In some respects, I find that the NGO community tends to enjoy a bit too much self-congratulation (to the extent that some are calling for more reflection on failure) but behind closed doors, we seem to find it quite difficult to be positive about our work. How can we strike that balance between ‘lesson learning’ and recognising what has worked well?
I’ve recently returned from a trip to Sierra Leone where some of our local partners had come together as part of a peer review process to reflect on work done and to think about the way forward. To facilitate this review process, we decided to use an Appreciative Inquiry (AI) approach.
The basic principle behind AI is that there is something good in every individual and every organisation. It also recognises that questions can lead respondents in a particular direction. So, for example, if we ask ‘What do you think went wrong?’ we’re likely to get a response that focuses on the negative. Given this, AI encourages us to ask questions of our peers in a way that helps them to focus on their strengths e.g. ‘What do you think went well?’ Or at least to ensure that we ask non-leading questions e.g. ‘How did you feel about that?’
Now, perhaps it’s because I’m British but I confess there’s something about AI that sets my teeth on edge. There’s something about it that feels rather, well, cheesy and I also worry that focusing on the positive might mean we end up avoiding the (equally legitimate) challenges to our work that need to be addressed.
As it turns out, my experience of working with AI was not what I expected. Firstly, I was interested to see how helpful it was as a way of keeping discussions constructive between peers, avoiding such questions as ‘Don’t you think that was a bit of a silly idea?’ and the like. Secondly, I didn’t find that the process resulted in partner ignoring the challenges in their work- if anything, they required regular prompting to identify the positives. And thirdly, I found it to be more empowering (and less cheesy) than I expected. Listening to people tell you what they are proud of and even what they enjoyed about an experience in their own words really made me see how much these sorts of conversations are usually shaped by the person asking the questions. I felt that people came away from discussions feeling more energised and keen to replicate models that they had found to work well, alongside ideas of what they might like to do differently next time.
I recognise that AI, like any approach, will be more appropriate in some contexts than others, or might just vary from one group of people to another. I know some of my colleagues have not always found it helpful. However, I do think that there’s something to be said for reviewing the way we reflect on our work internally as organisations and with our partners: there are lessons to be learned that are positive as well as negative. In the right circumstances (and if we can manage to hold back our cynical sniggers), I really think it can be a useful process.