We’re almost at the end of February and the end of the series in hearing new voices in L&D. This piece from Qian Feng is a great piece helping us to understand how to look past what are seemingly accurate problem statements and really examining the structures and systems which could be causing the issue instead. I have a bias towards systems thinking and Qian describes this really well below.
I don’t edit or amend the pieces being written for me. I’m not an editor, and that’s not something that matters for the purposes of this series. Each piece is submitted in the author’s own writing style. I’m also not fact-checking, unless there’s something that needs to be fact-checked.
Qian is a learning & development professional who is passionate about cultivating a culture of learning to unlock our collective potential. She has extensive experience building large-scale capability transformation programs for organizations in the life sciences industry. Qian just completed a Master of Design degree in Strategic Foresight and Innovation from OCAD University in Toronto. She gets excited about the intersection of learning, systems thinking, and technology. She is also passionate about helping organizations create meaningful and fulfilling work and always looking for ideas to engage people in learning.
You can connect with Qian on LinkedIn.
No Time for Learning: Are We Solving the Wrong Problem?
If you ask a typical corporate employee what is their biggest barrier to learning, you will probably hear something like “I simply don’t have time!”
According to a Josh Bersin study, “the average employee only has 24 minutes a week to learn”. And this was 2015 data. Adding 7 years of rapid digital adoption plus the unprecedented level of change and uncertainty catalyzed by the pandemic, this number is likely even smaller today.
No time for learning is one of the biggest challenges in corporate L&D today. As a L&D consultant, I hear this regularly from learners that I interview, as well as from L&D teams and leaders that I work with. Yet we know that in this time of skills gaps, the Great Resignation, widespread burnout, learning is more important than ever before.
So as L&D professionals, how do we address this challenge?
There are many great solutions that our industry has produced in the last few years. From Learning in the Flow of Work to microlearning, gamification to focusing on human-centered learning experience design, we’ve come a long way to making learning more engaging, embedded into day-to-day workflow, and digestible to meet the needs of our busy lives.
But are these solutions enough? Will we solve the problem of ‘no time for learning’ if we continue down this path?
My suspicion is no. Why? Because I’d like to think that ‘no time for learning’ is not the problem, it’s a symptom of many underlying problems in our work and organizations today. Unless we solve the fundamental problems that’s causing the lack of time for learning, our efforts will likely fall short to create long-term outcomes that we’re hoping for.
To illustrate this point, let me share a quick story.
Sometime in the 1800s in India, there was a problem: there were too many poisonous cobra snakes on the streets of Delhi, their population was growing rapidly and becoming a danger for people. So the government came up with a solution. They offered a bounty for every cobra caught and killed. This incentive worked well initially and the number of cobras on the streets started to decline. However, as time went on, the problem didn’t go away—instead, the number of cobras started rising again no matter how many dead cobras were collected. Why did this happen? Turns out that people started breeding cobras in order to collect the reward. And guess what happened next? The government stopped the bounty program. Cobras were now worth nothing, so the breeders set them free, leading to more cobras on the streets of Delhi than before.
This story, known as the Cobra Effect, is commonly used to illustrate the point that we live in complex systems. And in systems, problems don’t just get solved by applying a quick ‘fix’, because cause and effect are not linear. Sometimes there are unintended consequences to a seemingly perfect fix, especially when you add the test of time. In the cobra example, putting an incentive on catching cobras actually amplified the problem. So what should have been done? The key is to understand the fundamental problems underlying the symptom. What’s causing the rising number of cobras in the first place? Fix that instead.
It’s time to add systems thinking to our L&D’s toolbox
The point of the story is that we need to dig a bit deeper on the fundamental causes behind the ‘no time for learning’ symptom. I often hear the argument that because people are more distracted than ever, and have no time for learning, therefore we need to keep learning more bite-sized, more micro. I have no problem with bite-sized or microlearning, there are many great use cases. But at the same time, could we actually perpetuate the problem?
I don’t know the answer exactly. But what I do know is that we need systems thinking in our L&D’s toolbox if we want to find out how to help people invest more time in learning (because we know that those who spend more time learning on the job are more engaged, productive, and successful than those who do not).
Systems thinking helps us do that because it’s an entirely different way of looking at problems than what we’re used to. It focuses on looking at things as a whole as opposed to a collection of individual parts. It helps us understand the dynamic and complex web of systems that we’re all a part of every day and helps us see how things influence one another both in the short- and long-term. It helps us find the root cause of problems and come up with solutions that address them.
Let’s start with this tool: the iceberg model (a.k.a. causal layered analysis)
While systems thinking is a vast and rich discipline of its own with many tools and methods that one can spend a lifetime learning, I’d like to introduce a simple tool that we can incorporate in our L&D practices.
You may have heard about it before as the iceberg model. It’s official name is causal layered analysis created by Dr. Sohail Inayatullah. It’s a technique of breaking down the driving forces behind the symptoms that we see on the surface through 4 layers of analysis as shown below.
Going back to ‘no time for learning’ as an example, this is what’s happening on the surface (the top level). Going down a level, what are the trends and changes that have occurred? One possible answer could be that people are increasingly getting burnout, overwhelmed with the amount of changes in a particular organization while keeping up with the productivity level that’s expected. Now what’s the underlying structure that’s behind this? It could be that there’s a lot of process and system inefficiencies that’s causing people to waste time navigating the systems as opposed to doing actual work or developing themselves. Or it could be that people are not finding the learning offerings from this particular organization useful for their rapidly changing role. Then going down to the bottom layer looking at the deep beliefs or values people hold in the system, we might find that there’s a lack of culture of learning at this organization. While there are many learning programs and initiatives offered, speed and productivity are valued the most and there is lack of integration of the learning mindset/culture into the day-to-day work and decision making.
The root cause of ‘no time for learning’ can be very different depending on the context of the analysis. But with using the iceberg model, we can begin to see that simply making learning more bite-sized or engaging is not enough to address the root cause of the issue. This technique can be used in various ways such as in a needs analysis, or in the design phase of a learning program to ensure we are designing solutions that address the fundamental problem.
As a L&D practitioner, I think it’s crucial that we take a systems view in our work in order to generate real and long-term impact for our learners, our teams, and our organization. And I hope the iceberg model I shared above can be useful to get us started.
I’d love to hear your feedback on my thoughts!
Thinking About Learning 