 Most people have heard of the 80-20 rule or the Pareto principle, but very few understand it or know how to use it properly. That all changes today. I'm going to take you step-by-step through all of the basics that you can start using it right away to become more efficient and effective. Hi, my name is Raph. Welcome to Riser, where my mission is to help you go further, faster in your career. I believe that prioritisation is one of those foundational skills, essential for you to do your job efficiently and effectively, and as I've discovered is an essential life skill as well. And that's why some of my very first episodes on this channel are devoted to this topic. I'll link to the playlist below. But today, we're going to focus on the Pareto principle, of course, and following the same format as the other methods, what it is, how to make a Pareto chart, step-by-step with some hints and tips, how to use it to improve both your results and your personal productivity at work, the pros and cons of using it in the real world, and we're also going to rate it for a bit of fun, which will help you decide if and when you should use it, and a useful power tip at the end. I strongly suggest you step through all of this with me, but I have included time codes in the description box below if you want to jump to a particular chapter. So, what is the Pareto principle? Well, the Pareto principle states that for many outcomes, 80% of the effects come from about 20% of the causes. For this reason, it's often referred to as the 80-20 rule. It was named after Wilfredo Pareto, who in the late 1800s discovered this connection when he found that 80% of the land in Italy was owned by only 20% of the population, and he began noticing similar patterns elsewhere. This principle is all about the concept of the vital few causes being responsible for the overwhelming majority of the effects, and it occurs everywhere, from economics to nature and even language. For example, of the 170,000 words in the English language, just around 3,000 of them make up about 95% of all the words we speak. I use this example because it perfectly demonstrates that even though it's called the 80-20 rule, it's often much more pronounced than that. What is true is that we typically find a few things causing most of the effects, so always think of this principle in terms of the vital few as opposed to a fixed number or percentage. So how does this concept actually help us? Well, it's particularly useful in business to prioritize the most important drivers of success or failure and the root causes of issues, and it also helps us to figure out where we might be reaching diminishing returns for the amount of effort required, and there's going to be a future episode devoted to that particular topic. And lastly, and this goes without saying, but focusing on the vital few can be applied to really lift your personal productivity as well. Now, unlike the matrices that we use to help us in previous episodes, Pareto prioritization uses a chart called, you guessed it, Pareto chart. I'm now going to step you through exactly how to make one and then how to use it, so back to the studio. We start with the data set. This can really be anything we want, but in our case, I've just created a fake data set to represent all the complaints received by a small hotel from their guest surveys over the course of a calendar year. Thought it would be a bit of fun. We then need to categorize our data by grouping similar elements so that we can analyze it. Now, in our case, we've assumed that our guests have filled out a survey which has been designed to analyze by category. If your data isn't categorized, you'll need to do this. It's part art and part science. And for the sake of this exercise, I'll assume you know how to do this. But if you don't, and you'd like to see a video on how to do that, then drop us a comment below. So what we want to do is sum up our data to get totals, which has already been done for us in this example. You can see we've got our categories of complaints there, as well as the volume or frequency of those complaints. And also for the sake of this exercise, I've made 30 categories of complaints and there are exactly 1,000 complaints from our guests in total. If we look at this data as a bar graph, this is how it appears. You can see we have our volume on the left-hand side y-axis with our complaints categories on the x-axis. So this is a pretty standard bar chart that you would have seen before. Now here's how to create a Pareto chart from this information. Firstly, we want to sort our data into descending order from high to low, like this. So now when we create our chart, the bars are going to appear in descending order from the most frequent complaints to the least frequent when we move left to right. Now we're going to turn this into a Pareto chart by adding a second y-axis on the right-hand side to show the percentage totals as we add them up from left to right. By the way, this axis is always set at 100% maximum, 100% representing the sum total of all of our complaints. These two y-axes work together, the ones on the left and right-hand side, which some people find a little confusing. So I'll go through step-by-step to show you exactly how it works and hopefully it'll all make perfect sense. Starting with the biggest bar on the left-hand side, room temperature. 227 complaints is 23% of the total. Remember we had 1,000 complaints total. I've rounded the percentages to the nearest percent, so 22.7% becomes 23%, okay? Now if we plotted a mark or a dot on that bar in the exact height that corresponds with 23% on the right-hand side, here's where it would land. And I've drawn this dotted line out here to prove it to you. Now let's move on to the next bar, the next complaint, no or poor internet. And once again, we plot a dot, but now we are plotting the total or cumulative percentage we have now reached. So together 227 plus 187 is 414 or 41.4%, which has been rounded down to 41%. Hopefully you're following along. Together these two categories make up 41% of our total complaints. Noise brings us up to 55%, dirty rooms brings us up to 66%, room service food brings us up to 74%, and rude slash unfriendly staff brings us up to 80%. Now we're at 80%, let's keep this in view, but we keep going until we've completed the cumulative percentages. Now if you're using Microsoft Excel, you can create a Pareto chart pretty easily by creating a cumulative percentage column in your data, and then formatting that second Y axis as a line, just as we have here. It's a bit of a pain, but it's very doable, and I'm not going to go into it here because boring. And also because Excel now has a Pareto chart for you. To use it, all you need to do is select your data, select Pareto chart and voila. The only downside is it's a bit of a pain to format, but for a quick easy chart, it's great. Okay, so assuming you've created your Pareto chart, we can go back and I'll show you how to read it. Remembering that we had 30 categories of complaints. We know that the top six issues here are causing 80% of the damage. So you can see that 80-20 relationship at work. Of course, I designed it to work out like that for the purpose of this demonstration, but it could just as well be 70-30, 90-10, or something else. At the surface level, we're gaining three initial insights from this graph. Firstly, it's telling us that theoretically, if we were to resolve those top six issues, we would eliminate 80% of the complaints, and hopefully the same proportion of customer dissatisfaction as well. So it's indicating where we should be spending our efforts. Secondly, it's really also telling us not to spend our time on all of those smaller complaints, what we sometimes call the rats and mice, because if you add all of those up, you only get to 20% of our total complaint volume. And sticking with that cheesy theme, we sometimes refer to this shape of graph as having a long tail. We don't generally want to be focusing on the tail, although there are a few exceptions. And thirdly, this graph shows us that it's not that easy to determine the exact cutoff point where we don't want to be focusing our efforts. There's potentially a bit more investigation to do. So we've just covered a couple of basic but really powerful insights that we can draw from this information. So in many instances where you have numbers, where you have quantitative data, you can now very easily apply a Pareto analysis and draw similar insights. But stepping back from this, you can also apply the principle of the vital few to almost anything else. This disproportionate or non-linear relationship between causes and effects is, like I said earlier, everywhere. And you can apply this way of thinking to many of your initiatives even if you don't have a whole pile of data. For example, when selecting those few stakeholders to regularly connect with, or which tasks or initiatives you're going to focus on, or even where you're going to spend your personal time or money. So those are the basics, but I urge you not to stop there to really understand and address the vital few we need to dig a little deeper. For example, here's what I see at a glance when looking at this chart. I see that there's a common theme running through many of these complaints. I see that dirty room, rude and unfriendly staff, room service other, unattentive staff, parking slash valet, wake-up call, front desk, do not disturb, not adhere to, and adjunct services, these all have something in common. They're all staff-related. Hmm. And look at this, someone's been naughty, theft. And now I'm even going back and looking at room service food because that's staff-related as well. So looking a bit deeper at this data, there definitely seems to be a service aspect worth looking into. We can start to form a hypothesis around this, and arguably some of the other categories could be partially a result of poor service as well. But even if we take the 11 categories highlighted and add those together, we get to 401 complaints. Over 40% of our total complaints, which could be from a common cause or common causes. Interesting. So the message is, don't just stop at the surface, look into what this data is telling you, and keep asking questions. Now let's look at some of the pros and cons of using this in practice. Starting with the pros, the Pareto distribution allows us to quickly assess which factors create most of the effect. In addition to this, generally wherever you have a large amount of information, you can use a Pareto chart to quickly cut through the noise and focus on the priorities. And it's not to be underestimated as a communication tool either. The information it gives us allows us to frame problems and solutions in an engaging, informative way, and can help us reach consensus on priorities. Now on to the cons. Now I'm going to have to split hairs a little here because Pareto chart is designed specifically to identify the vital few, and it does that job pretty well. But if I were to be picky, you can fall into the trap of becoming over-reliant on surface-level metrics. Remember that it only tells part of the story and you'll need to dig deeper. Because of this, it does require some skill, depending on the data that you're looking to analyze. And lastly, because it's sometimes seen as a tool to identify an 80-20 ratio specifically, it can be misused. Remember, we're really looking for that disproportionate effect from the vital causes, so not 80-20 per se. Let's rate the Pareto method by looking at the dimensions of usability, accuracy and adaptability. In terms of usability, it's very easy to understand. Suitable for sorting a wide variety of data because we see the vital few everywhere. But it does take a little practice and there is some skill involved in parsing out the information, so I deducted the star, giving it 4 out of 5 stars. In terms of accuracy, which is how accurate the method is at determining relative priorities, I gave it 4 stars. I think that's pretty self-explanatory. And it's another one of those very adaptable tools you can use together with other prioritization models, so I've given it 4 stars here as well. So our friend Pareto gets a total of 12 out of a possible 15 stars, which compared to other methods we've rated is a high score. And I think it's well deserved. Now for the power tip. You can use Pareto charts multiple times to analyze your same data set in different ways by applying it each time you gain more understanding. Using the example of the hotel from earlier, let's jump back to the studio. Okay, so remember this chart? Remember how we identified there could be this theme of customer service that might be interconnected? Basically, we have a hypothesis that there might be a common cause or causes across these. If we simply stuck these together into one category, as we said, they make up 40% of the total complaints. But we know it's not as simple as that, because there are probably a few things going on within these. So the first thing we might want to do is understand a little more about what's really going on here. One way to do this is through conducting what we call a root cause analysis, which I'm not going to go into here, but there are various ways to find out the underlying causes of these issues. And I'll be covering those in future episodes. So that aside, once you understand your common causes, in our example, let's say they turn out to be things like poor training, lack of standard operating guidelines, etc., you can once again use a Pareto chart to understand which of these causes to focus on that will lead to the outcome you desire. So don't be afraid to use the Pareto chart more than once within the same piece of analysis. The Pareto principle is such a simple and powerful tool that can be used in so many different situations, but just like any other method, it does have its pros and cons, so make sure it's used appropriately. Now, if this is your first time here and you want to learn how to be more efficient and effective at work, start now by subscribing and clicking the bell so you don't miss anything. And if you have any questions, let me know in the comments below. If you enjoyed this content, hit the thumbs up button. It really helps with the YouTube algorithm. And don't forget to share it with a friend or a colleague. Till next time, keep rising.