Wabi Sabi Learning for a Complex World

Adapted from a presentation given at the Canadian Evaluation Society BCY Conference in November, 2014 by Ben Kadel and April Struthers.

The Japanese have a concept called wabi-sabi. It’s sometimes described as the beauty of things that are imperfect, impermanent, and incomplete. It refers to objects that grow more beautiful over time, as experience adds to their value — think of cathedral steps slowly carved by generations of pilgrim’s steps or the beauty of morning dew before the heat of a summer’s day.

Wabi sabi learning offers the best chance for gracefully navigating the complex, confusing world we all work in today. Wabi sabi learning embodies the messy elegance of real learning — elegant because simple processes repeated over time yield dramatic results, but messy because it forces us to confront our limitations. Wabi sabi learning gives us the ability to turn imperfections into beauty.

For many of us, conventional ideas about training and careers just don’t make sense anymore. The old model says you pick a career and then you get trained. Experts figure out the right way to do things and put it in books that the rest of us digest and follow. But the rate of change is just too great. Most of the specialized training we received in school just doesn’t apply anymore and we wake up facing situations that no one could have predicted, let alone “train us” to respond to.

That’s certainly the case for us. Somehow we woke up one day to discover that we were professional evaluators. I can assure you, when I was in elementary school and people asked me “what do you want to be when you grow up” not once did I say “an evaluator.” I wanted to be an architect and April wanted to be an archaeologist. But after multiple careers and unexpected twists along the way, we found ourselves doing evaluations.

Luckily, along the way (and pretty much by accident), we figured out a robust process for learning that works without text books or “best practices.” So, how did we do it?

Basically, we were the kids who just kept taking things apart to see how they work; we kept asking “why.”

And that curiosity continued throughout our careers. No matter what kind of project we were working on, we kept asking questions. Why were we seeing what we were seeing? Why did things work the way they did? And, more importantly, why didn’t they work sometime?

So we kept asking questions — often really uncomfortable questions… like “what are you actually trying to accomplish here” and “how will you know if you’re on the right track?”

At some point we figured out that we were actually scientists and had accidentally developed our own version of the scientific method applied to everyday life — our own wabi sabi way of learning.

Science at its core is really just a learning process that tries to draw lessons from experience so that we can respond better in the future. It observes the world and looks for patterns. Then it tries to synthesize those patterns into theories that predict what is likely to happen in a particular situation.

Of course, this is pretty much what all humans do and it is just as likely to give rise to superstition as to real learning.

The problem is that we humans have limited perspectives and some known biases that make it hard for any of us to get the whole picture. One of the biggest challenges is the confirmation bias — the fact that we don’t so much believe what we see as see what we believe.

The difference between what most people do and wabi sabi learning is that real learning doesn’t stop asking questions just because you have a theory that sounds good. The trick of science is that it turns the confirmation bias on its head. It attempts to test and disprove its own assumptions. It tries to break the model to see if the model actually works.

It does this by making predictions based on our theories and then running real-world trials to see if the prediction holds. Then it uses the results to refine and revise its assumptions and theories, rather than rejecting information that challenges our beliefs.

We can apply this same logic to everything we do and create rich opportunities for deep learning in virtually any situation. All that is required is that we clarify our expectations about how the work we are doing will actually lead to the outcomes we are hoping for, then determine some reasonable indicators and establish some targets to help track real progress. The trick is that we must actually use that experience to reflect on what actually happened to figure out what worked, what didn’t and how we can refine our logic models to do better the next time.

Done well, this simple process has the potential to create real innovation and increase the capacity, impact and effectiveness of the entire organization.

At least, that’s how it’s supposed to work.

The problem is there’s a big difference between what science actually is and what most people think it is. We call this common misunderstanding ‘scientism’ — a fantasy that science is the ability to prove things; to have all the answers. Scientism is all lab coat, no substance.

But real science is more adventure than text book. It is an ongoing quest to learn from experience and test assumptions. Scientism, on the other hand, is a comfortable lie about certainty.

And it’s the illusions of scientism that keeps us from real learning . To enter into the messy elegance of wabi sabi learning, we have to abandon the comfort and safety of “scientism” and enter into the courageous adventure of real science.

  • Real science is about asking good questions and being open to surprise. Scientism is about certainty and facts.
  • Real science is a dynamic process of learning from experience, even when the experience isn’t what you hoped it would be. Scientism is about trying to get an “A” on the test.
  • Real science is about exploration and it’s frequently uncomfortable. Scientism tries to make everything safe and (ironically) ends up focusing on assigning blame and credit.

Real science happens in an uncomfortable place just beyond the comfort zone but before the freak out zone. The comfort zone is the place where the confirmation bias lives. We bend over backwards to avoid anything that might upset our expectations. But the freak out zone is equally dangerous to learning as people simply shut down, fight back, or run away.

So, what can we do in positions with limited resources and power? We have to recognize the value of the growth edge and be able to take our colleagues and clients into the discomfort zone without letting them freak out. In other words, you need to develop the trust of your project partners.

Generally speaking, research focuses on three core elements of trust: integrity, capability, and alignment.

  • Integrity is simply the ability to say what you mean and mean what you say.
  • Capability is a confidence that you can actually deliver on what you are promising.
  • Alignment is a confidence that our interests are aligned — that you are working with me rather than against me.

And developing trust takes time and effort. Trust is a continuous variable that can be grown over time.

In practical terms, this means that we need to do three things: inoculate, iterate, and demonstrate.

Psychological inoculation is like being a tour guide of the experience. You are giving people a little head’s up about what they might experience in a given situation.

By letting people know that there might be some discomfort coming up, you do a number of things.

First, you normalize the experience. You let people know that discomfort doesn’t mean anything is “wrong.

You also make it possible to talk about and address the discomfort as it arises.

Also, being courageous by talking frankly about the sources of discomfort in learning and evaluations demonstrates true integrity to project partners.

And you can use inoculation to ask people to be courageous; and recognize it in them.

The second practice, iteration, is simply breaking a big scary goal into small, manageable steps that you can repeat to build something bigger and more important.

The growth edge is always a moving target and, hopefully, an increasing capacity. So like any muscle that hasn’t been used for a while, you will want to start small but work consistently. In the end, it’s more important to go to the gym regularly, than to try to lift heavy weights once a year.

Some of the muscles you are growing in your colleagues are a tolerance for ambiguity, a healthy sense of curiosity, and the ability to stand the discomfort of maybe being wrong. By taking project partners through small, relatively safe experiences of stepping into the discomfort of the growth edge and then reaping the reward of discovery, you can actually unleash a real desire in the team for the excitement of exploration.

And at each phase of the project and with each iteration, focus on demonstrating the value of the learning from the perspective of project partners.

Look for challenging decisions that partners need to make where actionable data can help them solve a problem.

When gathering data, look for ways in which early feedback can support project delivery rather than waiting for a “big reveal” after the work is already done.

And in the analysis, focus on realistic concrete recommendations that will make your project partners look like heroes to their stakeholders.

Ultimately, we believe that the greatest potential we have as evaluators is as trusted learning partners, and to do that we need to understand the messy, uncomfortable experience of real learning.

It isn’t enough for us to be technically competent, we have to understand the emotional experience that we are taking our partners through and support them in that adventure.

We have to remember that the greatest impact we can have lies more in a way of thinking than any particular technique or process. We need to encourage our partners to come with us into the discomfort zone where real learning and real discovery happens and that means that we have to be courageous ourselves and earn the trust of our partners to let us take them there.

Part of that courage comes from recognizing that we aren’t the only experts in the room. We have access to loads of expertise. Our main challenge is finding ways to bring out the expertise in ways that both supports and challenges our partners — of testing the elements so that the truths can emerge from a mess of beliefs and misperceptions.

When we do that, we will discover the real power of messy elegance — the ability to take people through a process that is elegantly simple, where simple questions yield powerful discoveries. But we have to be willing to step into the messiness of working outside the comfort zone.

Practically, that means we need to:

  • inoculate — to make it safe to step into discomfort and encourage our partners to come along.
  • iterate — to break big scary things into challenging yet manageable bite-sized experiences that begin to grow the exploration muscle.
  • demonstrate the value of what we do at every step of the process.

And, of course, before you can do this effectively with others, you need to be able to do the same thing with yourself. Challenge your assumptions and be willing to step into that uncomfortable place where learning actually happens.

Ask yourself:

  1. What are some assumptions you are making about your projects?
  2. What if the opposite were true?
  3. How could you start to test your assumptions — not just confirm them?
  4. At the end of the day, how could you use real-world feedback to improve the work you do?

We would love to hear about your experience with wabi sabi learning and the important lessons you learn by simply comparing your expectations with your experience as a way of challenging your own confirmation biases.

Changing the way you feel about work.