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  • Keith Hopper

The key to helping others see and experience the benefits of a Learning Loop is to guide them through a small initial loop of their own and use structured questions to encourage effective loop design and meaningful reflection.

Effective Learning Loops consist of four deliberate steps: Planning, Doing, Checking and Adjusting.

Planning: Determining where you’re uncertain - particularly on project next steps or around an idea you’d like to try, or simply an area where you’d like to get smarter.

Sample coaching questions:

  • Where are the uncertainties you’re currently facing with the project - for example, thoughts about how to proceed that are untried or untested, or a lack of clarity on how to achieve your desired outcomes.

  • “What do you have to do next on this project and what’s holding you back? Is there an area where you’re stuck or where the next step is unclear or unproven? A problem you’re trying to solve?”

Doing: Identifying and executing on a meaningful effort to try.

Sample coaching questions:

  • What's one small thing you might try next to help you learn?

  • What specifically might you do with your target user/customer to better get at the truth? Is there something you might show them to get feedback on, or ask them to commit to?

  • What are you hoping to learn by running your loop?

Checking: Pausing and objectively reflecting on what was learned.

Sample coaching questions:

  • Where has your understanding changed? What do you know or believe now that’s different from when you started your loop?

  • What surprised you?

Adjusting: Ask yourself how you should respond differently now that you have new knowledge.

Sample coaching questions:

  • What does this mean for you moving forward? What will you do differently moving forward?

  • How might you make the next loop smaller, faster, easier or more creatively reveal the truth behind your uncertainty?

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  • Keith Hopper

When trying to figure out if an innovative idea is going to work, it's common to see the situation as pretty straightforward and not question our current understanding. Turns out, there’s a weird human quirk that explains this called the “illusion of explanatory depth.”

Simply put, the illusion can be described as: thinking we understand something when we actually don’t, and it’s particularly strong when we’re faced with something conceptual or nuanced, like a thorny business problem or a novel solution approach.

Researcher Rebecca Lawson designed an experiment to highlight this phenomenon. She asked subjects to draw a picture of a bicycle, showing how it works - connecting all the bits in the way they should be connected. Turns out very few people could do it correctly, yet virtually everyone claimed to understand the way a bicycle works before they were asked to actually explain how it works.

When first imagining an innovative solution to a tough problem, we typically don’t invest in trying to learn more, because - like the bicycle - we simply don’t recognize that our understanding is limited.

In the case of a novel innovation, the problem and solution appear to be straightforward because we’ve never encountered it before in a way that exposes the critical elements, the key subtleties and the characteristics that matter. We haven’t had our illusion questioned. And when our illusion isn’t questioned, we run the risk of thinking we have all the answers and blazing forward with a mistaken approach.

The secret to overcoming the illusion of explanatory depth is to confront ourselves early with assumptions that might lie behind the problem and solution - how do we know the problem is important enough to solve? Are we targeting the right customer? Will users embrace our solution approach?

Even better, run a small test that reveals new information we didn’t know earlier. This new information can challenge our early explanation and show us that our understanding is limited.

Like being confronted with a sketch of a bicycle that doesn’t make sense, new information can shatter our illusion of deep understanding.

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It can be difficult to introduce learning activities like Continuous Discovery into a project once it’s underway and racing towards a deadline. Stakeholders can feel overly confident the current project direction is correct, and any new information that is gathered might threaten the timeline or worse, their opinion as to what should be built.

To address this, you might consider introducing what I call Learning Swimlanes.

A Learning Swimlane is a process that runs in parallel to a project or product launch, focusing on gathering information and insights about users as they are first encountering the new solution. It uses planned observations and interventions to ensure that the team is able to learn from the new customer experience, developing meaningful insights that can help answer key questions and explain successes as well as issues and barriers as they emerge.

Ideally, Learning Swimlanes are set up and run alongside the work the core team is doing to execute and launch the new project and avoids distracting the core team from launch. This parallel approach facilitates buy-in on integrating a swimlane and helps ensure learning isn’t de-prioritized by firefighting post launch, when learning can be most important.

Learning Swimlanes can be particularly useful during the beta or pilot phase of a project, when there is significant uncertainty and the organization needs to maximize learning. Swimlanes can involve monitoring user behavior and support requests along with connecting directly with users to gather insights through activities like qualitative interviews, spot surveys and requests for feedback.

By quickly developing a holistic understanding of the new user experience, Learning Swimlanes can help identify issues early and provide a deeper understanding of what’s behind the issues - for example, why users are behaving the way they are and what project assumptions might be revealing themselves as incorrect.

By being on the ready with critical information that explains issues and addresses questions as they arise, Swimlanes can demonstrate the power of Continuous Learning vs. learning as an afterthought. This subsequently can be used to make an argument for integrating Continuous Learning and Discovery earlier in the next project’s lifecycle to avoid future issues before they arise.

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