“Learn Business, Creative & Tech Skills With Online Video Tutorials. Start Today!” is a catch phrase from just one of the many technology and service providers who promise to up-skill your workforce.

Upskilling the workforce is no doubt on everybodies priority list. If not, it should be. Enabling your workforce with the skills they require to do their current job and prepare for the future is probably in every CEO’s top 5 of priorities. Meanwhile, your workforce also requires to learn new skills to better handle disruptions and new ways of working. In short…skills are in high demand.

But when skills are in such high demand, why is L&D then spending so much time, effort and money on knowledge solutions rather than skills solutions? Should that not shift as well?

“Now wait a minute!“, you might think, “Why do you say that L&D is not focusing their effort on building skills? We’re all building skills strategies, skills ecosystems, Skills taxonomies. We’re buying LXP’s and massive content libraries that build skills? So with all this going on, you can hardly make that claim, right?“

Well….I wish you were right and I was wrong…but unfortunately I do not think that I am wrong.

To explain, we first need to go back to the basics….the differences between building knowledge and skills.

Knowledge vs Skills

If you read my articles (thanks for that by the way!) you know that I frequently use definitions from wikipedia, as source that I find more often than not sufficiently reliable for my non-scientific and opinionated stories.

The definition of knowledge on wikipedia reads as follows: “Knowledge is a familiarity or awareness, of someone or something, such as facts (descriptive knowledge), skills (procedural knowledge), or objects (acquaintance knowledge), often contributing to understanding“.

Whereas descriptive knowledge is described as “knowledge that can be expressed in a declarative sentence or an indicative proposition“. So for example “I know that the Etruscan Civilization predates the Roman civilization“.

And procedural knowledge reads as “the knowledge exercised in the performance of some task”. So for example: “I know that an important data cleaning step is to take out all leading and trailing whitespaces”. It’s a bit unfortunate and somewhat confusing that the wiki definition makes such a clear reference to skills. I think this is because procedural knowledge is often regarded as a prerequisite for skills, but I will get back to that later.

And finally, acquaintance knowledge is defined as “familiarity with a person, place, or thing, typically obtained through perceptual experience”. So “I know more about Spain after having traveled there with my family for almost 3 months”.

Now…. without going into Plato’s 4 levels of knowledge and make this a very philosophical treaty that reminds me of my Greek lessons in High School and advanced algebra at University (it’s always interesting to realize how much these two topic relate, but that’s another story)…in very simplistic terms (very simplistic) knowledge is a theoretical or practical understanding of a subject.

A Skill is defined in Wikipedia as “the learned ability to perform an action with determined results with good execution often within a given amount of time, energy, or both“. Where Ability is described as “powers an agent has to perform various actions. They include common abilities, like walking, and rare abilities, like performing a double backflip. Abilities are intelligent powers: they are guided by the person’s intention and executing them successfully results in an action”

So where knowledge relates to understanding, skills relate to execution. Or more precise, successful execution of a task.

A task based example: Create a Chart on a Learning Dashboard

Suppose you are asked to add a visual to the learning dashboard that enables L&D leadership to better tell the story of learning hours and how it evolves over time. Now think about what you need to execute that task. I can come up with a long list of needs, for example:

  • Tools to design, build and deploy the new visual to the dashboard
  • Time out of your busy schedule to execute this task
  • The right mental state and attitude to perform this complex task
  • A process that you need to follow to ensure adherence to internal quality and data privacy policies. Note, I mean not just processes that are well documented and mature, it could as easily be a process you execute based on experience and intuition. especially if you have been doing this for many years already.
  • Access to relevant people including (but not limited to) your customers, experts who might have already been involved in the dashboard, testers etc…
  • Knowledge on a number of things, for example
    • Understanding the data model used
    • Understand what data is available for use, and more important what data must be available for you to build the visual
    • Understand what requirements your customers have
    • Understand what visualization standards and good practices you should adhere to (think color codes, not using pie charts etc)
    • Understand what visualization options you have available, and more importantly what visualization type(s) will best fit the customer needs and context

And finally a whole list of skills, including (but for sure not limited to):

Now, the above list is not meant to be a full job description of a learning analytics data visualization expert, but it does illustrate a couple of things.

First; being able to execute a task successfully requires much more than just skills. Although, executing a complex task successfully without having the right skills will be near impossible.

Secondly; For a complex task like creating a world class & intuitive to use data visual, you need to have a rather long list of knowledge and skills. Some knowledge and skills area’s are more explicit (understanding of requirements, Power BI skills), while other might be less visible (knowledge of good data visualization practices, structured writing skills). We can also see all 3 different knowledge types represented: descriptive knowledge is represented by for example the understanding of available visualization types, procedural knowledge is represented by understanding visualization standards and acquaintance knowledge is represented by understanding the data model and customer requirements.

Third; Skills can also be knowledge area’s. This is where it becomes tricky….but in essence what I mean is that you can be extremely knowledgeable about Power BI: having read all the books, memorized all the functions and watched all the video’s…..without ever having opened the program! In Dutch we call this ‘book wisdom’ referring to people who only have a theoretical understanding of a topic without any practical experience.

Fourth: You can develop skills without knowledge. Or more precisely, you can develop skills without fully understanding why you are doing what you are doing. I sometimes do this myself…when I work with expert data scientists who create elaborate DAX equations for example, I use trial and error to apply these same equations in a slightly different context increasing my skills in Power BI without explicitly building knowledge on how DAX works (I must confess that google is my friend here!). This can work, but only for experimentation. Whenever it comes to proper product development, I leave the DAX programming to experts because (1) it would take me too much time, (2) I would not be certain of the quality of the results (and being a perfectionist, I always drive for the highest possible quality).

Another example is when you focus a person’s work effort fully on a single skill like baking bread. You provide that person with the minimal required procedural knowledge: the correct quantities of much flour, water, yeast and salt; kneading time; resting time; oven temperature and baking time, and then let the person execute the task. No doubt after a while that person becomes really good at it. The challenge is that building skills with limited understanding of what you are doing is dangerous when input starts to vary, or the context changes. The person who’s been baking the same bread for weeks and has become very good at it will struggle when for example the quantity of ingredients is increased. If you do not understand that you also need to increase baking times, your new batches will fail. Also when that same person is asked to replace water and yeast with olive oil to bake focaccia, he/she will struggle due to the lack of understanding how different ingredients change ratios and times.

Building knowledge and skills

When considering building knowledge and skills, please realize that I am not an expert in either. I am no epistemologist, not even an educated instruction designer, so I am not the right person to ask for example how to determine how much knowledge you need to learn a skill or execute a specific task successfully. But from almost 20 years experience in corporate L&D (that must count for something!) I do know that knowledge and skills are intertwined:

  • Without knowledge you will struggle to develop your skills and apply whatever skills you develop in a different context or setting. Basically you have learned a single ‘trick’ that you can perform well within a set process/context/environment. This is not necessarily a bad thing I think, but it will not get you very far when conditions change.
  • Without skills, your knowledge is only useful for debates, quizzes and puzzles, but has no practical use at all.
  • Building skills is so much more complex than building knowledge

The last one requires some explanation:

When considering how to build knowledge, you possibly immediately think about reading books, podcasts, video’s, google search and many other forms of information we have at our fingertips. Absorbing information is only one example of perception as a source of knowledge. And perception is only one of in general 4 to 5 ways to acquire knowledge, the others being reason (this is the foundation of science, math and philosophy), introspection, memory and testimony.

There are whole libraries of books written on knowledge; on what it is (and what not), how to acquire knowledge and what the value of knowledge is. In addition we have interesting emerging fields of study on how the internet (and technology in general) is changing our perception of knowledge and information, is even changing our brain as the internet is becoming an extension of our memory.

Again, this is not a dissertation on the topic of knowledge, rather an attempt to explain as best as I can the huge difference between knowledge and skills.

  • SKILLS
  • KNOWLEDGE
What is then required to build a skill?

Good question.

It’s almost impossible to answer. In terms of time and effort some say you need 10.000 hours to become an expert. The notion of 10.000 hours was popularized by Malcom Gladwell in his bestseller “Outliers” from 2008, but was actually based on a research article in 2007 by K. Anders Ericsson. Others have meanwhile criticized and de-bunked the 10.000 hour rule claiming that 10.000 hours of practice by itself is not sufficient.

Personally I think the time to develop a skills will be heavily depending on (a) the person, (b) the skill: how well can a person learn the new skills given abilities, current skills and current knowledge? Is the skill complex like data science, or fairly simple like baking cookies and (c) the target level of performance you want to achieve: do you just want to be ‘good enough’ to do your job, or become the world’s leading expert? In his book ‘the first 20 hours‘ John Kaufman claims that there is a huge difference between the amount of hours you need to become the best golf player in the world versus learn to play golf well enough to have a go at a local championship.

The creator of the youtube channel Veritasium (one of my favorite youtube channels!), Dr. Derek Muller, recently published a must see video on “The 4 things it takes to be an expert” in which he does not at all talks about how much effort it requires to become an expert, but explains that 4 crucial elements are required: A valid environment, many repetitions, timely feedback and deliberate practice:

This has lead me to the following list based on both Kaufman and Muller:

  1. Learning in context (a valid environment)
  2. Deliberate and plenty of practice, practice & practice
  3. Receive directed, timely and frequent feedback
  4. Setting a target performance level

This list is for sure not exhaustive, not fully inclusive, and not intended to be used as a checklist. It is mere shared to support the notion that building a skill requires more and different elements compared to learning knowledge.

Learning in context

Not long ago I was reviewing a training on HR analytics, naturally a topic of interest to me. I was surprised to see that examples and case studies were used from marketing. I must confess that data analytics in marketing is often more advanced than in HR and L&D and there is much we can learn from them (more on this in a later post!), but I wondered why the training did not include HR and L&D examples as there are plenty of those going around.

As an HR professional working in corporate environments for close to 20 years, I also have seen countless compliance courses and none of them ever covered examples of misconducts in the HR space. And that includes courses on data privacy, a topic which lends itself very well for cases considering the employee data many of us handle on a day to day basis. Instead, all examples on data privacy were related to customer data….not unimportant I agree, but hardly relevant for HR.

When building skills, it is key to learn the skills in the context of where you expect to apply the skills. So learning how to build a learning analytics dashboard will be more efficient if it’s done using (practice) examples from L&D, and ideally even using examples and challenges from the actual workplace. Using examples and exercises that are very generic or from a different domain like finance or marketing & sales will make it much harder to transfer the skills you learn in a training to your work and performance.

The concept of learning in the context of work is unfortunately not mainstream in L&D. And scientific evidence is not easy to find and little conclusive. The key reason is that it is actually very difficult to measure and demonstrate learning transfer. I am also not claiming that teaching people skills without putting it in context does not work, but I would argue it is less effective as the participants will need to internalize what they have learned and transpose it to their context on their own. And as time is important (and time to upskill is a very good candidate for the ‘ultimate learning KPI‘) it is worth putting skills development in context as much as possible. It will simply mean that the newly learned skills will be applied at work faster.

Deliberate and plenty of practice, practice & practice

You cannot build skills without practice. And that is deliberate practice.

I remember when I was taking piano lessons and I had to deliberately practice chord combinations and playing the base line with left and melody with right for each and every song. First separate hands starting with small parts of the song, then left and right combined with bigger chunks and finally the entire song.

Without focused and deliberate practice you cannot build a skill. This in contrast to knowledge where ‘deliberate practice’ is not required (and I am not counting memorization as practice). Practice also means you need to have the opportunity to make mistakes is a safe and risk free environment and learn from them.

Receive directed, timely and frequent feedback

Coaching is often seen as the best way of learning new skills. We certainly have no lack of available coaches for a variety of skills. What makes coaching so effective is the ability to provide immediate and directed feedback. What goes well, but more importantly what are area’s for improvement. Providing challenges, provide encouragement and support. All forms of feedback. With directed feedback I refer to the ability of a (good) coach to pinpoint exactly what went wrong, so you know what to do differently next time.

Building a skill cannot be done without frequent and directed feedback.

Setting a target performance level

Different from acquiring knowledge, which is fairly absolute (as long as you do not include belief systems into your definition of knowledge and possibly excluding emerging scientific knowledge) and thus had a high degree of certainty regarding what is right (and what is wrong), skills can be applied on many different levels.

If you want to learn Learning Analytics, you do not need to become a machine learning jedi, or python wizard. You do not need to become the world expert on learning analytics as well. You need to master the skill of Learning Analytics at the level that will make you perform successful at your current job (or give you the best chances of landing that new job).

So where we can accurately and objectively measure knowledge (with the exception of acquaintance knowledge – for example…how well do you know yourself?) by asking questions and validate answers, the art and science of measuring the level of skills is far more complicated!

Again, taking the example of learning analytics. I can test you knowledge by asking you to name 5 popular learning KPI’s, but how do I test your skills in designing a learning data model? Or how do I validate your skill in diagnostic analytics? Or you skills in building a new chart in Power BI?

Most likely there’s a balanced combination of ‘time to complete’ and ‘the quality of result’ involved. But the more complex the task and skill required, the harder it is to quantify what measures of time and quality define ‘good’, or good enough.

Now consider the majority of what we do in L&D.

I cannot make a sure claim that building skills takes more effort than building knowledge. This is not the same thing as saying that they take the same effort. As with many things ‘it depends’ on a lot of factors. But with the understanding that building skills takes (as a minimum) specific elements that are different from building knowledge, namely: context, practice, feedback and clear target performance levels, I’m willing to support the claim that building knowledge is different from building skills!

With this in mind, now let’s look at what we are actually doing in L&D.

Taking the top trends for 2021 and 2022 (using a very unscientific collection of data from 10 websites) shows that the top trend in L&D is microlearning….congratulations!

Microlearning as top trend is followed by hopefully familiar topics like adaptive/personalized learning (these terms are most of the time combined or mixed up so I took the big step of putting them together!), social learning, gamification, on demand learning (whatever that means). I’ll include Learning Analytics to make it a top 6, although not really a format rather than something that needs to be an intrinsic part of your l&d processes. Further trends mentioned are video, podcasts, Mobile, AR/VR..

A somewhat more scientific ATD report on the state of the industry 2021(using 2020 data) claims that 18% of training hours available was based on F2F training, 35% using virtual classrooms, and 32% via self paced online learning (e-learning), while “Studies from ATD show that e-learning use is expected to continue to grow over the next 5 years.”

A trend that is not explicitly mentioned but is all around us is the enormous rise of massive content libraries. Every (well almost every) L&D department is buying content ‘off the shelve’ from LinkedIn Learning, Coursera, Skillsoft, Plurasight, Studytube, Udemy and many others. Most of this content is generic, most of this content is ‘traditional elearning’, i.e. self paced online learning (heavily relying on video) with very little interaction (I would not consider a ‘test’ at the end of the course ‘interaction’).

Now look at these trends and numbers and ask yourself the question “which of these trends and formats truly contribute to building skills. Which of these these focus area’s of L&D provide the ability of learners to learn in context, practice a lot, receive feedback and set clear performance targets?

I’m afraid very few….

AR/VR could come close if designed very well and used for the correct reasons (so not just to make learning more ‘fun’). Social learning has potential if it’s well facilitated, well structured and using smart technology (and no…yammer is not smart technology). But that is about it. I have also seen many F2F trainings that did not provide the right workplace context, nor allowed practice, and were even more a one-directional big clunk of teachers telling rather than a dialogue (let alone feedback) to put my faith fully in F2F or virtual facilitated events.

My conclusion therefore is that L&D is not focused on building skills but on building knowledge. Strategically, this is where we as L&D need to ask ourselves if this is where we want to put our money, our effort and our focus.

Knowledge and Skills: Why we in L&D are mostly building knowledge and NOT skills

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