Frameworks & Approaches
Frameworks & Approaches describe popular ways to gather and make sense of data.
Organisations and individuals grow in the direction of what they repeatedly ask questions about and focus their attention on.
The purpose of Appreciative Inquiry is therefore to build on the root causes of success – not of failure, to build on our strengths – not our weaknesses.
David Cooperrider – founder of Appreciative Inquiry
Appreciative Inquiry – A Learning Clip
HOW IT WORKS
Appreciative Inquiry (AI) is both a planning and evaluation tool that focuses on strengths and assets rather than problems and deficits in a community, organisation or programme.
It follows four steps:
- DISCOVER: Identify processes that work well and make positive progress.
- DREAM: Envision processes and action that would create even better futures.
- DESIGN: Plan and prioritise actions.
- DESTINY (or DEPLOY): Implement the proposed design.
LOCAL CASE STUDY
Explore a local example of Appreciative Inquiry being used to help a local community organisation evaluate how effective their outreach programmes have been.
Aotearoa New Zealand
- AI Practitioner (International Journal of Appreciative Inquiry): provides a wide variety of articles and resources available for free download.
- AI Commons: a global portal for AI research and case studies hosted by Case Western Reserve University.
The cycle repeats as new discoveries are made through reflection on what has changed and what seems to be working well.
AI seeks to uncover the best of what a community, programme or organisation is currently doing, by interviewing participants.
The interviews encourage participants to examine what is good about their current situation and explore what works well within the community or programme.
Data from those interviews helps construct a plan to enrich the community or improve the programme by building on what already works and what is already considered to be successful.
- Creates energy and motivation.
- Engaging, powerful, uplifting.
- Can be transformative by focusing on strengths rather than problems.
- Well proven in a diverse range of contexts.
- Compatible with Kaupapa Māori approaches.
- Critics say AI focuses only on the strengths and positive aspects of a community, person or organisation so it may make decisions based on an unbalanced understanding of the issues.
- People may feel that their problems and issues are being minimised.
- AI is a holistic approach to development, including planning, action and reflection – so if you’re just looking for an evidence-gathering approach or to evaluate, this may not be appropriate as it requires a commitment to the whole cycle.