* Information provided by the Applied Improvisation Network’s (AIC) Delphi Study (learn more here).

Introduction to the Delphi Study Method

A Delphi study is a structured method designed to harness expert opinions to reach a consensus on a specific issue. It involves multiple rounds of questionnaires, with each iteration refining and focusing the responses based on the analysis of earlier rounds. This approach helps clarify collective viewpoints and narrow down diverging opinions.

Overview of AIN’s 2014 Delphi Study

In 2014, the Applied Improvisation Network (AIN) conducted a Delphi study to define key concepts and practices in Applied Improvisation (AI). Participants included experts who met rigorous criteria including significant experience in AI training and contributions to AI literature. The study unfolded over three rounds, each designed to delve deeper into the facets of AI.

Key Outcomes of the Delphi Study

Shared Definition of Applied Improvisation:

Applied Improvisation is the application of improvisational theater’s principles, tools, and mindsets in non-theatrical settings, enhancing personal development, team building, creativity, and innovation.

The Non-Linear Process of Applied Improvisation

1. Teaching/Demonstration: Introducing the skill through direct instruction or demonstration.

2. Experiential Application: Participants actively engage with the skill in a real-world or simulated context.

3. Reflection/Debriefing: Participants reflect on their experiences to derive new insights and integrate learning into other areas of their life or work.

Top 10 Elements of Applied Improvisation

1. Making your partner look good.

2. Embracing the “Yes… And” philosophy.

3. Cultivating an atmosphere of play.

4. Engaging in curious listening.

5. Practicing complete acceptance.

6. Enhancing flexibility and spontaneity.

7. Focusing on the here and now.

8. Encouraging risk-taking.

9. Developing personal awareness and mindfulness.

10. Balancing freedom with structure.

Core Themes and Discussion Points in Applied Improvisation

– Implicit vs. Explicit Use of AI: Is our use of AI intended to be recognized and named, or are we incorporating it more subtly? This affects how AI is marketed and discussed within facilitation styles.

– AI Mindset: Integrating improvisational principles into daily life, maintaining presence, and supporting acceptance are crucial for embodying an AI mindset.

– Safety vs. Comfort: Establishing a safe environment is essential for effective AI practice, though the level of comfort may vary. Safety strategies include clear communication about the process and adjusting     the risk level of activities.

– Planning/Structure vs. Freedom: Effective AI facilitation involves careful planning yet remains adaptable to the needs of the participants in real-time.

– Experience Levels: The facilitator’s experience significantly impacts the balance between structured planning and in-the-moment freedom.

– Goal Setting and Achievement: Clearly defining and agreeing on goals with clients ensures alignment and measures the success of AI activities.

– Surprise and Discovery: While surprises may occur during activities, insights and discoveries are often facilitated during debriefs and reflections.

– The Role of Fun: Fun is frequently a central element of AI, enhancing engagement and learning, though opinions vary on its necessity.

* This study reflects a growing consensus on AI’s definition and its applications but also highlights areas of ongoing debate such as the necessity of safety measures, the balance between structure and flexibility, and the distinct identity of AI from other forms of improvisation. This evolving dialogue continues to shape the AI community and its practices, aiming for a deeper understanding and more effective application in diverse contexts.

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