How To Learn Faster Than 99% of People At Work

Most people think that getting a raise is about working harder or being more likable, but that is not entirely true. And if you believe this, your career growth will be slow and painful. I've been a learning coach for the past 13 years, and I've coached thousands of professionals to succeed in their careers by getting promotions and raises faster than their peers. And what I've realized is that while who you know and how much they like you does influence your career success, that's only half the equation. The other half is tied directly to your ability to learn. So, in this video, I'll explain exactly why your ability to learn is so important for getting a raise. And then I'll give you a practical framework called the value delivery matrix, which allows you to learn so effectively. You'll get paid what you're worth months or even years earlier than usual. So, let's start by explaining how your learning ability gets you a raise. The way you need to think about it is that businesses exist to solve problems. And when the business can solve a problem for a user, it is able to generate money. And so your job and basically any job exists to essentially solve problems. And if you can solve these problems better than anyone else, you are more valuable for the business. But just because you are competent and you can solve problems in your daily work doesn't mean that you're going to get a promotion or you'll get a raise. at least not very quickly. And so to fasttrack your career, your ability to solve these problems needs to outpace the problems that are presented to you. And when your ability to solve problems is higher than your position or your pay, this is when a business becomes incentivized to pay you more, to either retain you or to promote you so that you can solve even harder, more valuable problems that then generate the business more money. And this is where your ability to learn fits in. For most problems you're given, you will not know how to solve it immediately. And specifically, there are two things that you will always be lacking or missing when you come to solve a new problem. And that is data and strategy. Data refers to the information you have available about the problem as well as possible solutions. So your background knowledge and your expertise, this is all data that comes together to help you solve the problem. Strategy is about the way you use this data to formulate a solution that actually works. And so the first step to solving this problem and actually the step that determines whether you will even succeed at solving this in the first place is learning. You need to learn and gather the necessary data and you need to learn about the right strategy and approach. And here's the biggest thing about this. When I look at how someone approaches solving a problem, and most experienced managers will be able to do this as well, I can with a surprisingly high amount of accuracy tell whether someone will be able to solve this problem eventually or not just by looking at their approach. Good managers will notice this and they'll pay attention to this because if there's an issue in this early part, then there's not even any need to wait for the outcome. And so a lot of the time whether someone gets a raise or a promotion is not only based on the outcome they reached but it's based on another person's belief that you can solve future problems. And people form this belief of whether you will be able to solve future problems and deliver a return on the investment based on the way you approach a problem and learn. And this is precisely why being a fast learner is one of the most in- demand skills that employers look for. Trust me, as someone who does this for a living and has also interviewed hundreds of people, it is very, very hard to find. So, now that we've understood how your ability to learn increases your chances of getting a raise or getting promoted, now I'll introduce the value delivery matrix. The value delivery matrix shows you not only how you can solve problems extremely fast but how you can do it in a way that instills the belief in other people that you are a problem solver. And so there are two axes to the value delivery matrix. The first is data and the second is strategy. And as a quick recap data refers to what you know that helps you solve the problem and strategy refers to how you use what you know. And often for complex professional problems, the strategy is the really tricky and valuable part. Now, by the way, if learning to learn and getting better at learning and developing this extremely hot in demand skill is a priority for you and you're wondering where you can get more data on how to learn. There are many sources of information available for you online. But if I had to pick just one, I would definitely say it has to be my newsletter where I share not only the data that is what I think the most high yield information that will improve your

ability to learn, but I also share with you the strategy on how to think about learning. I tell you what are the things that are important for learning faster and overrated and a waste of time. Each newsletter is one email, takes a few minutes to read, sent to your inbox once a week. It's completely free to join. So, if you're interested, I'll leave a link to that in the description below. Now, back to the matrix. There are four quadrants depending on your combination. And the idea is that you can use this matrix to figure out where you are with your current approach and your method of learning. Uh, and the goal is to get to this top right quadrant here, which is the optimal quadrant. And it's at this quadrant where your ability to learn will outpace the problems that you're given. and show other people that you are worth paying more. So let's start with the bottom left quadrant because this is unfortunately actually where a lot of professionals are and this is why you get stuck. Uh and this is called the treadmill quadrant. The treadmill quadrant is where you have the wrong data and the wrong strategy. Having the wrong data means you don't have access to the right information or actually you're learning from the wrong information that's going to lead you astray. You might also spend a lot of time going through irrelevant information. The wrong strategy means that you don't actually know how to use all of this information in the first place. You're doing a lot of learning, but it's not really getting you any closer to solving the problem. I call it the treadmill quadrant because you do a lot of busy work and learning, but you're not really progressing. This is a really frustrating and sometimes embarrassing place to be because you're doing so much work, but at the end of the day, you don't have a great solution or a strategy to present to other people or whatever you do present is just not very good. Now, if I'm working with someone, there are a couple of signs that will tell me that someone is probably in this treadmill quadrant. Uh, and that is that they spend a lot of time on trying to learn and solve problems. However, they consistently get feedback that their solutions and the quality of their work is just not hitting the mark. It's this idea that no matter how hard they try, it just doesn't seem to be good enough. Now, if you feel like you are in this quadrant, uh don't despair because the reason most people are in this quadrant is that they simply just don't have the strategies to help them get the right data and get the right strategy. And so, I'll go through each of those. Now, we're going to start with figuring out the right strategy. Because while most people rush to figure out what to do to solve a problem, the best problem solvers start with how to think about the problem. And also, once you know how to think about a problem, it helps to frame and contextualize what you're learning, which enhances your ability to get the right data in the first place. And so one simple and effective strategy that can apply to basically any type of problem you're solving in any industry is something that I call topdown uncertainty mapping. And there are three parts to this technique. The first part is to identify the root causes of your problem. Most problems you're given are given to you as a single package. And so it's confusing how to solve it because it's actually made up of multiple different components that then relate to each other. This is the top- down part of the technique. We take that single packaged problem that we're given and then we dissect it down into each of the component causes where if we were to solve all of these things, the ultimate problem would be solved. This not only gives us more focus when we're learning about and trying to create a strategy, but it also reveals to us assumptions and gaps in our knowledge. The second part after we've done our top- down causes is to identify our level of uncertainty for each of those root causes. A simple way of doing this is to establish whether it is a known or an unknown type of problem or solution. If you have a known problem with an existing established solution that's widely used in the industry, it means that you probably don't have to reinvent the wheel. You can look for existing frameworks and existing models that other people have used successfully. You can learn from what has worked already and just adapt that. The next level down would be a known problem, but the solution is not very clear. Simply copying someone else's solution isn't going to work here because of differences in context. If this is the case, we need to figure out what the best practices are. We may not have a robust comprehensive framework that tells us step by step exactly what to do and how to think about it. But there may be general guidelines about how to approach this kind of problem which you can then use to create your own structure. or if there aren't even general guidelines, you can use existing structures that other people have tried to form what you think is your own set of guidelines and best practices. And the next level down is if it's an unclear problem to begin with. If the problem is unclear, we are not even ready to think about a solution. So how you create the right strategy would be to get clarity on the problem. The good thing is that if it's an unclear problem, you'll normally figure that out even in this first step because as you're trying to establish the root

causes, you'll realize that there's a high level of uncertainty. This means you need to go and investigate. You need to learn a little bit more. You need to map things together, see the big picture, and then try to get clarity on the problem so that you can then start formulating your strategy for a solution. Now, the third part to this technique is mapping. Mapping means that you are going to connect the areas you were the most uncertain about where you felt you had the biggest gaps in knowledge with the thing that you are learning and these become your priorities. You want to spend more of your time early on learning about the things that you have the biggest gaps on because the big gaps are more likely to change your overall strategy and approach. And so by using this technique, we can gain the right strategy, which means we now know how to think about the problem, moving us from the treadmill quadrant to this top left misdirected quadrant. You would be in this quadrant if you only use this technique uh and you still have the wrong data despite having the right strategy. What this really means is that you have the right way of thinking about the problem, but the information sources that you're actually learning from are incomplete or unreliable or inaccurate. And this quadrant is actually really dangerous because uh it can develop false confidence. As you learn more, you are getting more confident because it's making more sense to you and you can see a solution taking shape. But if you didn't already have expertise and knowledge about this, you can't actually tell that the information you're learning from is incorrect. In this quadrant, it can feel quite confusing and again sometimes embarrassing because you present something that you feel confident in, but then either the results are not very good or your manager or supervisor or someone with more experience points out all of these assumptions and flaws in the reasoning which you were completely oblivious to before. I've recently been noticing this being more common than it used to be because people are relying more heavily on AI and LLMs like chatbt to generate their information which is not always accurate and reliable in the first place. In some cases I've seen people generating the entire data and strategy just using chatbt uh which tends to generate something that is not quite fit for the context and also just makes you look lazy which is definitely not going to get you a raise or a promotion. And so naturally the way that we fix this is by getting the right data. And a super simple technique for helping us get the right data is a technique called the 3S screen. This is a technique that allows us to screen through and filter vast amounts of information to figure out what is actually worth spending my time learning in the first place. What are the sources that are reliable and what are the pieces that are relevant to me? The three S's stand for source, signal, and scrutiny. Source means we ask ourselves where is this information and data coming from? Is this coming from a random blog post somewhere or someone's anecdotal advice or is it coming from the words of an experienced expert or a credible source or maybe like a validated proven data set? The second S stands for signal. Signal means asking yourself, is this information signal or noise? A signal is a valuable piece of information that is worth focusing on. Whereas noise is just distracting information that might lead you astray. And the way you can tell whether it's signal or noise is by looking at the information and asking yourself, is this a oneoff opinion or a oneoff piece of information or is it backed by consistent patterns and trends? What are other people saying? Do they support this argument or not? It doesn't have to be supported by literally everyone to be considered a signal. But if there's only one person saying something and everyone else disagrees, it's probably noise. And the third is a scrutiny, which is this something that has been challenged or tested? If you're reading and learning something online, is it coming from a peer-reviewed validated journal or uh the opinion of someone who's been really pressure tested? or if it's an internal opinion coming from someone within your team, has that been challenged and pushed back against? It is an enormous waste of time when you're learning something to spend that time consuming information that's not even relevant to you, that's not reliable. When you do that, you actually end up in a worse position than before you started because now you have incorrect things you have to later unlearn. So using something like the 3S screen to filter through all that information can not only save you a lot of time, but also help you to just form more reliable opinions. Now, if you did use this 3S screen, but you didn't use the top- down uncertainty mapping and you didn't have the right strategy, then actually you would end up in this bottom right quadrant, which is the overwhelmed quadrant. And this would be where you have the right data, but you have the wrong strategy. You're using all the right information sources, but you just don't know how to put it together. This is really common when you're used to just book learning for academics or

passing exams, but then you struggle when you need to apply it for real world problems. And the real danger with this quadrant is that it creates this illusion of knowledge. Well, there's two big dangers actually. One is that it creates this illusion of knowledge and two is that it creates a massive learning debt. The illusion of knowledge means that you think you are very capable because you technically know a lot of stuff but not really very functionally useful. But the thing is you would think that if you have all the right data and you've got the right knowledge then it's a relatively simple thing to just apply one of these you know strategies and then you can get the right strategy and then everything is fine. But what I've actually found in real life is that when someone is really used to learning data in a way that's not easy to apply for their actual problem solving, they then need to spend time going back and relearning the stuff that they already learned because it's actually organized in such a incompatible way. They just have to go through and pretty much just relearn it all over again the right way. And this is the reason why this is called the overwhelmed quadrant because as you continue to learn more about solving this problem, you become increasingly overwhelmed as you're now aware of all of the different things you have to somehow connect together which you just can't. And this is the second most common quadrant to be in uh once people escape the treadmill where they focus too much on just learning and consuming stuff but they don't have the right strategy. which is why uh I started with the right strategy because once you have that in place it's just easier to organize the right data in the right way and so obviously when you're able to do both of these things which is the goal we are here and this is the optimum quadrant and so the signs that someone is in the optimum quadrant which is pretty uncommon is that as they learn more their confidence goes up but unlike here in the misdirected quadrant it's not false confidence uh because as they learn more and spend more time on learning what also happens is that their level of nuance increases instead of just how do I solve this problem it becomes there are multiple ways that we can tackle this problem and it's about evaluating which one is the best fit another sign is that as we spend this time to learn more we should feel that we are becoming less and less overwhelmed as we learn more and consume more of the right data we also feel that it's starting to make more sense and it's getting simpler to think about. And so as you operate in this optimum quadrant and you're using techniques like this to get the right data and the right strategy, not only do you increase in your confidence, but other people also feel more confident in your ability to solve the problem. And so even though with each problem that you encounter, the data and the strategy is constantly changing and is variable, your ability to learn remains something that is a constant or rather even grows. So even if the data or the strategy and the problem changes, which it will, your ability to learn and tackle that problem continues to provide you a return on that investment every single day. And that is how you can learn so fast that there is no other choice than to give you a raise or a promotion. And if you want even more strategies on how to learn faster, then you might want to check out this video here. Thanks so much for watching and I'll see you in the next one.