future actions poses a far more fundamental question. Exactly what cognitive operations, or cognitive processes, are involved in this mental simulation? In an initial study along these lines, R. M. Berger et al. (1957) developed a series of 31 performance tests intended to measure key cognitive capacities that might be relevant to planning. This test battery included measures of temporal and hierarchical


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ordering, production of alternative methods, tributes to the successful planning of control specification of necessary details, recognition of operations. Evidence bearing on the importance of adaptrelevant causal variables, and identification of ability, or flexibility, in planning has been prodownstream consequences. For example, foresight, or the identification of downstream con- vided by Keane (1996). He presented undersequences, was assessed by tests that asked peo- graduates with stories summarizing a problemple to identify the conditions calling for use of solving plan before asking them to work on an object, route planning, and the consequences solving an analogous insight problem. Stories reflecting plans, however, were varied, not only of novel events. These tests, along with a battery of reference with respect to content but also with respect to measures, were administered to 364 Air Force the adaptability of the plan being presented; enlistees. A subsequent factoring of these tests adaptable plans were those more easily adjusted led to the identification of six factors that ap- to the target problem. It was found that people peared relevant to planning: (a) judgment, (b) were more likely to apply presented plans in solving insight problems if the presented plan perceptual foresight, (c) conceptual foresight, evidenced greater adaptability. A subsequent (d) ordering, (e) elaboration, and (f) adaptive analysis of solution content indicated, moreflexibility. Although this kind of exploratory over, that people's plans for solving these infactoring is subject to certain criticisms (Horn & sight problems stressed adaptation rather than Knapp, 1973), various studies of planning con- pragmatic outcomes. ducted over the last 40 years tend to provide Noice (1991) chose to study planning in a some support for the relevance of these factors (e.g., Kettner, Guilford, & Christensen, 1959; more naturalistic context. She asked novice and professional actors to learn short, six-page Robertson & Black, 1986). scripts and then recall script characteristics. A In one study along these lines, Byrne (1981) content coding of the recalled material indicated had people verbally report the actions involved that professional actors, unlike novices, learned in pastry preparation (making lemon meringue scripts by actively asking questions designed to pies and sherry trifles) and found that activities infer the character's plan with respect to various were ordered into interrelated sequences of ac- interactions as they unfold over time. Thus, this tivity, with pauses in reporting being longer as study seems to provide some support for the people moved from one chunk of activity to importance of elaboration in planning. another. Along similar lines, Franklin and Although other examples of this sort might Bower (1988) found that plans for joining a club be cited, the foregoing examples, in fact, sugwere organized, or ordered, in terms of temporal gest that the model of planning capacities procontingencies. Not only has evidence been proposed by R. M. Berger et al. (1957) is indeed vided for the need to order activities in terms of plausible. By the same token, however, factoreither temporal or event contingencies (Gaer- analytic identification of underlying perforling, 1996); evidence has accrued for the mean- mance capacities is only one approach that ingfulness of a number of other factors pro- might be used to identify the cognitive proposed by R. M. Berger et al. (1957). cesses involved in planning. One alternative The importance of judgment in planning has involves the use of cognitive theory to develop been demonstrated by Gaerling (1994, 1996). theoretical process models. Another alternative He used a variation on Hayes-Roth and Hayes- involves naturalistic observations of people's Roth's (1979) errand planning task in which the behavior when they are planning real-world conditions of task performance (e.g., imposition activities. of time constraints) were varied and found that Table 1 summarizes the processes identified people would change plans on the basis of task in 14 studies using a theoretical, empirical, or attributes (distance and wait time) and their mixed approach to identify the cognitive operimplications for performance requirements. An- ations involved in planning. The 10 theoretical zai (1984), using a reasonably realistic simula- studies presented in Table 1 display some tion of a ship piloting task, has shown that the marked differences resulting from the particular emergence of predictive and forecasting strate- form of planning of concern and the assumpgies, with the acquisition of expertise, con- tions made about the nature of planning. Even

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Table I Planning Process Models Model

Approach, assumptions, and key processes

Krietler and Krietler (1972)

Theoretical Goals and plans are embedded in environmental opportunities and influenced by individuals' imposition of meaning Build representation of environment, identify opportunities, gather information about opportunities, generate situational goals, construct initial plan, identify contingencies in goal attainment, adjust plan based on contingencies, monitor plan implementation Theoretical with confirmatory tests examining route planning Planning is an opportunistic process taking into account goals and local opportunities; holds that a number of interactive systems are involved in plan generation and plan adjustment Execute (define priorities), metaplan (define problem and policies), plan abstraction (formulate intentions and strategies), use knowledge base (apply information), plan (generate action outcome sequence) Theoretical with emphasis on development of planning skills Planning involves consciously preparing an action sequence to achieve a goal Define goal state, define problem state, note differences between problem and goal state, determine situational constraints on planning, formulate plan, execute plan, store plan in memory Theoretical with emphasis on error minimization Planning is a process of identifying a solution and managing contingencies Define objectives, generate alternatives, compare alternatives against objectives, generate plan, identify contingencies, revise plan, implement revised plan Theoretical based on planning managerial tasks Planning activities are goal oriented and involve searching for paths to goal attainment Goal identification, goal prioritization, objective selection, resource analysis, initial plan formation, contingency analysis and plan modification, generation of backup plans, adaptive implementation monitoring Theoretical with confirmatory tests examining recipe preparation Planning is a goal-based activity in which previous plans relevant to activated plans are drawn from memory and used to generate new plans wherein success and failure provide a basis for plan refinement Generate and evaluate goals, retrieve past plans associated with goals, modify past plans to fit local conditions, apply plan, evaluate plan success or failure, identify plan failure predictions Theoretical based on analysis of planning requirements Planning involves goal attainment within the constraints set by the contingencies confronting the individual in task performance Build representation of the environment, select goals, make decision about the need for plan, generate strategy, evaluate cost and benefits of strategy and revise plan, implement plan and monitor plan implementation, revise plan with contingency changes, reflect on plan Theoretical based on analysis of findings obtained in earlier studies of planning performance Planning is a goal-based performance activity requiring appraisal of the environment Goal elaboration, hypotheses formation, prognosis, implementation planning, monitoring and revision, self-reflection Theoretical based on performance within changing environment Planning is a goal-based activity but situated within an environment that can effect likely success Search for necessary means and approach, identify requisite preconditions for approach, estimate problems in reaching goals given time and conditions, organize actions into major operations, search for optimal sequence of operations, decide investment in open actions, generate plan, anticipate variations and complications, develop backup plans and markers for their application Theoretical based on analysis of performance in complex control systems Planning is a response to a dynamic, changing system intended to optimize control Allocate attention, observe system state, evaluate status of performance, create target state for system, formulate plan, execute

Hayes-Roth and Hayes-Roth (1979)

Pea (1982)

Woods and Davies (1973)

Lebedev (1989)

Hammond (1990)

Scholnick and Friedman (1993)

Doerner and Schaub (1994)

Brichin and Rachadzo (1995)

Bainbridge (1997)

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Table 1

(continued) Model

Bonissone et al. (1994)

Hill et al. (1995) This document is copyrighted by the American Psychological Association or one of its allied publishers. This article is intended solely for the personal use of the individual user and is not to be disseminated broadly.

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Hine and Gifford (1997)

Xiao et al. (1997)

Approach, assumptions, and key processes Qualitative, empirical based on observations of strategic planning organizations Planning occurs in a dynamic, changing environment and must integrate strategic and tactical considerations under conditions that permit a response to others' actions Monitor targets, evaluate goal attainment possibilities, generate strategies, project responses to strategy, adjust strategy to optimize outcomes, develop plan, implement plan, adjust plan based on outcomes of actions, reevaluate strategies and goals based on outcome Qualitative, empirical based on analysis of work flow planning Planning involves an optimal sequencing of activities to maximize efficiency Acquire information about cases, identify requirements and contingencies, identify relevant task performance scripts, formulate plan by adjusting scripts within a procedural structure, execute plan, monitor implementation Qualitative, empirical based on analysis of decisions in framing practices Planning involves consideration of economic trade-offs and is based on optimization of goal attainment with a dynamic context Identify goals, develop initial plan, monitor environmental contingencies, project likely actions-events and implications for plan, implement and adjust plan Qualitative, empirical based on performance of anesthesiologists Planning occurs within a context of preexisting knowledge wherein general rules specify optimal outcomes often crucial in planning Identify goals, identify constraints, identify options, identify outcome criteria, assess cues pointing to outcomes, define target end state, specify general procedures, construct plan, develop action rules for executing and adjusting plan, construct expectations about course of plan implementation, identify monitoring foci, identify and monitor cues for adjusting plan

bearing this caveat in mind, one must recognize certain similarities in the content of the planning processes identified. To begin, following Hayes-Roth and HayesRoth (1979), most of these studies assumed that multiple processes are involved in planning that interact with each other in a dynamic fashion. Many of these theorists, moreover—for example, Hammond (1990), Pea (1982), and Scholnick and Friedman (1993)—assume that planning begins with the activation or specification of certain goals and ends with analysis of the plan and subsequent storage of key components of the plan (e.g., success or failure, causes for success or failure, requisite action sequences, or relevant implementation requirements) in long-term memory. Three other commonalities apparent in these studies suggest that (a) some form of environmental analysis occurs before plan development that involves identification of resources, contingencies, and requirements; (b) plans are revised on the basis of forecasting of outcomes from initial plans; and (c) initial plans based on analysis of forecasted outcomes may be revised and backup plans generated.

In reviewing the four empirical studies of planning processes conducted by Bonissone, Dutta, and Woods (1994); Hill, Long, Smith, and Whitefield (1995); Hine and Gifford (1997); and Xiao, Milgram, and Doyle (1997), one finds some support for the propositions flowing from these theoretical efforts. These empirical studies, however, suggest three noteworthy extensions of the general theoretical structure sketched out thus far. First, after initial goal generation, a broad preliminary plan, or general model, may be formulated that is used as a basis for identifying key causes and projecting downstream consequences. Second, this prognostic activity, in keeping with the observations of Doerner and Schaub (1994), is often used in revision of the initial plan and generation of more detailed action plans. Third, as illustrated in Xiao et al.'s (1997) study of anesthesiologists, planning may involve the identification and monitoring of marker events for execution of backup plans, and time may be spent in marshaling resources or arranging the environment to support intended actions. The Xiao et al. (1997) study is of interest, moreover, because it seems to provide an un-


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usually comprehensive description of the cognitive operations involved in planning. This study involved detailed examination of 40 cases in which the anesthesiologists involved were asked to give a report before the case, "think aloud" and answer probe questions during the case, and comment on case transcripts a week later. Analysis of the resulting case material, with respect to decision flow, indicated that planning involved the identification of guiding rules applicable to the situation at hand and subsequent tailoring of general rules to the local situation, with plans being developed to take into account potential contingencies and problems that must be avoided during implementation. On the basis of these observations, it appears that planning requires generation of a prototype plan, projection of contingencies, revision and detailing of the prototype, and development and application of implementation guidelines. Within this framework, planning begins with environmental monitoring and needs assessment, followed by generation and prioritization of applicable goals. With goal identification, it becomes possible to identify the key steps and relevant contingencies needed to formulate a prototype plan. Given this prototype, key causes and contingencies operating in the local situation can be identified and the potential consequences of plan execution can be projected, leading to development of a revised, more detailed plan. With development of a more detailed plan, implementation issues can be ad-

dressed, including identification of marker events for monitoring, generation of backup plans, and acquisition of action support resources. In addition, periodic reevaluations and transformations of the planned activities may occur given progress made toward relevant goals. Finally, outcome information is appraised and stored for future use. Table 2 summarizes these operations in the context of a given planning episode. These operations are noteworthy, in part because they suggest that planning may involve the generation of multiple, progressively more detailed plans in which initial plans, or plan abstractions drawn from past experience, are used to identify and appraise environmental contingencies and probable outcomes. This provides a basis for the development of more detailed, situated plans. Of course, these observations not only underscore the need for capacities, such as elaboration and forecasting; they imply that knowledge may play a critical role in planning.

Knowledge Broadly speaking, three general approaches have been proposed to account for the use of knowledge in planning. One approach holds that the knowledge used in planning is based on scripts, or learned action sequences, activated on the basis of goal-relevant cues (e.g., Read, 1987; Schank & Abelson, 1977; Wilensky, 1983). The second approach holds that the use of knowledge in planning is primarily case

Table 2 Key Planning Activities Generation

Projection and revision

Implementation

1. Monitor environment—assess needs and opportunities 2. Generate and organize applicable goals 3. Identify key steps, major causal actions, and probable restrictions 4. Generate prototype plan

1. Identify manipulable causes and contingencies-restrictions operating in situation 2. Generate consequences of implementing plan in situation 3. Produce revised, more detailed plan tailored to situation

1. Use plan to generate evaluative marker events to guide monitoring 2. Generate backup plans to take into account problems identified in monitoring 3. Acquire resources needed for plan and critical backup plans 4. Implement plan and monitor markers 5. Reevaluate plan periodically 6. Adjust and transform plan to cope with event changes 7. Abstract key success and failure elements for use in future planning


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based (e.g., Alterman, 1988; Hammond, 1990). The third approach holds that plans are formulated on the basis of general rules, principles, or procedures (e.g., Cormier, Carlson, & Das, 1990; Xiao et al., 1997). In fact, the evidence compiled by C. R. Berger and Jordan (1992) tends to argue for use of a case-based approach in understanding how knowledge is applied in planning. They asked 72 undergraduates to generate plans for (a) requesting a date, (b) persuading someone to change his or her opinion, (c) ingratiating oneself to a roommate, and (d) becoming a millionaire. A think-aloud procedure was used to examine how undergraduates generated plans for each of these tasks. A subsequent content analysis indicated that the most frequently used forms of knowledge in generating plans were specific episodes, hypothetical episodes, ensemble episodes, and role models. Although the findings of C. R. Berger and Jordan (1992), along with other studies by Alterman (1988), Hammond (1990), and Hershey, Walsh, Read, and Chulef (1990), indicate that past cases linked to activated goals and relevant situational cues provide a basis for planning, this case-based model is not necessarily incompatible with other approaches. For example, cases may also be associated with relevant scripts applied in earlier planning efforts, and these scripts may be sorted, selected, manipulated, and ordered to provide a basis for the generation of more detailed plans after initial plan generation. Along similar lines, the evidence compiled by Blessing and Ross (1996), Reeves and Weisberg (1994), and Vollmeyer, Burns, and Holyoak (1996) suggests that, at least under certain conditions (e.g., when multiple cases are available, people engage in active processing, and means-ends analysis is not applied), people can abstract principles from cases. Thus, given adequate expertise, principles may be used, along with prototypic cases, in generating plans. This observation is consistent with the findings of Palmer and Drake (1997), Hershey et al. (1990), Sonnentag (1998), and Xiao et al. (1997), indicating that principles are applied by experts forming plans in domains ranging from musical performance to financial management and anesthesiology. However, often these principles seem to be applied in initial selection, or generation, of a

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prototype plan rather than in later phases of planning.

Planning Model Our foregoing observations about the use of cases in planning and the kinds of cognitive operations involved in planning paint a rather coherent picture of planning as a general phenomenon. One plausible model of how knowledge and cognitive processes operate together in the production of plans has been presented by Mumford, Schultz, and Osborn (in press). This model is illustrated in Figure 1. As noted earlier, plans are based on goals and the contingencies applying to goal attainment (Earley & Perry, 1987; Gaerling, 1994, 1996). To identify operable goals and contingencies on goal attainment, however, people must engage in some form of opportunistic environmental scanning or, alternatively, a directed search for goal attainment opportunities and constraints on goal attainment (Daft, Sarmunen, & Parks, 1988). After goals and applicable constraints on goal attainment have been identified, it becomes possible for people to begin forming a plan. Cases drawn from past experience provide an initial model, typically a rather general model, that represents a kind of seed point specifying both potential actions and the information that must be acquired to develop a more detailed plan applying in the local situation (C. R. Berger & DiBattista, 1992; Xiao et al., 1997). This elaborative search requires acquiring information bearing on (a) key causes operating in the situation; (b) the actions, or action sequences, needed to affect these causes; (c) operative restrictions that might limit the effectiveness of these actions; (d) actions that might be taken to affect those restrictions; (e) resources needed to execute these actions; and (f) critical outcome events, including negative events, that must be considered. With this information available, it becomes possible to formulate an initial situated plan; formationof this initial plan is based on modification of selected prototype cases (Hammond, 1990; Kuipers et al., 1988). It seems likely that construction of these initial situated plans proceeds through analogical reasoning mechanisms in which actions are ordered and structured to attain operative goals while satisfying the constraints imposed


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by identified contingencies, resources, and restrictions (Holyoak & Thagard, 1997). An initial situated plan, however, is not a final plan. Instead, an initial situated plan will provide a basis for forecasting the outcomes associated with alternative actions. In fact, studies conducted by R. M. Berger et al. (1957), Doerner and Schaub (1944), and Noice (1991) indicate that outcome forecasting plays a central role in plan refinement, serving to optimize outcomes, identify interdependencies and conflicts, organize and time actions, identify potential execution problems and backup plans, and specify markers for monitoring progress (Serfaty, MacMillian, Entin, & Entin, 1997; Xiao et al., 1997). These refinements will result in the formation of a fully situated plan that provides a basis for action. What must be recognized here, however, is that plan execution is not simply a lock-step implementation of a prespecified action sequence. Instead, plan execution appears to proceed in an opportunistic fashion involving both progressive refinement of the initial plan and exploitation of emerging opportunities consistent with this plan (Hayes-Roth & Hayes-Roth, 1979; Patalano & Seifert, 1997). In this sense, a plan provides a mental model for interpreting events occurring during plan execution while directing attention to key events that would indicate a need for "on-line" revision of the plan. Thus, Patalano and Siefert (1997) found that the availability of a plan led to more rapid recognition of emerging opportunities for goal attainment, whereas L. M. Ward, Snodgrass, Chew, and Russell (1988) found that recognition memory was greater for plan-relevant as opposed to plan-irrelevant information. This opportunistic adjustment process is feasible in part because of the strategy people apply in plan execution. Typically, plans are executed in chunks with sets of interrelated activities occurring in an organized sequence (Byrne, 1981; Franklin & Bower, 1988). This modular implementation, of course, permits ready readjustment after a given module has been executed. Moreover, search and evaluation may occur during these readjustment periods (Gronlund, Dougherty, Durso, & Canning, 2000). Having presented this overachieving model of planning, we now examine the implications of the model with respect to planning perfor-

mance. In the course of this effort, we consider what the model has to say about the nature of people's planning activities, taking into account the available literature. In our review, we consider evidence bearing on the nature of planning performance, the individual and situational factors that shape planning performance, and errors likely to occur in planning. Planning Parameters

What Is a Good Plan? As Smith et al. (1990) pointed out, the contributions of planning to performance are contingent on having developed a good, or highquality, plan. Two general approaches are commonly applied in assessing the quality of plans: (a) the plan characteristics approach and (b) the plan process approach. The plan characteristics approach examines objective features of plans and uses observed markers of these features as a basis for drawing inferences about the quality of a plan. The plan process approach, on the other hand, evaluates the quality of plans on the basis of underlying psychological processes held to lead to successful planning. Lebedev (1989) described the general kinds of characteristics used to evaluate plans in the plan characteristics approach. He argued that plans should be evaluated with respect to six general characteristics: (a) feasibility, (b) rationality, (c) flexibility, (d) detailedness, (e) depth, and (f) level. In fact, these output characteristics are frequently used to evaluate the quality of plans. For example, S. Krietler and Krietler (1987) assessed plans using output characteristics, such as the number of alternatives considered (flexibility), the number of steps in the plan (detailedness), the number of eventualities considered (depth), and the number of general labels applied (level). Along similar lines, in a study of group planning activities, Weldon et al. (1991) assessed efficiency—or, in Lebedev's (1989) terms, rationality—by measuring the number of times individuals returned to a storage box to obtain additional supplies when working on an object assembly task. Although the plan characteristics approach has been widely used in assessing the quality of plans, certain questions have been raised about the appropriateness of applying this approach. One criticism entails the limited evidence avail-


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able for the reliability and validity of measures of overt plan characteristics (Nurmi, 1989). Another, perhaps somewhat more trenchant criticism focuses on the construct validity of these measures. For example, D. S. Kirschenbaum (1985) noted that highly detailed plans may not always prove useful because of the difficulties associated with changing detailed plans in dynamic environments. Along similar lines, Liberman and Trope (1998) noted that the degree of detail called for in plans may vary as a function of where the individual is in the planning process, with more detailed plans proving beneficial later in this process. Recognizing these problems with the plan characteristics approach, the plan process approach attempts to assess the quality of plans by examining the nature or kinds of cognitive activities involved in plan development. Thus, in the plan process approach, performance in prognosis, identification of relevant causes, information acquisition, and constraint identification are used in evaluating the quality of plans (Doerner & Schaub, 1994; Eisenhardt, 1989). Doerner and Schaub (1994) measured planning quality by examining identification of pertinent causes. Smith et al. (1990), in a study of group planning, measured planning quality by assessing future orientation; analysis of strengths, weaknesses, and opportunities; and effective allocation of resources. Although the plan process approach offers certain advantages with respect to the construct validity of the resulting measures, evidence is not always available for the reliability and validity of these measures, nor has their superiority with respect to plan characteristics measures been unambiguously demonstrated. A notable exception to this general trend may be found in a study conducted by Isenberg (1986). He asked general managers and students to "think aloud" while working through a managerial case study calling for significant planning activities. Subsequently, the resulting protocols were coded for the presence of both plan characteristics (e.g., length of protocol and number of steps) and processes (e.g., contingencies, causes, and conditional reasoning). In a comparison of experienced managers and students, Isenberg (1986) found that overt plan characteristics, such as length and number of steps, did not differentiate managers and students in the expected fashion. In fact, experi-

enced managers tended to produce shorter protocols that contained fewer specifics. Instead, expert managers, as compared with students, stressed causes and contingencies, applied general models, and examined conditions bearing on the application of these models. Moreover, use of these elements in planning was more strongly related to external evaluators' assessments of plan quality than were overt plan characteristics. Although some caution is called for in evaluating the results obtained in a single study, Isenberg's (1986) findings do suggest that plans and plan quality are more appropriately evaluated in terms of key process characteristics. Thus, in evaluating plans, it may be more appropriate to consider attributes of the type presented in our planning model, such as resolution of goal conflicts, identification of contingencies, specification of relevant causes, and effective ordering of operations, than to evaluate superficial content characteristics of the plan. Moreover, it appears that successful, high-quality plans are those that take these process considerations into account.

What Behaviors Are Associated With Effective Planning? If it is granted that plans should be evaluated with respect to the capacities underlying performance, as opposed to superficial features, the question arises as to what behaviors mark effective planning performance with respect to these processes. Perhaps the most clear-cut conclusion to be drawn in this regard is that effective planners are efficient in organizing activities in relation to goals (H. B. Miller & Baird, 1972). For example, Hayes-Roth (1980; HayesRoth & Hayes-Roth, 1979) and Pea (1982) have argued that planning requires people to manage time in relation to goals. Successful planners not only optimize time allocation to different activities; they also prioritize activities on the basis of goals, look for activities that serve multiple goals, and actively assess the costbenefit trade-offs of different activities. In keeping with these cost-benefit propositions, Simons and Galotti (1992) found that effective planners tend to organize goals and distinguish high- and medium-priority goals from low-priority goals.


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The findings of Simons and Galotti (1992) are of interest because they suggest that successful planners not only organize their activities but also maintain flexibility in their activity organizations. Some support for this conclusion has been provided by Goldin and Hayes-Roth (1980). They found that successful planners tended to avoid early commitments to detailed action plans and specific goals, preferring to first explore the task, the opportunities presented, and the contingencies imposed. In addition to careful analysis of the planning context (Berg, Strough, Calderone, Sansone, & Weir, 1998), successful planning appears to require flexible, adaptive use of the models, or cases, drawn from previous efforts. This adaptive modification of plan models, in turn, requires the use of models that are neither highly abstract nor overly detailed (Hayes-Roth & Hayes-Roth, 1979; Kuipers et al., 1988). Instead, the use of midrange models that provide some general direction, albeit direction appropriate to the situation at hand, appears to contribute to performance. The value of applying midrange models in planning has been demonstrated by Patalano and Seifert (1997). They asked undergraduates to read a scenario in which they were to retrieve a set of objects from a friend's dormitory room. In some conditions, undergraduates worked without a plan; in other conditions, they were given plans that specified particular actions, were given plans that specified more general types of actions, or were asked to generate plans specifying the "kinds" or types of actions they would take. Subsequently, these undergraduates were presented with a list of objects that might be relevant to retrieving one of the goal objects. It was found that the use of midrange plans, as opposed to more specific plans, led to recognition of a wider range of opportunities for goal attainment. Moreover, self-generated plans produced somewhat better performance than given plans, a finding suggesting that active involvement in plan construction also leads to better performance. Another way the construction and application of midrange models contributes to performance is that they guide information search activities, and allocation of attention, to critical environmental contingencies (Bayster & Ford, 1997; Martin & Ewert, 1997). Use of actively constructed, midrange models may also influence

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the quality of people's plans by providing a framework for organizing activities in relation to sets of goals (Eisenhardt, 1989). Finally, these midrange models provide a reasonably cost-efficient, or manageable, basis for mental simulation of the outcomes of plan execution. Successful planners, of course, use these simulations as a basis for restructuring plans (Goldin & Hayes-Roth, 1980), taking into account a variety of factors, including the time and effort expended on goals, prerequisite resource requirements, and the merits of different activity orderings. Planning performance also appears to depend on the strategies applied in information search, as well as the use of midrange models. The effects of information search on planning performance are illustrated in a study by Berger and DiBattista (1992). They had undergraduates seek out target and situation information either before or after devising initial plans to reach one of two social goals. Across the two types of goals, it was found that the quality and diversity of the information acquired influenced planning performance but only when information was sought before initial plan generation. Information seeking before initial plan generation was related to both plan length and identification of relevant contingencies. Not only does the success of a plan depend on structured systematic information search; successful planners apparently use the information derived from search and simulation in certain specific ways. In one study along these lines, J. B. Thomas and McDaniel (1990) examined the strategic planning strategies of hospital chief executive officers. Using survey questions examining the environmental attributes considered in strategic planning, they found that the controllability of events influenced plan development, with successful planners focusing on controllable events. In addition to focusing on controllable or manipulable events, successful planners appear to (a) identify critical contingencies or restrictions applying in the situation (Xiao et al., 1997); (b) investigate the possibility of, and consequences in attending to, the removal of restrictions or changes in key contingencies (Richard, Poitrenaud, & Tijus, 1993); (c) construct plans through progressive, sequential refinements of an initial model (Earley & Perry, 1987; Kuipers et al., 1988); (d) develop backup


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plans to cope with probable changes in conditions, integrating these backup plans into more general approaches (Xiao et al., 1997); (e) adjust plans on the basis of contingencies calling for execution of backup plans (Doerner & Schaub, 1994); and (f) periodically scan the environment to identify emerging opportunities or new contingencies that call for the execution of backup plans or the revision and adjustment of current plans (Eisenhardt, 1989; Thomas, 1980). Individual Influences

Who Is an Effective Planner? These observations about the behaviors characteristic of successful planners broach a new question. What characteristics of the individual influence the expression of these behaviors? The Isenberg (1986) study described earlier provides some important clues in this regard. More specifically, it appears that the ability to develop usable, high-quality plans depends on expertise. Some support for this conclusion has been provided by Hershey et al. (1990). They identified two extreme groups with respect to financial planning expertise using measures of domainrelevant knowledge and occupational reputation. Think-aloud protocols were obtained as members of these two groups worked through a plan development problem asking how a young person should invest in an individual retirement account. Comparison of these groups indicated that experts, as opposed to novices, took less time in plan development and requested less information. Experts, however, appeared to focus more on goal-relevant information, applying available models linked to these goals as a basis for plan development. Experts' efficient use of preexisting models in planning has also been observed among computer programmers. Sonnentag (1998) compared 12 high and 12 low performers on a software design task. Verbal protocols, visualization data, and knowledge about strategies were assessed as programmers worked a software development plan to address a lift control problem. In keeping with the findings of Hershey et al. (1990), it was found that experts, as compared with novices, took less time to solve the plan development problem and requested less information about requirements. Experts,

however, were more likely to use visualization techniques and general strategies, apparently applying extant models that were tailored to the goals of the problem at hand through "local" planning occurring after relatively rapid selection of a general approach. Thus, it appears that expertise provides people with a series of planning models along with an awareness of the environmental contingencies that influence how these models must be reshaped and re-formed in the local situation. This conclusion is, of course, consistent with both the role of case-based knowledge in planning (Hammond, 1990) and the kinds of processes by which knowledge is applied in planning (Xiao et al., 1997). By the same token, however, it should be recognized that expertise may have a number of other effects on planning. First, availability of the complex, principlebased knowledge structures characteristic of experts (Chi, Glaser, & Rees, 1982) apparently allows people both to identify key contingencies applying in a situation and to make accurate predictions about the probable consequences of different actions (Abernathy, Neal, & Koning, 1994; S. S. Kirschenbaum, 1992; Saariluoma & Hohlfeld, 1994). Second, experts, relative to novices, are more likely to attend to important structural considerations in monitoring and more likely to recognize structural as opposed to execution errors and to change strategies on the basis of error identification (Palmer & Drake, 1997). Third, experts, by virtue of having a larger range of representations available, are apparently able to generate more elaborations and more alternative orderings (Noice, 1991). Fourth, experts may show better judgment than novices when choosing among alternatives (Baltes, Staudinger, Maercker, & Smith, 1995). Finally, the use of available principles and strategies by experts may allow them to more rapidly identify and exploit emergent events (Patalano & Seifert, 1997). These complex effects of expertise on planning performance are illustrated in a study by Kuipers et al. (1988). They obtained thinkaloud protocols from expert physicians as they worked on a series of "real-world" treatment planning scenarios. In addition, cross-examination protocols were obtained. These protocol data were then analyzed with respect to decision requirements. It was found that experts formulated plans iteratively, applying rules that took


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into account key outcomes. Estimates of the tive approach to environmental contingencies status of patients with regard to these rules, and constraints. Another way these disposihowever, were assessed against well-known ex- tional characteristics might influence planning, amples that provided benchmarks for making however, is by encouraging people to attend decisions during plan formulation. Thus, exper- to, and adjust, their actions on the basis of tise in planning may depend on having appro- information bearing on relevant goals and priate benchmarks available as well as viable contingencies. Some support for this interpretation may be principles and strategies. Along similar lines, Anzai (1984) examined planning in a complex found in a recent study by Berzonsky, Nurmi, piloting task. In this study, expert-novice com- Kinney, and Tammi (1999). They asked Finnish parisons were made, and the resulting infer- and American adolescents to complete a selfences were tested through use of a simulation. report measure examining informational, norThe results obtained in this study indicate that mative, and diffuse-avoidant identity processexperts apply long-term goals in planning, with ing orientations or problem-solving styles. expertise in planning ship movements emerg- These undergraduates were also asked to coming as people grasp key causes and lags in plete a measure (reflective thinking) examining the use of planning as a coping strategy. It was causation. Although expertise is clearly an important found that the people evidencing informational, factor shaping the capacity for planning, it is as opposed to normative and diffuse, identity certainly not the only variable that might be processing styles were more likely to use planrelevant. For example, in a study of leaders' ning as a coping strategy. Other studies by planning skills, Zaccaro, Connelly, Mumford, D'Zurilla and Nezu (1990) and Norman, ColMarks, and Gilbert (2000) found that intelli- lins, Conner, Martin, and Ranee (1995) indicate gence was related to performance on planning that this kind of problem-focused informationexercises. Not only do basic cognitive abilities, processing style is also related to better decision such as intelligence, influence the quality of making and more effective adaptation to both people's plans; it also appears that generation of job and academic settings where planning is a viable plans depends on whether people possess significant component of performance. requisite domain-specific skills. For example, in the case of musicians, requisite domain-specific How Does Planning Contribute skills, such as eye-hand coordination, may in- to Performance? fluence both the nature and success of planning efforts (Palmer, 1997). In this regard, however, Just as certain characteristics of the individit is important to recognize that virtually no ual contribute to planning, one might ask how studies have been conducted examining the planning on the part of individuals contributes specific mechanisms by which general abilities to subsequent task performance. Planning, in and domain-specific skills shape planning per- fact, appears to influence performance in five formance. Thus, these capacities may exert ways: (a) It contributes to more effective probboth direct and indirect effects, exercising their lem solving; (b) it promotes learning; (c) it influence through intervening mechanisms enhances motivation; (d) it facilitates adaptasuch as expertise acquisition and attentional tion; and (e) it enhances coordination. In the allocation. ensuing discussion, we examine each of these In addition to general cognitive abilities, a performance outcomes. variety of dispositional characteristics have Problem solving. One important contribubeen shown to be related to planning. Among tion of planning to performance is that plans the dispositional characteristics that appear provide a mental model, or a cognitive repremost important are openness or flexibility sentation, of the problem, delineating key is(Showers & Cantor, 1985), self-efficacy (Lar- sues, relevant strategies, and expected outson, Piersel, Imao, & Allen, 1990), internal lo- comes. Accordingly, in a study comparing succus of control (Lachman & Burack, 1993), and cessful and unsuccessful problem solvers on optimism or agreeableness (Norem & Illing- arithmetic word problems, Hegarty, Mayer, and worth, 1993). Of course, all of these character- Monk (1995) found that construction of plans istics might operate by inducing an open, adap- led to better problem solving. Not only does


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planning appear to contribute to performance on the problem at hand; it may also make transfer more likely. In one study examining transfer effects, Catrambone (1995) found that delineating and labeling subgoal steps in examples contributed not only to problem solving but also to transfer. Apparently, planning promotes more effective problem solving by organizing problemsolving activities in a flexible representational system. Planning, however, may contribute to problem solving in at least five other ways. First, planning may reduce resource demands by organizing problem-solving activities into chunks that can be executed more efficiently (G. Ward & Allport, 1997). Second, planning may encourage people to identify and attend to key information needed for problem solving (O'Brien & Albrecht, 1992). Third, planning may help people develop viable problem representations and identify cues needed to guide their problem-solving efforts (Gollwitzer, 1999). Fourth, planning may lead to the generation and application of more efficient information search strategies (S. S. Kirschenbaum, 1992). Fifth, by providing a broader organizing structure, planning may facilitate the storage and recall of information (Goschke & Kuhl, 1993). In fact, L. M. Ward et al. (1988) provided a rather compelling demonstration of the effects of planning on memory. In their study, undergraduates were to enter a room with instructions to plan to redecorate it, plan to hide something, or wait for the experimenter. It was found that both recognition and recall of objects in the room, particularly plan-relevant objects, were higher in the two planning conditions. Learning. The effects of planning on problem solving would lead one to expect that planning might contribute to learning through the active acquisition, organization, and elaboration of information. Studies examining student characteristics provide some support for this proposition. For example, Kops and Belmont (1985) found that good and poor students differed in planning skills, whereas Schofield and Ashman (1987) found that gifted students differed from their less gifted counterparts with respect to the use of higher level, more complex planning strategies. Perhaps the most comprehensive set of studies of planning and learning has been conducted by Das, Naglieri, and their colleagues (Das & Heemsbergen, 1983; Naglieri &

Das, 1987; Naglieri, Das, & Jarman, 1990; Naglieri, Das, Stevens, & Ledbetter, 1991). These studies, based on Luria's (1966) work, have used a scoring of the Wechsler Adult Intelligence Scale (WAIS) to assess planning skills: specifically, successive and sequential planning. The findings obtained indicate that measures of these planning skills yield moderate (r = .30) positive correlations with measures of academic achievement. Although some caution must be exercised in interpreting these findings, given the controversy surrounding the WAIS scoring system being applied (Keith & Kranzler, 1999; Naglieri, 1999), it does appear that planning can contribute to learning. One illustrative study is that of Cormier et al. (1990), who compared good and poor planners under conditions calling for plan verbalization. They found that verbalization, by encouraging active plan articulation, led to better performance by poor planners on Raven's progressive matrices problems. Along similar lines, Trabasso, Stein, Rodkin, Munger, and Baughn (1992) found that children's learning was improved by exploratory questions intended to frame event interpretations in terms of goals and plans. Thus, in accordance with Zelazo, Carter, Reznick, and Frye (1997), it seems reasonable to conclude that planning can, at least at times, contribute to learning, although more research is needed examining the mechanisms by which this occurs. Motivation. Planning's effects on learning, however, may not be purely cognitive but instead may involve some element of motivation. Gollwitzer (1999) has argued that a plan may be viewed as a form of intention. In a series of studies intended to examine the effects of planning on motivation, Gollwitzer and his colleagues (e.g., Gollwitzer, 1999; Gollwitzer & Brandstatter, 1997; Gollwitzer & Kinney, 1989; Schaal & Gollwitzer, 1999) found that plan intentions result in people being more likely to (a) start a project, (b) complete difficult projects, and (c) not become distracted when working on a project. The work of Gollwitzer and his colleagues (e.g., Gollwitzer, 1999) stresses the direct effects of planning on motivation. However, it should be recognized that planning may also have a number of more complex, indirect effects on motivation. Planning's indirect effects on motivation include clarification of paths to


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goal attainment; clarification of goals; specifi- mance: providing a basis for the communication cation of specific, attainable goals; and active of objectives and the coordination of activities involvement of the individual in the goal-setting (Agre & Chapman, 1990; Leudar & Costall, process. As pointed out by Cervone, Jiwani, and 1996). In one study along these lines, Weingart Wood (1991); Hollenbeck, Williams, and Klein (1992) examined group performance in building (1989); and Smith et al. (1990), these second- Tinker Toy structures under conditions in which order effects may make planning a particularly task complexity and goal difficulty were manipulated. She found that complexity and difficulty powerful influence on motivation. Adaptability. In addition to its effects on led to more coordinated planning, and higher problem solving, learning, and motivation, quality planning, among group members. In anplanning may have a number of somewhat more other study examining the use of materials in subtle effects involving the enhancement of construction activities, Weldon et al. (1991) anadaptability. In one study along these lines, alyzed the content of group discussions and Oswald, Mossholder, and Harris (1997) exam- found that planning mediated the impact of goal ined how the availability of strategic plans in- setting and goal difficulty on group perforfluenced managers' perceptions of and reactions mance, with planning contributing to the attainto their environment. They found that the avail- ment of difficult group goals. Thus, planning ability of plans made managers more aware of may play a central role in organizing perforcompetitive strengths and weaknesses, suggest- mance in team settings by promoting commuing that plans may engender a more analytical nication, coordination, effective use of reappraisal of environmental events while encour- sources, role definition, and role integration aging individuals to identify and exploit emerg- (Hjelmquist, 1990; Waldron & Applegate, ing environmental opportunities (Gollwitzer & 1994). Kinney, 1989; Sanbonmatsu & Fazio, 1990). In keeping with these propositions, J. B. Thomas Situational Influences and McDaniel (1990), in still another study of strategic planning, found that plan availability When Is Planning Useful? influenced the range and relevance of the environmental information being considered. The general description of planning preIn addition to its effects on environmental sented here leads one to an obvious, but perhaps appraisal, planning may have two other note- critical, conclusion. Planning, whatever its worthy implications for adaptation. First, stud- contributions to individual performance, is a ies of prospective memory (recognition of op- resource-intensive activity calling for enviportunities for goal completion with emerging ronmental appraisal, goal appraisal, continenvironmental opportunities) indicate that plan- gency projection, interactive plan development, ning, particularly when people periodically re- and monitoring (Hewes, Graham, Monsour, & vise and update plans, promotes recognition and Doelger, 1989). This observation, in turn, poses exploitation of new opportunities for goal at- a new question: When is it in the individual's tainment as well as adaptive reprioritization of best interest to make an investment, potentially tasks (Kliegel, McDaniel, & Einstein, 1999; a substantive investment, of cognitive resources Marsh, Hicks, & Landau, 1998). Second, the in planning? evidence compiled by Xiao et al. (1997) sugIn a recent study intended to address this gests that this active, directed environmental issue, O'Hara and Payne (1998) examined the monitoring may contribute not only to the de- conditions under which people are likely to velopment of backup plans but also to their invest resources in planning. They asked undertimely, and efficient, execution in relation to graduates to work on an eight-panel puzzle task changing environmental contingencies. in which the requisite investment in planning Coordination. Performance, of course, is was manipulated by varying cost, or difficulty, not always a simple matter of individual through command length and number of moves achievement. Often, people must work in team required. They found that planning stopped or organizational settings to accomplish rele- early in the low-cost condition (e.g., short comvant objectives. In team settings, however, plan- mand length and few moves) because expected ning may have still another impact on perfor- improvements in performance did not offset the


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costs involved in planning. In a series of follow-up studies, it was found that planning-related utterances were less frequent in the lowcost condition, whereas learning increased in the high-cost condition in which planning was required. Thus, people appear more likely to engage in planning on difficult tasks in which associated performance gains outweigh costs. Some support for this conclusion has been provided by Gardner and Rogoff (1990). They presented maze problems to children ranging in age from 4 to 9 years. The demands made on this task were manipulated by varying the difficulty of route search. The need for accuracy was manipulated through conditions engendering a speed-accuracy trade-off. Consistent with the findings of O'Hara and Payne (1998), route search difficulty increased the amount of planning observed. Further, more planning activity was observed in conditions calling for accuracy as opposed to speed. Time pressure, of course, makes it difficult to apply the kinds of resourceintensive cognitive processes involved in planning, whereas the need for viable solutions may place a premium on planning. Although task difficulty and solution quality requirements appear to engender planning, a number of other variables also seem to influence people's willingness to invest cognitive resources in planning. For example, one might argue that planning is more likely to occur when people are motivated to invest effort in task performance. In keeping with these observations about motivation, S. Krietler and Krietler (1987) found that activation of personally meaningful goals in task performance led to greater and more extensive planning. Somewhat more compelling evidence bearing on the role of motivation in planning has been provided by Smith et al. (1990). They asked business students to work in groups on a management simulation exercise. Motivation was manipulated by providing charts to half of the groups that specified difficult, challenging output goals; the remaining groups were simply instructed to do their best. The quality of the groups' plans was assessed through a processoriented measure given to the person assuming the management role in each group. It was found that planning quality, as assessed by this process measure, was positively correlated with the presence of specific challenging goals (r = .48). Other work by Earley and Perry (1987)

also underscores the importance of challenging, motivating goals in determining investment in planning. In addition to motivation, however, a number of other conditions act to shape people's willingness to engage in planning. Johannsen and Rouse (1983), in a study of pilots' planning activities, found that planning depth and quality were likely to be higher when people had to manage multiple events. Their findings also suggested that planning is more likely to occur if (a) a large amount of time must be invested in the performance, (b) the planning activities are critical to obtaining broader objectives, and (c) there is not strong environmental or technical support available for performing the task. A similar point has been made by Castrogiovani (1996), who argued that planning is more likely to occur among entrepreneurs when substantial environmental support is not available and when a high degree of uncertainty surrounds the enterprise. Thus, planning is more likely to occur when external resources cannot be relied on and uncertainty surrounds critical, time-consuming efforts, conditions in which planning may play a key role in ensuring success. Some support for this argument has been provided by J. W. Dean and Sharfman (1996). They examined 52 strategic decisions in 24 companies by asking participants in the decision process to complete a set of retrospective behavioral descriptions. Other measures considered the strategic environment confronting the organization as well as procedural rationality and politics. They found that the implementation of viable plans was linked to procedural rationality but not politics, with environmental turbulence, or uncertainty, contributing to the need for planning. With regard to uncertainty, however, an important caveat seems in order. McCaskey (1974) argued that, under conditions of extremely high uncertainty induced by rapid environmental change, inadequate information, or unclear causation, effective planning may prove difficult if not impossible, leading people to limit investment in planning. Along similar lines, one might argue that high degrees of goal conflict and goal ambiguity may also prohibit devoting substantial resources to planning (J. W. Dean & Sharfman, 1996). These observations suggest that planning may prove more beneficial under moderate, as opposed to very


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while leading people to focus on immediate practical difficulties in plan execution. These effects of time pressure on the use of higher level cognitive functions may also limit the adaptability of plans (Carstensen, Isaacowitz, & Charles, 1999). Stability. Of course, in dynamic, highly unstable environments, planning must be sensitive to emerging opportunities and constraints. Broadly speaking, when confronting an unstable, dynamic environment, people must rely on more general models in developing plans, and planning can be expected to be a more cognitively demanding activity relying on principles What Situational Factors Are Associated and approaches rather than specific action orWith Successful Planning? dering (Pava, 1986). In a naturalistic case study Our foregoing observations with regard to the examining how people cope with instability and need for planning under certain conditions also uncertainty in planning complex events, specifsuggest that certain characteristics of the situa- ically the Olympics, Lowendahl (1995) found tion will influence the nature and success of that planning often proceeded as an interrelated people's planning efforts. Indeed, situational set of subplans organized on the basis of a factors, such as the salience of certain goals and broader model; subplans were executed opporconstraints, as well as known interdependencies tunistically as conditions emerged that permitamong various environmental events, appear to ted plan development and execution. This ininfluence the content of people's plans. Al- cremental execution strategy may, in fact, be though a variety of situational factors might essential in dynamic, unstable environments influence people's planning activities, most where forecasting becomes difficult and key studies of situational factors influencing plan- contingencies, resources, and goals are subject ning performance have focused on one of five to change. key variables: (a) time, (b) stability, (c) diffiDifficulty. In addition to time and instabilculty, (d) workload, and (e) support systems. ity, planning also appears to be influenced by Time. Time considerations exert a complex the difficulty, or complexity, of the task at hand. set of effects on planning, operating as a per- Typically, as the number and complexity of formance constraint, a goal, and a set of event actions increase, the time required between regularities around which plans are organized steps increases, suggesting that more processing (Bluedorn & Denhardt, 1988). In their study of and attentional resources will be called for on errand planning, Hayes-Roth and Hayes-Roth difficult planning tasks (Spitz, Minsky, & (1979) found that both time constraints and Bessellieu, 1984; Welsh, Cicerello, Cuneo, & temporal event contingencies influenced the Brennan, 1995). Difficulty and complexity, strategies people applied in planning. In a re- however, may exert a number of somewhat lated study involving a similar errand planning more complex effects on planning. For examtask, Gaerling (1994) found that when time ple, C. R. Berger et al. (1989) found that the minimization constraints were removed, people need for more complex plans led to loss in terms would consider other aspects of efficiency, such of both access to key plan components and the as wait time, and would focus activities on the fluency with which a plan (in this study, comremoval of constraints that would enhance later munication plans) could be executed. Along performance. Thus, time constraints appear to similar lines, one might expect that complexity take precedence over other requirements in would make identification of relevant causes, planning, potentially limiting the complexity management of contingencies, and ordering of and effectiveness of the resulting plans. In fact, activities more demanding and time consuming. Liberman and Trope (1998) have found that Workload. Increases in difficulty and comtime pressure, induced by temporal nearness, plexity increase workload. Workload, however, limits the use of higher level cognitive strategies can also be affected by other components of

low or very high, conditions of uncertainty. In this regard, however, it should be recognized that certain effects of planning on performance, including opportunity recognition, enhanced environmental monitoring, better coordination, and more rapid response generation, may result in planning having some value under conditions of high uncertainty, particularly if planning is carried out at a macro, prototype level rather than a more micro, detailed level (Crossan, Lane, White, & Klus, 1996; D. S. Kirschenbaum, 1985; Pava, 1986).


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performance such as the need to carry out other activities, operator control requirements, stress, and the individual's skill in executing requisite activities. High workload conditions may stimulate planning as a workload reduction strategy (Johannsen & Rouse, 1983). High workload, however, may also decrease the coherence of plans, the range of information considered, and the use of high-level cognitive strategies (Penningroth & Rosenberg, 1995). The effects of high-load conditions on planning, moreover, may vary as a function of where high-load conditions occur in the planning process, with more debilitating effects being observed during the initial plan development phase as opposed to the later implementation phase. Support systems. One final situational factor that consistently appears to influence the nature and success of people's planning activities is the availability of social and technical support systems (B. V. Dean, 1958). For example, R. M. Taylor, Finnie, and Hoy (1997) examined the effects of aviation planning support systems on pilot performance. They found that support systems enhanced situational awareness, reduced workload, and improved prediction. These gains, however, were offset by an undue reliance on the support system causing pilots to miss salient changes in the performance context. Along similar lines, C. R. Berger et al. (1989) found that having others ask questions about plans increased plan length and complexity but, by the same token, decreased execution fluency. Thus, the effects of support systems on planning may be quite complex, requiring the tailoring of support interventions to the unique issues impinging on performance within the setting at hand. Errors

What Errors Are Likely to Occur in Planning? In keeping with the impact of time constraints on planning performance, studies examining planning errors have focused on estimation of the time needed to complete requisite activities. In an initial investigation along these lines, Hayes-Roth and Hayes-Roth (1979) found that people tended to underestimate the time required to complete planned activities. Josephs and Hahn (1995) examined the existence of bias

in task time estimates on various academic tasks (e.g., writing and reading manuscripts) and, like Hayes-Roth and Hayes-Roth (1979), found that people tended to underestimate task completion times in planning. Not only do people underestimate the time needed to complete their own work; Hinds's (1999) findings indicate that experts underestimate the time novices need to complete a task. These time estimation errors become more pronounced when financial incentives are provided for rapid performance (Byram, 1997) and when people minimize the cognitive effort devoted to planning (Josephs & Hahn, 1995). The question posed by these findings is whether techniques can be found that will reduce estimation errors. Studies conducted by Byram (1997) and Hinds (1999) have examined the effectiveness of various debiasing techniques in self-estimations and others' estimations of performance times. In both of these studies, it was found that use of debiasing techniques, including decomposition, surprises, multiple scenarios (e.g., optimistic, best guess, and pessimistic), and list generation, seemed to have little effect on time estimation errors. One potential explanation for the persuasiveness of estimation errors is the use of anchoring strategies (Josephs & Hahn, 1995). Another potential explanation for these estimation errors may be found in a multiple-study investigation conducted by Buehler, Griffin, and Ross (1994). In an initial study, they asked undergraduates to "think aloud" as they described a school project they were to complete over the next 2 weeks. A content analysis of the resulting protocols for likely progression, potential impediments, prior successes, prior failures, others' experiences, personal disposition, and deadlines indicated that most responses focused on likely progression toward success rather than impediments. In a subsequent experimental study, it was found that temporal estimation errors could be eliminated by presenting priming questions in which students were asked to recall relevant past experiences before generating predictions about the time needed to complete an academic task. Thus, it appears that people's estimates of completion times may be based on the use of idealized cases that result in a tendency to discount the kinds of problems likely to be encountered in plan execution.


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Time estimation errors are not the only concepts to another (Palmer & Van de Sande, errors observed in planning. For example, 1995). In appraising the implications of planning Langholtz, Gettys, and Foote (1994, 1995) asked United States Coast Guard personnel errors, however, it is important to bear in mind to work on a task in which they were to a point made by Johnston, Driskell, and Salas schedule the operation of two patrol boats (1997). They noted that the nature of the task to having different fuel and personnel require- be performed and the conditions of task performents. As people were working on these sim- mance may, at times, result in planning strateulations, manipulations were made to increase gies that are apparently suboptimal, proving or decrease the availability of personnel. It adaptive. Accordingly, in a study comparing was found that people did not allocate re- vigilant decision makers, people conducting a sources effectively with respect to either un- thorough systematic information search, and anticipated gains or unanticipated losses in hypervigilant decision makers, people conductpersonnel. Thus, it appears that errors may ing a rapid selective search, they found that occur in planning as a result of assumptions under conditions of stress and time pressure, about the stability of resources, causes, and hypervigilant decision makers evidenced better performance than vigilant decision makcontingencies. Of course, these assumptional errors suggest ers. These observations seem consistent with that errors might also arise as a result of the Boudes and Cellier's (1996) findings indicating kinds of problems people encounter in execut- that air traffic controllers evidenced planning ing requisite processing operations. In keeping biases, overestimating horizontal speed, that with this proposition, Doerner and Schaub had the effect of reducing certain high-risk (1994) found that the processes involved in events: plane crashes. planning led to a consistent set of errors based on (a) failure to balance contradictory goals; (b) Can Planning Errors Be Remediated? selective, self-confirming acquisition of information; (c) oversimplification of causal relaEven bearing in mind this caveat with regard tionships; (d) failure to take into account non- to the potential adaptive value of certain errors, linear relationships; (e) discounting of side ef- in many cases it would seem desirable to find fects and negative downstream consequences; techniques that might be used to minimize the (f) failure to monitor lagged outcomes; and (g) occurrence of these errors. As noted earlier, in premature action when confronted with loss. the case of time estimation errors, the available In addition to process-based errors, errors evidence does not indicate that these errors can may emerge in planning as a result of the nature be easily remediated. However, it is possible of the knowledge being applied. Bastardi and that interventions can be designed to remediate Shafir (1998) and Hershey et al. (1990) found at least some process and knowledge use errors. that expert financial planners were subject to the Among the interventions that have been proerror of applying available, well-rehearsed posed, one finds a wide range of error remediamodels even when they were not the most ap- tion strategies, including (a) anticipation of popropriate models for application in the situation tential problems and key contingencies (Woods at hand. Use of inappropriate models, moreover, & Davies, 1973), (b) mathematical modeling may lead people to search for irrelevant infor- (Lind & Larsen, 1992), (c) social judgment mation that can inadvertently bias planning and analysis (Orphen, 1987), and (d) evaluation of decision making. Orasanu, Martin, and Davison plans based on probable outcome scenarios (1998), in a study of pilot errors, also stressed (Lundberg, Hartman, & White, 1991). the role of knowledge, noting that selection of Although all of these techniques seem plauinappropriate representations contributes to ac- sible, strong evidence bearing on their ability to cidents in aviation. Moreover, it appears that the improve planning performance is not available. timing of errors may be conditioned by the A notable exception, however, may be found in knowledge structures being applied in plan gen- question-driven reasoning (Graesser, Baggett, eration. Typically, both preservation and antici- & Williams, 1996), a technique intended to patory errors are more likely to occur as indi- articulate potential problems and key continviduals make the transition from one set of gencies. Schwenck and Cosier (1980) used


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question-driven reasoning to improve financial planning performance. In an undergraduate sample, they compared four question-driven reasoning techniques: (a) dialectical inquiry involving comparison of a plan and counterplan, (b) neutrally worded expert plan critiques, (c) emotionally worded plan critiques, and (d) review of expert reports about the plan. They found that dialectical inquiry and the availability of neutrally worded plan critiques contributed to the production of higher quality plans, apparently by articulating assumptions and key contingencies. Despite the evidence garnered in this study for the potential value of at least one error remediation technique, caution is called for in generalizing these findings to real-world settings. The findings obtained by Hartman, Lundberg, and White (1993) suggest that people may not be willing to routinely apply cognitively demanding error remediation techniques, such as dialectical analysis or scenario analysis, in planning real-world tasks. Moreover, introduction of these techniques may need to be carefully timed in terms of an individual's position in a general cycle of planning activities. In an extensive series of studies, Gollwitzer (1999), Gollwitzer and Kinney (1989), and S. E. Taylor and Gollwitzer (1995) found that deliberation, or controlled conscious analysis, occurs before plan implementation, with plan implementation being characterized by a more action-oriented, optimistic mind-set. Thus, the kinds of cognitive, analytic interventions likely to prove effective in remediating errors may need to be introduced early in people's planning efforts, during initial plan development and refinement, if they are to make a real contribution to performance. Conclusions Before turning to the broader implications of this review, it would seem germane to consider a limitation of the approach applied herein. In the present effort, we have expressly focused on the nature of planning as it influences performance. Thus, certain aspects of planning, such as the early development of planning capacities (e.g., Zelazo et al., 1997) and the relationship between planning and decision making (e.g., Paquette & Kida, 1988), have received only scant attention. As a result, the present effort should not be viewed as an all-encompassing

analysis of planning. By the same token, however, this review does suggest that planning has a persuasive, complex influence on performance and, at least in some situations, may play a critical role in shaping performance. Planning is apparently a crucial aspect of performance when people are confronted with complex, dynamic, demanding tasks in which coordination of activities is required for goal attainment. Accordingly, one might expect planning to have a pervasive impact on performance across a range of situations. Indeed, in the present review, planning was found to influence performance in management (Isenberg, 1986), music (Palmer, 1997), medicine (Kuipers et al., 1988), and academics (Josephs & Hahn, 1995). Not only is planning a significant aspect of high-level performance in a number of domains; by virtue of its multifaceted, complex influences on performance, as evidenced in its effects on problem solving, learning, motivation, adaptability, and coordination, planning represents a pervasive and unusually powerful influence on performance. The apparent effects of planning on performance, however, bring to fore another question: Exactly how do people go about planning? Although a number of models of planning have been proposed over the years, the evidence examined in this review paints a reasonably coherent picture of the cognitive operations involved in planning. Like most other complex cognitive activities, planning appears to depend on knowledge and expertise (Hershey et al., 1990; Sonnentag, 1998). However, the use of expertise in planning appears to rely on casebased reasoning (Hammond, 1990). Cases drawn from past experience are used to form initial models and direct environmental analyses examining causes, resources, restrictions, and contingencies. These initial plans, in turn, provide a basis for mental simulations. Forecasting the consequences and results of plan execution leads to the refinement of initial plans to cope with performance contingencies operating in the environment, including contingencies that might arise from changes in the conditions shaping performance. Thus, people do not create a single grand plan but, instead, create a series of progressively more complex and detailed plans that may be used to guide action under a number of different conditions (Earley


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& Perry, 1987; Vye, Goldman, Voss, Hmelo, & Williams, 1997). This characterization of the planning process has a number of implications. To begin, planning is a demanding, resource-intensive process and, therefore, may not prove especially useful on simple, undemanding tasks in which wellrehearsed scripts are available. Planning performance, furthermore, will depend on the individual's capability for complex cognitive analysis, being influenced by individual factors (e.g., expertise, intelligence, and openness) that promote active cognitive processing as well as situational factors (e.g., time constraints, difficulty, and workload) that influence the resources available for cognitive processing. These observations, of course, simply that a host of individual and situational factors might influence performance in planning. In fact, studies of errors in planning indicate that planning performance can be disrupted by a number of variables related to both relevant individual and situational factors, including failure to consider alternative models, inability to identify key causes, and failure to spend adequate time organizing goals and analyzing situational contingencies. Planning errors, however, may also reflect certain unique biases linked to the fundamental nature of planning. For example, time is a general constraint on most, but not necessarily all, planning activities, and time constraints influence not only the strategies applied in planning but also the kinds of errors observed. Along similar lines, planning is inherently a goal-directed activity, and characteristic biases associated with the processing of goal-relevant information, such as failure to take into account loss, apparently influence the nature and success of planning activities. Thus, planning performance may evidence a unique set of errors, or performance restrictions, that extend beyond traditional decision-making biases. Indeed, because planning involves forecasting and the analysis of multifaceted, dynamic environments, these processing errors may exert a more pervasive effect on performance than is characteristic of many other forms of complex performance. This observation suggests that a greater investment in the development and evaluation of error remediation techniques may prove worthwhile. In fact, given the impact of planning on complex, real-world performance, there appears to

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be sound reason for more intensive, and more systematic, research on the nature and implications of planning performance. At this juncture, research along three broad avenues seems indicated: (a) basic processing operations, (b) performance-shaping factors, and (c) errors. In the ensuing discussion, we try to outline some key considerations that should be taken into account in further research along these lines. At the outset of this article, we reviewed a variety of studies examining how knowledge is applied in planning and the processes people apply in working with this knowledge (e.g., Hammond, 1990; Xiao et al., 1997). With regard to knowledge, it seems reasonable to hold that planning proceeds through the use of cases. Unfortunately, we do not know much about why people select certain cases for application in planning. Although Keane's (1996) study suggests that adaptability may be an important consideration, it seems likely that other factors, such as case accessibility, salience of certain goals, and identification of certain contingencies, causes, and restrictions, may prove some importance. Along similar lines, we need to know more about the characteristics of cases that lead to successful performance. For example, is the use of cases that embody desired outcomes more likely, or less likely to lead to effective performance than the use of cases that articulate key causes and restrictions operating in the situation at hand? Finally, given the complexity of case-based reasoning (Klodner, 1993), we need studies examining the ways in which case material is recalled and manipulated in planning. These observations about case-based reasoning, of course, bring us to the processes applied in constructing plans. At this point, sufficient evidence is available to formulate some plausible hypotheses about the kinds of processes involved in planning. Indeed, in this article we have proposed one model that holds that planning involves environmental scanning; identification of applicable cases; elaboration of resources, restrictions, and causes; forecasting and revision; and opportunistic implementation. However, this model must be viewed as a tentative description of planning until more research has been conducted on the nature and significance of these processes. In addition, research along the lines of Doerner and Schaub's (1994) studies is needed examining how execu-


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tion of these processes influences planning performance under different conditions. Put more directly, we need studies examining the factors that allow people to identify key causes and the ways these causes, along with relevant resources and restrictions, are used in forecasting and revision. The work of Langholtz et al. (1995) provides a useful illustration of the potential value of future research along these lines. Not only is research on basic processes needed, but we need more studies examining the individual and situational factors that shape planning performance. There is value in studies examining individual characteristics related to planning performance, especially studies examining characteristics, such as openness, conscientiousness, mastery motives, and critical thinking, likely to be related to planning. With regard to situational influences, the planning literature stresses the impact of objective situational attributes such as time pressure and workload. It is possible, however, that social interactional processes (e.g., Weldon et al., 1991) represent equally important influences on planning performance. These social situational influences may, in fact, be more complex and pervasive than has traditionally been assumed. For example, in organizational settings, corporate culture may influence selection of the cases applied in planning (Dutton & Dukerich, 1991; Mumford et al., in press). Along somewhat different lines, past investments in particular patterns of interaction may represent a significant constraint on planning performance (C. C. Miller & Cardinal, 1994). Clearly, there is a need for research examining how social interactions, and social information processing, influence plans and planning performance.

in planning (Mumford et al., in press). Moreover, "errors" in planning may, given the adaptive social demands placed on people, prove advantageous under certain conditions. Thus, use of relatively simple forecasting heuristics may prove attractive, despite the potential for error, when the environment is uncertain and causes cannot be unambiguously identified (Bluedorn, Johnson, Cartwright, & Barringer, 1994). These observations, of course, suggest a need for a wider range of more comprehensive studies examining the nature and implications of the errors arising in naturalistic planning processes (e.g., Bartel, 1994; D'Aveni & MacMillian, 1990). In considering these observations about potential directions for future research, it would seem useful to bear in mind a final point. Research along the lines just sketched out is most likely to prove useful if it proceeds as an integrated, multifaceted, cross-disciplinary program. For example, studies of naturally occurring errors have important implications for research on planning processes, and studies of social interactional demands may lead to the identification of new kinds of errors. Unfortunately, planning research has often suffered precisely because these kinds of cross-field effects have not been carefully examined. We hope that the present effort will serve as an impetus for not only further research on planning but also the integration of various research themes into a more encompassing model of planning processes and planning performance.

A third line of research by our foregoing observations about the role of social mechanisms in shaping plans and planning performance. Current research on planning has examined planning errors primarily from a cognitive perspective, stressing time estimation errors and failure to consider problems likely to be encountered (e.g., Buehler et al., 1994). This optimistic bias, however, is not the only kind of biasing factor that might influence planning performance. For example, social demands, such as escalating commitment with public presentation of a plan or overweighting of environmental information provided by high-status role models, may represent noteworthy sources of errors

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Received July 14, 2000 Revision received January 18, 2001 Accepted January 22, 2001 •