If you are creating software, business processes, or digital content for profit, then you are a member of the knowledge economy and may find this article to be worth your time.
Knowledge workers can typically be found in the following departments (sorry if I’m forgetting any):
- Human resources
- Information Technology
- Data Science & Analytics
- Executive Team
Given the pervasiveness of knowledge workers in most post-industrial companies, all else being equal, it is reasonable to conclude that companies that hire, develop, and retain the most productive knowledge workers will see improved business metrics over the long term and may ultimately dominate their respective industries.
If you buy into this argument, then the rest of the article will likely resonate with you.
Historical knowledge is useful but insufficient in an ever-changing world. Career paths regularly pop into and out of existence. For example, when I first started working as a software developer, there was no such thing as a cloud architect, because compute clouds didn’t exist. Given a quickly changing digital world, adaptation becomes crucial for individuals, teams, and entire companies.
Learning is the process that sentient beings employ to acquire the knowledge needed to adapt to new circumstances. Since adaptation is required, learning is critical.
Given how critical learning is to success, one would think that every individual and organization participating in the knowledge economy would optimize their behavior to become the best learners they could be. In theory, this makes sense, but in practice, I have found there to be a stubbornly persistent learning gap, which ultimately leads to a knowledge gap. I believe the gaps exist because individuals are never taught how to learn effectively and organizations often don’t prioritize it.
The truth about learning
A recurring truth I’ve seen repeated in almost all the books I’ve read, as well as experienced first hand, is that learning is slow. There seems to be no getting around this simple fact. Slow learning is a cognitive sciences first principle.
It’s also a bit intuitive right? Parents regularly experience this while teaching their children how to read. If your children are anything like mine, you’d have observed that it took a minimum of 2 years to become a reasonably good reader.
The CTO of AWS Werner Vogels sums it up with the quote, “There is no compression algorithm for experience” and for years I have been telling project managers that the task they are looking to accomplish, “requires 10 years of experience and then a few weeks”.
The fact that learning can take a long time has a few important repercussions:
- Knowledge transfers are largely impossible if performed at the end of knowledge acquisition.
- The churn of knowledge workers is particularly expensive for companies.
- Training seminars aren’t learning environments.
- Small gains in the learning rate can have a huge return on investment.
I will address each point in this list in order, saving my favorite topic, learning rate improvement, for last.
Knowledge transfers are impossible because knowledge resides in one’s brain and is largely the product of facts and experiences. While individuals may be able to acquire some facts, they likely won’t be able to experience those facts in the same order or under the same conditions as someone else.
Poor knowledge sharing at the organizational level is a form of intellectual debt. Similar to technical, cultural, and fiscal debt, the debt tends to go unnoticed in the beginning and accrue over time. Individual research is often a high-value activity for exploring possibilities in the short term. However, failure to build a team around a promising direction can create an unmanageable intellectual debt burden that ends up costing an organization more money in the long run.
Given knowledge transfers are impossible, workers should shift the narrative and ask their managers what they really want. It’s likely the manager doesn’t actually want a transfer of knowledge, but to instead just get access to key systems and documents.
An alternative approach to knowledge transfers that can help address intellectual debt, is to size projects properly and pay down the costs of knowledge transfers on an ongoing basis. Proper sizing leads to teams of at least 3 with some overlap in skill set. For maximum return on this investment, knowledge workers should be conducting peer reviews of the work being performed.
Lastly, teams of knowledge workers should aggressively build abstractions that reduce the amount an individual needs to know in order to be productive. For marketing, this might look like a press release template. For legal this might be standard language around similar contracts and for software developers, this means leveraging pre-built libraries.
Churn is expensive
I have written at length on my blog about this subject so I won’t bore you here with all the ways that churn happens at a company and will instead focus on the intellectual cost of knowledge worker churn.
Consider that in order for a knowledge worker to be productive they must become familiar with the general business processes, including all the basics that all workers would have to learn. Then that same worker added to a new team, must acquire the knowledge to use the technologies favored by that particular team. After that, a new hire will also need to learn the standards and practices of the team. Lastly, the person may have to learn the history of the work they are being charged with bringing into the future because without a grasp of history one is doomed to repeat it.
In practice, I have found that it takes a minimum of 2 months for most knowledge workers to contribute meaningfully to a project and much more time for projects that are more complex. Learning in a complex project does not scale linearly because you have to learn about each part of the project and the network of connections those parts make. I’ll leave it up to managers to decide how much churn is acceptable and to employ strategies to reduce it, as that isn’t the central focus of this article.
In short, knowledge leaves the organization alongside employees; thus, churn makes organizations dumber.
Training isn’t learning
Training should not be confused with learning. In the knowledge professions, this tends to take the role of conferences, 3-day seminars, and lunch and learns. All three of these things serve an important purpose, but they won’t enable folks to learn meaningfully. In the book Pragmatic Thinking & Learning they call this “sheep dip training”.
I like to think about these types of events as solving the following problems.
- Legal compliance
- Marketing and sales opportunity for sponsors
- A chance to network with colleagues
- Initial exposure to new ideas
- Certification pre-requisite
Given it solves a number of problems, training is still relevant and useful, it’s just insufficient to truly learn and by extension create knowledge. In order for an organization to create lasting knowledge, it must prioritize and promote learning as part of the typical workday instead of facilitating sheep dip training.
Bend the curve to close the gap
Congrats if you are still with me, we are finally going to get into some meaningful steps folks can take to help improve their learning rates. Improving the learning rate of a team or individual is one of the most productive activities any knowledge worker can engage in.
The reason should seem obvious. Increasing the learning rate allows folks to acquire knowledge more quickly which may help reduce the impact of the previous three issues associated with slow learning. Additionally, improved learning habits will benefit the individual for their entire career.
Learning is still going to be slow compared to most things in life, but it can be a bit faster if one learns how to learn.
Folks assume that re-reading and drilling will improve their learning and their ability to retain knowledge. Research suggests that in the short term this works, but in the long term, this behavior can decrease one’s ability to retain information.
Instead of drilling, folks should take breaks of varying lengths between study sessions. The literature suggests that if one waits a while and then tries to recall what was learned before studying again, retention can be greatly improved.
I recently started using babbel.com to learn Italian and noticed they employ this technique. It seems reasonable to assume that a company devoted to teaching languages, would employ the technique, based on evidence of its efficacy.
What’s interesting is that one need not actually remember the content during the break period to see retention gains. The act of pausing and then trying to remember is actually enough to offer meaningful improvements over the long term.
Exercise has been shown to improve one’s capacity to absorb information. In the book Spark the author makes the argument and provides compelling evidence that exercise can increase neuron growth and help forge new connections. Additionally, students who exercised before an exam performed better than those that didn’t.
For this reason, I often go for walks during times when I want to increase my capacity to learn. The quiet helps me focus and the exercise helps forge the neural connections that are necessary for long-term learning and growth. I’d encourage others to engage in some form of physical activity often.
Become a teacher
Teachers tend to be excellent learners. They understand through trial and error and formal training, how different people learn in different settings which they can use to refine their own learning style. Additionally, a teacher is almost always required to become a subject matter expert. Moving from novice to expert is a process that many folks never experience, but it is common for educators. Since becoming an expert is often a goal of learning, teaching can be instructive towards our learning goals.
In practice, most knowledge workers won’t just quit their job to become a professor, but that doesn’t mean they won’t be presented with opportunities to teach others. There are many ways we can all learn to be teachers and thus better students. Some of my favorites include parenting, mentoring colleagues, conducting lunch and learns, and writing blog articles. In short, learning to teach helps folks learn to learn.
Write it down
Writing things down can be used in two ways, and both are effective. The first is to actively take notes on a notepad. Handwritten notes may feel inefficient, but it is exactly this inefficiency that leads to better learning and retention. Handwriting notes is a technique that seems obvious, but most folks don’t do it these days because they adopted the practices of reading on an e-reader, tablet, or phone and conducting meetings via computer with screen recording enable.
Typing during a zoom meeting is distracting to all the participants and highlighting on an e-book you never go back to doesn’t offer any long term value. Instead, folks might consider taking purposeful notes in a physical notebook that can be easily referenced at a later date. One of the great things about taking notes this way is that you can quickly draw a diagram to illustrate complex connections between topics which helps reinforce one’s understanding of the subject.
The second way we can use writing to help with learning is to simply write a blog article or book report, in the same vein as a college student writing papers as part of their coursework. The practice of writing should not stop with graduation. Knowledge workers should continue to write about their most interesting projects and thoughts in order to reinforce their own knowledge and help others gain initial exposure to ideas. Ask yourself this; who do you think is going to remember more of this article, you or me? The act of writing is not just a way to share knowledge, but to acquire it as well.
The authors of Make it Stick, make the argument that learning should be difficult, which implies that, easy learning is an oxymoron. Said another way, if it’s easy you likely haven’t learned very much. The book calls these, “desired difficulties”. One example the author highlights is how folks were able to recall more of what they learned when the text they were reading was slightly blurry or skewed.
The book also discusses how struggling to generate answers to tough test questions produced more long term retention. It turns out it’s better for teachers to give hard tests, not only in the interest of assessing what the student learned but also in the interest of enabling them to learn in the first place.
In the workplace, the test might be to apply your newly learned knowledge in a novel way to help solve business problems or field questions from senior leadership. I always advise anyone looking to advance their knowledge and their career to seek out the most difficult projects they could possibly complete successfully.
A failure to solve a difficult problem will yield value in the form of learning and if successful will yield value beyond just learning. Either way, the individual will gain more from a harder challenge than from an easier one. If managers wish for their reports to learn more, then they should work to increase the difficulty of each subsequent project the team is responsible for.
The book Range explains, in great detail, how individuals that pursue a wide array of activities, having only minimal overlap, can often produce better learning effects than individuals who are comparatively narrowly focused. The concept flies contrary to the dogma most of us have heard our entire lives. From a very early age we are taught to focus, focus, focus and we’ll achieve our goals. It turns out that this is a false narrative that can lead to successful learning in subjects that benefit from such a style and poor learning in most other areas.
The reason it can be difficult to learn from a narrow focus is that humans use analogies and concepts from other subject areas to form general mental models. Generalized mental models tend to stick with folks more than specific models since they are more widely applicable and therefore command more of the individual’s attention.
In the book Where Good Ideas Come From, Steven Johnson makes the argument that most good ideas come from networks of people. A network of people is by definition more general than a single individual. It thus seems reasonable that one would want to create teams with diverse perspectives in order to improve both learning and by extension idea generation. Knowledge workers should look to a broad array of subjects in order to improve their learning, but also to a broad array of people. Fields that exclude groups of people will fail to learn as effectively as those that embrace diversity.
Most of the content in this article was acquired through years of trial and error, lengthy team discussions, and individual study. If you are looking to up your learning game, I would highly recommend reading the following books and corresponding chapters.
- Slack by Tom DeMarco: chapter 26 - Where learning happens
- Pragmatic Thinking & Learning by Andy Hunt: chapter 6 - Learn Deliberately
- Make it stick by Peter C. Brown, Henry L. Roediger III, and Mark A. McDanial
- Range by David Epstein: Chapter 4 - Learning Fast and Slow
- Spark by John J. Ratey MD: Chapter 2 - Learning
- Where Good Ideas Come From by Steven Johnson