HR PLATFORM

Part I & II
July, 1998

Introduction

Part I: Organizational Adaptation
     - The Adaptive Systems Framework
     - Orientations Toward Use of Feedback
     - Applying the Adaptive Systems Framework

Part II: Studying Organizational Effectivness And Adaptation
     - Levels of Analysis: Micro variables and Macro Patterns
     - A Systems Theoretic Approach
     - Transformational Dynamics in Organizations
     - The Burke-Litwin Model of Individual and Organizational Performance
     - Organizational Learning
     - Conclusions

Part III: Adaptation for Substance Abuse Treatment Organizations
     - Factors Affecting Change in Substance Abuse Treatment Organizations
     - Implications
     - Suggestions for Future Research
     - Conclusions
     - References

This paper focuses on how to improve treatment through change, learning, development, innovation, and adaptation processes at the organizational level. It uses these approaches to suggest future directions of research and action for substance abuse treatment organizations.

Because of conceptual vagueness, the vast body of literature on organizational change and organizational learning frequently is unhelpful for guiding either research or practice. Part I attempts to clean up some of the conceptual clutter regarding organizational learning by presenting a series of simple models that highlight the four distinguishing characteristics of adaptive systems: (a) feedback, (b) coordination, (c) reactive learning, and (d) generative learning. The framework presented is descriptive, so it does not dictate what should be done to improve the study or operation of organizations. Rather, it provides a definition of adaptation and a conceptually precise way to categorize certain phenomena related to organizational learning.

Part II provides a discussion of prescriptive approaches to understanding organizational change. The Burke-Litwin model, which provides a complex causal model of organizational functioning, is used to guide organizational diagnosis and change efforts. The work of organizational learning theorists like Peter Senge (1990) is reviewed as a pragmatic approach for building a "learning organization." Part II concludes by integrating the literatures on organizational change and learning using the conceptual framework outlined in Part I.

Finally, in Part III, the theories and concepts discussed in Parts I and II are applied specifically to substance abuse treatment organizations. Through a series of theoretical propositions derived from the adaptive systems model explained in Part I, and to some extent in Part II, advice is presented for practitioners and social scientists. Social scientists can use the propositions as a starting point for conducting applied research by translating relevant propositions into empirical hypotheses. Practitioners can use the same propositions to develop actionable guidelines for how substance abuse treatment organizations can function more effectively. The paper concludes by suggesting some promising directions for future theory and research.

Organizational learning and adaptation are relatively new areas of study in the social and behavioral sciences. This section defines organizational learning and organizational adaptation and explains the essential processes by which they occur. A conceptual framework is used to present the nature of systemic adaptation. An application of this framework and some limitations of the framework also are discussed. In subsequent sections, the adaptive systems framework is used as a starting point to explore in more detail the nature of organizations that learn and the critical variables that govern organizational adaptation and change.

A fruitful discussion of organizational adaptation in general, and the application of these ideas to substance abuse treatment organizations in particular, first requires an understanding of what is meant by adaptation and what distinguishes adaptation from other sorts of organizational activities and functioning. This section lays out a conceptual framework based on four distinguishing features of adaptation in individuals and organizations: (a) discrepancy reduction through simple self-regulation, (b) flexible functioning through complex self-regulation, (c) learning by reactive self-improvement and problem solving, and (d) adaptive learning (see Table 1).

Each of these four adaptive features can be thought of as stages that build on each other. The corresponding models represent the five levels at which organizations may function, with none of the adaptive features just mentioned exhibited at level 1 and all four features at level 5.

Table 1. Models of organization based on five levels of organizational functioning. Each level of functioning depends on the number of adaptive features represented in the model (the level 1 model has none of the features; the level 5 model has all four features). The basis for organizational change is described for each level.

The simplest model of an organization incorporates none of the distinguishing features of adaptation. Figure 1 shows a generic input-throughput-output model of organization. The model is useful because of its simplicity: The organization exists to transform inputs into outputs. That is, value-adding throughput activities transform inputs into more valuable outputs.

Figure 1. The simplest, most generic model of organization functioning: a basic input-output mechanism. This is a static, closed-system model lacking any and all features of adaption. The model represents a closed system because it does not interact with the environment, and it is static because there is not feedback on performance, and therefore throughput cannot be regulated or changed.

Organizational Effectiveness

The effectiveness of an organization may be seen as either impact (magnitude of output) or efficiency (ratio of output to input). The trade-off between impact and efficiency is an important concept. A for-profit company generally regards efficiency as the ultimate goal. The profit equation P = R - E (Profit is equal to revenue minus expenses) may be equated with VS = O - I (Value Surplus is equal to the total value of output minus the total value of inputs used to produce them). Only through a value surplus may a private company sustain itself as a profitable enterprise. Similarly, only through a value surplus, albeit more broadly conceived (i.e., including intangible societal benefits), can a not-for-profit or subsidized endeavor justify its existence. This can be viewed as a positive feedback loop whereby success (i.e., a favorable ratio of outputs over inputs) secures a value surplus that can be used not only to sustain the organization, but to enrich, expand, and enlarge it.

Figure 2 shows an input-throughput-output model with the addition of a negative feedback loop. Feedback allows the system to strive for equilibrium. For example, a heater that is a level 1 system will continue to produce heat at the same rate regardless of whether additional heat is needed. It cannot itself assess when it is appropriate to turn itself on or off. At level 2, however, the heater becomes a thermostat capable of self-regulation. Thus, whereas a level 1 system has an open loop where the basic activity of the system remains constant and unrestrained, self-regulatory systems alter the rate of activity in order to achieve a steady state. There are two key components to the feedback feature of level 2 functioning: (a) self-regulation and (b) feedforward.

Figure 2. A simple control system: an input-throughput-output system with a self-regulatory mechanism that uses negative feedback to strive toward and maintain a steady state. Because it is a simple control system, feedback is used only to alter the amount of input through the system. Regardless of activity level, the throughput process itself remains essentially the same.

Feedback and Self-Regulation

A thermostat regulates temperature not by producing heat at a constant rate, but by attempting to minimize the gap between the actual temperature and the ideal temperature (see Figure 3). This model represents the cycle of monitoring (monitoring the ambient temperature), comparative evaluation (comparing the actual temperature with some predetermined target point or range of temperatures), and goal execution (altering heat output in order to reduce the ideal-actual discrepancy) of self-regulation as described in cybernetics (Weiner, 1948, 1961) and control theory (Carver & Scheier, 1981; Karoly, 1993; Powers, 1973a, 1973b, 1978). Miller, Galanter, and Pribram (1960) call this a TOTE (Test-Operate-Test-Exit) cycle (see Figure 4). In a TOTE cycle, a testing mechanism looks for a discrepancy and initiates the operate mechanism (the throughput) to eliminate the discrepancy. Discrepancy is tested again and, if the operate function has brought the present state to a satisfactory level, the testing mechanism terminates the process and exits.

Figure 3. Example of a simple control system: a thermostat. The thermostat regulates room temperature through the following sequence of events: (a) feedforward the goal or target temperature; (b) monitor actual room temperature; (c) compare two temperatures for possible gap; (d) modify system inputs as appropriate (e.g., turn on/keep on or turn off/keep off the heat); (e) throughput activity responds to change in system inputs, automatically consuming the resources available for the primary activity of the system (e.g., heating); (f) if resources are being consumed and the throughput activity is operating, the room temperature is expected to move in the appropriate direction.

Feedback and Feedforward

Implicit in the thermostat analogy is the goal of the system, which feeds forward the set point, the ideal temperature toward which the system strives. This feedforward, what Powers (1973a) calls a reference signal, is the basis on which self-regulating systems assess and correct discrepancies. The feedback mechanism of a thermostat measures the actual temperature, and through a process of comparison and reaction, the heating mechanism responds appropriately to reduce any gaps between actual and ideal temperature (i.e., the performance-standard mismatch) and maintain the steady state. This comparison-and-reaction process is regulated by the test mechanism of a TOTE cycle, also called a comparator because it compares existing conditions or performance with some preset standard toward which the system strives (see Figure 4).

Figure 4. A Test-Operate-Test-Exit or TOTE unit (adapted from Carver & Scheier, 1981). The unit will continue to operate and test until the discrepancy between actual and ideal has been eliminated, at which point the unit shuts down (exits). Thus, the first ten initiates the operate-test cycle, and the last test terminates the cycle and diverts the system to exit.

Dynamic Steady States

Cannon (1929, 1932) and Lewin (1938, 1951) proposed the concepts of dynamic homeostasis and quasi-static equilibrium, respectively, as processes by which biological (Cannon) and psychological (Lewin) steady states are maintained. Because of constant environmental disturbances and fluctuations, the system oscillates back and forth around its target, but never precisely reaches it for any length of time. This is simply an acknowledgment that external conditions change—if they did not, self-regulation would serve no purpose.

One important aspect of negative feedback loops in self-regulating systems is time. More specifically, there may be a delay between the operate or throughput function and its impact on the test or monitoring function. A control system that does not take such a delay into account may behave inadvertently as a discrepancy-inducing cycle by continuously operating to close a gap that only gets larger due to a vicious cycle of overcompensation. For example, if a thermostat's thermometer reacted to changes in ambient temperature an hour after they actually occurred, then the heater would run for a full hour after the temperature had reached its set point. By that time, the temperature may have become so hot that the air conditioner would have been initiated, but it too would be expected to run for an hour longer than necessary due to the time delay. In some cases, such cycles can be self-amplifying, causing the system to stray farther and farther from the set point.

Feedback does not necessarily imply a changing relationship between the system and its environment. Although the environment might change, and the system may be active or inactive, the relationship between the system and the environment is fixed. This limitation is reflected in the nature of possible corrective responses to the performance-standard mismatch: Corrective response is limited to more or less persistent or intense use of a single fixed throughput activity.

Figure 5 incorporates the second feature necessary for adaptation: the regulation and coordination of multiple activities. The coordination of multiple activities interacting within the same system, along with the hierarchical feedback loops that engage them, creates an "elaborate and flexible functional capability" not present in level 2 systems with a single feedback loop (Ford, 1987). Carver and Scheier (1981) describe this as a system’s hierarchical decision-making chains, where the output of one feedback loop may serve as the feedforward for a subordinate loop. Thus, the feedforward for a thermostat is the output of a superordinate system—the human occupants who set the target temperature. For simplicity, Figure 5 shows this as the feedback loop leading from output back to output.

Figure 5. A complex control system. At level 3, the addition of multiple and hierarchical goals and feedback loops creates a system of complex self-regulation, where resources must be allocated (or not) to various activities, the activities must be coordinated to achieve terminal objectives, and feedback may or may not be used to alter the regulation of the systems's throughput activities.

Thus, the output function displayed in Figure 5 represents not only output in the form of value or energy, but also information to help coordinate and control subordinate feedback systems, which, although not displayed as such, exist underneath the feedback system depicted here. These are called "nested" feedback loops.

The idea of multiple feedback loops implies that the system may now have multiple goals and that there may be multiple activities for achieving them. A computer-simulated chess opponent, for example, must consider a multitude of goals and subgoals. Even the terminal goal is not altogether clear; it can be to win the match or simply not to lose it. This will dictate tactics for, say, attaining or avoiding a stalemate. Both goals, winning and not losing, may be pursued simultaneously—successfully winning accomplishes both goals. However, these goals occasionally will conflict, such as when a draw is offered by the computer's opponent, in which case the computer must decide which is more important, to win or not to lose, and elaborate strategies must be employed to help it execute various activities and accomplish various goals.

Ford (1987) uses the example of a guided missile instead of a computer chess game. A guided missile has several options in terms of the activities it may perform: It can arm or disarm, go faster or slower, up or down, left or right; but it must execute these actions while attempting to both hit its target and avoid things that are not its target. Again, there may be a trade-off. The system, in pursuing multiple objectives simultaneously and negotiating the options presented, must coordinate activities in a much more complex fashion than, say, a thermostat. Where the thermostat had one simple rule, the guided missile must have meta-rules to govern and coordinate a complex network of rules. One meta-rule might be that the system gives precedence to the nontarget avoidance objective over the target pursuit objective under certain conditions (e.g., when it is armed rather than disarmed, when it is over civilian populations rather than uninhabited areas). These meta-rules, along with the stored behavioral routines or strategies used to execute them, constitute the regulatory and control functions of a system.

To be effective, a guided missile must simultaneously pursue its target and avoid nontargets. It is not enough to switch off between objectives and pursue one while neglecting the other. Actions must be coordinated carefully—the missile must be able to take evasive action while simultaneously minimizing deviation from its target. This sort of coordinated execution of multiple objectives results in a much more elaborate system than that presented in the previous model. In level 3 systems, multiple feedback loops and hierarchical rule structures may be used to create very smart missiles and computer chess players.

Although complex control systems may be thought of as "smart" in some ways, they are also very dumb: They still cannot learn. Their behavior is limited to exactly what their designers have programmed. Although the rules, meta-rules, and functional strategies may be intricate, the system is just a fancier version of the thermostat. It may not modify itself or change its behavior to deal with novel conditions or unexpected problems in the environment.

Self-improving systems (see Figure 6) are expected to learn from their interactions with the environment. This is what Ford (1987) calls "adaptation through self-programming." The system not only may now change which activities it executes and to what degree, it may change and improve the nature of the activities themselves. Whereas level 3 functioning may achieve improvements in efficiency and effectiveness through better coordination of activities and allocation of resources, the activities that are coordinated and those to which resources are allocated are still fixed. Level 4 functioning represents an improvement of the activities themselves. At level 4, feedback is used not only to regulate, but to learn.

Figure 6. A self-improving system. Based on reactive learning, activities are modified or created in order to solve existing problems and achieve fixed goals.

The Learning Function of Feedback

The feedback loop now serves not only to control inputs, but also to learn and therefore improve the throughput activities. David Nadler (1977) pointed out two implications of this learning function of feedback. First, feedback now can be used both to regulate the consumption of input and intensity/persistence of output and to improve the throughput activities themselves. "Feedback can be more than just a device to regulate flows through the system—it can be a way to change how the system does its work" (p. 69). Second, due to the increased complexity of the model, feedback now comes in many forms and may be used, or not, in different ways. The system now may seek out different sorts of feedback relevant to potentially new throughput activities. System dynamics may be considerably more complicated because feedback, standard-matching, and self-correction routines are no longer straightforward and automatic. Relevant information may exist, but the system may choose not to use it.

Nadler’s second point involves not only the choice of whether or not to feed back relevant information, but also the issue of where, and the extent to which, information and feedback is sought. In other words, what is the intensity and direction of the system’s attention? A system can direct its attentional resources in a number of ways. One simple but important dichotomy is based on the source of the information—internal or external—to which the system attends. If the source of information is internal, the system is attending to itself (self-focus), whereas external information means that the system is attending to its environment (environment focus). Psychologists have tended to assume that individuals’ attentional resources are fixed (e.g., Carver & Scheier, 1981; Duval & Wicklund, 1972; Kanfer & Ackerman, 1989; Kanfer, Ackerman, Murtha, Dugdale, & Leissa, 1994). This implies that, especially when attentional resources are taxed, attending more to the environment will necessitate attending less to the self, and vice versa. Thus, attention will tend to shift between being primarily self-directed and primarily environment-directed, depending on various aspects of the person and the situation (Carver & Scheier, 1981).

Whereas the attentional resources of individuals may be fixed, an organization’s ability to attend to itself and/or its environment is more likely limited by the value surplus created by its throughput activities. The more energic inputs it can secure relative to the amount used by its operate, or throughput, function, the more energy that is available to the regulatory activities of the system such as attending to relevant internal and external information. Where information relevant to a particular goal-activity relationship is not used, the organization likely functions as if it were an open loop system (i.e., a model one system lacking the feedback loop), and it will habitually act, or fail to act, in the same way over time. Only when internal or external conditions cause the organization to redirect its focus toward the appropriate information can the organization alter the relevant behaviors.

Level 4 systems are the first presented here that may be called adaptive. However, the potential of these systems is restricted to fixed terminal objectives. That is, although operational objectives or subgoals may be altered, or new ones invented (entire layers may even be added to the existing hierarchy of rules and feedback loops), they serve a set of fixed terminal goals. For instance, although efforts are currently underway to build a self-improving computer chess player that will learn and improve the more it plays, its terminal goals of winning and not losing are fixed. This computer will never throw a match in order to make its opponent feel better (even if the opponent was a sore loser and this behavior was prudent for the computer’s survival), nor will it ever get bored and decide to learn a new game. It is not self-aware, the hierarchy of goals and feedback loops is finite, and its terminal goals do not change. Although it may learn, and is therefore adaptive in a reactive sense, it does not have the adaptive qualities of living organisms and social organizations, which are adaptive in terms of activities and the terminal goals they serve.

The adaptive systems model (Figure 7) depicts systems as dynamic not only in terms of input-throughput-output activities, but also in terms of the goals or intended outcomes of those activities. Regulatory and control processes may use feedback in four ways: (a) to alter resource inputs via self-regulation; (b) to select among different means of achieving goals; (c) to alter means for achieving goals; and (d) to alter the basic goals or purposes toward which the system is striving.

Figure 7. A system with all four characteristics of adaption. Adaptive systems use feedback to (a) regulate input through the system, (b) coordinate hierarchically nested activities and feedback loops, (c) improve activities through reactive learning, and (d) redefine the goals of the system through generative learning.

Adaptive Systems Are Guided by Purpose

Whereas the temperature of a room, the weather, the flow of water in a river, and the orbit of planets around a star are all complex systems, they are not guided by conscious and unconscious goals as sentient organisms and social organizations are. All previous models were able to use mechanical or computer analogies. Generative learning applies only to adaptive systems such as humans and human organizations. Level 5 systems are self-constructing and self-organizing, guided by terminal goals and purposes that are, at least to some extent, of their own creation.

Norman and Shalice (1986) observed that patients with frontal lobe brain damage are no longer able to self-generate goals and intentions. Although they respond perfectly well to situational demands and the instructions of others, they are incapable of planning or engaging in nonautomatic behaviors. This suggests a separate, superordinate mental function to generate intention that is distinct from the mental functions that carry out those intentions (Kuhl, 1994). Self-generation of intentions, however, does not occur in a vacuum—it relies on feedback from the environment.

The goals of adaptive systems are interdependent and may be conflicting. Inevitably, certain goals take precedence over others. According to need theories, the goals toward which humans strive may be understood according to a limited and finite set of basic, fundamental needs. The point is that whereas humans and social organizations may follow certain patterns in the formulation and pursuit of goals, and those patterns are influenced by a dynamic interaction between person and environment, the goals of humans are self-created.

The use of feedback and its effects on behavior are largely determined by goals and individual orientations toward either (a) learning and improvement or (b) decision making and performance. The most useful framework for understanding such orientations in individuals was provided by Carol Dweck and her colleagues in their theory of goal orientation (Dweck & Leggett, 1988; Elliott & Dweck, 1988). An individual’s orientation toward the pursuit of goals and the use of feedback on relevant performance tends to focus on either learning or performance. In the face of initial failure to achieve goals (i.e., negative feedback), those with a learning orientation will concentrate on using that feedback to improve future performance, whereas those with a performance orientation will tend to allocate their resources elsewhere.

Although the concept of "the learning organization" (e.g., Senge, 1990) is now taking hold in business lexicon, application of its principles requires a philosophy of learning that is based on challenging assumptions, detecting and correcting errors, and striving for improvement in the long run rather than demonstration of performance in the short run (Ackoff, 1993). For example, in their discussion of the philosophical underpinnings of total quality management, Hackman and Wageman (1995) note that although measurement and feedback are key to the learning process, this process will be "rendered impotent" if a learning orientation is not adopted over the short-term performance orientation that tends to pervade most organizations.

It is important to note that a learning orientation need not be at the expense of a performance orientation. In a discussion of Dweck’s theory on individual differences in learning orientation, Button, Mathieu, and Zajac (1996) noted that concern for performance and concern for learning are more likely independent axes than opposite poles of a single continuum. Thus it is possible to be high on both. This is also true for organizations. After all, an organization that does not demonstrate requisite performance in the short run may not survive. Thus, although learning results from a focus on improving performance in the long run, it is not incompatible with concerns for short-term performance as well.

Chaffee (1985) and Hart (1992) comment that the simultaneous adoption of multiple strategic orientations will have a greater impact on organizational competitiveness in the long run than a single orientation. Of the five orientations described by Hart, three are relevant in terms of our discussion: (a) the rational/performance mode, (b) the transactive/learning mode, and (c) the symbolic/purpose mode. In his discussion of strategic modes, Hart notes that:

As the five "levels" described in the adaptive systems framework suggest, there is a hierarchical quality to these orientations. Etzioni (1967, 1986, 1989), for example, offers an organizational decision theory of "mixed scanning" where decision makers switch between various levels of the decision process, from high-level goal setting (like Hart’s symbolic/purpose mode) to subordinate goal execution processes (the rational/performance mode). Along the same lines, Chaffee (1985) notes that there is a hierarchical relationship between the three strategic modes, with the purposive or "interpretive" mode at the top, then the learning or "adaptive" mode, and finally the rational or "linear" performance mode.

The work of Etzioni (1967, 1986), and particularly of Hart (1992) and Chafee (1985), highlights a central theme of the adaptive systems framework: To be successful, organizations must effectively function at multiple levels simultaneously, including mechanistic or linear functioning (levels 1 through 3) to transactive learning (level 4) to generative learning (level 5).

An example using synergy and team learning is presented below to clarify how the systems framework can be used as a lens through which to view other concepts related to organizational functioning and effectiveness. Some concluding comments are offered about the intended use of the framework.

Consider the concept of synergy through the perspective of the adaptive conceptual framework presented above. A useful tool for thinking about synergy is the "lost in the wilderness" exercise commonly used to stimulate group interaction and, it is hoped, synergy. In this exercise, participants are asked to imagine that they are stranded in some desolate location (e.g., the wilderness, the desert, an island, the Arctic) and must decide which items are needed for survival. The choice is typically constrained by either number or weight of the items. The list of items may include things like a compass, a frisbee, a knife, a rope, or a pencil. The idea is to select those items that will be most useful for your individual and/or group survival. For the sake of discussion, let us assume that there is a correct answer to this problem—some best combination of items that will maximize survival potential. To assess the idea of synergy, let us make the example more concrete with some assumptions. First, assume that there is a list of 40 items and your group can take only 20, so scores can range from 0 to 20 correct responses on the exercise. Also, assume there are four group members participating in the exercise: Anne, Bob, Chris, and Dorothy. If these members took the "survival" test individually, they would score as follows: A = 7, B = 2, C = 15, and D = 8. Finally, assume that among all their selections, only one of the 20 correct items (say, a screwdriver) would be chosen by none of them. Now, let us consider what the likely score of the group will be according to each model.

Level 1 systems have no feedback. There is no way to regulate flow through the system. Thus, each person would have equal contribution to the decision, but individual members would have to act independently, since this is a mechanistic model. If a voting or round-robin selection process ensued, so that all members were equally but individually operating to make a decision, we would expect the group to achieve the average of their individual scores. In this example, the group would achieve a score of 8.

Level 2 systems have feedback, but it is still an individual affair (coordination is the hallmark of level 3 systems). Thus, Bob may realize from past experience that he is terrible at this exercise, so he may decline to contribute. The remaining three group members would then operate in the same way already described, but now the group average consists of only three scores, so the group raises its average score from 8 to 10. By this logic, it is even possible for three of the members to refuse to contribute based on past experience so that Chris brings the group average up to his individual score of 15.

A complex system adds an important new component: coordination. Although this system may still only regulate flow through the various fixed activities of the system, functioning is considerably more flexible. Different members of the group may have different areas of expertise. By managing the process, the group may now allocate particular activities or choices to the people with relevant expertise. For instance, the nutrition expert might select the correct food, whereas the engineer could pick the best tools. In this way, the group can achieve cooperative synergy. The group can score 19 by properly coordinating and allocating the group’s resources. Of course, the downside is that, although the group could achieve a score of 19, it might also achieve a score of 2. Another aspect of level 3 systems is hierarchy, and if Bob is the "team leader" and forces his own personal selection based on formal position or persuasive power rather than expertise, the group will end up with his dismal individual score of 2. We might call this "negative synergy."

At level 4 functioning, the group may learn, and a new capability not possible among the members individually might be created through team synergy. At this level of functioning, the team could potentially, through discussion and pooling of knowledge, figure out that the screwdriver (the one item none would have chosen individually) is an important item to have, thus raising the score to 20. Let us not forget, however, that there also may be a downside to group process. As Asch (1952) and Janis (1972) have demonstrated, subtle pressures on individual members to conform to the will of the group, perceived or actual, can lead to disastrous blunders that few, if any, of the group members would have committed individually.

Functioning at level 5, the group would be able to learn how to function better as a group. They might achieve only a score of 16 or 17 (scores cannot reflect level 5 functioning), but by reflecting on the group process and engaging in generative learning, they would better understand themselves individually and in relation to one another and their environment. Through generative learning, the group would be able to question the purpose and utility of the exercise; to explore group processes and the functionality of their shared assumptions; and to improve collaboration, cohesion, and group functioning. Emotional relationships might even replace task accomplishment as the most important aspect of the group for its members. There are advantages and disadvantages to functioning at this level. The effectiveness of a task group with a clear goal and unambiguous work might suffer, for example, if time were unnecessarily spent reframing the problem at hand and questioning the purpose of the group. In this case, level 5 functioning would merely act as a distraction. On the other hand, in less straightforward circumstances, dealing with process issues within the group and reconsidering its purpose might be expected to enhance the long-range cohesion and success of the group and its members.

The adaptive systems framework is an attempt to clarify the nature and underlying processes of organizational change. However, the framework provides only a conceptual tool with which to think about organizations. An essential point of clarification now must be made regarding the five models presented above: The adaptive systems framework put forth in this paper is intended to be descriptive, not prescriptive. This framework offers a taxonomy for categorizing levels of systemic functioning, from static (level 1) all the way to complex and generative (level 5). The point is not that an individual, group, or organization gets stuck at a suboptimal level and needs to "get to level 5" to be effective. The framework is better understood in terms of the implicit theories people have about how a system functions. In truth, individuals and organizations necessarily function at all five levels. With few exceptions (e.g., frontal lobe patients), humans and organizations are always best described by the generative model, whether they think they are or not.

Functioning at the level of generative learning (level 5) is descriptive of how individuals and social organizations actually function. This level of functioning can be consistent or inconsistent, to a great or small extent, explicit or implicit, conscious or subconscious, systematic or unsystematic, effective or ineffective. By conceptualizing an organization as simple (model 2), mechanistic (model 3), or reactive (model 4), we inhibit that organization's conscious, consistent, and effective generative learning processes that are increasingly critical for the survival of modern organizations. Kuhn’s (1962) point that major scientific breakthroughs are often initiated by mistakes or unexpected findings that challenge our underlying assumptions or "paradigms" makes it clear that we need not consciously pursue generative learning for it to occur. The Hawthorne studies, for example, originally set out to complete a series of time and motion studies, but found an entirely unexpected phenomenon resulting in what Kuhn (1962) calls a paradigm shift. This does not, however, preclude us from conscious attempts to make mistakes, challenge assumptions, and consistently revisit our implicit understanding about the nature of problems, meaning, and purpose.

Although the framework presented here cannot do justice to the complexity of individuals, much less groups and organizations, it does tap the essence of the general patterns of interrelationship that are organizations. Thus, the adaptive systems framework is useful because (a) it defines and explains organizational change and adaptation in terms of four essential characteristics, and (b) it reflects the mental models people use when thinking about organizations. The first useful feature, describing the systemic characteristics of organizational change, provides a foundation on which to build more pragmatic causal models of organizational functioning. In Part II, we explore these prescriptive, pragmatic notions that more directly guide practitioners and applied social scientists.

Although systems theory and the adaptive systems framework presented above offer useful ways of thinking about organizations, they do not directly point to specific methods by which organizational functioning can be improved. Rather, their value lies in describing how the systems concept links individual behavior to organizational dynamics. This section begins by exploring how a systems approach, and the adaptive systems framework in particular, helps link micro variables at the individual level to broader patterns of organizational functioning. Two pragmatic theories of organizational change and learning based on the systems approach will then be presented, followed by an attempt to integrate the two theories based on the adaptive systems framework.

Katz and Kahn call the chicken and egg dilemma of specific micro variables and overarching macro patterns the "problem of levels" (1978, p. 12) and propose that a systems theoretic approach is the key to resolving the dilemma. They argue:

Katz and Kahn conclude by noting that "this reductionistic emphasis in its very character tends to lose the problem with which it should be concerned" (p. 14).

Although sociologists have taken the first steps toward identifying key relationship patterns at macro levels of analysis (e.g., organizational and societal), they have failed to attain anything beyond a cursory understanding of these patterns because of their inability to link them to the underlying psychological and behavioral phenomena that must be measured to get a clear picture of the relationships with which they are concerned. Thus, sociologists have broadly identified some important patterns, but have not identified the measurable psychological and behavioral variables that, through their interrelationships, create those patterns.

Systems theory enables scholars to start at the point of macro patterns and break them down into component micro concepts without losing the link of the parts to the whole (c.f., Katz & Kahn, 1978; Mayntz, 1997). Thus, the psychological and behavioral dynamics that make up macro patterns can be selected and studied in relation to the pattern as a whole. The adaptive systems framework suggests that the variables critical to organizational development and learning are the governing variables of the system. Governing variables consist of the overarching purposes, directions, and strategies for the system as a whole, as well as the leadership and decision-making processes by which they are set. By linking the "micro" to the "macro" through governing variables, we are able to better understand the patterns of behavior that create and sustain organizations.

The adaptive systems framework is a conceptually abstract approach to understanding organizations. It does not define the specific variables that "govern" the system, nor does it state the nature of their patterns of interrelationship. Furthermore, the adaptive systems framework is purely descriptive. Although it may facilitate a conceptual understanding of systemic adaptation and learning, it does not offer concrete or practical suggestions about how organizations work or how to improve their effectiveness.

More practical approaches to studying organizations and improving their effectiveness come from two related streams of scholarly work. The first concerns an understanding of the transformational dynamics of organizations, concentrating primarily on a model proposed by W. Warner Burke and George Litwin. Their model of individual and organizational performance (Burke & Litwin, 1992) is not merely descriptive; it is also predictive and, by extension, prescriptive. The Burke-Litwin model offers one useful approach to conceptualizing and studying the governing variables of organizations, how they relate to other key organizational variables, and the dynamics of organizational change and development. The second stream of work revolves around organizational learning, including a review of Peter Senge’s work (1990) on the learning organization. Not surprisingly, the Burke-Litwin model of organizational effectiveness and Senge’s work on organizational learning both stem from a systems theoretic approach to understanding organizations.

The Burke-Litwin model (1992; Burke, 1994) is an ideal starting point for understanding the transformational aspects of organizational dynamics and organizational change. First, however, it is necessary to understand what transformational means, and the distinction between transformational and transactional dynamics. The distinction between transformational and transactional organizational dynamics is based on Burns’s (1978) conceptions of leadership. This section begins by summarizing the conceptual distinction between transformational and transactional leadership offered by Burns (1978) and others (Bass, 1985; Kanter, 1983; Rost, 1991; Tichy & Devanna, 1986).

The leaders and managers of an organization can be viewed in terms of the specific functions they serve or the behaviors in which they engage. According to Rost (1991), the dominant perspective on leadership in the 20th century has been leadership as effective management. Management and leadership are more appropriately viewed, however, as distinct processes. The distinctive nature of these processes can be understood using Burns's (1978) concepts of bureaucratic authority, transactional leadership, and transformational leadership.

The nature of bureaucratic management and administration is highlighted by the defining features of level 3 systems: hierarchy and coordination. Here, managers are seen primarily as Taylor and Weber viewed them—as coordinators, supervisors, and resource allocators. Bureaucratic managers rely on hierarchical authority, rules, and threat of punishment to execute their prescribed tasks and maintain organizational effectiveness. Burns (1978) and others (O'Toole, 1994; Rost, 1991) have pointed out that "leaders" who rule only by coercive power and legitimate authority are not leaders at all. Others have made similar distinctions between managers who use existing policies and structures to allocate resources and maintain organizational performance and leaders who initiate organizational change and development (e.g., Zaleznik, 1977).

Burns (1978) holds that the roles and behaviors of leaders and their followers are not fixed according to existing systems, policies, and structures, and are not based on coercive or authoritarian relationships. Instead, leaders are constantly redefining their roles and changing their behavior in an evolving exchange with followers. Burns's description of leaders "modifying their behavior as they meet responsiveness or resistance" (p. 440) is consistent with reactive learning in level 4 systems. Leaders do not simply rely on existing, formally prescribed duties and lines of authority to carry out their work. Instead, they may modify their behavior in order to more effectively achieve prescribed goals.

Transactional leadership processes are not concerned with altering the fundamental goals of the organization or its members. Thus, transactional leaders tend to influence and motivate through reciprocal exchange processes (c.f., Bass, 1985; Burns, 1978), appealing to the self-interest of others and rewarding desired behaviors quid pro quo. Although new behaviors may be learned, at both the individual and group levels, purpose in transactional leadership is fixed, consisting of the formally prescribed goals of the organization.

When discussing transformational leadership, Burns (1978) invokes terms like morally purposeful and the shaping of purpose, and Tichy and Devanna (1986) refer to planful opportunism and organizational self-renewal. The adaptive systems framework offers a distinction between transactional and transformational leadership that is perhaps more clear: Transformational leadership is based on processes of generative learning (level 5), whereas transactional leadership is characterized by reactive learning (level 4).

As with all adaptive systems, the purposes of organizations must evolve over time. The process by which this occurs for an organization and its members is transformational leadership. Rost (1991) summarizes this point by stating that the reciprocal influence relationship between leaders and followers is characterized by common purpose. Mutually shaping a common purpose over time suggests "development (progressive change) in the purposes of the leaders and followers rather than fixed, stable positions on what often are complicated and rapidly changing issues" (Rost, 1991, p. 120).

Transformational change is discontinuous, based on self-renewal of identity and purpose, whereas transactional change leaves the organization’s identity and goals fixed, instead focusing only on the means by which desired ends will be optimally achieved. The Burke-Litwin model takes advantage of this useful distinction by applying it not just to leadership, but to organizations in general.

The Burke-Litwin model originates from the work of George Litwin and his colleagues (Litwin & Stringer, 1968; Tagiuri & Litwin, 1968) on organizational climate in relation to managerial behaviors, norms, and values; organizational structure and policies; and group and organizational performance (see Burke, 1994; Burke & Litwin, 1992). Litwin describes climate as the perceptions, expectations, and feelings of an organization or group. Climate is malleable, meaning it is often transitory and may be influenced both by enduring aspects of organizations (e.g., shared norms) and by transient aspects of organizations (e.g., supervisory behaviors). Litwin and Stringer (1968) experimentally manipulated work unit climate through managerial behavior and, based on their theory, predicted its impact on performance. This was an important first step toward building a predictive, not just descriptive, model of organizations.

The Burke-Litwin model (see Figure 8) is valuable not only because it specifies the causal relationships between key organization variables, but also because it clearly differentiates between transformational and transactional dynamics in organizations. Organization climate, for instance, is a transactional factor. Although it is strongly influenced by more enduring aspects of organizations, and therefore may be relatively predictable on average in the long run, it is also fairly easy to influence in the short term (Schneider et al., 1996). Changing the underlying, enduring aspects of organizations, such as culture, is considerably more difficult, but may have more impact on long-term performance because it operates at the transformational rather than transactional level of organization dynamics (Burke, 1994; Schneider et al., 1996).

Figure 8 presents a summary of the Burke-Litwin model. Following principles of a systems theoretic view (Katz & Kahn, 1978), the Burke-Litwin model begins with environment, from which inputs are brought into the organization, and ends with individual and organizational performance, or the outputs. In a sense, however, the model finally ends with the environment once again, as the model also includes a feedback loop linking outputs back to environment and system inputs. The factors depicted in between environment and performance are the throughput. It is here that the model offers some specificity on the mechanisms by which the organization does its work.

Figure 8. The Burke-Litwin model of individual and organizational performance (adapted from Burke & Litwin, 1992).

Transformational Dynamics

The transformational factors are represented by the top three boxes in the model presented in Figure 8. Consistent with our discussion thus far, Burke defines transformational factors as "areas in which alteration is likely caused by interaction with environmental forces (both within and without) and which require entirely new behavior sets" (1994, p. 129).

Mission and strategy refer to what the organization members hold to be the central purposes of the organization, and the general strategy by which the organization plans to pursue them. Note that this may or may not be accurately captured by a mission statement. This factor is based on what organization members believe to be the mission and the strategy, not necessarily what is written in a formal statement.

Burke (1994) describes culture as "the relatively enduring set of values and norms that underlie a social system. These may not be entirely conscious. Rather, they constitute a ‘meaning system’ that allows members of a social system to attribute meaning and value to the variety of external and internal events they experience" (p. 126). Culture is strongly influenced by the history, traditions, and customs that are passed down to new members over time.

Leadership is defined as the behaviors of senior management that establish direction for the organization and encourage organization members to take the requisite actions to move in that direction. Transformational leadership, as discussed above, and the values held and communicated by executives are included in this variable.

Leadership is central in the Burke-Litwin model, having a strong causal impact on culture and on mission. O’Toole’s (1994) notion of values-based leadership, for example, clearly establishes the link between culture and effective transformational leadership. Leadership is also closely tied to mission and strategy. Although formalized statements of mission and strategy represent the linear, analytical goals and strategies of the organization and its members, the purpose created by transformational leadership may occur through more creative direction-setting activities, such as creating a shared vision for the future that is vivid and inspiring to organization members. Tichy and Devanna (1986), for example, discuss how effective transformational leadership entails "right-brain" visioning before "left-brain" strategizing. Thus, the leadership-to-strategy arrow may require leaders to translate a creative, personal, emotional vision into a pragmatic, analytical mission and strategy. A vivid, well-communicated vision is an important part of charting a new direction for an organization and its members (Beckhard & Harris, 1987; Kotter, 1996; Tichy & Devanna, 1986).

The remaining throughput factors make up the transactional variables of the model. Changing transactional factors is easier than changing transformational factors, but will have less of a long-term impact on performance if transformational factors are unaffected and remain essentially unchanged.

Because it is a causal model, the Burke-Litwin model can serve scholarly and empirical as well as practical purposes. Researchers may use the model to define important organizational variables, whereas practitioners can use the model to help guide change efforts. One key to using the Burke-Litwin model effectively is finding levers for facilitating lasting organizational change. Forces for change are weighted more heavily at the top, starting with the environment. The environment supplies the most potent forces for change, particularly generative change. Although this may seem paradoxical, that reaction to environmental forces may result in nonreactive, generative learning; the key lies in the relationship between the environment and the transformational factors. Tichy and Devanna’s (1986) notion of "planful opportunism" is a good way to think about this interaction. After environmental forces, leadership, mission and strategy, and culture are the most important factors for transformational organizational change.

Although the Burke-Litwin model is a useful causal model for diagnostic purposes, it does not elaborate on the specific means by which change occurs. That is, the model suggests which variables to change in order to spur transformational or transactional change, but it does not elaborate on exactly how to do so. Thus, we understand the whats and the whys, but not necessarily the hows. So that we may understand the specific hows of facilitating successful organizational development and learning, the next section turns to a related stream of literature on learning organizations.

Conceptual foundations for organizational learning were laid by Harvard’s Chris Argyris and MIT’s Donald Schön (Argyris, Putnam, & Smith, 1985; Argyris & Schön, 1974, 1978, 1985; Schön, 1983). Argyris and Schön have written extensively on learning through action and reflection, challenging assumptions and implicit theories, and working on the processes by which problems are defined and solved. Following is a brief summary of their work, then a review of a more recent approach developed by Peter M. Senge (whose work was also influenced by Argyris and Schön).

A previous paper (De Smet, 1997a), drawing primarily from Argyris and Schön, used the adaptive systems framework, presented above, to outline the essential steps of organizational learning: (a) goal setting, (b) model building, (c) hypothesis testing, and (d) learning and action.

Goal setting is the first step to learning. In different ways, it drives both transformational and transactional change. Transactional improvement is by nature incremental and entails solving a series of operational problems over time. This is what Argyris and Schön (1978) call "single-loop" learning. Double-loop learning, on the other hand, is discontinuous. Instead of searching for new action strategies for achieving a given goal, double-loop learning occurs when the strategic or "governing variables" (Argyris et al., 1985) that frame the operational problems are themselves revisited. Schön (1983) calls this "problem setting" and explains the importance of this process as follows:

Thus, the first step in examining a particular problem is to frame it, at least in a general sense, by setting the goals of the situation.

The second step is to build causal models based on the implicit theories of the leaders, managers, and decision makers who run the organization. For some time, cognitive psychologists have understood that humans carry around in their minds a set of vocabularies and categories, scripts and schemata, and other implicit forms of knowing and understanding the world around them (for a more complete discussion, see Nisbett and Ross [1980]). This is what

Schön (1983) calls "tacit knowing" (see also Argyris et al., 1985; Kuhn, 1962). The model building step aims to make tacit knowledge explicit so that it can be systematically explored and tested.

Once identified, naïve theories and mental models are put to the test. Testing hypotheses requires not only measuring operationalized variables, but also making changes and experimenting so that alternative explanations can be explored and eliminated. Although strict scientific experimentation is not necessary, some degree of systematic inquiry is desirable. Even lacking scientific rigor, the process of systematically acting and reflecting is likely to generate feedback and learning (Argyris et al., 1985; Argyris & Schön, 1978; Schön, 1983; Weick, 1979). It is important to remember that the goal here is negative feedback. That is, we aim to disconfirm some of our hypotheses, or at least to use feedback to extend or generate new hypotheses. If hypotheses are completely confirmed and the data cannot be used to revise them, the process has failed to produce information that can be used to improve performance.

Finally, hypothesis testing is expected to result in improved organizational functioning. Improvement of functioning, and therefore learning in the organizational sense and not just in terms of individual knowledge, requires action. Without action to improve functioning, learning cannot be said to have taken place.

There are three ways that feedback can lead to improvement. First, based on level 3 feedback (complex self-regulation), incremental improvement can be achieved through better activity coordination and resource allocation decisions. The same things are done, but they are done in incrementally different amounts, sequences, or combinations.

The second way to improve functioning is based on the level 4 model (self-improvement), which can be thought of as operational problem solving or single-loop learning. Here, failure to achieve intended results through specified means results in a search for better means, but the problem to be solved is seen in exactly the same way. Improving existing means or creating new means to achieve the desired ends as originally framed is Argyris and Schön’s (1985) definition of single-loop learning.

The third way to improve, based on level 5 functioning (adaptation), is through transformational, discontinuous, adaptive change. Here, unexpected results contained in the feedback lead to a new understanding of the organization’s purpose or a fundamental reframing of the problem under consideration. This is essentially how double-loop learning is defined.

Although a general description of how organizations learn provides a useful starting point for understanding organizational learning dynamics, it does not offer a great deal of insight about how to achieve systematic learning. What must an organization do, specifically, to institutionalize the learning process? In his landmark book, The Fifth Discipline: The Art and Practice of the Learning Organization (1990), Peter Senge answered by proposing five critical elements, or disciplines, that facilitate systematic learning, growth, and adaptation: (a) personal mastery, (b) mental models, (c) shared vision, (d) team learning, and (e) systems thinking.

By personal mastery, Senge is referring to learning at the individual level. Although individual learning does not guarantee organizational learning, it is a prerequisite. If the members of an organization do not strive to learn and develop, neither will the organization to which they belong.

Building on the idea of cognitive psychology and tacit knowing, as discussed above, Senge argues that the primary reason why good ideas are not recognized, and why they often fail even when they are recognized, is problematic mental models. Our mental models, our implicit beliefs and assumptions about the way things are, are often unconscious, but they guide our behavior nonetheless. Deeply ingrained mental models shared by a group or organization are not dissimilar from the concept of organizational culture. The way we approach a problem or task is constrained by what we assume without question to be true.

According to Senge, the key to mental modeling as a discipline lies in the reflection and inquiry skills whereby organization members learn to identify, question, and challenge their implicit assumptions and overcome the defensive routines that tend to protect these assumptions (Argyris & Schön, 1985). We must strike a balance between what Argyris calls "inquiry and advocacy." When organization members spend too much time asking questions (inquiry), unsatisfied until they know everything about everything, they may be paralyzed and fail to act. On the other hand, when they concentrate only on their own position and the current way of doing things, never stopping to question its merits (advocacy), they fail to learn and change. The key is to balance reflection, inquiry, and learning, on the one hand, with planning, advocacy, and action, on the other.

Although a personal vision and individual learning are important, learning at the organizational level requires that they overlap. The individual members of an organization must share a vision for the organization. What is the basic purpose of the organization? Where will it be, ideally, in 10, 20, or 30 years? Traditionally, these questions are answered by senior management, but Senge argues that the top-down approach tends to kill organizational learning. A good vision, generated at the top and communicated to the rest of the organization, may engender compliance, but it will not garner true commitment from the organization’s members. To get real commitment and the creative energy that comes with it means that the vision must evolve through a series of dialogues at all levels of the organization. (For a theoretical distinction between compliance and commitment, see Kelman [1958, 1974].)

Developing shared vision is not the only task. Senge argues that the "governing ideas" must be mutually created and shared throughout the organization as well. By governing ideas, Senge is talking about not only the corporate vision, but also its purpose and direction (reflected in the mission statement) and core beliefs and values (i.e., culture). Creating shared vision, purpose, and values is not an easy task for leaders of organizations that do not already have them. Senge emphasizes that, to be successful, the leader’s role must be that of designer, steward, and teacher, rather than general or captain.

Like the synergy illustration provided above, Senge’s concept of team learning focuses on the synergistic qualities created through group dialogue and discussion. Mental models and defensive routines often get in the way of constructive dialogue and discussion because our habitual ways of behaving and interacting restrain our ability to challenge assumptions and propose new ways of doing things (Argyris & Schön, 1985). When we are prisoners of our own assumptions and defensive routines, current reality tends to be viewed as the only possible reality, and learning becomes impossible.

Another of Senge’s points on team learning is that it is a team skill that must be used and practiced. A group of talented individual learners who are motivated to learn is not enough for learning to occur at the group level. As with the synergy example, learning groups must learn how to learn together.

Much of Senge’s discussion of systems thinking already has been addressed. For example, Senge’s "second law" of the fifth discipline states, "The harder you push, the harder the system pushes back" (1990, p. 58). This is similar to Lewin’s notion of driving and restraining forces. Senge, like Lewin, advises that adding driving forces tends not to be very helpful, and that the key to change lies in reducing what he calls balancing forces (what Lewin called restraining forces).

Senge also points out that "today’s problems come from yesterday’s solutions," "cause and effect are not closely related in time and space," and "the cure can be worse than the disease." Senge is emphasizing two key points. First, short-term fixes are often even bigger problems later on, highlighting the importance of examining both short- and long-range organizational outcomes. Second, managing complex organizations is not about finding simple solutions to simple problems. Our assumption that a root problem is not far away from its symptoms often misleads us.

A third important point is that "small changes can produce big results—but the areas of highest leverage are often the least obvious" (Senge, 1990, p. 63). Like the levers in the Burke-Litwin model, leverage is not always easy to find, but if it is found, lasting and substantial change can result.

The adaptive systems framework can be used to synthesize and integrate current literature on organizational change and organizational learning. Although clearly related, recent literature on organizational learning (e.g., Senge, 1990) has remained largely separate from parallel work on organizational development and transformational change (e.g., Burke, 1994). The similar yet fragmented work in these areas points out the need for a parsimonious, theory-based, and precisely defined conceptual framework to integrate the two approaches. The adaptive systems framework can serve this purpose.

Recall that the five levels of the adaptive systems framework are not discrete levels of functioning. As shown in Figure 9, these levels can be thought of as defining points on a continuum of functioning. Transactional change occurs between level 2 (simple self-regulation) and level 4 (reactive learning), whereas transformational change occurs between level 4 (reactive learning) and level 5 (generative learning). The five levels of functioning also delineate four different learning dynamics: (a) continuing operations, (b) resource management, (c) innovation, and (d) adaptation (for a thorough description of the adaptive systems framework continuum depicted in Figure 9, see De Smet [1997b]).

The integration of work on organizational change with organizational learning using the adaptive systems framework provides a theoretical basis on which to make a series of predictions about how and when particular organizational dynamics will lead to effective organizational management, innovation, and adaptation, and when each of these sorts of changes will be successful given key internal and environmental conditions. The following section, applies and extends these predictions as they relate to substance abuse treatment organizations.

Although the characteristics of organizational learning, effectiveness, and adaptation presented above apply to organizations in general, special problems are presented by particular types of organizations. Large consumer products firms (e.g., Procter & Gamble), for instance, have particular advertising and promotional concerns that are not relevant for small professional service firms (e.g., a law firm or accounting firm). Substance abuse treatment organizations also have concerns that may not be relevant for other types of organizations. Factors affecting innovation and adaptation in substance abuse treatment organizations, their implications, and recommendations and suggestions for future research are discussed below.

Many factors that affect public organizations and the delivery of therapeutic services have special implications for adaptation and change in substance abuse treatment organizations. Nutt and Backoff (1987, 1992, 1993), for example, have compiled a body of work on the special nature of strategy development, implementation, and transformation in public- and "third-sector" organizations. Many of the specific issues raised by Nutt and Backoff (1993) are addressed below in the discussion of the implications of (a) the adaptive systems framework and (b) the unique qualities of substance abuse treatment organizations on (c) change and learning in those organizations. That discussion will be facilitated, however, by first briefly reviewing two critical factors affecting change in substance abuse treatment organizations: (a) subsidy and (b) clarity and scope of the services provided. These two factors are important because they affect the way in which the organization interacts with its environment and the nature and use of the organization’s feedback loop (these implications are discussed at length in the next section).

Subsidy
The General Nature of Subsidization

The generic purpose of any formal organization is to generate more value, either to customers or to society, than it costs to do so. If the costs of adding value exceed the value added, then the activity or program constitutes a net drain on the system in which it operates. Organizations and governments subsidize particular activities to correct inefficiencies. Training and education are good examples of organizational and societal/governmental subsidized interventions, respectively. Thus, an activity may be considered "subsidized" whenever it is funded or supported by resources it does not directly generate.

From an economic perspective, subsidized government interventions are necessary in order to correct market inefficiencies (Arrow & Debreu, 1954). The free market is "inefficient" when it fails to acknowledge important costs or benefits of a particular activity, such as when organizations engage in an activity to a greater extent than is warranted by the overall costs and benefits. Pollution, for instance, tends to have an equally negative impact on polluters and nonpolluters alike, but organizations pollute because they reap all the benefits. Thus, even when total costs outweigh total benefits, the marginal benefits may outweigh the marginal costs for those choosing to engage in the activity. This is the basic concept of externalities, that costs or other effects of an activity or economic transaction are borne by individuals and groups external to that transaction. Externalities explain one reason why subsidized intervention is necessary.

Other forms of subsidized intervention address the opposite problem, that of costs being borne primarily by those choosing to engage in the activity while benefits are less clear and/or more widespread. Research activities are a good example. Absent intervention, the costs of conducting research tend to be borne only by those who engage in it, whereas the benefits tend to spill over and positively affect all who acquire the information generated and who indirectly benefit from its application. Thus, the net benefits of research may be positive overall, but may not be beneficial for those who might engage in the activity. Subsidized intervention in this case might include a private firm’s attempt to restrict spillover, and thus gain competitive advantage from research, or for the government to fund important research directly. Substance abuse treatment can be considered similarly. Although in many cases the cost of treatment cannot be borne by the clients alone, the net gain to society is positive for ethical and practical reasons, thus constituting a spillover that justifies subsidization by society. All of these activities represent what Katz and Kahn (1978) call political and maintenance functions. That is, they are supported (i.e., subsidized) by the production functions that directly generate surplus energy.

Subsidy and Bureaucratic Inefficiency

Because the resources that sustain subsidized entities are not directly tied to that entity’s performance in the market place, but instead to its budget, publicly funded service institutions strive toward maximization of size, budget, and impact, rather than optimization of efficiency (Drucker, 1985). Thus, they tend to act more like a level 1 or level 2 system, striving not to improve the efficiency or effectiveness of their throughput activities, but simply to increase the flow of resources through the system, maximizing inputs and outputs and attempting to expand or enlarge the system itself.

Budget maximization and bureaucratic inefficiency result from focusing on acquiring more energy and resources rather than doing more with them. Theory and research demonstrate that bureaucratic inefficiency tends to occur whenever the parties engaged in subsidized activities concentrate their energies on claiming existing value rather than adding value (c.f., Downs, 1967; Milgrom & Roberts, 1992; Niskanen, 1991; Onis, 1995). Katz and Kahn (1978) similarly note that, although private companies tend to grow in order to increase value surplus (i.e., margins), subsidized institutions such as public universities may pursue growth regardless of any actual or anticipated marginal value achieved because budgetary allocation from the state, not value added, is proximally responsible for a subsidized entity’s survival and prosperity.

One way to address the bureaucratic inefficiencies that result from subsidization is to impose some form of market or other feedback that rewards optimizing throughput instead of maximizing resource consumption. Although imposing market-type feedback on publicly subsidized activities may not make sense, other forms of feedback mechanisms, when integrated with organization development techniques, can be used to improve organizational efficiency and effectiveness. The task of using performance feedback is particularly difficult for substance abuse treatment organizations, however, because of the unclear scope of the services provided and their long-term impact on clients.

Clarity and Scope of Services Provided

Designing and implementing performance feedback mechanisms is particularly difficult for substance abuse treatment organizations because of the intangibility and ambiguous scope of the services they provide. Management theory and research have conventionally focused, at least in practice, on manufacturing organizations. Increasingly, attention is turning to service organizations (e.g., Schneider, 1990), but even services can be more or less tangible.

Tangibility of Services and Scope of Service Impact

Although we tend to think of services as intangible and products as tangible, different products and services can be thought of as possessing varying levels of "tangibility," or conceptual concreteness. McDonald’s, for instance, is a service firm. What they have to offer, above all else, is convenience. But their service is a relatively tangible one, meaning that the service is conceptually clear and concrete. When McDonald’s provides its services to a customer, the customer can measure exactly how long it took to deliver the order and will know immediately whether or not it was delivered promptly and prepared to specification. Similarly, traveling on an airline is a conceptually clear and concrete service. Passengers know exactly when the service starts and ends, and when it is complete, they immediately know whether or not they have safely arrived at the specified destination. Nor is it necessary for the customer to determine these things based on subjective standards. Even naïve external observers would know whether these services were satisfactory or not if they knew what the customer had requested.

Many services are conceptually concrete and easily lend themselves to assessments of quality and customer satisfaction. Substance abuse treatment is different; it is conceptually "fuzzy." Even from the perspective of a single client, it is not clear when the work of the organization begins and ends. The extent and quality of the service are also difficult to measure. When considering all the stakeholders, not just a particular client, by including society and the political constituents who may be providing financial support, the goals and nature of the services provided are even less clear.

The Problem With Customer Satisfaction

When the outputs of an organization are relatively tangible, assessment of quality can be conducted in an objective fashion by checking to see if products have been made to specifications. Alternatively, for private profit-seeking firms, the market will offer feedback through low demand if a product or a service is undesirable or has design flaws. When all else fails, customer satisfaction offers a useful subjective approach to gauging performance effectiveness. Although more elaborate methods can be used to assess the impact and effectiveness of subsidized, intangible services, customer satisfaction is often used as a general barometer for overall service quality. A few subsidized services, however, do not lend themselves to the customer satisfaction approach. With substance abuse treatment organizations, for example, a client’s "satisfaction" may need to get worse before it gets better. Thus, the customer satisfaction bellwether that is useful for so many subsidized services is inadequate for assessing substance abuse treatment organizations. Treating opiate addicts with an unlimited supply of morphine, for instance, might provide a boost to customer satisfaction, but others would not consider it to be an effective form of treatment. Although drug testing provides one way to gauge the impact of the services provided, it does not directly assess quality of service. Because of the inherently intangible quality of the service itself, there is no easy way to assess the performance of substance abuse treatment efforts.

The Human Factor

Related to the intangible aspect of the service itself is the human element of the "output." That is, substance abuse treatment organizations can be effective only through the behavior of their clients. Unlike a fast-food restaurant or an airline, where the customer passively consumes the service provided, substance abusers must fully and actively participate in the provision of the service. This is certainly an unusual notion for most organizations. Only in educational and therapeutic settings can it be said that the key "service provider" is not an employee, but the client. The fuzziness of the service extends to the organization itself. In most organizations, the customer is considered part of the external environment, but with substance abuse treatment organizations, given the importance of active participation in treatment, the client may legitimately be considered a member of the organization.

Time Frame

Finally, the fuzziness of substance abuse treatment services applies also to the time frame of intended outcomes, which tends to be longer and more ambiguous for therapeutic organizations than for others. Senge’s advice to concentrate on long-term rather than just short-term outcomes is especially true of substance abuse treatment organizations.

The factors described above present unique challenges for the study and operation of therapeutic and human service organizations in the public sector. Nutt and Backoff (1993) provide a useful summary of some key issues related to change in public- and third-sector organizations (see Table 2). Because of subsidization, for example, market characteristics are unclear and goals are vague. Nutt and Backoff (1993) explain as follows:

There is no equivalent for profit that applies to public sector organizations. In such organizations, goals tend to be both vague and disputed. Attempts to sweep away this ambiguity encounter several problems. The difficulty of goal setting can supersede the development of strategic options. Goal-setting processes that become ends in themselves stymie action. However, leaving goals implicit makes it difficult to modify or even evaluate current practices. (p. 313)

Although addressing all of the developmental challenges confronting substance abuse treatment organizations is beyond the scope of this paper, three of the most pressing challenges are highlighted: (a) defining the organization, (b) dealing with political resistance to performance feedback, and (c) fully understanding the impact of treatment.

Table 2. Summary of strategic and organizational change considerations for public-sector organizations (adapted from Nutt & Backoff, 1993).

Defining the Organization

Given the particular issues that substance abuse treatment organizations must address (see Table 2), such as goal ambiguity, unclear performance expectations, multiple and conflicting stakeholder interests, frequent political influence attempts, regulatory constraints, and heightened public scrutiny, perhaps their most pressing imperative is a definition of the organization and the environment in which it operates. This imperative includes defining the organization’s core identity and purpose, demarcation of organization boundaries, and identification of key client or other stakeholder groups whom the organization is expected to serve or to whom the organization is accountable.

Defining Purpose

Shared vision and common purpose are necessary to sustain organizational innovation and adaptation. A mutual understanding of "what we do," "who we are," and "whom we serve" by an organization’s members and other stakeholders is a crucial first step to building shared purpose and a common vision. As discussed above, molding a common purpose for an organization is central to transformational leadership and successful organizational development. For transactional change, too, or even resource allocation, clear organizational goals are necessary to regulate throughput and maintain efficient and effective functioning.

Proposition 1. Substance abuse treatment organizations will be more effective when they explicitly identify their core identity and purpose.

Nutt and Backoff (1993) note that this task should not be approached in the same way for public organizations as for private firms

Proposition 2. Substance abuse treatment organizations that explore origins, history, and trends before attempting to change are more likely to create transformational change (i.e., they are more likely to successfully adapt) (Nutt & Backoff, 1993).

Finally, in defining core identity and purpose, private firms may emphasize products or services offered and strategic performance goals for the organization. Public organizations, however, were created not to offer a product or service at a profit, but to enhance the public welfare. Thus, a public organization should emphasize vision, values, and ideals over strategic goals and performance objectives.

Proposition 3. Substance abuse treatment organizations that emphasize values and ideals over specific performance objectives are more likely to create transformational change (i.e., they are more likely to successfully adapt) (Nutt & Backoff, 1993).

Defining the Client System

Another aspect of defining the organization and its purpose is targeting the appropriate group of clients. Because they are subsidized, it is not always clear who the relevant constituents of a substance abuse treatment organization are, or who the "customers" who directly consume the organization’s services are. Whereas a substance abuse treatment client receiving treatment services clearly belongs to this "customer" group, it is not clear whether a spouse who participates in marital counseling or benefits from other ancillary services is a customer as well, or just an incidental beneficiary. As this example points out, it may not be black and white. Constituency groups within the client system may be prioritized, with currently participating clients targeted as the primary customers; with parents, spouses, and children of current clients as secondary customers; and with others in society such as voters and taxpayers as tertiary customers. Whatever the extent of the client system, using feedback to improve performance requires an understanding of who is being served and how. Thus, it is imperative for substance abuse treatment organizations to define the client system.

Proposition 4. Substance abuse treatment organizations will be more effective when they explicitly define the client system.

A vision and purpose cannot be constructed to guide an organization effectively when there is confusion about who is to be served. Definition of the client system and other relevant stakeholder groups, to the extent it can be measured, may help explain the success of treatment efforts. It could be that a narrower or broader conception of the client system facilitates performance, either in general or under particular environmental and organizational conditions. Although there is little evidence to support an answer one way or the other, it is an empirical question that should be studied.

Proposition 5. The effectiveness of substance abuse treatment organizations will partially depend on how broadly the client system is defined.

Proposition 6. The effectiveness of substance abuse treatment organizations will partially depend on how various stakeholder groups are defined and prioritized in relation to the primary customer or client group.

Defining the Boundaries of the Organization

Defining the organization itself is just as important to clarity of purpose as defining the client system. For example, are family members who actively participate in treatment considered voluntary members of the treatment organization? Although there is no exchange of services for money, these family members are clearly engaged in an exchange of valuable resources. Like the treatment service providers, they are supplying time and energy to assist in the treatment of addicts; in exchange, they hope that treatment of their loved ones will be more successful. Although it is unclear how peripheral members of the organization should be defined, the issue should be addressed. Vision and purpose will not guide a system effectively when it is not clear who is and who is not a part of that system.

Proposition 7. Substance abuse treatment organizations will be more effective when they explicitly define the boundaries of the organization.

Proposition 8. The effectiveness of substance abuse treatment organizations will partially depend on how broadly the organization is defined.

The explicit demarcation of boundaries does not mean that organizational boundaries must be defined with exact specifications in closed or rigid terms. The boundaries of an organization, however identified, can be more or less open (Katz & Kahn, 1978). An organization that is open will be more apt to change, will be more flexible, will more easily absorb environmental perturbations, and will adapt to environmental changes. On the other hand, an organization that is constantly changing may find it difficult to improve coordination and efficiency incrementally. When a steady state is achieved, rigidity and higher control allow a system to improve the efficiency of self-regulation toward a set of fixed performance goals. Perseverance in the face of environmental change may be more desirable under these conditions. However, an organization whose boundaries are rigid and impermeable may not be able to sustain itself in the face of rapid environmental change.

Proposition 9. The effectiveness of substance abuse treatment organizations will partially depend on the openness and flexibility of the organization’s boundaries.

Proposition 10. The success of a given level of boundary openness and adaptive flexibility will depend on the nature and speed changes in the environment (more change requires more openness and flexibility).

The advantages and disadvantages of open and flexible boundaries versus closed and rigid boundaries must be weighed. This is what Nutt and Backoff (1993) refer to as a key issue tension faced by public organizations. They argue that forming issues as tensions is especially appropriate for public-sector organizations and suggest that they "find ways to manage these issue tensions and realize ideals by building on strengths, overcoming weaknesses, exploiting opportunities, and blunting threats" (p. 320).

Proposition 11. Substance abuse treatment organizations will be more effective when they frame boundary issues as tensions (see Nutt & Backoff, 1993).

Defining Relationships With Others

Substance abuse treatment organizations interact with identifiable systems other than themselves and their clients, such as funding or regulatory agencies; providers of medical, social, and ancillary services; and the criminal justice system. Organization members who interact with these other systems or represent multiple constituencies fill boundary-spanning roles and may experience high levels of role conflict, role ambiguity, and job-related stress (Katz & Kahn, 1978). Because of the fuzziness of substance abuse treatment organizations’ boundaries, they may have more boundary-spanning roles than other organizations. It is important to define these roles, both to enhance the effectiveness of linkages with other groups and organizations and to reduce the ambiguity and stress experienced by those who fill or enact these roles.

Proposition 12. Substance abuse treatment organizations will be more effective when they explicitly define their relationships with groups and organizations that can inhibit or enhance successful treatment of their clients.

Proposition 13. The effectiveness of substance abuse treatment organizations will partially depend on the strategies used to interact with these other groups and organizations.

Proposition 14. The effectiveness of substance abuse treatment organizations will partially depend on the effectiveness of liaisons who link the substance abuse treatment organization with these other groups and organizations.

Because of political influence, many stakeholders, and heightened public scrutiny, public- and third-sector organizations must develop a "cooperative ecology" in order to implement change successfully (Nutt & Backoff, 1993). Both the type of changes that are planned and the ways in which the changes are implemented must be co-developed with key stakeholders. Therefore, they must involve key stakeholder groups in the planning of change and make resource and stakeholder assessments to gauge potential costs, possible negative impact on others, and potential political resistance or support before attempting innovative or adaptive change. Stakeholder resistance, resource gaps, and other barriers likely to block change will be addressed in a more effective and more timely manner when stakeholders participate in fostered and stakeholder assessments.

Proposition 15. Substance abuse treatment organizations that create forums in which the participation of key stakeholders is stressed are more likely to create viable change (Nutt & Backoff, 1993).

Proposition 16. Substance abuse treatment organizations will more successfully implement changes when change strategies are co-developed with key stakeholders.

Proposition 17. Substance abuse treatment organizations that perform explicit, systematic stakeholder and resource assessments are more likely to create viable change strategies (Nutt & Backoff, 1993).

Political Resistance to Performance Feedback

Katz and Kahn (1978) noted that researchers often overlook the inputs of an organization, but that these are the most important variables for continued functioning. Because substance abuse treatment is often subsidized and the services provided are intangible and have a long-term impact that is difficult to measure, inputs are often secured as much by political means as by the provision of effective treatment.

Proposition 18. Nonmarket feedback is more ambiguous than market feedback and therefore more sensitive to political influence.

Proposition 19. Increased number of stakeholders and greater sensitivity to political influence will result in more political influence attempts toward substance abuse treatment organizations.

Proposition 20. Increased number of stakeholders who may affect resource availability, and greater sensitivity to political influence in the absence of market feedback, will result in more political influence attempts toward key stakeholder groups.

Evaluation Research as Feedback

Without performance feedback, a subsidized entity will be rewarded not for its value to the suprasystem that supports it, but to the political forces that keep its coffers full. In place of the relatively unambiguous market feedback that private firms receive, evaluation research may be used as performance feedback to maintain adequate efficiency and effectiveness.

Proposition 21. In the absence of market feedback, evaluative research may help align rewards with the performance goals of the organization and key stakeholder groups.

Because evaluators may or may not be independent, and evaluation research is often sensitive to assumptions and interpretations, it is unclear whether feedback provided by evaluative research will curb political dynamics or have the opposite effect. In general, the less conflict there is between stakeholders, the less sensitivity there is to interpretations and assumptions, and the more independent the researchers, the more likely it is that evaluation research will limit instead of heighten political dynamics.

Proposition 22. Because it introduces performance feedback into the system, conducting evaluative research will affect the frequency and intensity of political influence attempts. Whether evaluative research curbs or heightens political dynamics depends on the political climate and the nature and findings of the research.

Proposition 22a. The greater the conflict between various stakeholder groups and the more ambiguous the political environment, the more likely political influence attempts will be used to sway the use or outcome of evaluative research.

Proposition 22b. The more an evaluative research effort is perceived as sensitive to assumptions and interpretations, the more likely political influence attempts will be used to sway the use or outcome of evaluative research.

Proposition 22c. The more evaluation researchers are perceived to be biased or potentially biased, the more likely political influence attempts will be used to sway their methods, results, and recommendations of their research.

Assessing Outcomes in Relation to Costs

By excluding costs from evaluative research examining the impact of subsidized services or continued need for those services, the implications of low impact or persistent need are highly ambiguous. Without relevant cost data, low impact can be used to argue for additional resources and expansion of services provided, or for the opposite, reform or program closure, based on ineffective results. Thus, evaluative research that does not account for costs as well as impact is likely to heighten political dynamics with regard to the interpretation of research results. On the other hand, inclusion of cost data may heighten resistance from the organization under scrutiny, since there is an implication that efficiency is at question and imposition of tighter cost controls, not more resources to expand treatment, is perceived as the likely result.

Proposition 23. Failing to link costs and outcomes will increase political attempts to influence the interpretation of evaluative research results.

Proposition 24. Linking costs and outcomes will increase political resistance to the evaluative effort by the organization and key stakeholders who support it and will undermine change efforts.

Political Resistance to Cost Evaluation

Cost-benefit analysis can be applied using a mechanistic mental model and a performance orientation, where program costs and benefits are tallied to determine cost-justifiability (i.e., whether the organization should be expanded, curtailed, or eliminated), or an adaptive mental model and a learning orientation, where feedback is intended to point out the causes of cost-inefficiencies, offer insight into how activities can be improved, and identify opportunities for innovation and adaptation. The obvious consequence of using performance feedback solely for cost-justifiability appraisal (i.e., performance orientation) is that opportunities to improve performance and "expand the pie" through innovation and adaptation may be lost. A perhaps more compelling reason to adopt a developmental focus (i.e., learning orientation) is that cost-justifiability appraisals tend to increase organizational resistance to change and decrease the likelihood that evaluation research results will have any impact at all. As Weiss (1973a, 1973b) notes, a politically favored organization or program will survive despite a negative evaluation, and favorably evaluated programs may still perish due to hostile political forces. Because feedback indicating lack of impact can be justified by a subsidized entity as being due to a lack of resources, thus bolstering arguments for further funding and an increase in budget, but poor performance feedback in the form of cost-benefit analysis results cannot be similarly justified, evaluative research linking costs and outcomes is more likely to be perceived as a threat. Thus, appraisal-focused cost-benefit research will tend to heighten political dynamics rather than attenuate them.

Proposition 25. Performance feedback generated by evaluative research that links costs and outcomes will be less likely to facilitate improved effectiveness (or it will not be conducted in the first place) when powerful stakeholders perceive it as a threat to the organization.

Proposition 26. Performance feedback generated by evaluative research that links costs and outcomes will be more likely to increase political attempts to influence the perceptions and expectations of others, rather than actual performance, when powerful stakeholders perceive it as a threat to the organization.

The threat of a go/no go cost-justifiability evaluation will lead to managing expectations and perceptions to ensure political survival. A learning orientation, however, will facilitate improvement and will help overcome political resistance because the evaluation will not be used to withhold resources or shut down the program. Rather, a developmental approach to cost evaluation is likely to foster a focus on creating value, not just claiming it.

Proposition 27. Performance feedback will be more likely to facilitate improved effectiveness when powerful stakeholders perceive it as an opportunity rather than a threat.

Proposition 28. Performance feedback will be more likely to decrease political dynamics when powerful stakeholders perceive it as an opportunity rather than a threat.

Proposition 29. Evaluative research that links costs and outcomes as part of a developmentally oriented (rather than appraisal oriented) evaluation effort will be more likely to be perceived as an opportunity (rather than a threat) by the organization and key stakeholders who support it.

Proposition 29a. Developmentally oriented evaluation and research will be more likely to attenuate (rather than heighten) political dynamics.

Proposition 29b. Developmentally oriented evaluation and research will be more likely to facilitate (rather than inhibit) successful change efforts.

Because existing cost analysis methodologies do not support this shift away from discrete "yes/no" resource allocation, Yates (1994) and De Smet (1997a) have developed a cost assessment method consistent with an innovative activity improvement orientation.

Understanding Impact

Finally, substance abuse treatment organizations must develop a better understanding of service activities’ impact on clients. Nutt and Backoff (1993) note that scope of impact may be broadly or narrowly conceived (see Table 2). Similarly, Senge (1990) comments that cause and effect are often far away from one another in time and space. This is particularly problematic for substance abuse treatment. Understanding the nature of treatment impact and the processes that contribute to successful outcomes will stem from (a) an organization’s conception of its identity and purpose and (b) evaluative research linking various activities that occur inside and outside the formal boundaries of the substance abuse treatment organization to short- and long-range socioemotional, behavioral, and economic outcomes. Only by understanding purpose and impact can organizations generate useful performance feedback to effectively self-regulate and learn over time.

Proposition 30. Substance abuse treatment organizations will better understand their impact on clients when the organization has a shared understanding of its own purpose.

Proposition 31. Evaluative research that links basic throughput activities to both short- and long-range outcomes will be more likely to generate information on organizational impact.

Proposition 32. Substance abuse treatment organizations that understand their purpose and their impact are better able to generate useful performance feedback for self-regulation and learning.

The type of self-regulation and/or organizational learning that occurs will depend in part on the nature of the performance feedback and how it is used (see Figure 9).

Proposition 33. Substance abuse treatment organizations that identify optimal methods (i.e., "best practices") by evaluating activities in relation to costs and intended outcomes will improve more effectively through better resource allocation, activity coordination, and activity execution.

Proposition 34. Substance abuse treatment organizations that experiment with different activities and track their impact on valued outcomes will improve more effectively through better innovation.

Proposition 34a. When experimentation and innovation are directed toward improving service technologies (e.g., treatment modalities), innovation is likely to be technology driven.

Proposition 34b. When experimentation and innovation are directed toward improving organizational processes (e.g., internal synergies and linkages), innovation is likely to be capability driven.

Proposition 35. Substance abuse treatment organizations that explicitly identify, reflect on, and revise their purpose based on the interaction of internal strengths and weaknesses with external or environmental demands will improve more effectively through adaptation.

Proposition 35a. When purpose and identity are changed in response to perceived environmental threats, adaptation is likely to be reactive.

Proposition 35b. When purpose and identity are changed in response to perceived opportunities, adaptation is likely to be generative.

Future research on organizational learning and adaptation, both generally and for substance abuse treatment, has three tasks: (a) generate theories and hypotheses (such as the propositions presented above), (b) develop tools and methodologies for measurement and analysis, and (c) test and refine the theories and hypotheses. The first task, to generate theory, is inductive in nature. A useful starting point is the sociological case study method. These methods, however, are too "blunt" (Katz & Kahn, 1978) and need the assistance of more precise constructs and research tools, many of which do not yet exist. Thus, the second task—to develop the proper tools—must be integrated with theory building. Finally, the theories and hypotheses generated must then be tested and put into practice. Although this is familiar territory for many

social scientists, new approaches to data analysis must be developed here as well. More widespread use of nonlinear statistical techniques, for example, is essential for understanding complex dynamic systems.

Although the field of organization development and learning is still in its infancy, enough is known to at least point researchers and practitioners in some promising directions. Some of the most promising areas of study are (a) the feedback process, (b) environmental variables, and (c) governing variables.

The Feedback Process

Although the feedback concept is well represented in theories about organizational learning, it has not received much empirical attention. The feedback process itself, including the means by which organizations assess the environment and their actual versus ideal performance, is critical for learning and adaptation. Initial questions could be as simple as, what sort of feedback about their organizations do managers most want to see? It may be that the preference for one type of information over another leads to superior information gathering—even if it is unsystematic and unscientific—and that paying attention to that information is enough to make a difference in performance. One simple way to categorize focus of attention, for example, is internal and external. Studies have shown that individuals, for instance, perform better on certain tasks when their focus of attention is internal (see Carver & Scheier, 1981). Although it is not clear exactly how we might test the attentional focus of an organization instead of an individual, one obvious possibility is to test the self versus the environmental focus of key individual organization members such as leaders or others in powerful or boundary-spanning roles.

Environmental Variables

The environment is another area ripe for research, particularly in the area of substance abuse treatment. Part of the problem with studying the effects of environmental variables is that the smallest unit of analysis tends to be the organization. As those who have conducted research on groups have found, getting a sufficient sample size can be very difficult even with small groups. Organizations present quite a larger problem. Nevertheless, environmental variables should not be ignored simply because they are difficult to study (c.f., Lawrence & Lorsch, 1967). Theory, along with the research that is available, suggests that the environment may be the most important determinant of organizational functioning and survival.

The Political Environment

One key aspect of the environment for substance abuse treatment organizations is the political environment. Aspects of the political environment might include the nature and perceived certainty of funding, the resource and position power of relevant stakeholders, and the likelihood that circumstances will change as new political appointees are ushered in every 4 years or so.

Relationships With Suprasystems

Another important environmental variable is the substance abuse treatment organization’s relationship to other systems, including suprasystems—broader systems within which it operates. Is the organization governed by the state, by a federal agency, or by a board of trustees? What are its relations with local religious and community groups? These types of questions are not traditional, but they are important. To understand a complex system, we must understand its relationship with the environment.

Governing Variables

Potentially the most useful research lies in the investigation of governing variables such as mission and strategy, leadership, and culture. Vision and mission statements, for example, are thought to be important for organizational success (Kotter, 1996), yet there is no solid research on whether having a good, well-communicated vision statement enhances organizational performance. Similarly, research on leadership has not been very fruitful, in large part because the construct has been ill-defined and poorly operationalized (c.f., Hogan, Curphy, & Hogan, 1994; Rost, 1991). To be useful, future research efforts on these topics need to be grounded in constructs and theories that are relevant for complex organizations. Open systems theory, the adaptive systems framework, and the Burke-Litwin model may be useful in this respect.

In this final section, it may be helpful to highlight the importance of studying organizational processes related to learning and growing. For example, suppose you were hired to assist or facilitate a reengineering effort to restructure certain aspects of distribution and related services of a large treatment program. At an offsite meeting, key managers and workers gathered to begin redesigning the work. The first step was to assess where they were and where they wanted to go. What emerged from those who actually performed the work was considerably different from what senior managers had previously explained because the formally prescribed work design was no longer viable.

Counseling units within the program, as well as contract counselors and ancillary service providers and linkages with other systems (e.g., welfare, the criminal justice system), had all changed. After a contract clinician and ancillary service providers were brought in, it became clear that the program’s current understanding of operations and requirements of these other providers was also distorted and outdated. These other providers also had changed due to new external demands and internal growth and development.

This example demonstrates two important points. First, the success of the drug treatment was based more on informal learning processes than formal design. Although the organizational architecture had remained unchanged on paper, the social systems involved were constantly reacting and adapting to changing forces in the environment, an ever-shifting service landscape, and intense pressure for change. Second, the key inhibitor to future success was potentially these same processes. Although innovation had occurred at lower levels, the learning process needed to be addressed more formally at the organizational level. Simply redesigning service processes was not the critical task; reengineering represented just another episode of single-loop learning that would again be outdated in short order. The more important task is to institutionalize organizational learning and ensure that performance would evolve over time in a more effective and systematic manner. Substance abuse treatment organizations’ problems are made even more difficult than presented here because of factors related to subsidization and unclear scope of impact. The task for researchers and practitioners is the same: Learn how to learn at both individual and organizational levels.

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This document was written by Aaron L. De Smet, Teachers College, Columbia University. The National Institute on Drug Abuse (NIDA). NIDA is part of the National Institutes of Health (NIH), a component of the U.S. Department of Health and Human Services.

The original version of this document can be downloaded for free by following this link