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Appreciative Inquiry in Practical Terms Shoot for the moon. Even if you miss it you will land among the stars. - Les Brown Appreciative Inquiry (AI) has been described as “an exciting way to embrace organizational change.” AI works by “identifying what is positive and connecting to it in ways that heighten energy and vision for change.” Through AI questioning, we discover what we value about what we already have. This allows us to dream of and envision realistic possibilities, and design and deliver positive future outcomes. It’s precisely that sort of high reaching, visionary talk that causes skeptics to dismiss AI as the Organizational Development “Flavor of the Day” or even some form of New Age wishful thinking. But the AI process has actually been in practice for more than 20 years, and is based on solid, proven learning theory. The internet is dotted with research papers and case studies documenting how using Appreciative Inquiry has accelerated positive change in organizations around the world, including schools, governments, hospitals, religious institutions, not-for-profit agencies, and businesses. AI has literally transformed them, increasing productivity, renewing motivation, and focusing energy and action toward mutual goals for long-term, sustained performance improvement The Problem with Problem Solving It turns out this focus on the negative is precisely the problem with traditional problem solving. Looking for what is broken is a fine approach for troubleshooting a piece of equipment, but not so great for working with people. Performing a problem solving exercise automatically implies that something (or someone) within the organization is broken and needs to be ferreted out and fixed. Participants focus their thinking around the identified problem (usually a single issue), and brainstorm possible solutions. If the session is not carefully facilitated, it can quickly degrade into criticism and finger pointing. A clear solution may not emerge, leaving participants feeling demoralized and drained, with no clear path – and little hope -- for future positive change. Enter Appreciative Inquiry It’s not that AI practitioners simply paint a rosy picture so that everyone can view the glass as half full. Nor do they believe that AI can make difficult organizational problems magically disappear. Rather, by performing a specific process of positive questioning and analysis, and helping members of the organization understand and focus on what they truly value, an exciting new path emerges that energizes the organization to work together toward mutually desirable future outcomes. Team members move forward with a new focus, renewed energy, and a clear sense of direction. Where do you want to go? For example, you might envision a department with high morale as: …comprised of confident, happy team members who enjoy working together to develop award-winning work and exceed customer expectations. They take pride in solving difficult challenges -- together and on their own. We want to increase the fun and satisfaction in our work by becoming a department of high morale. Next, participants begin a four step process that AI practitioners call the “4-D Cycle:”
The phases do sound a bit New Age, don’t they? In plain language, for AI skeptics, what follows provides a simplified description of how a typical AI initiative plays out in practice. Discover Typical Discover questioning starts with the phrase, “Tell me about a time when …” to elicit a story about a positive experience within the organization pertaining to the focus topic. For example, if your focus is on increasing morale, a good, affirmative question set might include, “Tell me about a time at work when you felt most energized and enthusiastic, and when you felt especially good about the work you were doing and the team you were working with. What was the situation? What made this experience possible?” Sharing stories about past successes reminds participants that anything negative they are experiencing does not have to be permanent. The success story magnifies the positive experience and makes current challenges feel more manageable. Dream AI practitioners position Dream questions in a way that helps participants envision the positive change as if it were already happening. For example, “Imagine it is three years in the future. Your department is receiving an award for your work. You are so proud of the accomplishments of you and your teammates, and have enjoyed working together to do your best work. Morale is at an all-time high. The press has asked you for an interview to tell them what its like to work with your group. What made this award possible? What will you tell them?” Practitioners compile the responses and analyze them for reoccurring patterns. “Dreaming” may seem a bit out of place in a business setting, but envisioning a positive outcome is actually a common coaching technique. If you are involved in sports, you may be familiar with the technique of envisioning yourself making the big win before an event. The concept also dovetails with the second of Stephen Covey’s Seven Habits for Highly Effective People: “Begin with the End in Mind.“ Design Practitioners consider this the most difficult phase of the AI process. A small team is charged with analyzing participant responses and designing a roadmap for actions and resources required to realize the vision and dream for the organization. Goals and procedures that emerge from the Design phase must be bold enough to motivate participants, yet grounded in realism in order to create sustainable, long-term change. Deliver Just do it! Is AI the silver bullet to wipe out every organizational woe? Of course not. Organizations are comprised of people, and people are, as they say, messy. However, having only recently introduced AI to my own 20-person training team, I am witnessing some exciting positive patterns beginning to emerge among our team members. We just completed our first Appreciative quarterly performance interviews, and plan to continue that practice throughout the year. We also plan to complete an AI initiative around our internal project development process, with hopes of kindling heightened appreciation of the unique talents and contributions of each of our various team members and increased passion around working together to meet our shared bonus targets. There are a number of good internet articles and books currently available to help you learn more about AI, including a detailed workbook by AI founder, David Cooperrider. Maybe you (or your stakeholders) have been around the training block a few times and think you’ve heard it all before. Even so, if you don’t buy into all the hype around AI, there is very little to lose and a lot to be gained from performing a simple AI pilot with a small group in your organization. Give it a try! If you are interested in doing more research and reading on this most interesting subject, we have included a Reading List for your reference. Chris F. Willis, CEO, Media 1 Feedback Contact Us copyright ©2008 Media 1 |