The problems worth solving are all wicked!

In the real world, the problems we face can be roughly divided into two categories. Some are tame. Tame problems are simple and easy to analyze and categorize. Figuring out how to use an Excel function to perform a calculation is a tame problem. It may look hard, but it is actually pretty straightforward. Overcoming tame problems is generally a matter of perfecting a discreet skill or executing a relatively clear set of instructions, and increasing competency is mostly a matter of repetitive practice.  It is easy to train people to handle tame problems.

In contrast, some of the problems we deal with are wicked. Wicked problems are complex, hard to analyze and hard to categorize. Figuring out how to use the full range of Excel’s functionality to support the planning and execution of a market entry strategy is a relatively wicked problem. It isn’t just a matter of mastering Excel. You need to learn about the levers of market strategies, learn specifically about how those levers work in the market you are trying to enter and probably a variety of other things before you even start considering how to use Excel to support that strategy.  While it is easy to train someone in the tame skill set required to use Excel, it is not as easy to train someone in the wide range of skills and perspectives necessary to create a market strategy. The complexity makes the creation of market entry strategy a wicked problem.

One of the great challenges in the learning professions is that while it is easy to design training for tame problems, it is not as easy to design training for wicked problems. Tame problems can be solved in isolation.  You can solve them alone or with a teacher who knows the procedure for solving them.

There often is no simple step-by-step procedure that can be applied in a repetitive manner to solve a wicked problem, so wicked problems call for an alternative approach to learning. To solve wicked problems you often need to search broadly and deeply access multiple data sets and diverse perspectives or disciplines. Then you need to organize the data in novel ways to help you frame the problem and ideate solutions. Sometimes, you may not even have a clear sense of what the problem is until you begin experimenting with ways to address the symptoms.

The ambiguity of wicked problems can be daunting, but it also opens up new pathways to learning. If training alone isn’t the best way to learn to solve wicked problems, what might be better? Why not start by taking advantage of all the opportunities we have to learn in the wild world of real work?

Science and technology have enabled us to isolate problems and conduct controlled experiments. Based on these experiments we are able to engineer solutions to problems that we couldn’t even imagine in past centuries. In many domains – medicine being an obvious example – the discipline of laboratory research enables us to maximize the benefits of learning how to solve a problem while minimizing harm that might result from experiments gone awry.

However, we face many situations in which experimentation might be useful, but we don’t have the time or resources to isolate the problem in a laboratory. Moreover, there are many problems that can never be solved in the lab; they can only be solved in a real world context. These problems call for experimentation in the real world.

The real world is messy. In hospitals around the world, as the corona crisis emerged, hospitals in hot spots found that the protocols and supply chains they had built up over many years were not sufficient or appropriate for the challenges of broad testing and treatment of this rapidly spreading virus. The people on the front lines could not afford to wait for someone to conduct a laboratory experiment on how to deal with this new threat. They began their own real-world experiments to address gaps in supplies and protocols. They engineered solutions to shortages of PPE, equipment and facilities that were not designed for a pandemic. They took proactive steps to protect the lives of their patients, their colleagues and themselves. They shared what they learned with each other and colleagues in other hospitals so more people could benefit from the learning.

Thankfully, everyday life does not usually present most of us with challenges that are as overwhelming as working in an emergency room or intensive care unit during a pandemic. Still, even our mundane work lives are filled with an unending series of opportunities to conduct real-world experiments, and some of those experiments might lead to insights that could be leveraged for both individual and collective benefit.

Organizations with a learning-friendly environment are more likely to enjoy the learning and impact of real-world experimentation. It helps if someone in the organization intentionally and consistently:

  • encourages people to keep an eye out for these opportunities (which are often first noticed in the form of problems),
  • creates an environment in which it is safe to openly discuss these problems and ideate approaches that might address them,
  • provides support for people so they can conduct experiments to convert those problems into opportunities, while controlling risks in case the experiments don’t go as hoped,
  • establishes a process for reflecting on the results of those experiments so we can figure out what worked and what didn’t, and
  • facilitates forums where the most promising examples can be shared and applied to broaden learning and impact.

Over the years, my colleagues and I have conducted many experiments in how to establish conditions that maximize individual and organizational learning in the real world. Based on these experiments, we have formulated a workplace learning methodology we call Collegial Action Learning.

Collegial Action Learning puts the learner’s real challenges and opportunities at the center of learning design. Rather than starting with a solution and then searching for a problem to apply the solution to, we start with the real problems our clients face and work backward to help them find solutions they are willing and able to turn into real-world experiments. By starting with real problems and staying focused on real problems, CAL helps both learners and organizations learn more and convert that learning into results more quickly.

There is no doubt that laboratory research and traditional training are fantastic drivers of learning. When we are dealing with a well-defined problem that is easily broken down into a consistent set of parts, laboratory research is probably the best path to developing a solution. When we need people to learn a skill that can be broken down into a set of procedures that can be executed repeatedly to solve a relatively tame problem, traditional training is probably the way to go.

The reality, for most of us though, is that we are not dealing with these kinds of problems. Even the simplest of real world problems often involves a variable and evolving set of factors that make laboratory research and traditional training impractical options.

CAL is a learning design that helps people learn in the real world to solve the wicked problems that make the real world frustrating and interesting.


What is Collegial Action Learning?

Collegial Action Learning is a learning design that drives learning through rapid cycles of planning, experimentation and reflection. CAL posits that people learn as much if not more from experimentation and experience than from the teaching of experts. CAL combines individual experimentation with collaborative reflection and ideation to close the gap between learning and results. In an CAL initiative, professionals help each other refine and test their ideas so that everyone emerges better equipped to address real world challenges that are meaningful to the individuals and their organizations.

For more information on how to get ready for a Collegial Action Learning initiative see: Design Autonomy, Purpose and Meaningful Connections into Action Learning Initiatives.

For more information on what the flow of a kick-off session looks like see: Kicking Off a Collegial Action Learning Initiative – Start with real world interests, problems and priorities


For an exploration of wicked problems and related concepts:                Range:  Why Generalists Triumph in a Specialized World“, Chapter 2, “How the Wicked World was Made”

For an exploration of the concept of natural experimentation, a concept that shares traits with CAL, see: What Coronavirus Researchers Can Learn from Economists, By Anupam B. Jena and Christopher M. Worsham,, 6/30/2020

For an description of how doctors and nurses “learned on the go” by conducting rapid experiments to find ways to make the most of limited resources and help them cope with the demands of the emerging coronavirus crisis, see: A Brooklyn ICU amid a pandemic: patients alone, comforted by nurses and doctors, by Lenny Bernstein and Jon Gerberg, (April 5, 2020) @

For a great story about a high school student who decided to get his friends together and take a crack at solving a wicked problem that has been stumping adults, see:

Georgia Teens Create Company To Print And Deliver PPE To Health Care Workers on Weekend Edition Saturday @

Figuring out how to create a learning organization has been one of the Holy Grails in the field of adult learning research for the past 50 years. The following article summarizes many of the conditions necessary for the establishment of a learning organization. CAL starts the process of establishing many of these conditions. See: Is Yours a Learning Organization? by David Garvin, Amy C. Edmondson, and Francesca Gino, Harvard Business Review, March 2008

The concept of the learning organization owes much to the thinking of 20th century American philosopher and educator John Dewey. He advocated for broad application of the scientific method to improve educational experiences and results. The combination of self-driven experimentation and collegial reflection were pillars of his approach. See: On education and teacher education @

Gary Hamel provides a nice introduction to the principles of experimentation @:

© Dana Cogan 2020, all rights reserved.

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