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Inquiring Appreciatively in Albuquerque—Part 1
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By: Kim Hansen
This is a two-part article written by Kim Hansen, an instructional designer who works with evaluation. She attended a conference on Appreciative Inquiry, presented by Ms. Laverne Webb in Albuquerque, New Mexico. Ms. Webb works with AI in high conflict areas around the world. This article offers a brief overview of AI, and examines its use in evaluation and performance improvement of organizations.
Appreciative Inquiry (AI) is a methodology used by groups to cooperatively explore what is working well in an organization, so they may plan and implement further positive action. This process encourages change in other areas of the organization that may not be functioning as well. AI involves a pre-scripted approach to interviewing stakeholders, leading discussions, and creating shared goals, to focus an organization’s productive energy towards mutually positive outcomes. Planned exercises in visualizing “what could be”, as well as hands-on activities, and mind mapping techniques, are directed towards defining objectives. The goals are then implemented by creating concrete steps toward putting agreed upon changes into practice. The AI method inspires mutual imagination, innovation and creative thinking, to side-step habitual obstacles and ineffective ways of thinking about challenging issues, promoting positive action.
AI follows eight assumed observations of human systems.
Most folks would agree that our perceptions affect the attitudes and outcomes of our endeavors. We have all experienced the challenge of working with negative, complaining folks who seem to suck the life out of every project, as well as the pleasure of those whose positive open-minded spirit enhances and improves every group process they touch. It is not too much of a stretch to contemplate that having a facilitator guide a system in positive directions would be more productive, or at least more pleasant. The simple homilies many of us grew up with lend belief that there is old wisdom to a positive focus. What is different is that AI has formed these concepts into organizational strategies, focusing whole systems toward positive change within competitive corporate cultures and high conflict geographic areas and situations.
Sounds nice, but what does this look like in action? AI presents four cyclical process phases of working with a system: Inquire, Imagine, Innovate, and Implement. During the workshop we toured these phases with the AI approach, reflecting on the value of each process as we experienced it. We began working with the AI process within the conference setting, led by Ms. Webb.
Stage 1 Inquire – “Appreciating the best of what is.” Ms Webb began by having the groups focus on the issue of health and well being as a common concern and interest for most adults. We began by interviewing one another to recount past experiences of good health, reflecting on how we had felt, and the circumstances surrounding that sense of well-being. Our task as interviewers was to take notes, putting our full attention on the other’s story, while asking questions to prompt deeper reflection. This is a crucial stage in AI, as people experience uninterrupted time to tell their stories, emotionally connecting with the listener, who directs the tone to positive frames of reference. It is generally the area where people are most likely to want to vent their complaints, so focus is gently redirected towards positive reflection.
Stage 2 Imagine, we were directed to share and discuss each other's stories in a group, asking, “What might be?” The task was to notice possibilities and clarify values, sharing visions of what health and well-being could look like in our present life. The usual goals of less weight and stress, more sleep, relaxation, and exercise topped most lists. We broke into small groups, indexing ideas on sticky notes. We then performed a large group activity of bringing our vision into more tangible design by creating collages of what process our group would work with towards achieving our goals. Creative energy was tapped, and it was a relief to take a break from the jargon and clichés that usually weigh down group discussion. We then listed our ideas under broader topic headings, further defining categories of health and well-being.
During Phase 3, we were asked to innovate, co creating our vision through brainstorming a series of poster boards, winnowing down the concepts into concrete steps such as eat five servings of fruits and vegetables and walk an hour a day, etc. This activity was meant to set the strategic directions and align our unique standards and systems with our vision of health.
The final Stage 4 is to Implement. During this phase, a group would navigate the change according to the planned steps, monitor progress and evaluate results. The forthcoming evaluation would return the focus to the initial phase of “Inquiry” for further refinement.
Examining the task of evaluation underscores the potential value of AI. It is common to see fear of criticism undermine evaluation, often to the point were the process is ignored, or meaningless. The consequence is that positive changes are not made, obstacles become fixed, and problems continue to fester. If the goal of evaluation is to enhance performance improvement, then it makes intuitive sense to examine and understand what is working well to copy and expand upon those successful strategies, in comparison to investing attention and scarce resources into fixing what is not working. This may feel contrary to traditional problem analysis and our own human natures. As any parent or student can report, shifting a pattern of focus to inquiring over successful practices in achieving an A, rather than interrogation and fretting over a D can be difficult, even though criticism, nagging and blame does little to bring out the best in children, or anyone else.
Given that our natural reactions are to shadow, rather than spotlight our shortcomings, is there a more effective way to honestly evaluate the systems in which we work? AI adherents believe that methods of encouraging communication and positive outcomes promote empathy, trust, and cooperation, enhancing creative energy, so that successful strategies may expand to less functional areas of a system. As an Instructional Designer I work with both assessment and evaluation in all of my instructional projects. Reflecting on my own experience and AI, several questions came to mind.
The second part of this article will examine these questions, offering an exchange with Dr. Hallie Preskill, a professor at the University of New Mexico who uses AI in her work with evaluation.
For further information about AI and evaluation:
Preskill, H. & Coghlan, A. (2003). Evaluation and Appreciative Inquiry.
New Directions for Evaluation, Vol. 100. San Francisco: Jossey-Bass.
http://www.evaluationpractice.com/pubs.htm
For general information about Appreciative Inquiry please see:
http://www.taosinstitute.com
Kim Hansen is an Instructional Designer who develops online programmed instruction, interactive simulations, e-learning and presentation materials for technology and soft skill training. She works with clients to develop and enhance instruction through blending innovative technologies, identifying measurable objectives, and creating well designed assessments and evaluations. Her Masters degree is in Education and Information Learning Technologies, and she consults with clients within corporate, science, manufacturing, healthcare, and higher education environments.
You may see more of her work at Transformative Designs, where she specializes in transforming complex, abstract information, into clear, elegant, instruction.
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