System Level

Multinational organizations X and Y have decided to merge; the leadership of the merged organizations decides to take an AR approach to implementation. They appoint a team composed of members from both organizations to investigate how the cultures of the two organizations are alike and different. The team seeks the help of third-party consultants and academics and develops a research design that involves direct observation, surveys, and focus groups by members of both organizations. The results are shared and discussed in a series of workshops that involve hundreds of participants in both organizations, and these workshops produce a range of recommendations for how to proceed so as to effect a smoother transition to a merged company. Action teams then follow through on the priority recommendations. Large group conferences are convened on a periodic basis to monitor progress using selected organizational metrics and survey data, and further merger efforts are designed on the basis of these results.

Functional Level

A project team has been working for a year to implement a major change in enterprise-level information systems that was supposed to take three years. A year into the process, they are behind schedule. They decide to take an AR approach to fixing the problems. They define the key stakeholder groups whose cooperation they need to implement the change. They negotiate the agreement of the various stakeholders to use the AR approach to improve implementation. They hire neutral third parties to interview each stakeholder group and then discuss the results in joint meetings with the project team and representatives of each stakeholder group. The meeting results in agreed-on changes in how the project team is going about implementation that make it much easier for other stakeholders to become engaged. The implementation process speeds up, and the project team continues to gather and respond to information from stakeholders about their views on how the work is proceeding.

Enterprise Level

A manufacturing company is seeing a rapid change in customer preferences, market conditions, and competition. Both labor and management agree that transformative change is necessary and, with the help of OD practitioners, they convene a series of “Future Searches” in plants around the country, drawing together constituencies of labor, management, customers, suppliers, and community stakeholders to jointly assess the past, the current conditions, and to identify the necessary transformative changes that will ensure the survival of the firm. A steering group made up of leaders from the multiple Future Searches work to implement change ideas across the organization and catalyze new initiatives.

Team Level

A twenty-five-member staff group decides to conduct a retreat as a way of reviewing and improving team effectiveness and internal collaboration. In advance of the retreat, the staff members who are charged with planning the retreat send out an anonymous survey that assesses team performance on ten Likert-scaled items, including the level of collaboration, conflict resolution, openness, creativity, and efficiency, soliciting suggestion and recommendations for improvement. At the retreat the planning committee shares the results with the whole group. They discuss, debate, and finally agree on the meaning of the data and then decide on a five-point plan for staff improvement. They also agree to take a follow-up day off-site in six months to assess how they did on the five-point plan. In advance of the follow-up retreat they will ask staff members to anonymously complete the same battery of measures and to give examples to illustrate their answers.

Crosscutting Issue

The College of Arts and Sciences in a research university has made a commitment to making faculty in all departments more diverse. The dean has appointed a director of diversity initiatives, and a faculty member to be a diversity liaison for each unit. At a two-day workshop, facilitators, using open space and global café methods, help the liaisons share successful practices and imagine together what a more diverse university would look like. Using these co-created ideas as a springboard for discussion, they develop possible action scenarios and work to implement change in their departments. Periodically, the group reconvenes and shares progress and brainstorms on methods to overcome obstacles.

Individual Level

A new manager is two years into a five-year appointment. She wants to know where she stands with peers, colleagues, employees, and internal customers. With the help of the HR consultant in the organization, she conducts a 360-degree feedback project, using a standardized instrument. Based on the feedback she receives and the coaching the HR consultant provides, she decides to make certain changes in her approach. She discusses these changes with peers she works with, her boss, the customers, and those who report to her and asks their support for the changes, some of which involve her doing things differently and others that involve their doing things differently. Later on she asks for their direct feedback as the year unfolds.

AR methods can also enhance leadership development programs:

• Organization Z has instituted a leadership development institute for its managers two levels below the top tier. In addition to lectures, readings, and discussion, the thirty participants in the program are organized into five task forces. The job of each task force is to undertake data-based collaborative (that is, AR) approaches to investigating and bringing about a significant improvement in performance from a list of challenges identified by senior management. They must work for six months and present their results to senior management. They also must make presentations to their peers on what they learned about themselves, their team, and change management from the process.

AR methods can be part of planning and other structural interventions:

• A seventy-person organization is developing a strategic plan. They decide to take an appreciative inquiry and strengths-based approach. They engage the whole organization in a series of mutual interviews about when the organization and individual have been at their best and their hopes for the organization. At a workshop they report the results of the interviews in small groups and then aggregate the information from the small groups to a shared list of critical success factors. They develop a series of positive visions and illustrate them with graphic and dramatic elements of presentation to the total group. With this backdrop they review performance data and stakeholder feedback collected from surveys, discuss their position versus competitors, look at the likely trends in the market, and jointly develop a series of five-year strategic initiatives.

Each of the cases illustrated above has the core elements of AR: there is collaborative inquiry that helps define the situation and its possibilities. The group clarifies options, and solutions are selected, negotiated, “harvested,” or catalyzed. Ideally, in each of the cases, the lessons learned by the end of the initial cycle of AR/OD become the departure point for additional AR/OD activities if needed. This assessment can lead to a new round of goal setting, inquiry, analysis, action, and assessment.

The AR process can thus be described as a process of collaborative inquiry-based action that is focused on achieving practical results. The well-known cycle of experience, reflection, analysis, and experimentation (Kolb, 1984) helps describe AR as a learning process. By participating in AR, groups and individuals learn experientially and become more knowledgeable and competent in understanding their organization and in the processes of effective problem solving.

Despite the earlier statement that AR is primarily a method of action rather than research, it must be said that AR is also valuable to the field of applied behavioral science as a source of case studies, new practices, and theories of practice. Any of the above case examples could be “written up” by participants and become part of the OD and HRD literature. Many scholar-practitioners have made their academic careers in this way, and many OD practitioners have contributed thoughtful articles based on data generated by an AR approach.

Making the Case for AR/OD

OD consultants may need to make the case for AR/OD approaches relative to the approach of other experts whose method is to study the organization and make recommendations or simply to import solutions they have implemented elsewhere. The case can be made that AR/OD approaches can help the organization discover solutions already within the organization, imagine transformative possibilities, or prepare the organization to receive, evaluate, and incorporate outside recommendations with less resistance because those who must change are already engaged and empowered.

Some have argued that AR and OD approaches are most likely to be adopted when the need for change is clear, but the nature of the needed change and the path to get there is unclear and there is a norm of “figuring things out together.” Where there is a belief that the solutions are clear, and can be efficiently implemented by the chain of command, the likelihood leaders will adopt AR/OD approaches declines.

If the path forward is unclear, traditional AR as a method for discerning the needed direction has “face validity” within many organizations because it often uses recognizable forms of social science and humanities-based investigation methods and thus draws on the cultural prestige of scholarly investigatory approaches. Some of its classic concepts (such as force field analysis) draw on physical science metaphors. AR also can be framed in medical metaphors discussed in terms of “diagnosis, prescription, and treatment.” Such ideas have historically given consultants and clients alike a way of managing the anxiety and the uncertainty of the organizational change journey.

Organizations and OD practitioners for whom the above physical science and medical metaphors are no longer compelling may draw on other metaphors for justification and other methods for guidance. AI practitioners may claim empirical and theoretical support for their methods by reference to the new field of positive psychology. Practitioners of dialogic forms of AR can cite complexity science theories as a way of framing their efforts. Different forms of AR in different types of OD draw on different rationales from different scholarly disciplines. Often, however, the methods bear a family resemblance and there are common themes related to collective inquiry and action.

The AR/OD approach may also be justified in very practical terms: “look before you leap” or as American Frontiersman Davy Crockett was supposed to have said, “Be sure you are right, then go ahead.” AR in OD thus avoids the “Ready, fire, aim” syndrome that can afflict leaders in a variety of organizations. Although practitioners of dialogic OD may argue that their approaches represent a more rapid cycling from inquiry to action than traditional OD, they still advocate for developing shared understanding as a way of facilitating adaptive changes, rather than a few people at the top implementing preconceived ideas. In short, AR methods are more deliberative and interactive, but arguably more effective. AR methods may initially go slower in order to ultimately get things done faster.

Resistance to AR/OD in Organizations

However, the AR/OD approach is still not easy to sell or easy to implement. Several different sources of resistance are frequently encountered by OD consultants.

Some resistance is normative. While AR draws strength from social science and humanities–based inquiry methods, it arouses resistance when the norms of inquiry conflict with accepted images of leadership and problem solving in the organization. The use of inquiry methods presupposes a lack of certainty and openness to learning. AR therefore cuts across the widely held (if often unstated) belief that good/strong leaders have the answers already. Leaders may prefer to project an image of certainty and confidence and make decisions based on preexisting ideas or turn to “expert” consultants from brand name companies to give political cover for risky decisions.

AR, with its focus on collaboration and transparency, also confronts the standard hierarchical view of the organization. Some more recent trends in organizational life may have made leaders even more resistant to the egalitarian participatory bias of OD. These trends include the need for organizations to move more quickly to be competitive, the apparent efficiency achieved by quick decision-making processes, the decline of unions as a brake on management decision making, and the ascendancy of neo-liberal economics.

In order to overcome these resistances, AR/OD practitioners may need to help the organization reframe the meaning of effective leadership and explain how creating competence in collaborative processes can actually improve the agility of the organization. The OD consultant therefore must have the skills to surface the divergent assumptions about how effective change is created and work through the differences to achieved a realistic, shared perspective that supports the AR/OD approach.

Some resistance is based on the fact that AR/OD can be costly. In the examples above, AR is shown to be process-oriented, systematic, time-consuming, and perhaps expensive (sometimes involving the use of outside consultants). Sometimes, therefore, an AR/OD approach may be authorized only when traditional approaches have foundered or where there are good credible examples already of where AR/OD has been cost-effective and value-added.

Finally, AR methods, as illustrated by the examples above, require a fair amount of skill and knowledge about participatory processes in organizations to implement effectively. Leaders for whom AR/OD is attractive may not have the skill and competence in their organizations to go forward on their own. AR/OD practitioners must be able to reassure organizational leaders that they can provide the necessary support to see the process through successfully. This is not only true of classic OD practitioners, but dialogic OD consultants as well, although they may claim their methods are less expert-dependent.

Action Research and the Evolution of OD

Throughout, this chapter has referred to the current conversation within the OD community about newer versus older forms of OD and the methods associated with diagnostic versus dialogic OD. The section below deals with this discussion in more detail and describes how AR concepts and methods have also evolved. This draws heavily on the analysis of Robert Marshak (2009), Gervase Bushe (2013), and Bushe and Marshak (2009). Marshak described classic, neo-classic, and new OD models and then arrayed these approaches on a diagnostic-dialogic continuum. Bushe described the variety of methods that are utilized by dialogic OD consultants and their underlying assumptions and perspectives.

During the early period of OD (1950 to 1980), “classic AR” became core to “classic OD” (which is still practiced widely) and also is described by some as diagnostic OD. Diagnostic OD is based on a positivist-realist view that sees that reality, including social reality, is an “object” that can be researched and assessed. AR is the element in the OD effort that describes that reality. The resulting understanding then provides a basis for effective planned change.

In many settings, the interest in and practice of classic OD has been supplanted by an emphasis on change management. Change management involves expert consultants who present themselves as being able to help an organization transition to a new state (a state with fewer, more productive employees, a better marketing or IT function). Many of these change management efforts have a top-down, bottom-line driven approach, and under-attend to the existing culture and so slight the social aspect of organizational change. The consequences of this approach may undermine acceptance of change to such an extent that innovation is stymied.

AR though, when combined with change management in a genuine neo-classical OD effort, might receive the requisite buy-in to the change. This occurs when the change management project involves a genuinely collaborative approach and the ethos of AR is incorporated throughout these projects. Effecting such integration requires a good teamwork between expert consultants and OD consultants, strong change management skills, and a receptive client system.

The development of appreciative inquiry (AI) by Case Western Reserve University Professor David Cooperrider and succeeding generations of AI practitioners has created an alternative paradigm of action research and OD. AI practitioners challenged the positivistic assumptions of classic OD and drew on postmodernist theories of social constructionism and used more humanities-based techniques of inquiry (such as storytelling.) The AI practitioner works to uncover and tap new sources of creativity and energy, create greater momentum for organizational change, overcome classic resistance, and implement transformational change, rather than solve particular problems. As the AI name connotes, the inquiry involved is more of about the dynamism and demonstrated strengths of the organization and its culture in lieu of research into the causes of current problems, as classic AR might emphasize.

Large system OD methods emphasize emergent learning to produce “mindset shifts” for participants to generate transformational organizational change. If, early on, AR influenced OD, then newer approaches to OD are now influencing AR. Large system OD, using methods such as visioning, the Future Search, and the conference model, place a premium on getting “the whole system in the room.” While traditional AR/OD also seeks broad involvement of stakeholders, it is more accepting of gathering data from stakeholder groups and feeding back data to smaller representative groups for interpretation and action planning, and then back out to the organization in a sequential process of implementation.

In the large system approach, the data gathering and perspective sharing is in real time and results in a collective shift of understanding. It facilitates diverse constituencies in finding common ground and a shared future vision. In these approaches the participatory, interactive, and transformational aspects of OD and AR are emphasized over the analytic. Practitioners argue that when a large group of diverse organizational actors who all have an interest in moving an organization forward have an “aha” experience because they are simultaneously reviewing and interpreting data that they have co-generated, then a powerful transformation takes place, one that can accelerate change far beyond the capacity classic AR/OD methods

In other forms of dialogic OD “change in mindset” is also emphasized versus change in organization conditions. Change agents may focus on helping organizations address covert processes and employ new metaphors for helping organizational members understand how the organization functions and its new possibilities. They may introduce new analytical frameworks and self-assessment tools (“systems thinking,” complexity theory, surfacing and understanding mental models, etc.). The “research” part of AR in these models of OD may involve research in self-understanding or understanding the environment. The critical “action” part in AR may be an enlarged or transformed understanding of self, organization, and environment.

The resulting observable change in organizational behavior, structures, culture, and incentives, although hugely significant, is thus almost a by-product that occurs as these new self-understandings are translated into new organizational practices. This does not mean, however, that intensive follow-through is not required in the new OD, only that an essential element of change is the consciousness of leaders and other organizational actors.

Complexity science–based OD has its own form of AR that both incorporates and is different from the classic approach. Change agents operating out of the complex adaptive system (CAS) model believe they can facilitate this development by providing information, challenging assumptions, amplifying differences, and increasing connectivity. They may use data-gathering, feedback, and interpretation approaches that are similar in form to other AR/OD practitioners, but informed by CAS theory. The critical difference with classic AR/OD is that the desired goal is emergent and adaptive change, rather than a planned, systematic, collaborative, change process.

However, complexity science is emerging as a deeper aspect of this discussion than a just framework for a particular approach to OD. Dialogic OD practitioners tend to see a complexity science as creating new, more accurate perspective on the nature of organizational reality. They argue that the conditions of complexity and rapid change respond better to their general approaches and methods than to the classic OD/AR approaches.

AR/OD on a Global Stage

An organizational literature is focused on building new institutions. These institutions are defined as organizations created specifically for the purpose of changing some aspect of society. Many of these new institutions were and are in the developing world. These institutions can be for profit or non-profit, governmental or entrepreneurial, and they can be social or technological in nature (for example, introducing new ways of dealing with poverty or new ways of telecommunication).

When OD practitioners help create, develop, and renew new social or innovative private enterprises, they are engaging in an AR cycle “writ large.” Their researches or “field experiments” are at the level of the organizational system and focused on determining the best vehicles and forms for achieving a given social purpose. Often they generate knowledge that is usable by subsequent generations of entrepreneurial ventures, both social and for profit. OD practitioners in these types of organizations use AR methods to help organizations try out, assess, and then regularize the new practices required to realize their innovative missions.

Effective approaches to AR in the United States are not necessarily the same as AR approaches in other parts of the world. OD consultants have noted that the acceptability of certain OD interventions within organizations varies with the dominant national culture of those organizations. Marshak (2009) also points out that different cultures view change differently. He contrasts Asian models of cyclical change with European models of linear change. Litwin (2007) talks about several dimensions on which cultures vary and how various OD practices need to be framed for a specific culture. The dimensions she cites (based on the cross-cultural research of Geert Hofstede and subsequent similar studies) are Power-Distance, Uncertainty-Avoidance, Individualism-Collectivism, Masculinity-Femininity, and Long-Short-Term orientation.

AR, with its focus on participatory data collection, joint interpretation, and shared planning, requires a tolerance for ambiguity and partakes of collectivist norms and a long-term time perspective. This may help explain why it is sometimes resisted in the United States, where leaders tend to have a shorter-term time frame, as well as more individualistic modes of operation and decision making.

The GLOBE Study of leadership values of twenty-one countries provides an intriguing insight that Lewin’s formulation of AR was actually more representative of West European views of decision making than American views of his time. “For example, for a leader to be described as decisive in the U.S., he or she is expected to make quick and approximate decisions. In contrast, in France or Germany, being decisive tends to mean a more deliberate and precise approach to decision making” (Hoppe, 2007).

When Lewin suggested that leaders investigate the social realm into which they were intervening by mapping the perceptual world of the targets of change, he may have been influenced by his own West European cultural mindset. So AR and, by implication OD, was a marriage of cross-cultural influences—European deliberation and American pragmatism. The implication of this thinking for OD/AR practitioners is that the dialogue around the use of AR methods, the methods themselves, and the pacing of the work need to be nuanced by cross-cultural sensitivity.

The “Spirit” of AR

This chapter has described in some length the history, philosophy, method, applications, and evolution of AR methods in OD. However, in closing it should be added that AR principles do not necessarily require a lot of fanfare or self-consciousness to enact. Whenever we simply gather data about an organizational situation that we need to take action on, share that data back with colleagues, discuss it together, and then come up with an action plan on the basis of that data and follow through together, we call upon “the spirit of action research.”

As organizational actors, when we are in a committee trying to bring about change and we ask, “What has worked in the past?” we are invoking the spirit of AR. When we say “Can we put ourselves in the heads of those we are trying to persuade to adopt X, what might they be thinking?” and when we say, “We have completed the project. What have we learned about ourselves, our team, and the organization?” we are invoking the spirit of AR.

After sixty years of OD, in some organizations, and for many organizational actors, AR principles are simply a way of doing business. In some settings, AR may have “seeped into the culture.” Standard frameworks, like the balanced scorecard (BSC) have origins that are related to AR methods and approaches, but the origins go unrecognized. Approaches like BSC institutionalize social science methods for routine data gathering and organizational decision making. Organizational leaders who use these tools may be seen as particularly deliberate, thoughtful, and inclusive, and yet no one may connect the dots between them, how they operate, and the precepts of a German refugee social psychologist in the 1940s.

Technology and the Future of Action Research

With the advent of so many technology-enabled innovations such as social networking, crowd sourcing, data mining, data archiving, and sharing through blogs and wikis, it is possible we may soon see yet another evolution of AR methods. It’s relatively easy now to develop surveys and feedback data to groups using widely available programs like SurveyMonkey. Through blogs and social media sites like Facebook and Twitter, people can share information and react to issues. With Internet-based communications software, people can attend virtual meetings while remaining in geographically dispersed offices. Data mining, data science, and visualization approaches make it easier (for those with these skills) to interpret and share data in powerful ways. With YouTube, expressive modalities of sharing visions can be recorded and easily shared across time and space.

As these tools are more and more widely distributed geographically and all generations get on board, we could see a further democratization of AR. In the future, AR may no longer be just for OD consultants and clients, but organization members the world over may regularly engage in AR-type activities. They may routinely collect data about problems and feed back information to colleagues, come to a shared understanding of problems or, through discussion, clarify options and enable action. Many may come to use AR methods simply because they work. For example, Rolf Lynton (Lynton & Kiel, 2012) reports a case in which practitioners in a large-scale rural Indian anti-poverty non-profit agency decided to tape their staff meetings and bring them to a group of peers for critique as part of a self-organized training effort. In the future, AR could be for everyone, everywhere.