What is appreciative inquiry?
Appreciative Inquiry is an approach to collecting data that can be used in conjunction with many other methods. It is covered here because adopting an appreciative approach can be very helpful for ensuring productive public consultation sessions. Appreciative Inquiry (AI) is an approach that focuses on what is positive or good about a current system or initiative, so that what is good can be replicated or increased in the future. AI seeks to encourage and start with a place of appreciation, and then draw from that a vision of a positive future state.
In this video, the co-author of the book Appreciative Inquiry for Change Management, Sarah Lewis, gives a brief overview of AI (3.5 mins):
Why Use Appreciative Inquiry?
- It helps you and the participants to assess what is currently working about a program or initiative and also pinpoint what can work better in the future.
- The format helps overcome a potential limitation of focus group research, that is sometimes group interviews can focus on the negative aspects of a program or initiative.
Using Appreciative Inquiry:
- In AI, the research participants are considered active in the creation of solutions.
- AI is generally used with interview or focus group type data collection methods.
- For an approach to be AI, the question design is of crucial importance:
- Questions must be positively oriented.
- Should focus on the valued factors and forces in the system under study.
- These factors and forces are identified and used to guide future initiatives.
- Information from the questions is used to inform recommendations.
- Time should be taken before data collection to craft “good questions”:
- Use positive language.
- Pose questions as invitations.
- Evoke storytelling.
- Be conversational.
Effective AI questions:
- Four types of questions are asked:
- Deep story – intended to evoke stories about best experiences, and get people thinking positively. Encourage participants to include details.
- Value – helps participants discover what it is they value about the individual or collective system being discussed. Personalize the factos mentioned in the deep story question.
- Core factors – used to identify what are the core factors that participants believe are integral to the system under discussion. Asks for specifics.
- Future – is an invitation for participants to imagine an ideal future, like the deep story question, details are encouraged.
- AI data collection should usually occur face to face and in a semi-structured way where the interviewer is able to probe beyond superficial answers to ensure details are given.
- Sometimes people have difficulty maintaining a positive or appreciative orientation to the question, for this reason, asking the questions in order of deep story, value, core factors, future helps to bring focus back to specific positive experiences.
Tips from the Professor: AI is particularly useful in asking people questions about existing processes or programs. It helps to centre the conversation around what IS working, so that you can do more of what is good, rather than having a conversation devolve into complaints, which can sometimes happen during public consultations.