DBP 001: The Life-Changing Magic of Understanding Variation, with Cedric Chin, Pt 1

In today’s episode, I'm joined by Cedric Chin, a leading voice in business writing and the developer of XMrit, a revolutionary tool for business data analysis. 

We'll explore the secrets behind mastering skills and leading effectively, and how progress is a marathon, not a sprint. Cedric shares his journey of turning frustrations with Excel templates into a game-changing tool, and we discuss why understanding variation could be your hidden superpower. 

If you’ve ever felt overwhelmed by data or struggled to make meaningful improvements in business, this conversation is for you. Let’s get started!

Show Highlights:

• Learn insights about data-driven companies [05:12]
• This is the source behind most Amazon ideas [07:17]
• How to change your approach towards business and life? [09:44]
• Discover how XMR charts give you an understanding of variation [12:33]
• Navigating the significant and insignificant changes [14:31]
• Can your business grow by only talking to customers? [16:40]
• This is how you can get an exceptional variation [20:21]
• Find out how failure builds intuition [24:48]

To learn more about Cedric Chin and his work, check out the below websites:

https://commoncog.com/

https://xmrit.com/

https://shop.xmrit.com/metrics-masterclass 

Transcript:

0:00  All right, what's up, everybody? This is Daniel Barrett, and this is the very first, the inaugural interview episode of the Dan Barrett podcast, where we are going to talk about building awesome businesses and living awesome lives. And I could not be more excited to open this podcast up with this episode, because this week I am talking to Cedric Chin from common cog.com and also one of the brains behind zemrit, which is spelled x, m, R, i, t.com, now the reason I am so excited to start with this podcast is because Cedric is, in my opinion, a generational business writer. I think he is probably the most cogent, sort of coherent, rational voice in business operations today. He is someone I have been reading and looking up to for a very long time, and Cedric's articles about statistical process control, which, by the way, if you just tuned out because I said statistical process control, stay with me, because we're gonna, we're gonna get in some wild places in this conversation. But his articles about W Edwards, Deming, about Donald Wheeler, about statistical process control completely set my brain on fire. And the processes that I either pulled from Cedric's articles or pulled from the books that Cedric referenced, completely changed the way I ran my business, actually the way I live my life like and you will hear Cedric and I talk about the way that these sort of understandings of how the world works, this sort of understanding of how business and people and just the universe around us vacillate around us, and this weird cosmic, super variation, like the way You start to see that and understand it has absolutely wild ramifications for how you live your daily life. So if you have a business, this is going to help you run a better business. It is going to help you be more effective. But if you don't own a business, it's actually going to help you be more effective in your personal life in how you think about problems and how you think about literally just when you step on the scale in the morning and you feel bad because you gained a pound, this is going to help you with that. 

This is one of my favorite podcast conversations I have ever had, and I am so excited for you to get to know Cedric chin, from common cog.com you should absolutely go there. And from zemrit.com that is x, m, R, i, t.com, again, one of my again favorite websites, but we will get into why in the interview. So without any further ado, let's get into my conversation with Cedric chin. What's up, everybody? This is Daniel Barrett, and I am here with Cedric Chin from, of course, common cog.com if you've read probably I was going to say this to you, Cedric, and we were talking off the line. I didn't quite say this. What, in my opinion, a generational business blog, absolutely incredible. But also one of the minds behind zemerit.com which is x, m, R, I t.com Cedric chin, welcome to the podcast, my friend. I really appreciate having you here. Thank you for having me on. It's, uh,

3:56  I was super pumped. We've already been talking for like, 45 minutes or whatever? Yeah, because we have a lot to talk about, but I wanted to start with this question. There's a million ways we can go, but I wanted to start with your first interaction, if you remember, it with an xmR chart, and we'll get into what these are and why they're cool and why everybody should rush out and use them in their lives. But I'm curious, like, what is the story of your first sort of exposure to this idea of variation in business and everything that that entails? Ooh, do you want the story of the like, connect like, my first experience with these ideas, my first experience of an xmR chart. Because those are two very different things. Okay, all right.

4:48  Well, let's start with these ideas. Let's start with your first interaction with the day these ideas. When did this first start to like crawl into your mind as something that was, I mean, to be honest, right, something that you've dedicated a lot of time. Mean a lot of effort into expounding into the world, right? So when did you first kind of get the sense that that was going to happen? So I was very interested in figuring out how companies are data driven, and the story for like, why is, like, a bit convoluted. The short version of it was that I did content marketing for a bi company. And when you do good content marketing, you have to really understand your target audience. And so I really understood data analysts. My joke was that if you know to the content marketing team, that if you have a target persona, a data analyst or a data professional of some kind, sitting down at a bar, and you're sitting down at a table with them, can you get them to complain about their job in, like, within five minutes? Because if you can, then you know that you really understand them. But, yeah, I talked to a whole bunch of data professionals in that, you know, whilst doing content marketing for that business intelligence software company, and I did not know what a good data driven company looked like, right? I saw many examples of data people working in dysfunctional, bad, not data driven companies where data is more likely to be used as a political weapon, you know, by some executive trying to defend their turf, but not really used to improve the business. And so shortly after that, common cog is it's a niche publication, but it's fairly well read by people who are good at business, and one of the authors of working backwards, which is this book about how Amazon does what it does. So this is the person's name is Colin Breyer. 

The book was written by two people, Colin Brian Bill Carr, both early Amazonians, and Colin Bryer was Jeff Bezos, the second shadow. So Andy Jassy, who is the current CEO of Amazon, was the first shadow, and Colin was the second. And Colin reached out to me because he saw my review, my summary of working backwards. He saw that I had a technical background, right? I graduated with a computer science degree, and I can code. And he was like, Oh, you clearly understand what we're doing. Would you be willing to come and help us explicate the chapter six of the book, which is the weekly Business Review, which is basically how Amazon uses metrics and data in their operations. And I said, Of course, yes. Like, please. Like, it was amazing. Like, I got paid for it. But more importantly, every week, I got to speak with Colin, and I got to learn from him. And near the end of the project, he sort of said, offhand, right? Oh, you should go read Donald Wheeler, understanding variation, because a lot of the ideas in Amazon actually come from that body of work, but he didn't save that body. We just said, go read Donald right? It's pretty good book. I love him like you know, so I did not read Donald Wheeler's understanding variation immediately. There was no ebook version, so you have to go buy it, as you probably know you I know you bought it hard cover version. Yeah, I got the hard cover in my library right now. Yep,

7:37  it's a very small book as well, and it only takes you. So if anybody's listening and you want to go check this out, I I bet I've probably caused exceptional variation in Donald Wheeler's book sales multiple times. It's only going to take you two hours. I swear. It's 150 pages. It's really easy, easy to read. And the reason it's very easy to read was because it was actually from a 1993 presentation that he gave to Dupont. And these were business managers. These were not statistical, you know, they were not sophisticated people. I'm sorry, mathematically sophisticated people. They were smart people, but they were just business managers, right? So, so easy to read book, very little math inside. And it took me, I think it was like three, four months later. It was the start of the year, January. I was in the middle. It was probably four months later. I was in the middle of my Judo experiment. I don't know if you you know about it. So I went off and I did some judo for four months. I trained full time. And I remember reading it during that period. And I was so mind blown. I was like, Why didn't I read this earlier? The book basically contains, it's basically just about one chart. It's about something called an xmR chart. And the chart is life changing. You will never look at reality the same way. Again. It is very deceptively simple, but then once you start using it, it just, you know, it reaches inside your brain and rearranges your mental furniture. And the XML chart is actually the thing that is necessary to get the wbr to actually work, because the wbr depends on a understanding of variation that most people don't have, and that is actually really easy to understand, like when you know, I've taught many people these ideas already. One of my teammates was saying that, why has this not been taught in high school? This is these ideas are so simple and so powerful. They enable you to, you know, improve anything your life. Maybe not your marriage, but, uh, maybe your marriage. I

9:30  don't, I think your marriage I love, not gonna lie, I have a marriage section in my spreadsheet. I don't know if I'm supposed to, but I do. That's good to know. You know, it's so easy and it really changes the way that you approach improvement in business and in life, and it's already changed the world. I mean, it's the XML charts were behind the quality improvement when in the Allies building up to World War Two. It was behind a lot of the scale up of manufacturing in the US leading up to World War Two. It was also the. Key idea behind damming W Edwards Deming, who is the main person who taught this in the post World War period. He taught it to 80% of the Japanese industrialists, and basically the Japanese economic miracle, and what we now know today as lean manufacturing from the Toyota Production System. It all came from just judicious use of the XML chart, right? So it's like, Why didn't anybody tell me this?

10:26  I really is like, it's like discovering that everybody, yeah, it's like discovering that everybody has a superpower that they just didn't bother to tell you about. And it's like, why aren't we all, you know, using this, it's funny. You said that the book is really all about one chart. I still remember I read the book. I read understanding variation on a plane at your recommendation, because I'm a very frequent, common cog reader and subscriber and all this stuff. And bought the book, read it on a flight. Was an international flight, so they had enough time to finish the entire thing. And in that sitting, and I remember my friend was sitting next to me at the time, and he said, Oh, what are you reading? And I said, Oh, it's this book understanding variation. And he's like, What is it about? And I said, chart. And he's like, Oh, it's about charts. And I said, No, it's about chart, like, one chart. And he was like, you know, he gave me a look like, he was like, oh, okay, well, I'm gonna go back to my movie or whatever. Like, it just was not that did not pull him in, you know. Okay, so let's talk about we want to get to, by the way. And if you are curious, if anybody's listening to this, and you are curious about seeing xmR charts in action, of course, zebra, which is XM R, I t.com, is Cedric's tool to help you make these charts very easily. You can go there and see one right now if you want to picture what we're talking about. But before we get there, I want to talk about variation. You said that that xmR charts kind of give people an understanding of variation that almost nobody has. And I totally agree. I think that people right, they're human. The human brain is narrative driven. We view things as narratives, whether we want to or not, and it's a very easy for people. If they see a number go down, a number go up, you know, in their business, in their life, whatever, we ascribe a lot of meaning to that. So let's talk about variation, and let's give people get, try to give people a little bit of a window when you say xmR charts, give you an understanding of variation that most people don't have. What do you mean by that?

12:36  Right? So here's my standard spiel for why understanding variation is important this, this seems so dumb, right? This is, this is going to seem really dumb, like, Oh, my God, two adult men are talking about understanding variation. When you step on a weighing scale, you have, you know, you have a a number that shows up in your weighing scale. You know, and I know, we all know this deeply in our bones that the number is not going to be the same. When you measure it today, at 8am and 6pm It's not going to be the same tomorrow. There is going to be wiggling. If you chart it out, you know, on a on a line chart, it's going to wiggle, right? And if you eat more and exercise less, at some point, the wiggling will be go higher and higher and and then at some point you'll be fat, I mean. But the problem with measuring every day is that, because it wiggles so much, it's very hard to say, sort of say, like, today, I am fat. Today is the point that I've crossed the line of no return, right? But, you know, conceptually, it must happen, right? Because you all of us have had the experience of, you know, we're either measuring our heart rate or we're measuring our weight. You know, something very simple, and we know that the numbers will change because there is the fact of life, there is variation. There's variation in everything that we that we do, and this variation is a very big problem, right? It's a very big problem because when you're trying to look at some set of numbers, the numbers are going to wiggle. And it's very difficult to say this wiggling is normal. It's just, you know, there's nothing going on. It's just random, routine variation, like, the same way that you step on a scale at 8am and you step on a scale of 6pm you gain a bit of weight. That doesn't mean anything, right? 

Similarly, most numbers in the worry world will have this sort of wiggling that doesn't actually mean anything. It's just random variation, right? And then sometimes there will be a change, and the change actually matters. And you need to be able to tell when the change matters and when the change doesn't. So just because sales went down by 20% last month doesn't necessarily mean that something bad has happened. It could just be normal, wiggling variation. The way to check is you have to check at your sales, the rate of sales for the last 12 months or so. You need to collect a bit more data and sort of say, hey, is this change significant? Do I need to investigate is something bad going on in my business? And you need to be able to differentiate between routine variation, which is normal. Wiggling and exceptional variation, which is something is really going on. We have to check, right? So this sounds so bizarrely dumb and simple, like, like your friend will be okay. Let's go back to the movie. But if you think about it, if you are not able to differentiate between routine variation and exception routine wiggling and something's important going on, you can't make sense of data. You are data illiterate. There is no use to look at a chart, right? Because you got when you open a dashboard, a Google Ads dashboard, or a Google Analytics traffic dashboard, you're going to see a lot of wiggling, and you're not able to sort of tell like, hey, is this good? Is this bad? Did I do something that worked? 

Right? And if you try to do an experiment, and you say that, okay, this experiment should increase our revenue. And you look at you open your revenue chart, but most people don't even have the revenue chart, right? They just have spreadsheets. But say you're smart enough to go and, you know, take the revenue and put it on a graph, a line chart, and it wiggles. And you're like, oh, did it work? The thing that I did three months ago. Did it result in a change and increasing my revenue? Or is it just, you know, like, we do business as usual, and we just hope that, you know, the number goes up into the right over time, and and then one day it doesn't, and then you don't know what to do, because you don't know what actually drives that number. So I hope this sort of frames a bit of the problem, right? Like, if you're not able to understand variation, and every metric, every number, has variation, then you're not able to use numbers at all in your life, in your business, and that basically removes a very powerful source of knowledge from your hands. You're forced to rely on talking to customers, which is quite powerful, and you should do anyway, but there's a lag. There's certain things you can't find out, but just by talking to customers, and you're forced to rely on your gut instinct, which, to be fair, you can get good people can get very good gut instincts by just putting in the reps over many years. But you want to do better than that. You want to be better faster, right? So numbers are sort of like an additional way to do that. Okay, that's my spiel.

16:55  I That's an excellent spiel, and I think you're absolutely right, right? Like we've there's never been more data. But having data is not the same as being able to use it in a way that really makes you better. And one of the things you've written about quite extensively is, like you said, companies how they can actually be data driven. So let me ask you about that. Like, okay, let's say somebody buys Okay, cool. Everything has variability. Okay, there's up and down in my numbers and an xmR chart, which we haven't really gotten into, like, the logistics, and we could talk about that maybe, but an xmR chart is basically the whole point of it is for me to understand which of those ups and downs is important, and which aren't okay. So we've, that's the the sort of setup, how do businesses, or how can even people, just use that jump off from that point in order to, like you said, make your life better, improve your business improve. You know, we're Cedric, you and I are going to remarket this as a way of improving marriages. Okay? We're, this is what we're doing. This is now a relationship podcast.

18:06  You know, my wife sometimes say, is that really good, like, that dish, or is it, like, routine, variation, good, like everybody has every now and then, you're like, yeah, it just was amazing. But like, So, what is the practice of using this like so how do people let's say, Okay, we get xmR charts are cool. We get variability. How do we jump from that to my business is being more successful over time? Maybe we can. One of the things, by the way, I love about you, and I love about your approach, is your very big on case studies, very big on stories that sort of illustrate a lot of these concepts. So maybe let's talk about a specific example of a time where we can use this to make something better, sure. So the basic setup that I just gave you the spiel is that XML charts are this tool that can help you tell between random variation which is wiggling. This is something being meaningful, right? So it allows you to separate signal from noise. The embedded in that. The trick there is that once you have a tool that can separate signal from noise, you can start doing trial and error, right? So humans are very good at doing trial and error. You climb a tree, you fall off. You're like, Huh, okay, assuming that you don't die, you break your arm. Let's not do that again. Let's, let's climb a tree a different way or and we learn how to walk as toddlers, as babies, right? Like true trial and error. 

We just kept falling and we kept trying again. So human beings are very good and trial and error. And if you give them a tool that allows them to interpret a wiggling metric and says that, ah, this, the metric has actually changed at this point, right? You're able to start doing things like, Okay, I'm going to change my sales process this week, and we're going to wait six weeks, or we're going to wait six days. Usually, most sales processes, it takes about a it takes a weekly basis of measurement to sort of see if it changes. So we're going to wait six weeks and then we're going to see if this the results, the impact of that change. The sales process has impacted the metrics that we care about, and if it doesn't show any signal, the XML chart doesn't lie, right, doesn't show any signal, then you can't lie to yourself and say that, Oh, that improvement work. And then you're like, okay, so that improvement didn't work. What does? And you keep trying again and again until something starts working and you see an exceptional variation on the XML charty So you see a signal. And you're like, oh, so, improvements that we try in this category, right? This style makes a change, but everything else we've tried doesn't make a change. 

And then suddenly, you know your entire company who's following you along on this trial and error journey starts to build knowledge of what sort of things might work and what sort of things might not work, and then your intuition improves, right, very rapidly. Whereas in the past, if you didn't have an XML channel, you didn't have this ability to do rigorous trial and error, you will still be doing trial and error, but you'll be relying on gut feel. It might take a long time. It may require you to talk to a customer, you know, six months after you've done the thing, and then the customer said, Oh, you got me because of that promotion that you did. I said, Oh, okay, that works. We should try that. But you've six months have passed, right? Which, if compare six months to six weeks, how many more experiments could you have run to improve your business in those six months? If you had your answer in week six, right, instead of week whatever it is, right?

21:16  I'm happy in that sense, right? Like, yes, yeah, exactly, yeah, yeah, you can improve much faster. And in fact, if you have a process that shows change on a daily basis, right, and you put your daily data on an XML chart, then you have 300 say, 350 opportunities to improve in a year, or 300 Yeah, if you improve on a metric that changes every week, so you improve, you know, once a week, and you have to wait six weeks minimum, because six weeks minimum is the minimum number of data points you need to tell whether your process changes actually worked. Then you can only improve. Maybe, you know 50 times a year, right? And if you try to improve something, a metric that you measure every month, and you only have 12 opportunities to improve every year. So obviously shorter cycle times is better. But of course, some business processes take a long time to change, so sales, you can't really accelerate it to daily unless you have like daily sales calls. Most businesses have a sales team, and it takes about a week for sales to change, maybe a couple of weeks. But yeah, this is the basic idea. This is That's it. That's the thing behind the Amazon wbr. That's the thing that allowed factory workers in World War Two and factory workers in Japan to do trial and error until they came up with the Toyota Production System. Right? It's just this thing that allows you to tell the thing that I've worked on, the thing, the thing that I've changed in my business, in my process, has actually resulted in a change. And the reason I know that for sure is because I see the signal in this XML chart, in this metric that I care about, it could be revenue, could be marketing, qualified leads could be whatever you care about. And that's why we that you can apply to marriage, probably, if there's something measurable, like number of dates or an NPS score, yeah, be

22:56  careful there. And this is no, don't do anything dynamite to a bunch of, yeah, you know. But I mean, and I think just to underline this, underline this point, which I think is, is such a good point that you made the xmR chart is a way of making sure you cannot fool yourself, because it, in my experience, it is so common. I've done this. I've had clients that have done this like, it is so easy to do, you know, say you're going to experiment, you're going to try something new, like, in your sales process, I'm going to try a different closing pitch, or whatever. And to think to yourself, yeah, this is definitely working. And to feel that and to perceive that, and then when you put it on an xmR chart, there is nothing there. It is shocking how easy it is to do that. And the other thing to point out is that impact that you mentioned of like the compounding effect of actually finding things that work and then building on top of them is something that I think people have a lot of heart it's very hard for people to appreciate. I'd have a friend who would always say it this way. He would someone say like, well, how fast can you get? You know, how much? How quickly can you get better at something? And he would always phrase it. He would say, slower than you want, but faster than anyone else thinks possible. And the point being that, like every individual test, feels like it's taking forever. It's like, oh my god, I have to wait six weeks or, you know, but hitting and knowing what works and then building on top of that means that at the end of the year, you are massively improved over where you started, right?

24:42  Yes, so, and it's not just that. It's also when you fail, you it builds your intuition. It tells you, okay, we've tried that. Maybe that category of stuff isn't going to work. Let's, let's, let's try something else, right? So at the end of the the year, as well, everybody in your team were sat down for this process as you. Gone through this has a better intuition of what might work. They can't articulate it. They can't talk about it, but they feel it in their bones. And so you've basically, if you are very experienced business people, and you, sorry, business person, and you have a group of people that's maybe not that experienced XML charts, forcing them to go through this iterated process with you, where your instincts are better than them at the beginning, by the end of the year, you might find that they have caught up with your instincts, right? They have the same feelings that you do. I mean, that that is

25:27  such a major point, it is such a common problem for someone to say, and I've said this. I mean, we were talking about this before the before the the podcast, like saying, How do I give my team my gut feeling for where problems are going to occur or what's going to work, right? Like, how do I give that? It's such a common thing for people to say, like, well, I can't replace myself because, you know, maybe they don't say this explicitly, but essentially, I'm the smartest person in the room, right? When, in actuality, what they really mean is, like, I just have an intuition for this thing that's been built up over many years of experience. So for a while, was a joke that I would no one thought was funny but me, but I thought it was funny every time where we would make a standard operating procedure. So it's a step by step walkthrough. Here's how you do this task. And I would make this whole this 14 step thing, and then the 15th step would be, you know, and if none of that works, rely on your 13 years of experience. And it was just like, No, I thought that was funny, but it's like this kind of the hidden step in every process, right? So that's a massive sort of rising tide for every team. So let's Okay, so let's talk about zemerit specifically, and it is pronounced zemerit. I'm pretty sure this is spelled, x m R I t.com, anybody can go there right now, x m R I t.com, and start to use this tool. Literally, start to use it for free. It is absolutely incredible, super fast, super easy. You can start playing around with your own number. So highly encourage everyone to do that. Tell me a little bit about why you decided to create this tool. What was the process of because? Common cog, so again, common cog.com, that's the blog you've been writing for many years now. Highly successful, really insightful business writing. What was the process of deciding to sort of transition into, essentially, software project creation.

27:25  Yeah. Well, for starters, you read the book, you read the series that I wrote, and then you tried to do it in Excel, and it sucked. It really sucked. This is very annoying that that is the common experience that everybody has when they hear about XML shot. They're like, Oh my god, this is amazing. Let's go try it. And then they find an Excel template, or they find a Google Sheets template. There are Google Sheets templates out there, right? But then the obvious sort of thing is, like, this is this really stinks, right? Like, and if you're using it operationally, which means that every week, you're looking at some set of metrics, and hopefully not just one metric or five metrics, you maybe you need to look at least 10, right or 20, because your business, there are a whole bunch of metrics that you care about, even the simplest business, like common cog for example. Now we're up to 75 metrics, but, I mean, we can talk about that separately. That's the Xamarin metrics and common cog metrics in one deck. It's really painful to produce XML charts by hand. It's very pain. It's less painful to put it through spreadsheets. But if you're doing it operationally every week, and you're looking at 10, at least 10 metrics, you need something better. And so immediately I was like, Okay, I need to go find a programmer. I am, I am a software developer. My training is in running software teams. I'm not going to code because I other things that better, things that I can do, like, you know, write more essays or experiment with the business but and so I found an intern from a local university here in Singapore, and basically I said, Okay, over this, the over this summer, this three months, we are going to iterate until we find a an easy to use XML chart tool. 

When I got in to read my essays, and then we started iterating right at some point, we got to something where we could enter data. It was very rough, very ugly, very difficult to use in the beginning, but we iterated on it through trial and error. And eventually, I'd say, by the two month mark, we had something that was pretty close. Actually. It was still not as easy to use. We relied on uploading a CSV file, and then at some point, I brought Sam in. So Sam is my collaborator on Xamarin. Sam came from manufacturing. He cut his teeth in Six Sigma, right? And he was like, CSVs really suck. This needs to if we want this to spread and we want this, we want other people to use this to test this, so we actually validate these ideas and make it come real using their own data. We need to make it easy for them to just paste data in, yeah. And then at the end, you know, the end of the summer, basically the bulk of Xamarin had already taken shape. And then we did a round of four rounds of user testing. And so basically, what you're getting for free. Open Source, so you can steal the code as well if you know the program is something that has, you know, been integrated on for maybe close to six months, and we use it every week in common cog to run the business. So it's been battle tested, and right now we are planning more improvements, right? Because it's also not good enough for some things. But, yeah, it's, it's 100 year old technique, and there has been no serious software attempt to make it easy to use, and we wanted to change that. And so we decided to make it free and open source, because we want other people to steal these interface innovations that we've come up with and adopt it and put it in other pieces of software. And we also sell a paid course, which you've paid for, Yep, thank you for your support, which just pays, basically, it's, it's three $60 it pays for the continued development of the tool. And, yeah, we, I know Sam and I, we work on this because Sam was very excited, and was that he was very excited about, what's that?

31:00  XML charts. He couldn't believe. He couldn't believe that it worked outside of manufacturing. He was always taught to believe that it only worked inside manufacturing. Here I was sort of digging these ideas, saying that Amazon had put it to use, right? Amazon had gotten huge results from using it. Or descendants of the ideas is they don't actually use not every part of Amazon uses XML charts, because the secret is, once you understand variation, if you look at your data enough, you can develop an intuition for what is exceptional and what is routine, purely by looking at data like your brain would just like build this intuition. But for the vast majority of us, we don't look at data every day. We don't have a boss breathing down our necks like we would if we were working in Amazon. So we need some kind of assistance to sort of bootstrap our intuition. And XML charts, is that answer? So Sam was excited that it worked, and then now he uses it, and he works in a big tech company. He uses it in his big tech job. He's spreading the word inside there. So he also wanted, was very happy when we made the decision collectively to open source it, because that mean that his company could use it, and he now wants to. So he and I obviously want this, you know, to spread. We want people to know about this. It's just ridiculous that that's like, it's 100 years old.

32:21  Hey guys, hope you enjoyed part one of this episode. It's just too good to limit to one show. Join us next week to hear the rest you.