Appreciative inquiry (AI) can be used to identify the strengths, successes and unique attributes of a system or a group of people. Instead of starting from a problem, AI asks what we can learn from things that have worked or are currently working well. It focuses on what the participants appreciate about concrete situations in the past and present, as a basis for building an image of a preferred future. AI was developed by David Cooperrider and his colleagues at the Case Western Reserve University in the 1980s.
At FoAM we found (elements of) AI useful as a warming up exercise to link the topic of conversation to the real experiences of the people involved. We frame the conversation with a question, then ask the participants to think of a situation in which the question was positively resolved. For example, if a question is 'how can we work together on interesting things?', we invite participants to think of a time when they previously worked together on interesting things and to identify the key factors that made this situation possible.
In a short AI 'discovery' session, the participants interview each other in pairs, one at the time, after which the whole group comes together to report insights from their conversations and find common themes. The facilitator summarises and clusters the answers focusing on the affirmative or 'life-giving' success factors or criteria.
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* Note: the guiding questions for the interviews will depend on the themes/insights you are trying to distill. For example: if you are looking to identify actions, emotions and resources, the questions might be 'What did you do? How did you feel? What made this situation possible?', or 'What did you do to contribute to this situation? What were the other people doing? What else was around?', etc.
Read more about appreciative inquiry: http://appreciativeinquiry.case.edu/