Delivering and Rediscovering

What's so special about AI?

Examples & Results

Conclusion

Bibliography

Liz Mellish founded her management consulting practice,  Mellish & Associates, in 1984. Mellish & Associates consults to government, private, community and higher education  organisations in the areas of strategic management, leadership and change, professional and personal development and research projects. Liz is the federal president of the Institute of Management Consultants, Australia, and a director of a number of Corporate Governance Boards. She is currently completing her doctoral studies in the area of strategic change and consultancy intervention. 

What is Appreciative Inquiry? 

And how can it be adapted to fit your own environment? 

Liz Mellish guides us through the AI approach, which can result in participants influencing and determining their own preferred futures.

Ap-pre’ci-ate, v., 1. Valuing; the act of recognising the best in people or the world around us; affirming past and present strengths, successes and potentials; to perceive those things that give life (health, vitality, excellence) to living systems. 2. To increase in value – for example, the economy has appreciated in value. Synonyms: VALUING, PRIZING, ESTEEMING and HONOURING.

In-quire’ (kwir), v., 1. The act of exploration and discovery. 2. To ask questions; to be open to seeing new potentials and possibilities. Synonyms: DISCOVERY, SEARCH and SYSTEMATIC EXPLORATION, STUDY.

As organisations have evolved from the centralised functional hierarchies of the 1970s, through decentralised business units of the 1980s, to matrix structures of the early 1990s to increasingly networked and ‘starburst’ arrangements for the new millennium, participants have experienced unprecedented turbulence and turmoil. The triggers for these changes aren’t hard to identify: increased competition, global operating environments, technology enablers and emphases on core competence, partnerships and customer service.

The context for the application of OD approaches has changed to a more turbulent and impermanent environment. While there is still reliance on OD basics, considerable attention is being given to new concepts, interventions and areas of application. This second generation OD includes interest in organisational transformation, organisational culture, the learning organisation, teams and their various configurations, total quality management, visioning, and ‘getting the whole system on the room’.

Training leaders and managers are chartered with the responsibility of building adaptive and co-operative capability within, across and beyond traditional functions towards networked, cross-functional, just-in-time team arrangements to get work done. While corporate rhetoric about new directions, compelling visions, common values and improved operating systems is relentless, the hearts and minds of participants in change processes frequently remain unengaged, non-committed and, at best, compliant.

Managing change from the participants’ perspective so as to reconnect people to organisational strategy, to recapture their imaginations, to respect their contributions, and to energise and sustain the process demands a new philosophy, an innovative and inclusive approach to change.

One of the challenges, as an OD practitioner, is to take the best of the past into the future and to encourage clients to do the same when overwhelming feelings of hopelessness, ‘change for change sake’, fatigue, cynicism and so on set in. Most OD professionals will have worked with multiple intervention processes in order to sharpen strategic focus, and to build individual, group and organisational capability.

The underlying assumption, which has spawned many of our OD intervention processes (such as gap analysis, SWOT, benchmarking, performance indicators, process re-engineering), is that organisations are problems to be solved. Language to describe deficient and inadequate performance has evolved to define these ‘problems’ (see Table 1 below).

The need to reinvent or regenerate OD is clear. The choices appear to be:

to stay in the incremental problem based, diagnosis/treatment frame, or

to move on to a fresh perspective which simultaneously addresses the compelling triad of strategy, structure and culture in change.

Appreciative inquiry provides the OD practitioner not only with an approach to change, but also with an opportunity to fundamentally reframe one’s philosophical stance – that is, to be deliberately hopeful, to work with optimism, to create opportunity, to celebrate the human spirit in change.

Appreciative Inquiry: what is it?

Appreciative Inquiry (AI) is an approach to organisational development and change that grows out of social constructionist thought. The AI approach offers us all the process and potential to positively explore, collectively imagine, collaboratively design and jointly commit to a path forward.

Assumptions of AI include the following.

In every society, organisation or group something works. 
What we focus on becomes our reality.
Reality is created in the moment, and there are multiple realities.
The act of asking questions of an organisation or group influences the group in some way.
People have more confidence and comfort to journey to the future (the unknown) when they carry forward parts of the past (the known).
If we carry parts of the past forward, they should be what is best about the past.
It is important to value differences.
The language we use creates our reality.

Principles of AI

The principles of AI are as follows.

Appreciate: the best of what exists, hopes for the future.

Apply: knowledge of what works and what’s possible.

Provoke: imaginations regarding new ways of organising, creative improvements.

Collaborate: collective capacity building, expertise and resources.

4D model of AI

The 4D model of AI (see Figure 1 below) is infinitely transferable to any context – for example:

individuals reflecting on their career directions
an OD consultant working through a brief with a client
a group needing to frame up and agree their team approach
different groups needing to establish co-operative arrangements
an organisation considering strategic shifts
an organisation attempting to manage a merger
a researcher designing a data collection method/focus groups and the like
community consultations – for example, involvement in town planning and infrastructure development, decisions about sustainable development.

So how does AI work?

As we work with the approach, we discover that AI is a philosophy, a way of life. One assumes the position of being the detective for ‘good things’. One develops what we call an ‘appreciative ear’. One purposefully searches for and accentuates the positive. Simple really.

We know that high achievers apply to ‘two for one’ rule. They generate two positive thoughts for every negative thought. They choose to respond pro-actively and purposefully to setbacks; they learn and improve. We also know that people respond to attention (placebo principle) and to positive expectations (pygmalion effect).

We all have difficulties. However, it is our line of inquiry, our capacity to unearth what is helpful, our willingness to discover what we care about and what will sustain us in the future that counts.

The AI process therefore commences with context and topic. The client, the team or the organisation may request assistance with, for example, supporting a structural reconfiguration, developing a strategic plan, aligning service strategy to client demand, engaging the community in government decision making and resource allocation, facilitating a hostile group of stakeholders, changing a culture, developing partnering competence and building a team.

Create the questions to explore the topic

Based on the assumption that something works, people care enough to have raised the issue, start thinking about the questions you might ask. For example, questions might include: ‘What have we got to build on?’, ‘What works best around here?’, ‘Can you describe a time when you think the team/organisation performed really well?’, ‘What were the circumstances during that time?’, ‘When are you most proud to be associated with the team/organisation?’, ‘What’s the best possible outcome for you; how best may organisational strengths be employed?’, ‘Who will be impacted by change in/out of the organisation; who needs to be engaged to make it work?’

These questions help to frame the intent of the AI and provide a framework for creating questions to facilitate participants’ positive engagement in the change process.

Designing an inquiry protocol

A wide range of options exist when it comes to designing an inquiry protocol that suits the context and required outcomes. These include whole system interventions (100–1,000 participants) to small-group situations, spread over single episodes or longer-term phased interventions. The AI protocol is the starting point of the ‘Discovery’ phase (‘the best of what is’, see Figure 1). Useful guidelines for framing the AI protocol include having five questions relating to the topic and designed to reflect best experiences, values, life-giving force, hopes and priorities (see Table 2). This enables participants to take the best of the past (known) into the future (unknown) and provides rich experiential and contextual data from which to identify binding themes and to collectively imagine new and exciting possibilities.

Irrespective of the size of the group, commencing the process with paired interviews is valuable. Participants are encouraged to share stories, examples and hopes with their partner. After the interview, they remain with their partner and form small groups with three or four other pairs. Each person reflects and shares their partner’s information with the small group. Together, the group identifies binding topics, compelling themes and core values with which they want to move forward.

Again, there are options with regard to the collation and sharing of data which emerges from the ‘Discovery’ phase (see Figure 1). A small group may be requested to develop a new vision relative to the topic of the inquiry or the entire group may (with facilitator support) extract themes and topics that are used to inform the second of the 4D phases, ‘Dream’ (see Figure 1) and the development of provocative propositions.

Provocative propositions

During the ‘Dream’ phase (‘imagining what might be’), participants are asked to envision results and engage in future search. Information from the ‘Discover’ phase is used as a platform to speculate on possible and desired futures for the organisation, system or team. Participants may self-select, depending on their interest and expertise, key themes which they transform into statements of strategic and social intent – that is, positive propositions that excite them, stretch them and guide them towards a preferred future. The beauty in this process lies in the connections people see and express in where they want to go taking what they really value with them.

The process provides people with the opportunity to exercise their imaginative competence based on their best experiences, their core human values, their appreciation of interdependencies and their collective goodwill. The process generates a higher order convergence, which serves to connect multiple and equally important priorities without resorting to compliant compromises, parallel and competing visions, reductionist or subversive specialisations.

Commitment to provocative propositions, a compelling, overarching ‘flagpole’ statement, or a framework of principles provides the strategic and social architecture that informs to ‘Design’ phase of the AI (see Figure 1).

Operational implications of dreaming

In the ‘Design’ phase (‘co-constructing what should be’) participants co-construct their new reality based on their articulation of direction, principles, strategic framework. Questions relate to what would be ideal, how we can make it work and what conceptual, behaviour, operational changes we need to make.

Hard work is willingly undertaken here as concept teams, project teams, task forces and working parties form voluntarily to work through ‘making it happen’. The emphasis is on practically working through the transitions required to achieve the provocative propositions. In the process, propositions may be recast, the spirit of intent may be further questioned and infinite iterations may emerge.

The essence is that a positive momentum has been generated and, underpinned by a shared ‘headset of intent’, multiple intelligences are legitimised to progress the agenda. Having been through the ‘Discovery’ and ‘Dreaming’ phases, people see where they fit, how they’re connected to and valued in the process of achieving the outcome. This generates a confidence and capacity to contribute which, in organisations today, is priceless.

Delivering and rediscovering

The 4D cycle evolves through ‘Design’ to the ‘Deliver’ phase (‘sustaining, learning, adjusting’, see Figure 1) as participants affirm their achievements. Reflection on key measures of effectiveness, ways of knowing, recognising and acknowledging what has been achieved are encouraged.

Simple scorecards with key performance indicators linked to original propositions may be tabled and endorsed. New quantitative and qualitative benchmarks may be proposed so participants progressively validate their improvements. Positive shifts in strategy, structure and culture are marked and used to inform new questions and conversations as the 4D cycle is revisited for ongoing planning and review purposes.

What’s so special about AI?

For those of us involved in working with groups, large and small, in turbulent contexts where, increasingly, we experience the diminishing marginal returns of traditional practices, AI offers a new dimension in OD consulting.

The approach, principles and model provides an integrating framework within which multiple strategies, tailored to context may flexibly be applied. More fundamentally, as OD practitioners, change agents and leaders we are encouraged to acknowledge our own assumptions about professional practice and embody the spirit of AI in our lives.

Appreciative Inquiry is not a technique; it cannot be applied as a mechanism for change, it cannot be contrived. The approach requires willingness on behalf of the advocate and the client to search systematically for possibilities and potential, and to provide scope for diversity and synergy to co-exist in the pursuit of collective interest based on mutual understanding.

The potency of the approach lies in the frames of positive inquiry and the realisation that change and inquiry are simultaneous. A genuine curiosity, preparedness to listen and relentless reframing of issues into opportunities is grist to the appreciative inquiry mill. The outcomes are sweet in terms of participant generated, positive and sustainable change.

Examples and Results

In Australia, we have used AI extensively in government, in the higher education sector, in schools, with community organisations and in professional service firms. Effectively, it has provided an energising and participative dimension to complex planning, supporting structural changes, working collaboratively across business units, engaging communities and external stakeholders in matters ranging from policy development to resource allocation.

Results have been achieved in terms of improved service cultures, structural realignment without industrial disputation, community renewal projects, integrated government service delivery, reduced costs of duplication and in-house competition, school-based management, resolution of cultural conflicts.

Conclusion

We are convinced that the AI approach to change is suited to environments characterised by impermanence, turbulence, multiple and competing agendas, ideological diversity and cultural conflict. AI offers hope and space for participants to influence and determine their preferred future. The connections between macro and micro strategies, strategic and operational matters and individual fit within the system become clear. The approach generates focus, creativity and goodwill. These capacities are self-sustaining, build adaptive competence and sustain complex systems in change.

Reference

1. Job instruction, behaviour modelling, action learning, project management, coaching, mentoring, problem-based learning, business planning, change management, team development, network management, visualisation theory, imaging, futuring, scenario planning and so on.

Bibliography

G R Bushe, ‘Advances in Appreciative Inquiry as an Organization Development Intervention, Organization Development Journal, 13 [3] (1995), pp 14–22.

D L Cooperrider, ‘ Introduction to Appreciative Inquiry’, in W French and C Bell (eds.), Organization Development (5th ed) Prentice Hall (1995).

D L Cooperrider, ‘The ‘Child’ As Agent of Inquiry’, Organization Development Practitioner, 28 [1, 2] (1996), pp 5–1 1.

D L Cooperrider, ‘Resources for Getting Appreciative Inquiry Started: An Example OD Proposal’, Organization Development Practitioner, 28 [1, 2] (1996), pp 23–33.

K Gergen, K, The Saturated Self Basic Books (1991).

S Hammond, The Thin Book of Appreciative Inquiry. Plano, TX, Thin Book Publishing (1998).

Hammond and Royal (eds) Lessons From the Field: Applying Appreciative Inquiry Plano, TX, Practical Press, Inc. (1998) and Distributed by Mellish & Associates in Australia.

Mellish & Associates website http://www.mellish.com.au Appreciative Inquiry resources (1999).

L Mellish, Progressive reflections on Doctorate of Education research: An appreciative inquiry into organisational change and consultancy practice ,Poster session presented at The Australian Association for Research in Education Conference December Brisbane (1997).

L Mellish and B Limerick, Reclaiming our imaginative competence Paper presented at Australian Human Resources Institute National convention May Brisbane (1997).

S Srivastva and D Cooperrider, Appreciative Management and Leadership Williams Custom Publishing, Ohio (1999).
R Zemke ‘Don’t fix that company’, cover story Training US June 1999.

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