In the fifth article in his series, Larry Reynolds looks at the 'Appreciative Inquiry'.
Many approaches to organisational change are based on two key assumptions: first, that the change will be somehow led from the top of the organisation; and second, that the reason for change is that there is some kind of problem to be solved.
But what if you based your approach to change on the exact opposite of these two assumptions: that effective change is best bottom up, and that change is needed to enhance what is already good? Then one of the most useful tools in your organisational change toolkit would be appreciative enquiry, sometimes known to its aficionados as AI.
AI can be used as way of bringing about change in whole organisations, teams, and even individuals. In each case, the people involved in bringing about the change are invited to explore four key questions, often known as the 4-D cycle.
1.Discovery
What is it we currently do that works really well? When has this organisation been at its best? What are the core factors that give life to this organisation when it’s at its best? Sometimes known as the positive core, this phase of AI invites people to consider what’s good and what works.
2.Dream
Imagine your organisation at some point in the future, when everything is just as you always wished it to be. What would the organisation look like, sound like, feel like?
3.Design
How can we build on the positive core of the organisation in order to bring about our dream? What resources do we need to mobilise, what priorities do we need to set, in order to bring about this desired future?
4. Destiny
How do we put these plans into action? How can we ensure that we maintain momentum in order to achieve the dream?
There are obvious links to solutions focussed therapy (where the therapist focuses the client’s attention on times when things are going well, rather than problem solving when they are not) and strengths based leadership (which suggests that you’ll get the best from people if you encourage them to do more of what they’re already good at, rather than trying to help them remedy their weaknesses).
These four areas of discussion can be covered in an hour or two with an individual or a small group. With a larger team or organisation you probable need a couple of days on what is sometimes called an Appreciative Inquiry Summit.
Pros and cons
Most organisational change disappoints or fails entirely. There are many reasons why this should be so, but the most common reason is probably that the people whose behaviour is critical don’t feel engaged enough to want to change. Given that the subtext of many organisational changes is often ‘We want you to work harder and differently so that the organisation can be more efficient/make more money’, this is hardly surprising. The biggest advantage of the AI approach is that it’s very good at engaging people.
The second advantage of AI is that it focuses attention on strengths and what already works. At a personal level, there’s lots of evidence to show that the biggest improvements in performance come from using more of your strengths rather than trying to remedy your weaknesses, and it seems reasonable that something similar should apply to organisations too.
Before you start to think that AI sounds too good to be true, let me point out one very significant drawback of the AI approach.
It is this: although the AI approach has a very good chance of bringing about successful organisational change, it may not be the change that you, as the CEO, team leader or OD consultant want. As with all bottom up approaches to change, what you gain in terms of commitment you lose in terms of control over the outcome of the change.
In some cases this may not matter. Very often it is the people at the front line of an organisation who best understand the organisation’s strengths and how it can best develop – for everyone’s benefit. If this is the case in your organisation, you probably won’t much mind what sorts of changes the AI process brings about, as long as they are beneficial ones.
However, there are also cases where the people at the front line don’t have a sufficient understanding of the big issues facing the organisation. They may try to recreate the ‘good old days’ of the organisation and create a dream that harks back to the past, rather than one which recognises the challenges that the organisation will face in the future. In these situations, AI could be a dangerous distraction. It’s interesting to speculate, for example, how an AI approach to change might have worked in the American car industry.
The Discover phase would probably have celebrated the industry’s ability to innovate and produce wonderfully complex machines to a consistent standard at a reasonable price. But what would the Dream phase have produced? A dream of the US motor industry once more dominating the world and staffed by highly paid workers with guaranteed job security? Or a dream of the industry reinventing itself to produce electric cars now that the era of cheap energy is over?
In summary, AI is a great way of winning commitment to change, but gives no guarantees on the kind of change you might end up with.
Read the other articles in Larry's series:
John Kotter's leadership model
The change equation and change curve model
Systems Theory
Larry Reynolds is an organisational change facilitator. For free resources on ethical and sustainable leadership, influence and change visit www.21stcenturyleader.co.uk.
