Facilitating Learning Events

TL;DR:

Facilitating Learning Events: Balancing Process, Flexibility, and Curiosity for Real Insights

These days, if you’re in safety, operations, or any performance-driven field, you’re likely hearing a lot about Learning Teams, Root Cause Analysis (RCA), and Failure Modes and Effects Analysis (FMEA). Each one has a different way of guiding groups towards insights, but they all share one core goal: to help us learn as a team so we can handle complex issues better in the future.

I recently had the chance to dive into these methods in a webinar with Larry Sauber, a safety professional from a major oil and chemical company. We explored how facilitators can make these learning events more effective by focusing on one essential thing: learning itself. You’d think that would go without saying, but all too often, facilitators get hung up on following a rigid process instead of letting real insights emerge.

In this piece, I’ll break down some key points from that conversation, along with a few extra thoughts—like the role AI can play in team-based learning. (We didn’t talk much about AI in the webinar, but I think it’s worth including here as another way to enrich our understanding.)

Putting Learning First, Process Second

When you’re leading any kind of team-based analysis—whether it’s a Learning Team, RCA, or FMEA—the facilitator’s main responsibility is to foster genuine learning, not just push people through a set process. Sure, structure has its place. It keeps things on track, makes sure we cover the basics, and helps us avoid overlooking key details. But if we become too focused on process, the whole purpose of the event—learning—can get lost.

What makes a great facilitator is the ability to be resilient and flexible. They know when a process can add value and, just as importantly, when it’s better to set the process aside and explore ideas more freely. Think of a facilitator like a conductor in an orchestra: they guide the musicians (or, in our case, team members) to bring their unique perspectives to the table, and together they create something valuable and complete.

Why Teams Are Better Than Going Solo

One thing we all agreed on during the webinar is that a diverse team will almost always bring more to the table than an individual working alone. Each person contributes a unique perspective shaped by their background, role, and experience, which helps reveal different sides of a complex issue. Whether we’re talking about a Learning Team or an RCA, bringing more “eyes” onto the problem makes it easier to catch blind spots and develop more creative solutions.

The facilitator’s role here is to make sure everyone’s voice is heard, which can mean actively inviting quieter members to contribute or balancing out the more vocal participants. When you have that range of viewpoints in the mix, you get a fuller, more robust picture of the problem—and, ultimately, better solutions. Plus, it’s a natural fit to add AI to the team. Think of it as another “perspective” that adds data-driven insights to the human perspectives in the room.

AI as an Extra Set of Eyes

Now, we didn’t get into AI specifically in the webinar, but it’s worth mentioning because it can play a valuable role in team-based learning. With AI, you have a tool that can process massive amounts of data, spot patterns, and identify trends that might not be immediately obvious to the human eye. In an RCA, for instance, AI can help surface connections between equipment failures across sites, adding another layer of insight that helps the team dig deeper.

AI’s value isn’t just in the raw data it can provide. It also adds “contextual diversity” to the team—another viewpoint that complements human judgement and can help the team see the problem from different angles. When a facilitator integrates AI into the team’s process, it’s like having an extra set of eyes (that just happen to be really, really good at spotting patterns).

Navigating Complexity with Curiosity

One of the big takeaways from our discussion was the importance of curiosity in facilitating these learning events. Curiosity keeps the conversation open and focused on exploring possibilities rather than pushing the team towards a single conclusion too quickly. Larry summed it up well when he said, “Curiosity is mandatory for facilitators in Learning Teams.” That’s because, in a complex problem, it’s easy to get tunnel vision, focusing on one part of the story and missing the bigger picture.

For example, if we’re trying to understand why there are so many alarms in a control room, a curious facilitator might ask, “What’s a typical day like for a control room operator?” That question could lead the team to insights about system design, workload, or even cultural factors in the workplace that contribute to alarm fatigue. The best facilitators stay open, exploring conditions and contributors until the picture comes into focus.

Knowing When to Blend Methods

Each approach—Learning Teams, RCA, FMEA, and others like 8D Problem Solving—brings its own strengths. RCA is fantastic at starting with an event-based outcome, like an injury or a system failure, and reverse-engineering the causes and context that led to it. This reverse-engineering process allows the team to dig into contributors and conditions, taking them beyond a linear view of cause and effect to a more nuanced understanding of the situation.

With Sologic RCA, for example, we avoid limiting ourselves to a straight line from cause to effect. Instead, we look at contributors and conditions, which lets us get a sense of the bigger picture. Often, as we dig deeper, we start to see systemic issues like “inexperienced work teams” or “schedule pressure.” At this stage, switching to a Learning Team approach—where the conversation is more open and less structured—can be really helpful. This lets the team explore what works, what doesn’t, and what it takes to build resilience in a challenging work environment.

A Few Practical Tips for Facilitators

From our discussion, here are a few tips that can help facilitators guide the conversation in a productive direction:

• Ask open-ended questions. Questions like “What was your day like when this incident happened?” help people share stories that reveal important details.
• Encourage balanced participation. Make sure everyone has a chance to share insights, and manage the conversation so quieter voices are heard too.
• Adapt on the fly. If an unexpected insight comes up, be ready to dig deeper rather than steering the conversation back to a strict agenda.
• Combine methods when it makes sense.  For instance, you might start with FMEA to map potential risks, then shift to a Learning Team discussion to explore the context around those risks.

The Takeaway: Learning Comes First, Process Comes Second

Each approach—Learning Teams, RCA, FMEA, and others like 8D Problem Solving—brings its own strengths. RCA is fantastic at starting with an event-based outcome, like an injury or a system failure, and reverse-engineering the causes and context that led to it. This reverse-engineering process allows the team to dig into contributors and conditions, taking them beyond a linear view of cause and effect to a more nuanced understanding of the situation.

With Sologic RCA, for example, we avoid limiting ourselves to a straight line from cause to effect. Instead, we look at contributors and conditions, which lets us get a sense of the bigger picture. Often, as we dig deeper, we start to see systemic issues like “inexperienced work teams” or “schedule pressure.” At this stage, switching to a Learning Team approach—where the conversation is more open and less structured—can be really helpful. This lets the team explore what works, what doesn’t, and what it takes to build resilience in a challenging work environment.

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