As an Agile trainer with years of experience helping nonprofits maximize their impact, I’m always excited to discover tools and techniques that empower organizations to achieve their missions more effectively. Recently, our team at Agile in Nonprofits had a fun experience testing the use of Artificial Intelligence (AI) to generate an A3 report, a structured problem-solving document rooted in Lean methodologies. The results were truly insightful, highlighting the potential for AI to help streamline and enhance your problem-solving processes.

 

First, AI Aside, Why Create an A3?

Efficiency. At its core, an A3 is a one-page report that visually summarizes a problem, its analysis, proposed countermeasures, and action plans. It’s a powerful tool for structured thinking and clear communication, enabling teams to distill complex issues into a concise, actionable format. An A3 typically guides you through several key sections:

• Background/Theme
• Current Condition(s)
• Desired Condition(s)
• Analysis (often including the “Five Whys”)
• Proposed Countermeasures, Plan, and Follow-up

The beauty of the A3 lies in its structured approach, parsing aggregate details to encourage deep understanding and collaborative problem-solving.

 

Second, Why Use AI to Draft my A3?

Time. The power of AI in A3 creation lies in its ability to significantly speed up the process. Whereas traditional A3 creation involves manual input and facilitation, using AI allows for rapid generation of a basic draft from a transcript or other document.

Facilitating an interpersonal “Five Whys” session typically takes about an hour, but with AI, no session is required, so it’s considerably faster. Of course, AI isn’t perfect, and human oversight and refinement remain essential for nuanced understanding.

 

How We Constructed Our AI-Powered A3 Experience

Details. Our recent experiment involved using AI to generate an A3 based on a transcript of a team conversation. A team member copied our entire meeting transcript into an AI tool and typed a prompt requesting the generation of an A3 based on the meeting transcript into the tool.

One key aspect of an A3 is its visual layout, with the left side focusing on the analysis of current conditions, problem analysis, and improvement goals; and the right side focusing on proposed countermeasures, results, and follow-up.

 

What Our AI Prompt Included

We worded the request in the AI tool as follows:

 

Acting as a Lean A3 expert, based on the transcript of this meeting, create an A3 for the most important problem we discussed. I want it structured as follows:

 

Left Side of A3:

Problem statement: 1-2 sentences that include the 5 Ws – what, why, when, where, who

Current conditions: Do not duplicate information in the problem statement

Analysis: A 5 Whys root cause analysis

Desired Condition: What it would look like when the problem is solved

 

Right Side of A3:

Proposed countermeasures: Steps to solve the problem

Results: What metrics we should look for

Follow-up: Standard work we would put in place to keep the improvements

 

What a Hypothetical A3 Might Look Like: Improving Volunteer Onboarding

Let’s consider a hypothetical A3 as an illustration. 

 

Left Side

Problem Statement: A nonprofit, the fictional “Community Gardens United,” is experiencing a high dropout rate for new volunteers within their first month.

Current Condition: Community Gardens United observes that 40% of new volunteers do not complete their first month of service. This results in increased administrative burden for recruiting and training, and a diminished pool of active volunteers for ongoing projects.

Analysis (with AI’s Five Whys): An AI-generated A3 might surface insights like: 

• Why are volunteers dropping out? Because they feel unprepared or unsupported.
• Why do they feel unprepared? The initial orientation is overwhelming and lacks practical application.
• Why does it lack practical application? It’s a generic presentation and not tailored to specific roles.
• Why is it generic? Because the onboarding process hasn’t been updated in years.
• Why hasn’t it been updated? Because the staff are too busy with day-to-day operations.

Desired Condition: Improving new volunteer retention and engagement.

 

Right Side

• Countermeasure: Develop role-specific onboarding modules, including hands-on activities.
  • Result: New volunteers gain practical skills and confidence, leading to a 20% reduction in dropout rate within 3 months.
• Countermeasure: Implement a “buddy system” where experienced volunteers mentor new ones.
  • Result: Increased sense of belonging and support for new volunteers, improving retention by an additional 10% within 6 months.
• Countermeasure: Digitize onboarding materials and create an accessible online portal for resources.
  • Result: Volunteers can review information at their own pace, reducing information overload and improving initial understanding.
• Countermeasure: Schedule a monthly “Volunteer Check-in” meeting for new volunteers to ask questions and provide feedback.
  • Result: Early identification and resolution of volunteer concerns, fostering a more supportive environment.

 

This example demonstrates that an AI-generated A3 can be an essential and powerful “toolbox” addition for you. It provides a structured starting point, reducing the time and effort traditionally required for initial problem framing. As a result, nonprofits can quickly identify and address challenges, freeing up your valuable resources to focus on your core mission: creating twice the impact in half the time.

 

Intriguing, isn’t it? What we found is that sometimes, letting AI be an “assistant” in our usual brainstorming or problem-solving processes helps to bring new ideas or themes to light. Have you done the A3 exercise before? Have you tried an AI-assisted A3 exercise yet? We’d love to hear if you try it – how did it go? What did you like? What did you learn?