Weick and Quinn (1999) define the metaphor of episodic change as the inertia-prone organization in which the pace of change is “infrequent, discontinuous, and intentional” (p. 365). This is “second order change” through which outside agents create leverage to change meaning systems and schema, meaning that the organization takes action to replace past practices with new strategies, structure, skills, and people (p. 365). Reviewing academic literature on change, Weick and Quinn (1999) conclude that “failure” (p. 365) triggers all episodic change, as follows: the organization suffers loss, makes plans to change, implements the plan, and then deals with unintended consequences.
Concluding that “change starts with failure” (p. 381) suggests an academic myopia that misses common organizational realities. Although some failures may trigger some changes, emerging and urgent threats, looming government regulations, market opportunities, and new ideas can also trigger change initiatives. These and other change triggers are responses or attempts to influence environmental factors. In such cases, the failure could be in the lack of plan or action, not in triggering a change initiative. Threats to and opportunities for the organization can be disruptive (Schermerhorn, Hunt, & Osborn, 2007), but leaders can enhance adaptability by creating resilient organizations (Hamel & Välikangas, 2003) that can act quickly to reduce negative consequences, turn disruptions to advantage, or capitalize on new ideas and opportunities. In short, failure is not the only trigger for episodic change; rather, episodic change is the transformational change that organizations implement to address failings, threats, or opportunities.
The perspective that sees change as an episodic process has dominated organizational behavior since Kurt Lewin (1951) proposed a change model that saw social behavior as the product of two opposing forces. One side strives to maintain the status quo, an equilibrium state maintained by individual resistance and group conformity. The other side pushes for change toward a desired state. Lewin proposed that driving change in individual and social behavior is a function of reducing the forces maintaining the status quo while strengthening the forces for change. This process has three basic steps: unfreezing, moving, and refreezing. Unfreezing involves shaking up the status quo by increasing the driving forces that direct behavior away from the status quo while decreasing the restraining forces that attempt to maintain the status quo. With the status quo disrupted, change agents can “move” behavior and processes toward the desired state. Finally, once behavior is at the desired state, change agents “refreeze” the new behavior to maintain it over time.
Through the unfreeze-move-refreeze framework, episodic change becomes a foundation of planned process that organizations and people use to recognize and close the gap between the way things are and the way things should be. For example, John P. Kotter (1996) expanded Lewin’s model to provide a practical eight-step plan that organizations use to transform and control people, processes, and markets, as follows: (a) To “unfreeze” an organization: establish a sense of urgency; create a guiding coalition; develop a shared vision and strategy, and; communicate the change vision. (b) To “move” an organization: empower broad-based action by eliminating obstacles, changing systems, and encouraging risk; generate short-term wins, and; consolidate gains and produce more change. (c) To “refreeze” an organization: anchor new approaches in the culture; monitor progress; adjust the vision as required.
A key limitation of seeing change as purely an episodic process is that “freezing” represents a new status quo that must be shattered again whenever the organization faces new threats and opportunities. Further, locking into episodic change prevents leaders from recognizing a vital point about change: organizations cannot not change; status quo is an illusion that micro-level analysis shatters. Because episodic change models tend to be synoptic, they allow leaders to define a plan, but fail to show what occurs between each stage of the plan.
Tsoukas and Chia (2002) argue, “Change is the normal condition of organizational life” (p. 567). In other words, change is constant. Ignoring the dynamic phenomena between planned events can encumber change by hiding the micro-level processes that influence strategic implementation. When leaders assume that change is an episodic process initiated by external forces, they may miss the non-linear micro-processes that inhibit or drive change, misunderstand what happens in a change process as it happens, and mistakenly consider the organization to have a stable status quo. To address these problems, Tsoukas and Chia propose shifting perspective of change as a characteristic of the organization to seeing organization as “an emergent property of change” (p. 570). From this perspective, an organization becomes a set of conventions that balance a constantly changing context toward a pattern of evolution. As people face new realities, their beliefs, values, assumptions, and behaviors adjust. Change programs that adapt to context and individuals will be more successful. Leaders can encourage and provide a framework for change, but plans for specific outcomes will not be as successful as change initiatives that recognize new patterns of thought and action, and then guide desired patterns toward institutionalization.
Livne-Tarandach and Bartunek (2009) identify numerous additional weaknesses of episodic change theory. First, the macro perspective of episodic change fails to consider time, dynamic phenomena, and individual processes that influence strategic change initiatives. Second, by not considering time, plans can become irrelevant and ineffective in the midst of changing circumstances; this contributes to an escalation of commitment to a failed course of action (Brockner, 1992) while the environment changes around plans built for a different environment. By assuming that all players share the same goals and understanding of change initiatives can obscure the individual agendas and group politics that influence organizational processes.
Continuous change theory can help leaders to address the limitations of episodic change models by providing insight into the informal, continuous, and adaptive processes that dynamically interact and adapt to factors inside and outside the organization (Livne-Tarandach & Bartunek, 2009). Developing sensitivity to the change processes continuously at work within the organization can help leaders to evaluate and influence change readiness and develop organizations that can readily adapt in a turbulent environment.
Continuous change is the incremental change that happens to the organization through the dynamic interaction its of people, processes, and environment. Weick and Quinn (1999) define the metaphor of continuous change as the emergent and self-organizing organization that constantly evolves and adapts. This metaphor provides a view of “first order change” (p. 365), which shows an extension and evolution of past practices with current people, knowledge, and skills.
Rather than being an occasional disruption, continuous change involves unending modifications in process and practice. The tempo of episodic change is “infrequent, discontinuous, and intentional” (Weick & Quinn, 1999, p. 365) events that spur the spontaneous evolution of the organization. Alert reactions to inherent instability drives change, as small changes cumulate and multiply to drive cycles of adaptation and evolution. Rather than throwing out old processes and people through an unfreeze-move-refreeze process, the agent driving continuous change redirects and shapes the change, by identifying clarifying, and reframing current patterns while fostering creativity, transformation, and learning. Weick and Quinn (1999) propose that this process is a “freeze, rebalance, unfreeze” (p. 379) sequence. In this sense, freezing means to capture and define emergent processes, rebalancing means to reinterpret the patterns and reframe issues as opportunities. Unfreezing after rebalancing means to “resume improvisation and learning” (p. 380).
As Lewin’s linear model—“unfreeze-move-refreeze”—provides the theoretical foundation for episodic change processes, systems theory provides a basis for recognizing non-linear phenomena at work in continuous change processes. Bertalanffy (1972) proposed general systems theory to show the dynamic nature of change, defining a science of “wholenesss” (p. 37) while providing insight into how mechanistic and organismic models “are not mutually exclusive” (p. 25). Bertalanffy offered the biological organism as a metaphor to explain how organizations are complex open systems, a concept that Katz and Kahn (1966) later adapted for organizational development practice, and that would become an “anchor” for organizational behavior (McShane & Von Glinow, 2005; Jex, 2002).
The organization-as-organism metaphor offers insights into the dynamic process of input, process, and output that drive organizational adaptability. The organization imports sustenance from the environment while influencing the environment through its output. An organizational system consists of interrelated subsystems composed of individuals, groups, and processes dynamically interacting to maintain the organization within its competitive environment. These subsystems dynamically interact within organizational boundaries to maintain the organization and assure survivability, while the organization continuously exchanges resources with and adapts to its environment.
If the organization exists as a monopoly in a static competitive environment, leaders can maintain internal processes at a relatively steady state. However, as the competitive environment becomes increasingly dynamic, the internal people and processes must increasingly enhance productivity, innovation, and adaptation so the organization can survive. As an interrelated web of relationships, change that happens to an individual, group, or subsystem within the organizational system or to any variable outside of the organization can have unplanned and unintended consequences throughout the organization (Bertalanffy, 1972; Jex, 2002; Katz & Kahn, 1966; Gleick, 2008; Duncan, 2009).
Complexity science provides a model through which to understand better the complex web of micro-level connections among interacting variables that macro-level analysis overlooks. Complexity science integrates general systems theory with living systems to offer a framework for understanding organizations as complex open systems in a dynamic context. Dooley (2004) argues that complexity theory offers “superior explanatory power” (p. 374) because they account for organizations as living systems with characteristics of self-renewal, generating order from energy, self-organization, co-evolution with the environment, non-linearity, and emergence. Complexity science models also account for human factors, like autonomy, desires, norms, and preference; whereas episodic perspectives focus on macro-level process.
In addition, complexity theory accounts for time, cause, and links. Regarding time, episodic change models tend to see change as a sequence of events—unfreeze-move-refreeze—whereas complexity models specifically show events as they happen in time. Regarding cause, other models see change as a sequence of activities—state vision, develop change coalition, eliminate obstacles, celebrate wins, etc. In comparison, complexity models specifically address the underlying mechanisms of change.
Finally, complexity theory models explain how change occurs over time by specifically addressing the links between variables. Understanding the dynamically interacting links between variables can help leaders better understand how small changes in one area can have large impact on how events unfold during change processes. This “sensitive dependence on initial conditions” (Gleick, 2008, p. 23) would become known as the Butterfly Effect and served as the foundation of chaos theory; but helps leaders understand how chaos can find its way into even the most controlled processes. This suggests a counter-intuitive business strategy that de-emphasizes long-term change planning while refocusing resources on developing flexible organizations and operations with redundant processes that allow the organizational system to more effectively adapt in a turbulent environment.
Dooley (2004) proposes that viewing organizations as “complex adaptive systems” (CAS) (p. 374) provide insights into how system components interact in dynamical, non-linear, or self-organizing patterns. Complexity means that the behavior of the CAS depends on its structure, and that they are not predictable. Economics, traffic patterns, and cultures serve as examples of CAS. In such systems, individuals, “semi-autonomous agents” evolve over time through interaction and mutual adaptation. The goals of individual agents drive changes with mediating factors, including rewards, pace of intervention, and system structure.
Although the continuous change perspective helps to address some of the limitations of episodic change approaches, it has weaknesses. A key limitation of the continuous change perspective is that its models lack definition, method, and measurement. For example, Orlikowski (1996) found that continuous change processes are difficult to observe, making it difficult to determine when change has occurred and if it is desirable change. Being difficult to define also makes continuous change processes difficult to predict, control, or explain. In addition, little research exists to support emergent change as a practical model in real-world environments. Finally, cultivating dynamic processes to encourage organizational evolution can be a timely process with unintended consequences, which can require a planned intervention to correct.
Rather than being mutually exclusive opposites, continuous change and episodic change approaches provide different views of the same phenomena. Peering through both lenses provides a clearer picture of change. The macro perspective provides measurable milestones, while the micro perspective of changes as they happen (Tsoukas & Chia, 2002).
The distinction between micro and macro levels of analysis highlights one of the limitations in perceiving episodic and continuous change as mutually exclusive. From the macro perspective, the observer might see changes in strategy and processes. Observing the same change from the micro level might show how dynamically interacting individuals influence the changes in strategy and process.
Driving change through an episodic change perspective might involve adjusting artifacts, the surface features of an organization. For example, for macro-level episodic change, leaders might alter the organizational chart, redefine working relationships, or impose a new set of rules to guide behavior. In comparison, seeing an organization as a complex adaptive system helps to recognize that leaders have to dig into the micro level so they can identify and understand the deeply held beliefs, values, and assumptions that may be tacitly held by the organization and its members. What this starts to show is that organizational change is not just about changing macro-level artifacts, like charts and processes; but that it also involves digging into the micro-level phenomena that influence macro-level strategy and process (Anacona, 2001).
For example, continuous change perspectives predict that established employees will resist change, requiring external intervention that would “eliminate obstacles” (Kotter, 1996), which could mean replacing the resistant with the willing to accelerate implementation of new strategies. However, a four-year study of two Canadian medical facilities conducted by Reay, Golden-Biddle, and Germann (2006) showed that “embedded” employees contributed to change initiatives by applying their experience, connections, and familiarity with the culture and people. Insiders can accomplish change that outsiders cannot because the insiders have deep knowledge of structure, culture, and politics to drive the changes they want. Considering the structural, cultural, political, and cognitive components of “embededness” provides an opportunity to understand how established employees create change. With a strong knowledge and understanding of the context and people, seasoned actors can apply their experience with the system as a foundation for driving change. The results from this research contrast with traditional change models, which suggest that embedded employees are barriers to change because their work behaviors are fixed, requiring change models that start with an external jolt to unfreeze the status quo and external change agents to drive the change.
Recognizing the role that individual actors and collective action play in change processes, the multi-motor theory of organizational change proposed by Hinings, Greenwood, Reay, & Suddaby (2004) also shows the micro-level processes that continuously influence organizational change. Individuals interpret and recast institutions as they respond to them; reproducing, modifying, or creating new organizations. Hinings, et al. propose a model that shows the dynamics of institutional change as a closed-loop process, with the following steps:
A key limitation of this model is that a closed-loop does not depict a dynamic open system that evolves by interaction with its environment; but a closed-loop “crap circle” that magically fuels itself (Morse, 2005, p. 20); in other words, the model does not represent dynamic reality. The model proposed by Hinings et al. might be better draws as a growing or expanding spiral rather than as a closed loop; but they still offer an important conclusion: organizational change is the result of constant interactions among the organization, the people, and the processes in the organization—the micro and macro levels of analysis.
Livne-Tarandach and Bartunek (2009) build an argument for connecting theories from episodic and continuous perspectives to provide a more comprehensive framework for understanding and influencing change. Analyzing change literature, the researchers identify five different approaches to handling the paradox between episodic and continuous change approaches, selection, separation, integration, transcendence, and connection. Selection is based on dualistic absolutism, which means the researchers consider one or the other approach without acknowledging that another approach exists.
The separation approach acknowledge a dichotomy between episodic and continuous change approaches, but recommends selecting one approach over the other depending on the situation. The integration approach attempts to offer a compromise between two opposites, creating a middle way that focuses on similarities; however, it ignores the unique contributions of each extreme. The transcendence approach attempts to synthesize the dichotomy by leveraging the contributions of each extreme; however, it fails to account for the interplay between approaches. Connection offers a more complete framework for understanding change because it “seeks ways to embrace, draw energy from, and to give equal voice to bipolar positions” (p. 17). Offering the Taoist concept of Yin and Yang as a metaphor, Livne-Tarandach and Bartunek propose that linking the opposite perspectives allows researchers to see the essential elements viewed through each perspective.
In static environments, organizational leaders have the luxury of long-range business plans that only require infrequent adjustments to correct for failures or take advantage of opportunities. Today’s competitive environment is hardly static. To survive in increasingly turbulent environments, organizational leaders have to develop continuous change as a core competency. This does not mean the end of strategic planning and occasional organizational transformations. Linking both perspectives provides leaders with a more complete picture of the same phenomena. Episodic change theory provides executives with definable and measurable processes for driving change at the macro level of the organization, whereas continuous change theory provides an understanding of the inherent dynamic processes that affect change at the macro level.
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