APPRECIATIVE INQUIRY: NEW THINKING AT WORK Sherene Zolno

Abstract: Many of us have been taught that legitimate knowledge derives from an emphasis on what is rational, objective, empirical, and problematic. Called ‘critical thinking,’ this ability to identify and successfully solve problems is viewed in most workplace settings as crucial for organizational effectiveness and change. Other means of understanding reality – “appreciation,” “valuing,” and “affirming,” – are considered Pollyannish, i.e., soft-headed and non-essential. By legitimizing only the first form of thinking we shut down an entire mode of learning and severely limit the capacity for innovative approaches to organizing and change. A new and inclusive philosophy and approach, however, legitimizes the second form of thinking and facilitates positive organizational change. By connecting people to the organization’s strategy, capturing their imaginations, respecting their contributions, and energizing the change process, this approach, called Appreciative Inquiry, enables organizational members to increase their influence on their organization’s structure and nature.

Published in The 2002 Annual: Developing Human Resources, Pfeiffer & Company.

WHAT IS APPRECIATIVE INQUIRY?

David Kolb (1984), in his theory of experiential learning, describes the importance of both appreciative apprehension and critical comprehension as different processes of knowing. Critical comprehension is based on skepticism and doubt, while appreciative apprehension is based on belief, trust and conviction.

One mistake we make is to define “appreciative” in a limited way as meaning only “gratitude.” Appreciative also includes the meanings “to see” (where you pay attention), “to value” and “to increase in value.” When Kolb says, “Appreciation is the process of valuing,” he is reminding us that it takes more than just the facts to make effective choices about the world.

“Appreciation of an apprehended moment is a judgment of both value and fact. To appreciate apprehended reality is to embrace it. And from this affirmative embrace flows a deeper fullness and richness of experience.” –David Kolb1

1 Reprinted from D.A. Kolb, Experiential Learning: Experience as the Source of Learning and Development, copyright 1984, with permission from Prentice-Hall.

Defining Appreciative Inquiry

"AI is: A whole system empowering process that looks for the best, what's even better, and collaboratively plans how to arrive at a higher performing state?" Roland developed from Mac’s definition below for Dale, a college Dean. 7-2005.

“An empowering process that looks for the best, what's even better, and how do we get there?" Malcolm J. Odell, Jr., MS, PhD. Mac is the most experienced AI Consultant Globally.

Appreciative inquiry is a philosophy that “invites us to choose consciously to seek out and inquire into that which is generative and life-enriching, both in our own lives and in the lives of others, and to explore our hopes and dreams for the future” (Watkins and Mohr, 2001, p 58) From the best selling book on Appreciative Inquiry – Solicited by roland and edited by roland and friends).

Instead of starting out to solve problems—a typical focus of traditionally trained managers, steeped in a philosophy of management by exception—AI focuses on what is going right, what is motivating, what is energizing, and what are the key strengths of a setting. Instead of asking the question, “What is going wrong and how do we solve that problem?” AI begins by asking, “What is going right and how do we leverage that strength to achieve quantum leaps in productivity improvement?” Roland Sullivan on Page 52- from just released second edition of “Practicing Organization Development” edited by Roland Sullivan and Bill Rothwell.

Appreciative Inquiry is a collaborative, strengths-based approach to retooling our human organizations through a positive approach to organization change and transformation. It appreciates through recognizing the best past and present strengths and potentials. It inquires through exploration and discovery in a systematic manner. It brings organizations alive through the mobilization of cooperation. It is best integrated into contemporary Organization Change theory and practice. Roland Sullivan created for a Large British Company.

Here's what other people are saying about AI:

* Appreciative inquiry is a way to rediscover and tap into our core strengths and highest potentials. It also helps us develop our self-talk in a constructive way and encourages us to bring out our best qualities in serving this institution. Appreciative inquiry is a method that helps us develop the goals and dreams that support the future of our Navy. It involves soliciting ideas from people throughout our fleet. Admiral Vern Clark, US Navy

* We have reached the end of problem solving as a mode of inquiry capable of inspiring, mobilizing, and sustaining human system change. The future of Organization Development belongs to methods that affirm, compel, and accelerate anticipatory learning involving larger and larger levels of collectivity. David L. Cooperrider, Case Western Reserve University and co-founder of Appreciative Inquiry

* Appreciative Inquiry is the philosophy that is allowing us to engage the hearts, minds, and souls of our people--all of our people. Only when we do that will we achieve breakthrough performance. Cindy Frick, Director, Organizational Development & Human Resource Planning, Roadway Express/Yellow Roadway

* We introduced the concept of Appreciative Inquiry into our 'Breakthrough Leadership at Roadway' curriculum.. Our senior managers have been enthusiastic about using this innovative approach to deal with some of our most pressing issues. It really does get everyone to focus on what's possible through interactive discovery and design sessions. The output has been amazing and provides a great map to desirable outcomes. Jim Staley, President, Roadway Express/Yellow Roadway

* Appreciative Inquiry is currently revolutionizing the field of organizational development. Robert Quinn, Distinguished Professor of Management, University of Michigan Business School

Appreciative Inquiry is the study and exploration of what gives life to human systems when they function at their best. This approach to personal change and organizational change is based on the assumption that questions and dialogue about strengths, successes, values, hopes, and dreams are themselves transformational. In short, Appreciative Inquiry suggests that human organizing and change, at its best, is a relationship process of inquiry, grounded in affirmation and appreciation. Diana Whitney and Amanda Trosten-Bloom, AI Practitioners and authors of The Power of Appreciative Inquiry

David Cooperrider (Srivastva & Cooperrider, 1990), of Case Western Reserve University, who is one of the original developers of Appreciative Inquiry, describes it as engaging people in “...an inquiry process that tries to apprehend the factors that give life to a living system.” Based on information derived from the inquiry, people would then “seek to articulate those possibilities that can lead to a better future.” The Appreciative Inquiry process as he has presented it, is about finding ways to successfully translate best intentions into reality, and values and beliefs into practice.

“It is important to recognize that the problem-solving method of organizational inquiry quite systematically paints a picture of organizational life in which a whole series of colors are considered untouchable. In this way, the totality of being is obviously obscured, leading to a narrowed conception of human nature and cultural possibility.” –David Cooperrider and Suresh Srivastva2

In other words, the expected outcome of the Appreciative Inquiry is an organization which has affirmed its strengths and fundamental values, used that information to engage in a process to envision a collectively desired future, and moved forward towards enacting that vision in daily worklife.

2 Reprinted from W.A. Passmore and R. W. Woodman, Research in Organizational Change and Development, copyright 1987, with permission from Elsevier Science.

Discovery“What gives life?”(The best of what is)

Appreciating

Discovery“What gives life?”(The best of what is)

Appreciating

Dream“What might be?”

(What is the world calling for)

Envisioning Results

Dream“What might be?”

(What is the world calling for)

Envisioning Results

Design“What should be--the ideal?”

Co-constructing

Design“What should be--the ideal?”

Co-constructing

Destiny“How to empower, learn,and adjust/improvise?”

Sustaining

Destiny“How to empower, learn,and adjust/improvise?”

Sustaining

Appreciative Inquiry “4-D” Cycle

AffirmativeTopic Choice

PROBLEM SOLVING VS. APPRECIATIVE INQUIRY

Because it is highly counter-intuitive in Western culture, it’s difficult to understand how affirming strengths and values can lead to transformational change. In fact, most leaders would feel remiss if they failed to engage in a rational process using problem-solving methods to identify ways to improve the cost effectiveness of internal systems. We need to question, however, whether problem solving has already fixed that which is solvable, and begin to focus on what is yet possible – the untapped potential beyond fixing what’s already in place.

Carl Jung, early 20th Century psychological researcher and therapist, noticed that a person’s problems faded when they were confronted with a new or stronger interest. He asserted that the greatest and most important problems in life were fundamentally unsolvable and could only be outgrown (Jung 1923).

For Jung, Cooperrider and others, problem solving appeared inherently conservative, limiting and slow. The philosophy and approach they sought to introduce instead focused on the future of the system as a whole, on engaging participants in collectively imagining new possibilities for their future, and on bypassing the process of solving yesterday’s problems.

Thomas White, President of GTE Telephone Operations, expressed his concerns with the limits of problem solving by asking this question: “Should we demoralize a successful group by concentrating on their failures, or help them over the remaining hurdles by building a bridge with their successes?” He felt that using Appreciative Inquiry helped GTE attain much better results than just trying to fix problems – that by shifting their internal conversation away from its focus on negative problems and toward valuing their capabilities, the re-energized organization improved financial results beyond what was expected with traditional problem solving alone (White, 1996).

“We are among the best problem solvers in the world. We trouble shoot everything. When used continually and over a long period of time, however, this approach can lead to a negative culture. If you combine a negative culture with all the challenges we face today, it could be easy to convince ourselves that we have too many problems to overcome––to slip into a paralyzing sense of hopelessness.”–Thomas White President, GTE Telephone Operations

Table 1 identifies some of the differences between problem solving, and Appreciative Inquiry.

As many organizational leaders are far from achieving the results they want, the need to reinvent the tools used in helping them is clear. The choice appears to be to stay in the incremental problem based, diagnosis/treatment frame, or to move on to a fresh perspective which can simultaneously address the compelling triad of strategy, structure and culture during change.

The Appreciative Inquiry process makes available a whole new array of alternatives to support organizational learning and expand possibilities for action. Using it, change leaders have an opportunity to reframe their philosophical stance in a fundamental way–– that is, during organizational improvement efforts, to be deliberately appreciative. They would thus be working with optimism and hope, actively engaged in valuing and celebrating the human spirit, while creating an enspirited environment welcoming to creativity and imagination.

Table 1 Problem Solving vs. Appreciative Inquiry PROBLEM SOLVING APPRECIATIVE INQUIRY

Identification of the problem Setting a context of appreciation of (seeing) what is

Analysis of Causes Inquiry: Discovery Phase “What’s going on” “Valuing the best of what is”

Proposed Solutions Envisioning: Dream Phase“Fix the problem at hand” “What might be”

Action Planning Dialoguing/Aligning: Design Phase“How to get it done” “This is what will be”

Action Innovating: Destiny Phase “Fix the problem” “Creating and sustaining it now”

BASIC ASSUMPTIONS . . . Problem Solving: Appreciative Inquiry:That the organization is That the organization is a problem to be solved a mystery to be embraced.

Reprinted with permission of the publisher. From Appreciative Inquiry, copyright 1999 by D. L. Cooperrider and D. Whitney, Berrett-Koehler Publishers, Inc. San Francisco, CA. All rights reserved.

OD DefinedWhile there are many definitions of Organization Development (OD) floating around today, we consolidated definitions from past and contemporary leaders of the field and came up with:

Organization Development (OD) is whole-system transformation and development using a values-based collaborative process. It focuses on applying positive behavioral science wisdom to perfecting, reinforcing, and measuring such organizational features as:

• Extraordinary performance• Building of executive teams• Aligned leadership• Relevant strategies • Synergistic and functional organization design• Clear organizational structure/chart including roles, responsibilities, and accountabilities• Cost effective business processes • Passionate and great human cultures• Changed behavior and mental sets • Globalization • Quickened learning environments• Or whatever the executive team believes must be focused on to achieve desired results.In essence, OD leads people to collectively learn and change to produce desired outcomes.

Organization Development: ElaboratedIn order to understand how OD works we would like to introduce you to the major components of the core framework of OD.

1. Working with Whole Systems:A systems perspective requires defining a boundary, which separates the system into an internal set of interdependent parts and an environment (the next larger system) with which it needs to interact (import/export energy). Thus, a system can be an entire enterprise, a specific unit, or even an individual and always includes internal and external customers/clients. When we apply the term “wholeness” to a system, we’re referring to the regularly interdependent parts forming an effective and aligned whole, interacting according to the influence of related forces. For a system to work smoothly, everyone who is affected by the organization needs to be positively engaged. A balance of influence from primary stakeholders such as owners, employees and customers is desired.

2. A Unique Value-Based Process:Values are enduring and positive beliefs on which the ideal or transformed state attributes its existence. Values have always been an OD signature. Additionally, the soul of OD is the process by which the desired state is achieved.“Process:  A progressive series of procedures and functions performed over a period of time bringing about a result. For OD purposes, the thoughts, feelings and interactions of those participating in the change process are of particular significance. For OD changing

processes often involves converting habitual patterns of thought, feeling, behavior (action) and interaction to more desirable states.”

3. Transformational vs. Developmental:'Transformation' is a fundamental paradigm shift from one state of being to a new state. Transformation requires a shift to new behaviors and mindsets to sustain future change. It is deep-rooted or second order change. 'Developmental' is first order change or improvement of an existing state.  Ideally, conscious transformation occurs when a system requires it.  Ongoing development then keeps the system moving forward. In development, core processes and domains are continually adapted through a simple continuous change cycle such as the classic Scan, Plan, Act, and Re-act model.

4.Strength-Focused Change:Instead of having an obsessive pre-occupation with root causality of problems and negativity, contemporary OD is leaning more and more toward strength-focused change. Positive change is driven by an appreciative or value-added approach where inquisition, hope, innovation, and engagement prevail.

5. A Research-Based Philosophy:OD has a traditional foundation in an applied behavioral knowledge of business, technology, sociology, anthropology, positive psychology, adult education, economics, and organizational behavior. The situation itself, and the beliefs of the consultant, are integrated with one goal in mind - achieving success for the organization and the customer. Tried and true relevant knowledge, skills and ways of being, especially about change are transferred to the system. In addition,enterprise learning and intelligence are discovered, reinforced and documented throughout the effort.

Guiding Concepts of Appreciative Inquiry Transformation (AIT)By Paul Kope, Internal Consultant with a Major British Company

Appreciative – AI assumes there is ‘good’ in every system and seeks to bring that goodness into the sunlight. The focus is on the “life-giving forces” present when the system is performing optimally.

Inquiry – AI seeks to understand through questions. It is based on the simple premise that organizations grow in the direction of what we repeatedly ask questions about and focus our attention on.

Complexity Theory / Systems View – Our world is a constant flux of dynamic processes. Questions are significant and can set in motion powerful change. AI helps us move from Understanding language as the Descriptor of Reality, to Understanding language as the Creator of Reality.

Positive Imaging -- Appreciative Inquiry turns our thoughts toward that which is valued, that which gives us joy and feelings of worthiness. These stories of positive and generative times lead to the creation of images that become the sunlight toward which people and our organizations turn.

Social Constructionism / The Power of Stories – We construct our realities through interactions with one another. Stories are powerful constructs. They stick like glue! They make information easier to remember, build identities and foster relationships. They are a medium for conveying values and vision, and move the internal dialogue of the system.

Change and Transition – AI is consistent with effective change & transition efforts – emphasizing collaboration and participation of all voices in the system, and approaching change as a personal journey (transition) versus just an event. AI is not an intervention in and of itself; rather, it brings a new lens to existing Organization Change and Development interventions/methodologies.

Best of Today – People become more confident when change includes carrying forward parts of the past. We must capture the best of what and who we are when we’re performing optimally, and build on top of that ‘foundation of excellence.’

Innovation for Tomorrow – The building process includes inquiring into people’s wishes in order to bring new innovation to our ‘foundation of excellence.’ When the collective imagination is mobilized, people find ways to move the organization forward toward a shared image inspiring imagination and creativity.

Improvement / Problem Solving – AI brings a new ‘lens’ to traditional approaches. People who live inside the system identify what they wish could be different, and by starting from an appreciative perspective, create the energy to address the things that need to change. AI does not deny problems. It redefines them.

Hope – AI speaks to human hope, an underrated power in our lives.

With gratitude and respect to the AI thought leaders who have authored these statements and inspired passion toward re-framing our organizations and our lives through a social constructionist lens.- Paul . MSA Comment: Paul created this for his client system where we assisted him in a grand Change effort. He coined the phrase Appreciative Inquiry Transformation (AIT).

COMPARING APPRECIATIVE INQUIRY TO ACTION RESEARCH: OD PRACTITIONER PERSPECTIVES

Organization Development Journal,  Summer 2005  by Egan, Toby Marshall, Lancaster, Cynthia M

Abstract This study examines the assumptions, approaches, and implications of appreciative inquiry (AI) and action research (AR) for organization development (OD) from the perspective of OD practitioners who use AI as an intervention approach. Interviews were conducted with OD practitioner informants to explore the strengths and weaknesses of AI compared to those of AR. Practitioners outlined the strengths and weaknesses of AI and AR and elaborated on ways that AI complements AR and other intervention approaches.

"No problem can be solved from the same level of consciousness that created it."

Albert Einstein

Appreciative inquiry (AI) has been steadily gaining recognition in scholarly and practitioner communities (Bushe, 1999) as an innovative approach to organization development (OD). The number of publications, websites, and training programs associated with AI appears to be rapidly increasing. Along with this increase in notoriety, questions have emerged regarding the elements that make this approach different from other OD interventions. Although AI is associated with action research (AR), there are key differences with regard to philosophical assumptions and practices (Gotches & Ludema, 1995). AR, a diagnostic intervention approach introduced by Lewin (1946) and identified as a central process for OD (Rothwell, Sullivan, & McLean, 1995), involves a focus on a particular problem and seeks to provide assistance in understanding and addressing the problem identified. AI scholars (Cooperrider & Srivastva, 1987) criticize AR as being overly focused on problem solving. Although Lewin aimed the AR approach toward real problems in social systems, the AI approach rejects a problem-solving orientation. "The idea is to look at an organization as a positive force, understanding its strengths, and figure out how to refine and enhance what it-or a system within it-is already doing well" (Zemke, 1999). These and other comparisons are important to understanding both AR and AI in the context of OD, and to understanding both as approaches for the improvement of organizational learning and performance.

This article explores the use of AI from the perspectives of OD practitioners who have extensive experience with AI interventions. Our interests as researchers and practitioners led us to an examination involving relevant literature and the perspectives of experts. We felt that AI (and AR for that matter) has been understudied and that further critical examination of AI and its differentiation from AR was important to further understanding of this emerging OD practice. Because we were unable to find literature that featured perspectives from multiple practitioners regarding the strengths and weaknesses of the approach, this study-exploring the experiences and viewpoints of OD practitioners using AI-promises to be a valuable contribution to the OD literature.

Framing AI and AR

Describing, comparing, and contrasting concepts and practices under examination is a key challenge. When you "frame" an issue you are naming it, and by naming it you are focusing on how you might set up its analysis and set the criteria for evaluation. Framing is a heuristic process, by which we mean that the definition of an issue already includes elements of the solution. (Coghlan& Brannick, 2001, p. 75)

In this study, we view AR and AI as related to OD and to one another, at least in terms of general aims and related processes. From our review of the literature and interviews with practitioners regarding similarities between the two approaches, we found that both AI and AR:

1. Engage real social systems

2. Are conducted in real time, not retrospectively or in advance of data gathering

3. Are change oriented processes interested in making improvements beyond the current organizational state

4. Are interactive and require involvement by organizational stakeholders

5. Tend to be cyclical and iterative processes

6. May use a variety of data collection approaches

7. Are action and reflection oriented

8. Are values oriented

9. Were founded by individuals interested in theory-building

10. Are applicable to a variety of human systems from individuals to organizations and even larger frameworks.

Although the intention of this study is to explore both AI and AR, within this article AR is most often explored from the perspective of AI. Study informants were proponents of and regularly used an AI approach to OD. The selection of this group of informants is based on the assumption that AI is growing in popularity in the OD community, but has not been explored for as long, or as in as much depth as AR. This assumption extends to the organization of this article, as it is assumed that those exploring this new approach to OD are likely more familiar with an AR approach to OD. Key references supporting the exploration of Λ? and AR are, however, provided throughout. Finally, Cooperrider and Srivastva (1987) have noted that those practicing and writing about AR have largely stepped away from theory and theorybuilding in favor of an exclusive focus on action. This was never the intent of Lewin, the father of AR (Lewin, 1946). This departure from theory by AR practitioners and scholars is a rationale often associated with the development of AI. We would like to acknowledge that this article is written for an audience interested in theory with a predisposition to practice. We do, however, provide some theoretical discussion and recommend theory-building associated with AI and AR.

Purpose and Scope of the Study

We examine the philosophical assumptions, strategies, and processes utilized in AI from the perspective of existing literature and experienced OD practitioners. From this vantage point, comparisons are made between AI and AR. The research questions utilized in this study were (a) what are the strengths and weaknesses of the AI approach from the perspective of experienced OD practitioners utilizing AI?, and (b) what are the comparative strengths and weaknesses of AR?

Philosophical and Theoretical Assumptions of Appreciative Inquiry in OD

AI was principally developed by David Cooperrider, an associate professor at the Weatherhead School of Management, case Western Reserve University. Cooperrider developed the AI approach along with Suresh Srivastva, Frank Barrett, John Carter, and other colleagues approximately twenty years ago. They challenged the traditional problem-solving approach to change management and introduced the term appreciative inquiry. In recent years, many practitioners have contributed to the extension and development of AI. AI has been used in international development efforts as well as within public and private sector organizations.

Although no study indicating the breadth or frequency at which the approach has been deployed was identified, organizations that have been identified in ??-related literature as utilizing AI include GTE (now Verizon), Avon, Nutrimental, The MYRADA project in Southern India, the Manitoba Skownan First Nation Project, The United States Navy, Roadway Express, McDonalds, John Deere, Green Mountain Coffee Growers, Lafarge North America, Benedictine University, and many others. The increased use of AI has led to its inclusion in the most frequently used OD texts (Cummings & Worley, 2004; French & Bell, 1998). According to Bushe (1999), AI is one of the more significant OD innovations in recent years. AI "refers to both a search for knowledge and a theory of intentional collective action, which are designed to help evolve the normative vision and will of a group, organization or society as a whole" (Cooperrider & Srivastva, 1987, p. 159). AI has been described as a philosophy of knowing, a methodology for managing change, and an approach to leadership and human development (Cooperrider & Srivastva, 1987; Hammond, 1998). Cooperrider and Whitney (1999) provided the following "practiceoriented" definition:

Appreciative inquiry is the cooperative search for the best in people, the organizations, and the world around them. It involves systematic discovery of what gives a system "life" when it is most effective and capable in economic, ecological, and human terms. AI involves the art and practice of asking questions that strengthen a system's capability to heighten positive potential. It mobilizes inquiry through Grafting an "unconditional positive question" often involving hundreds or sometimes thousands of people. In AI, intervention gives way to imagination and innovation; instead of negation, criticism, and spiraling diagnosis there is discovery, dream and design. AI assumes that every living system has untapped, rich, and inspiring accounts of the positive. Link this "positive change core" directly to any change agenda, and changes never thought possible are suddenly and democratically mobilized. (Cooperrider & Whitney, 1999, p. 10)

Although AI is often identified as being related to AR (Barrett, 1995), a significant difference is that AI is a product of the socio-rationalist paradigm (Gergen, 1991; 1999). From this perspective, reality is a product of the moment and is thus open to constant and ongoing change. Cooperrider and Srivastva (1987) argued that there is nothing inherently real about any particular social form. From this vantage point, there are no trans-cultural, everlasting, or valid principles of social organization to be uncovered. Although the underlying assumption of logical empiricism is that social phenomena are sufficiently lasting, stable, and replicable to allow for generalizations, socio-rationalism

contends that social order is fundamentally unstable. According to AI practitioners and scholars, "Social phenomena are guided by cognitive heuristics, limited only by the human imagination; the social order is a subject matter capable of infinite variation through the linkage of ideas and action" (Cooperrider & Srivastva, 1987, p. 139). According to Bushe (1995), "Socio-rationalists argue that the theories we hold, our beliefs about social systems, have a powerful effect on the nature of social 'reality.' Not only do we see what we believe, but the very act of believing creates it" (p. 15). From this point of view, development of new theories for organizational change is a powerful way to influence how OD interventions are formulated and applied.

The AI approach often engages an entire organization (Murrell, 1999). Cooperrider offered the "heliotropic hypothesis," which posits that social forms evolve toward the "light," toward images that are affirming and life giving (Hammond, 1998). From this perspective of AI, groups, organizations, communities, or societies have images of themselves that underlie selforganizing processes. AI promotes the principle that social systems tend naturally toward the most positive images held by their members (Bushe, 1995; 2000). AI posits that a conscious elaboration of positive imagery will support and extend positive results for the social system as a whole.

AI, it has been argued, alleviates the conflict and resistance to change often identified in literature about other approaches to OD and change (Barron & Moore, 1999). Where other organizational interventions concentrate on the problems to be fixed (Cooperrider & Srivastva, 1987), AI focuses on "what's working well." Instead of viewing an organization as having problems, AI views an organization as doing things right, and using those right things to build the organization's future (Hammond & Royal, 2001).

AI practitioners and authors have emphasized the importance of the appreciative interview. "We believe the seeds of change are implicit in the very first questions we ask" (Cooperrider & Whitney, 1999, p. 12). The appreciative interview and the "affirmative topic choice" have been reported to be essential parts of the initial stage of an AI intervention (see Figure 1). The selection of the topic for exploration is viewed as essential because AI researchers "believe the seeds of change are implicit in the very first questions" (Cooperrider & Whitney, 1999, p. 12). The step following topic identification, the discovery phase, is aimed at disclosing positive capacity regarding a chosen topic. AI researchers often recommend that everyone involved in the OD effort participate in interviews "because, in the process, people reclaim their ability to admire, to be surprised, to be inspired" (Cooperrider & Whitney, 1999, p. 14). A distinguishing characteristic of AI is that every question is positive in orientation (Hammond & Royal, 2001).

The third step is the dream phase (Cooperrider & Whitney, 2000). During this stage of intervention, insights from the first steps of the intervention are elaborated upon. From the perspective of the AI practitioner, the outlook and vision of the future for organization members is influenced by organization members' shared review of the data gathered in the previous phase. AI practitioners typically engage in a thematic analysis of interview

data focusing on the positive stories and capacities identified by interviewees. The reported results are identified as the organization's "dream" (Cooperrider & Srivastva, 1987). The dream is often described as a compelling statement of strategic intent in, a vision for what might be, or a powerful purpose. This phase often culminates in the drafting of a statement summarizing the organization's vision, purpose, and strategic intent.

The fourth step in the AI process, the design phase, is identified as focusing on the creation of agreed-upon concepts and principles. The positive narratives collected in the discovery phase are used to create provocative questions and propositions (Cooperrider & Whitney, 2000). Because of their connections to positive stories, provocative questions or propositions are said to come from the positive core of the organization. An example of such a question provided by Cooperrider and Whitney is, "What would our organization look like if it were designed to maximize the positive core and accelerate realizing our dreams?"

When individuals come to agreement on the design stage, the AI process moves to the final destiny phase: "Originally, the final 'D' stood for 'delivery' and was dedicated to writing action plans, building implementation strategies and monitoring progress" (Zemke, 1999, p. 31 ). According to Zemke, however, the stage has moved away from concrete activities to more of an open process. The final step in the AI process has more recently been described as focusing on sustaining the efforts of the previous stages (Cooperrider & Whitney, 1999). This step is focused on empowering, improving, and making adjustments toward ongoing change. Common models of the AI process are circular and imply that the steps are iterative-meaning, in this case, a return to another affirmative topic choice or to discovery.

The Foundations of the Action Research Approach in OD

AR was developed in the 1940s and 1950s and was focused on creating a research method that would lead to both practical results and the development of new social theory. AR was positioned as an important tool in social and organizational change (Goldstein, 1992). A key emphasis of AR has been the establishment of a co-research agenda whereby practitioners and organizational members work side-by-side to analyze, implement, and evaluate systems change. The outcomes of AR involve both the overt solving of a problem as well as the generation of new knowledge about the inner workings of AR as a learning process. This new knowledge is transferable to areas of focus for AR (Coghlan & Brannick, 2001). AR was and continues to be a cornerstone of OD (Rothwell etal, 1995).

In examining AR from the perspective of Lewin, the founder of AR, Argyris (1993) identified four key themes: (a) identifying theory and problems as inseparable elements in the exploration of social science; (b) developing research designs that considered the system or situation under study both holistically and as separate parts; (c) the creation of key concepts fthat were transferable frora'one AR situation to another; and (d) changing the way in which research was conducted so that subjects became clients engaged by skilled helpers/researchers, not as guinea pigs who are to be periodically prodded and analyzed from a distance.

Coghlan and Brannick (2001) utilized the work of Argyris, Putnam, and Smith (1995) in summarizing key elements of AR:

1. It involves change experiments on real problems in social systems. It focuses on a particular problem and seeks to provide assistance to the client system.

2. Like social management more generally, it involves iterative cycles of identifying a problem, planning, acting, and evaluating.

3. The intended change in an action research project typicalIy involves re-education, a term that refers to changing patterns of thinking and action that are currently well established in individuals and groups. A change intended by change agents is typically at the level of norms and values expressed in action. Effective re-education depends on participation by clients in diagnosis, fact finding and free choice to engage in new kinds of action.

4. It challenges the status quo from a participative perspective that is congruent with the requirements of effective re-education.

5. It is intended to contribute simultaneously to basic knowledge in social science and to social action in everyday life. High standards for developing theory and empirically testing propositions organized by theory are not to be sacrificed nor the relation to practice be lost. (Coghlan & Brannick, 2001, p. 5)

AR is a framework for diagnosing, implementing, and evaluating a change process (see Figure 2). "It allows for collaboration between practitioner and client throughout the process in order to distribute knowledge and understanding within the organization" (Cady & Caster, 2000, p. 80). Additionally, AR utilizes empirical data collection and feedback systems that are rigorously defined and analyzed. There does not appear to be complete agreement regarding the core philosophical assumptions underlying Lewin's perspective on action research. One interpretation, however, is that his support of empirical data collection and the development of theory with an apparent aim toward generalizability imply support of a logical empiricist perspective. In general, the logical empiricist perspective supports the idea of a shared reality and the possibility for replicating empirical approaches to social science problems that could be reused with a variety of people in a variety of settings.

Although there are several AR approaches varying from five to fourteen steps (Argyris, 1993; Barker & Barker, 1994; Cummings & Worley, 2004; Davis & Cook, 1998; DePoy, Hartman, & Haslett, 1999; McLean & Sullivan, 1989), the general approach involves data gathering, diagnosis, implementation, and evaluation of the intervention. All AR models appear to be comparable to the basic premises found in the Shewart cycle (Shewart, 1939) and the action research cycle forwarded by Lewin (1946) and include variations on the basic steps of (a) generating an initial idea, (b) engaging in fact finding, (c) planning, (d) taking the first action step, (e) evaluating, (f) amending the plan, and (g) taking another action step (see Cady & Caster, 2000, for comparisons of several AR models).

Most AR models appear to be cyclical or iterative. This cyclical effect implies a second process occurring concurrently with the aforementioned steps. This meta-learning step involves discovery of the process during engagement in the process. Knowledge is created through action and reflection about how the process itself is going. Inquiry into how the steps are being undertaken becomes as important as action about them. Figure 2 identifies the eight-step AR process presented by McLean and Sullivan (1989). Two of the differentiating factors between AR and AI can be found in the Assessment and Feedback stage, as well as the Evaluation stage, presented in the AR model.

Critical Comparisons of the Al and AR Approaches

AR has been criticized as a flawed method of organizational change and as an inadequate process for developing new theory. Cooperrider and Srivastva (1987) were critical of the lack of useful theory generated by traditional AR. They contended that both the method of AR and implicit theory of social organization used by AR are at fault. The problem, according to AI practitioners and scholars, is that most AR projects use rational empirical assumptions (Sussman & Evered, 1978) that treat social and psychological reality as something fundamentally stable and enduring, or external to the individual and organization. As previously mentioned, AI advocates criticize AR as a problem-solvingfocused approach. According to the AI literature, the problem-solving approach of AR limits the opportunities for organizations to be successful because it reinforces existing beliefs instead of addressing the possibilities for the creation of new (and presumably better) beliefs. AR is additionally criticized because it keeps the organization moving from one unsolved problem to another (Zemke, 1999).

According to Cady and Caster (2000), there are three main challenges facing AR: (a) AR is problem-solving oriented in comparison to the "positive process frameworks" utilized in AI; (b) AR has been left open to interpretation resulting in AR models that have become complex and somewhat intimidating for practitioners; and (c) AR has not been utilized in conjunction with other OD and change approaches. Despite these challenges, AR has been widely utilized for several decades (Cummings & Worley, 2004). There have been recent suggestions (Cady & Caster, 2000; Golembiewski, 1999; McLean, 1996) to integrate AI and AR approaches. The general suggestion for doing so is to

emphasize the positive questions and focus of the AI approach while collecting critical and constructive feedback during the intervention process.

Although both are intervention approaches to OD and change, AI and AR involve different assumptions and steps. AI practitioners and scholars identify the AI approach as a process focused on the creation and actualization of new principles, beliefs, and provocative propositions. According to Cooperrider and Srivastva (1987), AR is focused on problem solving in the forms of assessment and evaluation. Even though both intervention approaches may share the goal of learning or OD, the differences between the socio-rationalist assumptions in AI and the rational empiricist assumptions in AR are demonstrated in the models and descriptions of each approach. Although often described as being in direct opposition, many of the differences between AI and AR are neither dualistic nor exclusive to one or the other.

AI has also received criticism as an approach to OD and change. According to Golembiewski (1999), executives tend to favor an AI approach to OD over other approaches because it is more likely to heighten integrative rather than punitive impulses. If executives ask employees to think of the accomplishments of the organization and of leadership, the only option the AI process presents is positive information. Therefore, AI may be viewed as attractive to those holding positional power because it averts focus away from organizational challenges and specific performance or behavioral issues that may be of concern to employees. Employees may become frustrated, however, with managers and executives unwilling to discuss important challenges being faced by the organization.

Critics of AI argue that there is currently little research supporting AI or differentiating it as more favorable than other approaches. McLean (1996) stated,

Does appreciative inquiry have anything to say to our practice of OD? Certainly. But it's interesting how Cooperrider (legitimately) points to the paucity of research supporting the use of the AR model, yet provides no "proof (what would that look like, anyhow?) that appreciative inquiry can do any better. A synergistic approach will surely benefit all involved, (p. 3)

Golembiewski (1999) went on to say, "Social constructivism is an inhospitable foundation for anything that can be called empirical research, even loosely. And this 'creative theorizing' in AI takes on less the character of science than of advocacy, if not of self-serving spinning" (in Livingston, 1999, pp. 109-110).

Critics of AR have stated that AR focuses on only negative aspects or problems. A lack of cumulative research in support of AI may lead to the idea that a balanced approach including the challenges and problem areas, organizational accomplishments, and best practices may be equally or more effective (Burke, 1982). An organizational intervention that includes features from both approaches has been pondered. As McLean (1996) stated:

Appreciative Inquiry, however, seems to fall into the opposite trap of focusing only on what's going well, but still for the purpose of improving the organization and those within it. Improvement requires an understanding both of what's not working well and what can be built on because it is working well. (p. 2)

In response to some of the dialogue regarding integrated approaches, Cady and Caster (2000) suggested a model and process for the combination of AI and AR. The next section will explore experienced OD practitioner perspectives based on the theory, research, and practice of AI and AR.

Methodology and Research Design

Because of the apparent lack of current research and exploration of practice perspectives regarding the strengths and weaknesses of AI in comparison to AR, an exploratory, qualitative study was undertaken. Although not typically generalizable, data gathered from qualitative research can provide a breadth of understanding not easily accessed through other modes of inquiry (Lincoln & Guba, 1985). Key respondents were selected and questioned with the support of a consistent interview protocol. The data obtained through these interviews consisted of text in the form of rich oral descriptions (qualitative data). Frequencies and percentages of responses were organized to supply the reader with a summary of responses provided by interviewees.

Interviews with OD Practitioners

The following is a discussion of the interview protocol used to obtain more information regarding the strengths and challenges of AI and AR.

Participant Interviewees

Because we were unable to identify a public list of AI practitioners, a thorough literature search of OD-related journals was undertaken. The researchers identified four professional associations that, based on available printed materials, journal articles, and advertised workshops, were most likely to have practitioners involved in AI. Four professional associations (ASTD, ODI, ODN and AHRD) were contacted and asked for access to their published list of members. The identification of individuals who were known to facilitate AI was supported by cross-referencing literature from the professional associations with member listings. Assistance in identifying those professional association members involved with AI interventions was also requested from and provided by professional association contacts. The criteria for study participant identification included that they (a) had been involved in multiple AI interventions, (b) had participated in AI interventions of an ongoing nature (not just a training event), and (c) had more than ten years of experience in OD or related area.

Twenty-three OD professionals were identified as prospective participants. After contacting prospective participants, fourteen participants were identified as being

experienced with AI to the level desired for the study. Twelve OD professionals agreed to participate in the study. The participants in the study included four Fortune 500 corporate OD managers, two HR managers from medium-sized private sector organizations, two HRD managers from a medium-sized public sector organization, and four external OD consultants. The OD consultants worked with a variety of clients on AI interventions, including Fortune 500 organizations, medium-sized private sector organizations, and large and medium-sized public sector organizations. The interviewees' involvement in AI interventions included a variety of private sector industries, such as financial services, retail merchandising, pharmaceuticals, information technology, food and agricultural products, energy, and manufacturing. Additionally, these OD consultants were involved in public sector AI interventions, including public schools, foundations, healthcare organizations, and environmental associations. The employee size of the organizations reported to be part of AI interventions ranged from 7,000 to 160,000 in the private sector and 100 to 11,000 in the public sector.

Data Collection

The data were collected through in-depth qualitative interviews. The researchers conducted phone interviews with these twelve experienced AI facilitators. A semi-structured interview guide was used to organize data collection during the interview process. Semistructured interviews were selected because they are "reasonably objective while still permitting a thorough understanding of the respondent's opinions and the reasons behind them" (Borg & Gall, 1989, p. 452). Interview questions focused on process, perceptions, experiences, status, and outcomes. Because content analysis was the planned mode for data analysis, questions were developed with sufficient breadth so as not overly to direct the responses to specific issues. An AI approach (Cooperrider & Whitney, 1999) was used for the first half of each interview before the introduction of critical or problem-solving questions.

Data Analysis

A qualitative thematic strategy for data analysis was employed to organize and to make judgments about the meaning of the data. Content analysis is an approach utilized for the systematic examination of text from the interview data. The researchers utilized an inductive approach to the development of the coding scheme utilized to analyze participant responses (Glaser & Strauss, 1967; Lincoln & Cuba, 1985).

Findings: Strengths of Al and AR Approaches

As indicated in our introductory remarks, although we will identify and discuss themes from both the AI and AR interviews, we provide more discussion regarding AI as the interviewees selected had extensive experience in the facilitation of AI. We also found that, not surprisingly, the literature available on AI is considerably smaller than that of AR, making AI an important area for further exploration. Through responses to open-ended questions, interviewees identified contributions of the AI and AR approaches.

In response to the question, "In your view, what are the strengths of the AI approach?," OD professionals identified several areas associated with improved relationships among co-workers and between managers and employees. Each respondent emphasized the importance of the AI approach to the development of a shared sense of new possibilities for the organization. Sample comments illustrating the importance of AI to improved relationships and shared understanding included:

Appreciative Inquiry is an invitation to organization members from all levels to participate in the accessing of new possibilities for the organization and for all to engage in a goal setting process that begins with their collective imagination. Organization members discover the rich capacity of the system and the strengths of those around them.

I am impressed with the ability of the AI approach to support organization members in the development of possibilities for the future. The process allows for new ground to be broken around creativity, cooperation, and a clarified vision for the future that involves everyone.

An examination of the responses from participants indicated that all identified one of the most significant contributions of AI to be the development of cooperation in conjunction with improved skill development or improved utilization of interpersonal skills. This skill development was often attributed to the impact of the discovery phase of the Al process.

I find AI useful in assisting organization members to develop a deeper understanding of one another through listening more effectively. This appreciative regard is demonstrated by listening, and responses support cooperation between employees and [between] employees and managers. This support fuels the movement toward organizational improvement and success.

During an Al intervention, and beginning with my first question of them, the culture for appreciating one another shifts. Employees listen to each another more intently and focus more on the strengths each brings to the game.

The benefits of AI discussed by OD professionals were not unlike those described to be the benefits of AR (Goldstein, 1992) or identified as the intended outcomes of organization development (Egan, 2002). OD professionals interviewed for this study, however, emphasized many of the points found in the AI literature, particularly accession of the "capacities of the organization" toward a "better future." As stated by one OD professional, "Participants in the AI process experience a shift away from the problems toward the resources available to them and their coworkers. There is movement toward a realistic, more productive future that is high performing and dynamic."

Sixteen themes were identified during the interview process. The themes are provided in Table 1 with associated frequencies and percentages for each response.

The positive contributions identified by the participants are supported by the literature reviewed in this study. Participants' descriptions of the contributions of AI are found in the language and explanation of the AI process. Interviewee comments parallel those of the AI literature, such as the opportunity to be involved in the discovery phase, whereby participants access and understand their organizational capacity and share in positive organizational stories. The creation of the dream, whereby positive imagery about the organization can be developed, is also referred to indirectly through mentioning opportunities for individuals to access possibilities and create positive imagery for the organization. Additional references by interviewees that supported the concepts associated with AI included the power of the narrative or story, the heliotropic hypothesis, and the organization's inner dialogue. The themes from the discussion about AI appear to have been more about the discovery and dream stages than the design and destiny stages in the AI model (Figure 1). As one participant said,

Because AI is so new, it is important that we emphasize the initial stages of the AI process, so that we may better understand where it may lead. Without starting the process correctly, we may be unable to determine the long term impact of AI.

Participant responses to the question "What are the strengths of the AR approach?" identified several contributions. The manner in which some interviewees responded, however, was different from the discussion about the strengths of AI. Four respondents often qualified their identification of AR strengths with comments comparing them to AI strengths. For instance, one said, "A strength of AR is that it often includes members of the organization from a variety of backgrounds and roles. However, AI is more effective at making interpersonal connections while including organization members." Nonetheless, all respondents provided commentary regarding the strengths of AR. The themes for these responses are provided in Table 2.

Similar to the identified strengths of AI, OD practitioners' perspectives regarding the strengths of AR were similar to perspectives provided in the literature, including emphasis on inclusion and empowerment of employees, datadriven responses from assessment and evaluation, the transferability of the process from OD practitioner to client, and the focus on improvement of key organizational processes. These responses were different from the responses about AI, but were not disparaging regarding the AR process. All interviewees indicated that they were formally trained in OD and had learned about AR first, before AI, and that the foundations of AR influenced their work as OD practitioners.

Findings: Weaknesses of the AI and AR Approaches

In response to the question "What are the weaknesses of the AI approach?" all participants identified three challenges: Difficult interpersonal situations may be overlooked and remain unidentified as challenges to the success of the group or organization; feelings of anger or frustration are not voiced and may become barriers for some employees; and dissatisfied organization members may retreat and withdraw from

the process because they are unable to feel included by the AI approach. Two OD professionals responded as follows:

[During an AI intervention] it is sometimes difficult for the deeply rooted challenges between individuals to be addressed effectively. Employees may find some challenges to engaging authentically in the process when previously strained relationships show themselves in one-on-one relationships. This has been an ongoing challenge for a couple of my clients.

We want everyone to participate in the process but find that some refuse and withdraw. They don't directly impair the development of the team; they just remain passive. Some [organization members] have indicated that they feel they are unable to voice their true feelings... like anger.

Another theme from the interviews was that managers might avoid challenges by focusing on "the positive." As indicated by one interviewee, "I have been asked a couple of times by employees as to how they can be heard when their manager is not open to acknowledging when difficulty occurs." Several of the OD professionals discussed their observations that managers may use the AI approach inconsistently, resulting in a lack of focus on the key messages forwarded by the AI process. The long-term commitment to AI may be more challenging for organizations than other interventions. The ten themes identified by interviewees are in Table 3.

Interviewees also responded to the question, "What are the weaknesses of the AR approach?" Responses from interviewees to this question centered on a concern that the AR process did not lead to the creation of a vision for the organization, and did not thoroughly empower participants in the process to examine the breadth of organizational capacity that could be tapped for better use. Additionally, interviewees stated that a clear exploration of available opportunities could be overshadowed by negative perceptions or feelings, and that negative historical events or trends in the organization are often given too much attention. see Table 4 for key themes.

The themes identified by interviewees reflected many of the same concerns found in the literature. Few participants felt that the lack of research on AI was an important consideration in the identification of challenges to AI. It was explained that AI is too new of an approach to have been well researched. The major concerns are associated with the challenges faced when only positive content is the focus of workplace interactions. One study participant stated,

It is difficult to watch individuals who feel they must speak in negative or critical terms; some of them seem unable at times to redirect their energy into a positive direction. We must continue to pay attention to the more subtle interactions between organization members, so that we can better understand how the focus on positive imagery and communication is or is not transferred.

Responses regarding the weaknesses of AR were also parallel with discussion in the literature, but provided a practice level perspective. The weaknesses of AR that were identified in the interviews reinforced how important these OD practitioners feel the emphasis of vision, full assessment of capacity, and de-emphasis of negative perceptions are to successful interventions. These discussions made the more academic notions, like the aforementioned heliotropic hypothesis and constructivism, easy to understand as respondents tended to raise questions about the relevance of the past and overly narrow examinations of the organization were to longterm organizational success. The criticisms of AR were not provided in a manner that rejected the AR process wholesale, but rather challenged some of the underlying presumptions during the facilitation of AR.

Finally, interviewees were asked whether AI could effectively be included with AR or other problem-solving approaches. Interviewees were divided in their responses. A few OD practitioners indicated that the movement toward a combined AI and AR approach was "misguided and misses the point of the AI approach. We need to embrace the philosophy behind AI, not just use part of it." Other interviewees disagreed indicating that AI could be used in conjunction with other approaches because "it is important that the strength of AI be tapped, but it is also recognized that in some cases it is a consulting approach that can be used in conjunction with other approaches." A combined AI-AR model supported by the discussions with these practitioners is explored below. The mixed response from interviewees to this question is similarly to the various discussions in literature about AI (Bushe, 1995; Cady & Caster, 2000; Cooperrider & Srivastva, 1987; Golembiewski, 1999; McLean, 1996; Schiller, 1998).

Discussion

This study explored AI and AR approaches to OD, outlined key elements from each, and provided several strengths and weaknesses of both as identified by OD practitioners who use AI. The participants in this study confirmed many of the strengths of AI and AR found in OD literature (Bushe, 1995, 1998, 2000; Cady & Caster, 2000; Coghlan & Brannick, 2001; Cooperrider & Srivastva, 1987; Jones, 1998; Lewin, 1946). Further, this study found support for the potential limitations of AI as an exclusive organization intervention approach (Cady & Caster 2000; Golembiewski, 1999; McLean, 1996) and also elaborated on the limitations of AR. The perspectives shared by the participants in this study further detailed AI as an OD practice. Although there may be a difference of opinion regarding the exclusive use of an AI approach in OD interventions, the uniqueness of the AI approach may be beneficial to OD, even if merged with an AR approach (see Cady & Caster, 2000). Those interviewees from this study who indicated that they had used an OD approach that combined AI and AR insisted that further exploration of the best of both AI and AR or a systematic combined OD approach would be beneficial. There is much more to investigate regarding the potential for a combined model. We will conclude our exploration comparing AI and AR with the exploration of such a model.

As a result of the research reported on within this article and other inquiries regarding the possible integration of AI and AR, Egan (2004) created an Appreciative Action Research Model that combines the strengths of AI with AR while addressing some of the weaknesses. The model (see Figure 3 ) provides support for the aforementioned discovery, dream, and design steps in AI (Cooperrider & Whitney, 1999) supported by the assessment and feedback, and evaluation steps found in AR (McLean & Sullivan, 1989). As interviewees indicated, there is benefit in the development of a clear positive picture regarding capacity, vision, and what is working well in an organization.

By conceiving of the discovery and dream stages prior to assessment and feedback, the model supports the appreciative interview process, without interruptions or questions regarding problems or barriers to organizational success. In the Egan (2004) model, the problemoriented focus (Lewin, 1946) is addressed following the development of a clear understanding through an appreciative examination of the capacity of the organization and the creation of an affirming vision statement for the future of the organization.

This new model (Egan, 2004) supports insights provided by interviewees in the current study who reported combining AI and AR in practice. Additionally, it is not intended to negate the affirmative or the socio-rationalist assumptions underlying AI. We recognize that the integration of AR and AI actions and assumptions into one model presents some ambiguity. There is much more work required by OD practitioners, clients, and scholars to validate a combined approach, like that suggested by study interviewees and presented by Egan (2004). We have reviewed the work of scholars who manage the tension between paradigms in mixed method research (Tashakkori & Teddlie, 1998) and we suggest that a similar exploration is possible while using an appreciative action research approach.

Cady and Caster (2000) have discussed some of the additional merits of a combined framework. Their DIET (diagnose, intervene, evaluate, and transfer) approach is similar to Egan's (2004) in that it attempts to combine key assumptions of AI and AR, but different in that Cady and Caster attempt to integrate AI and AR perspectives from the beginning-suggesting the exploration of positive and negative feelings and analysis in the first step of an OD effort. As we understand Cady and Caster's process, there appears to be no clear suspension of a problem orientation at any point in their "bimodal" process that we interpret as a rejection of the aforementioned socio-rationalist perspective that is foundational to the AI process. Unlike Cady and Caster, Egan (2004) emphasizes that OD begins with the appreciative development of an understanding of collective capacity, mission, vision, goals, and steps that could be taken to accomplish those goals. These appreciative steps are followed by a mixed affirmative and problem solving approach to assess the established goals and what it would take to accomplish them.

This brief examination of the potential for combining AI and AR provides a starting point for additional exploration in this area. There is much more practice and research needed to determine if a model combining AI and AR would be beneficial to OD practice. We

believe this article will support further exploration of the possibilities of AI and AR as independent intervention approaches and in a combined framework for OD.

Conclusion The results from this study are not generalizable, but elaborative. The choice to interview OD practitioners regarding their approaches to AI was formulated in response to an apparent lack of studies exploring AI and AR from this perspective. Future examination of AI and AR interventions from both interpretive and empirical research perspectives is recommended. For instance, the strengths and weaknesses of AI and AR discussed in this study could be used as the basis for future development of a survey to be used with a larger sample of OD practitioners. Additionally, comparative research, such as that performed by Jones (1998), and other case study research may be of benefit to determine the impact of AI practices. Interpretive studies examining the experiences of practitioners and participants involved in AI and AR interventions may be of benefit to scholars and practitioners. Finally, as mentioned earlier, AR and AI were founded by individuals who believed that interventions should contribute to and be guided by theory and theory-building. It is important that future AI, AR, and combined approaches to OD embrace theory and theory-building as part of the practice-to-research-to-theory cycle.

In conclusion, as Cady and Caster (2000), McLean (1996), Golembiewski(1999), and others have suggested, there is not only much more to learn about both AI and AR, but there is also an imperative for further investigation regarding the integration between these two approaches to OD. As Cady and Caster stated,

[Blending] the humanistic side of OD with the empirically driven data collection is needed to add rigor to our field... [and] allows for seemingly polar opposite theories, such as the problem approach and the appreciative approach, to exist in a synchronous relationship, (p. 90)

Further discussion regarding these and many other issues associated with AI and AR is important to the future of OD. We hope that related exploration and dialogue regarding these provocative approaches to organizational change continues.

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Toby Marshall Egan, PhD

Cynthia M. Lancaster, M.Ed

Toby Marshall Egan, Assistant Professor in the Human Resource Development (HRD) program at Texas A & M University, received his PhD in HRD from the University of Minnesota. An experienced OD teacher and researcher, Toby has over fifteen years of practice in consulting. He has published OD-related articles in ODJ, Advances in Human Developing Resources and Human Resource Development Quarterly. Toby excels as an OD practitioner and has worked with numerous Fortune 500 and public sector clients.

Contact Information Human Resource Development Texas A & M University 511 Harrington 4226 TAMU College Station, TX 77843-4226 979-458-3585 Fax:979-8624347 egan@tamu.edu

Cynthia McLean Lancaster received her M.Ed, specializing in HRD from the University of Minnesota in 2003. She spent three years working as a Project Manager, helping to develop customized web-based training for a nationally recognized HR and training services firm. She has recently served as a consultant assisting with organizational assessments.

Contact Information

Cynthia McLean Lancaster

McLean Global Consulting

1553 Albert Street N

St. Paul, MN 55108

651-487-5287

cynthia.lancaster@mcleanglobal.com

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Strategic planning is an essential process used by most organizations to define how they will move toward the future. This process influences not only the senior executives but the entire staff of the organization. Due to a clearer understanding of the importance of this process and whom it affects, it is time to rethink the method. To ensure that the strategies become completely implemented throughout the entire organization, a process that includes the ideas of all stakeholders and moves the company in the direction it desires is required. Appreciative Inquiry is the method suggested to successfully complete all of the necessary elements of strategic planning.

Strategic planning is obviously an integral tool for any successful organization; however, the documented plan rarely becomes a full-fledged implementation. Executives need to share their vision with the rest of the organization but how can they ensure that the whole organization will move together in the planned direction? This paper will briefly discuss the history of strategic planning and explain why the traditional processes have continually failed. A few alternative approaches to strategic planning will then be provided, followed by a full justification of why the author believes that Appreciative Inquiry is the answer.

Appreciative Inquiry (AI) brings out the best of people and, consequently, of whole organizations. After the British Broadcasting Corporation (BBC) implemented AI across their company in 2002, the executive committee’s director general, Greg Dyke, no longer had to say “this is what I believe should happen”, he could now say “This is what you told us you wanted” and it changed the entire culture and moved the company closer to their goals (Berrisford, 2005, p. 23-24). Now, the core intrinsic values of the company are “owned by the staff, not imposed from ‘the top” (Berrisford, 2005, p. 24).

According to Cascio & Aguinis, (2005, p. 238), strategic workforce planning is “an effort to anticipate future business and environmental demands on an organization and to meet the HR requirements dictated by these conditions.” Wikipedia (2007, p. 1) provides a definition that says “strategic planning is an organization's process of defining its strategy and making decisions on allocating its resources to pursue this strategy, including its capital and people.”It is a process that is usually completed annually by the executives and/or the top management team of an organization. It is an important step for management to ensure that they are all moving in the same direction and to further extend their ideas into the various business units/departments and on down to the frontline staff. Senior executives spend a great portion of their time developing strategy as it is one of the most important parts of

their job (Beinhocker & Kaplan, 2002), yet all this effort seems to have little payoff.

Throughout the 60s, 70s, and 80s, strategic planning was promoted as steps of a process that usually included: external environmental analysis, risk analysis, and SWOT (strengths, weaknesses, opportunities, and threats) analysis; resulting in the development of corporate planning strategies (Stavros, Cooperrider, & Kelley, 2003). Gap analysis is an example of another common approach (Fitzgerald, Murrell, and Miller, 2003). According to Beinhocker & Kaplan (2002), a strategic planning process should serve two purposes: building “prepared minds” to ensure that decision makers are together on the business and the strategies, and to increase innovativeness and drive strategic creativity.

The main problem with the typical strategic planning processes is that no matter how good the plan is, it will not work unless it is acted upon. In the 1990s, it became apparent that something more had to occur to improve the current strategic planning methodologies. “In 1994, Mintzberg published "The Rise and Fall of Strategic Planning" in the Harvard Business Review” (Stavros, Cooperrider, & Kelley, 2003, p.14). Mintzberg’s article explained that traditional strategic planning methods served little or no purpose in the daily operations of corporations because they were merely rigid documents that were filed away (Stavros, Cooperrider, & Kelley). Beinhocker & Kaplan (2002, p. 51) also remind us that Mintzberg says the key starting point to a strategic planning process is to accept the fact that it should “not be designed to make strategy.” Mintzberg appropriately “calls the phrase “strategic planning” an oxymoron” (Beinhocker & Kaplan, p. 51) and argues that the real strategies are not usually defined in conference rooms but more likely to be discussed informally in hallway conversations, casual environments, or reflection time during airplane flights (Beinhocker & Kaplan). Harrison Owen (1995, p. 2), founder of Open Space Technology, says this about formal planning: “The formal sessions, although generally outstanding, could not hold a candle to the moments when the real action took place: The coffee breaks.”

It is interesting to note that when reviewing the history of strategic planning, it shows that the first writings on the topic were related to military strategies (Stavros, Cooperrider, & Kelley, 2003). Unfortunately, the same mentality of command and control and focusing on the problems is often used in today’s strategic planning meetings. As Ramsey (2006, p. 9) reminds us, “traditionally, much (OK – most) of organizational long range planning and day-to-day supervision has been content with pinpointing problem areas and finding remedies.” Beinhocker & Kaplan (2002) performed research on 30 companies and found that the annual strategic planning process usually only results in the following three things: (1) a replay of updates from the previous year’s presentations; (2) situations where most business unit leaders don’t want to take risks with announcing new ideas; and (3) these leaders work more on how to avoid embarrassment than on looking toward the future vision of the company. It seems as though nothing good is really coming out of all of this effort and time, but as Beinhocker & Kaplan (2002,

p.50) point out, “something good ought to come out of it. In a business environment of heightened risk and uncertainty, developing effective strategies is crucial.”

The Wikipedia (2007, ¶ Why strategic plans fail) definition of strategic planning goes on to state the following about why strategic plans fail: Any method that works in contrast to the deficit-thinking, traditional strategic planning methods would be considered an alternative one. This paper will briefly discuss a few methods of choice; however, it does not claim to be all-encompassing. The first method that could be extremely effective in ensuring that the strategic plan actually becomes implemented is Open Space Technology (OST). Open Space Technology is a contemporary practice of inviting the whole system into one room to share ideas and open up the dialogue to anything that comes to mind. It does have a bit of structure; however, the participants are the ones who create the agenda of the sessions. Founder of OST, Harrison Owen (1988, p. 7), explains that “In the "old days", there was validity to the thought that planning could operate by the simple formula that Past + Present = Future. However, when the world is changing as radically and discontinuously as it seems to be doing at the moment, a linear extrapolation from the past, through the present, into the future, is more than likely to bring the business to the point of failure.”

The only disadvantage of using OST for strategic planning events is that the focus can end up becoming a negative one and often-times is not focused on a particular topic. In Open Space, any topics can be discussed and a positive, strength-based approach is not encouraged. In the 1990s, American companies such as Hewlett-Packard, Ford, and Xerox began using a Japanese alternative strategic planning method called Hoshin Planning. The Hoshin Planning methodology has several advantages including a matrix that is deployed once the strategy is identified to improve the odds of implementation throughout the organization (Stavros, Cooperrider, & Kelley, 2003). Another advantage is the tools that are provided to assist with employee involvement and buy-in. The downfall is that the Hoshin Planning method still uses the traditional SWOT analysis which has failed to work effectively over the last 50 years. The Hoshin Planning strategy has led to other contemporary strategic approaches such as A Systems Thinking Approach to Strategic Planning and Management (Haines, 2000). According to Haines, we should "stamp out the outmoded way of planning, which no longer works in today's dynamic world" (p. i). Haines is referring to the traditional U. S. strategic planning methods. It is clear that these methods rarely move the entire organization toward its strategies of the future and, therefore, a better method is required.

Appreciative Inquiry focuses on what gives life and meaning to an organization and brings out their positive core through appreciative interviews. It shifts the focus from one of deficit-thinking, where organizations spend most of their time analyzing their problems and remembering what they did wrong, to a strength-based approach that hones in on the organization’s best face and moves toward making it even better. Appreciative Inquiry has also been defined as “a radically affirmative

approach to change which completely lets go of problem-based management and in so doing vitally transforms strategic planning, survey methods, culture change, merger integration methods, approaches to TQM, measurement systems, sociotechnical systems, etc.” (Cooperrider & Whitney, 1999, p. 3). Appreciative Inquiry should be foundationally appealing to senior executives and top management for strategic planning purposes since it is a methodology that is grounded in solid psychological/philosophical theories as described in the previous principles.

Another reason for the appealing nature of AI is the fact that it is generative in nature. The positive nature of AI will begin dispersing throughout the organization and the ongoing power of the AI cycle can be used over and over in all departments of the organization. In today’s organizational reality of constant change, leaders must look closely at where and how they want to change. In the highly competitive world of today’s companies, the ones that succeed and thrive are those who think strategically, plan well, effectively manage their human resources, positively lead their people, and successfully sustain their future (Stavros, Cooperrider, & Kelley, 2003). But, the real question is, how can they do it all? An Appreciative Inquiry approach to strategic planning is a step in the right direction. This method, appropriately labeled ‘Strategic Inquiry’ inspires the core stakeholders of an organization and focuses on the strengths that the organization currently possesses. Stavros, Cooperrider, & Kelley (2003, p. 11) explain Strategic Inquiry by providing a great example:

The best strategic planning method that will truly implement the vision throughout the entire organization is to use Appreciative Inquiry. It’s as simple as getting all the key players into one room and simply asking about what they are doing well and how that makes them feel. The next step is to do as John Kello (2006, p. 22) says and ask “"What, specifically, can we all do to spread those winning strategies and practices throughout our whole operation?" When individuals are embraced as a part of the whole of the organization in a positive manner, they become motivated to work towards a better future. Organizations, then, become like a bright light pointing in the direction of unimaginable outcomes. As Cooperrider, Barrett, & Srivastva (1995, p.189) put it “organizations are, to a large extent, affirmative projections. They are guided in their actions by anticipatory forestructures of knowledge which like a movie projector on a screen, projects a horizon of confident construction which energizes, intensifies, coordinates, and provokes action in the present.”

Recent studies suggest that a higher level of Emotional Intelligence (EI) in an organization’s leaders is the “key to creating a working climate that encourages employees to give their best” (Yoder, 2005, p. 48). Debra Yoder (p. 51) outlines a study that was performed to determine the relationship of EI to the organizational climate and found that “eight emotional intelligence competencies constituted 75% of the responses. These included developing others, teamwork and collaboration, organizational awareness, building bonds, visionary leadership, empathy, respect, and open communication.” Yoder goes on to explain that EI (and, therefore, AI) are not simply methods

of ‘doing’ something but rather are a way of being. For example, a person cannot just act empathetic; they must ‘be’ empathetic (Yoder).

Yoder (2005, p. 57) also accurately states “people perform at their best in an atmosphere of respect, empathy, and open communication” and she concludes her article with “leaderful organizations are the result of inviting and engaging emotional energy in powerful ways.” That is precisely the result of an Appreciative Inquiry process and, therefore, the ending result of a strategic planning session implementing Strategic Inquiry. As Ramsey (2006, p. 11) accurately states it in his recent article, “Today’s reality is that just fixing what’s broken isn’t good enough anymore.”

Cooperrider & Whitney (1999, p. 3-4) also explain it well when they explain that “human systems grow in the direction of what they persistently ask questions about and this propensity is strongest and most sustainable when the means and ends of inquiry are positively correlated. The single most prolific thing a group can do if its aims are to liberate the human spirit and consciously construct a better future is to make the positive change core the common and explicit property of all.” The team went around the room and had every person think about it and make an individual commitment to the team to try and live by the propositions defined. These are the results of the AI process: “At Leadshare in Canada AI was used to help this big eight accounting firm make the tough transition in the executive succession of a “legendary” managing partner. The managing partner seized the moment as an incredible leadership development opportunity for all 400 partners. Everyone was interviewed with AI. An extensive interview protocol was designed (it ended up taking about 2 hours per interview) focusing on affirmative topics like innovation, equality, partnership, speed to market, and valuing diversity (in Canada between francophone and anglophone). And not one outside consultant did the interviews. All were done internally, by 30 junior partners as part of a leadership development program. A powerful and instant intergenerational connection was made, and organizational history came alive in face-to-face story. Instead of amnesia, or a problem-to-be-solved, people began to relate to their history in a whole new way. Like a good piece of poetry filled with endless interpretive meaning, people at Leadshare ascended into their history as a reservoir of positive possibility. At the next annual partners meeting with over 400 people in the conference hall, the material was showcased and coupled to the future, as the strategic planning became one of the best the partners could ever remember.” (Cooperrider & Whitney, 1999, p. 7-8).

“Before their strategic planning session in 1997, Nutrimental Foods of Brazil closed down the plant for a full day to bring all 700 employees together for a day of Discovery into the factors and forces that have given life the system when it had been most effective, most alive, and most successful as a producer of high quality health foods. With cheers and good wishes a “smaller” group of 150 stakeholders—employees from all levels, suppliers, distributors, community leaders, financiers, and customers—then went into a four day strategy session to articulate a new and bold corporate dream. The stories from the day before were used just as an artist uses a palette of

colors—before painting a picture the artist assembles the red paints, blue, green, yellow and so on. With these “materials” in hand people were asked to dream: “What is the world calling us to become? What are those things about us that no matter how much we change, we want to continue into our new and different future? Lets assume that tonight while we were all asleep a miracle occurred where Nutrimental became exactly as we would like it to be—all of its best qualities are magnified, extended, multiplied the way we would like to see…in fact we wake up and it is now 2005…as you come into Nutrimental today what do you see that is different, and how do you know?” After four days of appreciative analysis, planning, and articulation of three new strategic business directions the organization launches into the future with focus, solidarity, and confidence. Six months later record bottom line figures of millions of dollars are recorded—profits are up 300%. The co-CEOs Rodrigo Loures and Arthur Lemme Nettto attribute the dramatic results to two things: bringing the whole system into the planning process, and realizing that organizations are in fact “centers of human relatedness” which thrive when there is an appreciative eye—when people see the best in one another, when they can dialogue their dreams and ultimate concerns in affirming ways, and when they are connected in full voice to create not just new worlds but better worlds” (Cooperrider & Whitney, 1999, p. 9-10).

Back to the definition from the text, Applied Psychology in Human Resource Management, where Cascio & Aguinis (2005, p. 238) state that strategic workforce planning is “an effort to anticipate future business and environmental demands on an organization and to meet the HR requirements dictated by these conditions”. The author whole-heartedly feels that this is an extremely deficit-based, negative definition and does not accurately reflect the true purpose of strategic planning.

Strategic planning should be more than an ‘effort’ that simply ‘meets’ the requirements that have been ‘dictated’ from above. A definition such as this one is the reason that the traditional strategic planning processes continue to fail and become a waste of time of senior executives and the entire staff. Strategic planning should be an inspirational, creative process that moves the organization toward achieving their fundamental dreams. It should be a proecess where the people of the organization collaborate to ensure that the new direction will “increase the odds that their strategic innovations will shape the world that lies ahead” (Beinhocker & Kaplan, 2002, p.57) A strategic planning session for organizations should ultimately be “the inspiration to SOAR” (Stavros, Cooperrider, & Kelley, 2003, p. 20)!