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Success Has Ingredients: Garbage In Garbage Out

Success Has Ingredients: Garbage In Garbage Out

Summary


What are the "ingredients" of success, intelligence, and skill? What are the constituent parts? The source materials?

Most people believe success, intelligence and skill are natural things you're either born with or without and there's nothing you can do to change it. They're wrong.

Success, intelligence and skill, like everything else in the universe, have "ingredients". The same way a chemical compound is made up of elements, success is made up of a different breed of elements. 

There's always building blocks, you've just got to know where to look! This video shows you how to find them, in everything! 

If you've ever wondered why some people are considered successful, intelligent and skilled, while others aren't — this video will show you how to reverse engineer it back to its constituent parts. (this is a valuable skill you can use for life!). 

Check out the video and let me know what you think in the comments section below?


Here's what we cover: 

1. The game-changing insight I learned from 436 job interviews over the past 5-months. 

2. How to determine whether somebody is "smart" on a 30-minute phone call by asking simple questions. 

3. Why you should focus on somebodies "inputs" to thoroughly understand their true "outputs". (this is fascinating!)

4. The secret of the worlds best chefs: Why the art of a meal (output) is in the sourcing of its ingredients (inputs).

5. The social network graph of all the worlds most famous geniuses and why genius must be input for genius to output. 

6. Why talented software engineers have a saying: "Garbage in garbage out" (GIGO). It's importance, and what it means...

7. Why you must focus on your inputs if you want to influence your outputs (will change your life).

8. How to filter out bad inputs, and discover and optimize for good inputs. (from friends to courses, to habits, to books, + more).


Resources mentioned: 

1. Social Networks of Famous Geniuses by Dean Keith Simonton — Get network image/diagram here.


To Your Success!

Sam Ovens & the team at Consulting.com.

Transcript / MP3

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Hey everyone, Sam Ovens here. And in today's video I want to talk to you about the ingredients of success and why if you put garbage in, you'll get garbage out, right? So first of all, why this is important and why you should listen to this video. So recently I've been doing a lot of job interviews, and I've honestly been talking to about 20 to 30 people every single week. And I think I've talked to about 436 people in total so far. And you know, there's a lot of job interviews and what I'm really looking for is, you know, really smart people, really talented people who are hardworking and who have got what it takes to join our team, and you know, solve the challenging problems that we're trying to solve. And on these job interviews, you know, I am tasked with basically trying to determine if somebody is smart and hungry and hardworking and has strong character, and I'm trying to just determine that in 30 minutes over the phone with questions. All right? That's quite challenging. It's more challenging than it sounds like because there are a lot of false negatives, a lot of false positives. And most of the questions I asked in the beginning were to do with somebody's outputs. And let me show you exactly what I mean here. So let's say we have a person here who I'm interviewing, right? Now, they've got outputs over here, and they also have inputs over here. All right? Now, what are outputs? Well, outputs in this case could be, you know, work that they've done or skills that they have, or experience that they possess from their previous position or their career, right? These are the typical things that people ask questions about when it comes to job interviews, right? They ask all about the outputs, and recruiters do this too. They ask you like, what skills should this person have and what type of industry should they have worked in? And also what type of companies, what type of position, right? They're trying to get a read, and they're trying it to get a signal and they're trying to optimize and filter, for people who match the output requirements and why? Well, it's probably the most simple way to do it, right? Like, oh, this person is skilled at that and this person sees this skilled at that, therefore this person must be a good fit. Right? The problem with this is that people can easily lie about this sort of stuff and they can easily mislead you. You know, if you ask someone, do you have experience with X? And they can tell you, "Yeah, I've got experience with X. I worked on this project or that project." And it's very hard then to decipher like, does this person actually have experienced or are they just telling me that they have experience, right? It's quite difficult. And for as long as I was asking questions about somebody's outputs, I was not able to get an accurate read on the candidates I was talking to. And then something, you know, really shifted. And I started to remember this documentary, this TV series called Chef's Table, right? And I watched the first, like two episodes of it because I was just kind of interested and curious. I was like, well, what makes a really good chef? You know, there's chef's that suck, that make really disgusting food, right? And in there's chef's that are best in the world, and what makes, what differentiates these two objects, right? What is the difference? And I was like, maybe these people are really good at preparation. Maybe they've got different methodologies, different tactics, different sequencing of different actions they take. And I was really quite curious. And so I started watching this documentary and within the first two episodes, I already had figured it out. Like what created the world's best chef's was their ability to source ingredients, right? And so what makes the best tasting food? The best ingredients, right? And so really it was this same thing. Like, if we look at here, if we have, you know, if we're looking at the world's be chef's and then if we have meal here, right? That could be, wait, let me read you all this. So world's be a chef needs put them here, this is the chef, and then let's say the output is the meal. Well, what are the inputs, right? And the inputs would be different ingredients. Oh, that's Ryan Green for ingredients. And so the best chef's in the world were the best at sourcing the best ingredients, and they took this to such an extreme that most of their time was actually spent out there on the road, traveling around and trying to find the best ingredients. Some chefs took it to the extreme that they started their own farm. I'm not joking. They started their own farm and when they were for a farm, what do you think they were doing? They were looking for the ingredients. What ingredients makes a good farm? Well, what are the constituent parts of a farm? I mean, we've basically got land, earth, dirt, and so what makes good land, right? And so it comes back to what crops have lived on this land. And also what is the climate and the weather patterns and things for this land. And also what are the, what historically has this land had fit into it? Like what fertilizers, pesticides, chemicals, things like that, right? So even when we're trying to find a good farm, we look at the inputs to a farm and we look at the quality of the land, the quality of the dirt, and then we look at the quality of the other objects on that land. And then we're able to get a good farm, because it's got good land. And then once we've got a good farm with good land, then we want to raise animals on it and the best way possible. And then we need a good farm with good earth, so that we can grow good plants on it, so that the animals can eat the good plants. Right? So what makes a good animal? Well, it's their food, what they're eating day to day and their environment that they're living in, right? And so the environment and the food is the inputs of an animal and that determines, you know, the how good that food is when it ends up on your plate. And so a lot of these chef's, they really focused and obsessed about inputs. So while a lot of people, including myself, used to think that, you know, a good chef, what makes the best chef in the world? Well, I thought it was probably some of their methods for preparing a meal, right? Probably like some kind of like chopping technique or I don't know. I really had no idea, but I thought it would probably be something to do with their technique and their method. And upon further investigation I found that to be false and really what it was all about was about the ingredients, the inputs. And so when I was doing these interviews it took me probably 300 interviews to realize that. So I was like, this is giving me flashbacks of this scenario here. You know, what makes the best meal are the best ingredients. And really it reminds me of a term that's commonly used in the software engineering world and that is garbage in, garbage out, right? And what it basically means is that outputs derive from inputs. And so here if we have a system, or could be anything. And then here we have inputs and then here we have outputs. All right? Then the quality of the inputs here determine the quality of the outputs over here. And if you put garbage in you'll get garbage out. So if we have, and why this is common in the software engineering world is because sometimes people believe that if you create a really good system, but let's say we have this really good tracking system, it's got AI, machine learning and all of these other bloody buzzwords in it, right? And so it's this mobile optimize, mobile first, crypto currency tracking optimization, machine learning algorithm, artificial intelligence, bitcoin engine, right? Some kind of crap like that. So they think that, you know, because we have this amazing system, it can do anything. It doesn't even matter what inputs you feed it, you can just give it nothing. You know, just put just a bunch of made up numbers into it and it will tell you the truth, right? No such thing exists, well, it doesn't matter how good the system is, if you feed it garbage, it will output garbage. So if you input X, you get X. And even with a lower quality system you can input, like you can input good data and you can get good data out, right? And so a common fallacy in the software engineering world is forgetting this, it's forgetting that the quality of a system's outputs are really fundamentally determined by the quality of its inputs. And sometimes, well actually quite a lot of the time, almost all of the time, your time as an engineer or a systems architect is better spent sanitizing inputs than it is working on fancy processes to deal with disparate sources of messy and dirty inputs, right? Because, of garbage in, garbage out. Now, why tell you this? Is because we come back to this. So I'm doing these job interviews and I do 300 of them or something and I've been asking questions about outputs. Like, do you have this skill and do you have that thing and all of this. And I realized that this was a really poor way to measure and it was a really poor way to interview people. And that reminded me of this documentary called Chef's Table. Where, you know, the ingredients of the food determined the quality of the meal, right? And the world's be chef's were the best sources of ingredients. And so then that reminded me of the garbage in garbage out thing. And then that led me to do a little bit of research. And what I was really interested in was the social networks of geniuses. And so I actually found a guy, and his name is Dean Simonton, D-E-A-N S-I-M-O-N-T-O-N. And this guy Dean, he spent quite a lot of time studying and analyzing, like historic documents and journals and records from the world's greatest geniuses like Einstein and Newton, Galileo and Copernicus, and all of these different geniuses. And what he was interested in was how were these geniuses interconnected through a social web or a social graph over time. Right? And what he found was actually quite fascinating, and I'll draw this for you very quickly. What he basically found was that geniuses are created by their inputs, right? The same thing occurs. So when he looked at Isaac Newton, I'll put Newton here. When he looked at Isaac Newton, he wanted to see, well, who were the inputs of Isaac Newton? What constituent parts or raw materials or source materials and ingredients were consumed by Newton's mind, and then processed, and mixed together to output the genius that was Newton, all right? And so he studied this and he looked for relationships between all of these different geniuses over time. And what he found was fascinating. He found that Newton had roughly 14 idols, right? And if we come out here, we're looking at idols and he found that Newton was, he learned a lot from Bacon, Copernicus, Galileo and Kepler, and about 10 other famous scientists and people who had come before him, right? These were incredible and influences to Newton. And he consumed their work, and he got to really stand on the shoulder of the giants that came before him. And that's why there is their quote that Newton, he himself said, and he said, "If I have seen further, it is by standing on the shoulder of giants." Right? Well, that's what he means by this is that in more simpler terms, Newton could have said, garbage in, garbage out, outputs derive from inputs. My output, which you believe is genius was derived from input of genius, all right? And so Newton's inputs were previous geniuses. And then what's interesting is that Newton's outputs actually created more geniuses. So if we had now to look at people like geniuses who came after Newton, they had been influenced by Newton. So if we look at Einstein, so Einstein's greatest influence had been Isaac Newton's work, right? Even though Isaac Newton was hundreds of years before Einstein, Newton was the greatest influence on Einstein. And so how was Einstein so smart? How was he such a genius? How did he do the things he did? A lot of people tend to think, oh well, he was just a genius. He was born with it. You know? And that's not true because at birth, I'm sure if anyone tried to even ask Einstein a question, he would not have been able to comprehend it or respond. Because at birth, Einstein did not even understand English or could speak, right? So he most certainly did not know like all the things that he did later in life at birth. And so, how did he become like that? Well, inputs, right? What were his inputs? Well, he was influenced by Newton, who were Newton's inputs, right? Well, he was influenced by Bacon and Copernicus and Kepler and Galileo. Right? And so it doesn't matter what we're looking at, it doesn't matter if we're looking at a computer system or a software or a tracking system, or if we're looking at just a person's ability to make a good decision, right? If I could be the best decision maker in the world, but if I get bad information that's inaccurate, then I'm going to optimize the best course of action given the information that I've been fed. And because the information I've been fed is wrong, it doesn't matter how good I am at optimizing these variables, my decision, even though I think I've absolutely chosen the best course of action, it is wrong. Not because of my ability to make decisions, but because of my ability to gather the best information, e.g. inputs. Right? So it doesn't matter what we're looking at, outputs derive from inputs, garbage in, garbage out. And this, again, brings me back to these 300 interviews that I've been doing, trying to find really smart people. And so I was asking these questions about the outputs and then I had a little flashback and I was like, "Oh yeah, that Chef's Table documentary, where the ingredients created the best meals and garbage in, garbage out, from the software and systems world. Oh yeah," and then I discovered this social network of the world's most famous geniuses. And then I realized that I've been looking at the wrong thing. I have been looking over here at these people's outputs and I should know better, I should be looking at the inputs. So I decided to start asking questions about this instead of this. And you're probably thinking, "Well, what sort of questions do you ask to determine inputs, right?" Well, what sort of, you know, I started thinking back to how did I learn the things that I know and I can always trace them back to key objects, right? So there is different projects I've worked on where I've had different experiences that have taught me a lot of lessons. So it could have been projects or problems or challenges faced, right? It could also be mentors and mentors could be different people that I worked with on my team, or it could be people who I paid to join a mastermind, or other people who I've come into contact with. And then there is also books, so books can be great sources of information. You know, there are a few books that have influenced my life in a massive way, more than any individual human has, right? And then there is also courses, you know, there's online courses I've taken, mastermind groups, things like that. And then there's just friends and really your network, your local network of the people around you. So like you're, the five people you spend the most time with and talk to the most, there's those people. And really these other things that shape like your ability and your intelligence, right? And a lot of people tend to look at intelligence as like, "Oh it's just this person's brain and their ability to process stuff," right? That's kind of true but not really. Mostly it's because they've had really good inputs and they've been exposed to really good inputs. And when you put good things in, good things come out just like we saw in the social network of genius. If you put genius and genius comes out, you put garbage in, garbage comes out. Right? Now, what I'll do is beneath this video in the resources section I'll include the actual social network image or diagram for Newton, and for a couple of other famous scientists and some of the world's greatest geniuses, so that you can see this, the actual work that I looked at here, cause it is quite interesting. So that'll be beneath the video in the resources section. Now we get back to this. So I started asking questions about inputs and I started asking like instead of saying, "Do you have the skill and are you good at this and can you do this," right? Which I got really bad answers before, I started asking, "Who is your idol when it comes to field?" Right? So, "Who is your idol when it comes to software engineering?" Or, "Who is somebody that has influenced the way you think about and the way you write software?" Right? So that was one of the questions, and this was a really fascinating question to ask because one, you couldn't really lie about this question. When I was asking the outputs one, do you have the skill? People would say yes or something like that, right? And it's very easy to say yes, but when I say, has anyone influenced you, the person could say no or yes, but I can't remember anybody's names. Or they could say yes and they would be able to recall the exact people who had influenced them perfectly by name and what things they'd learned from each person. Right? And so this is when this process got really fascinating for me, because the people who weren't very good at all, they could never recall any names. Some said they weren't influenced by anyone or some said, oh, they've been influenced by a lot of people when they can't really recall any of their names. And just think about that for a moment. You know, I mentioned that you've been in this specific example, some of these people had been software engineers for 20 years and they couldn't tell me a single person's name who had influenced them and their work. Now, if someone can't recall a name of somebody who has influenced them and they've been doing it for 20 years, this person obviously doesn't care. All right? And so I found a very strong and direct relationship and correlation between the clarity and the ability for somebody to recall who has influenced them in their work and the way they think, and the person's like objective, output and raw skill level. All right? Another question I asked was, "What books have taught you the most about X?" And X could be field. So it could be, you know, what books have taught you the most about media buying? What books have taught you the most about sales? What books have taught you the most about customer support? What books have taught you the most about software engineering? Right? And I just be quiet and I just wait. Now some people say, "Oh, I don't know. I can't remember any," bad sign. Right? But if you ask me, "Sam, what books have influenced you?" Oh my God, right? I can recall so many and I would happily talk to you about those books in a great detail, hundreds of them. And I'd be able to tell you what I learned from each one. And I'd be able to tell you how I discovered that book, what I learned from that book, how I implemented some of those learnings from that book in practice, and how those learnings further developed and further evolved. And also how I, from that book discovered another book that taught me these other things that I then discovered this other book and then this other book. And from that original book I discovered what inputs created that book, so I would study the author and then what influences that author had, had in order to take that and create this book, right? So I could go into ridiculous detail about these books. And that is, that's what's taught me, you know, what I know, or different courses and that's what's taught me what I know. So my output, my results and my ability now and my skill level and all of that, it's not really a function of me being born with any type of skill. It's more a function of the quality of the inputs that I have been in contact with over my life. Right? And I've had the, what do we call it? The privilege of coming into contact with really great inputs. And I make it a real priority of mine to find the best inputs and consume them and try to ignore and shut out all the bad inputs, because bad inputs can rot away good inputs, right? And so when I started asking these questions, if people couldn't tell me anybody who's influenced them or who they've idolized, and if they couldn't tell me any books, then pretty much with 100% certainty, and I know that nothing is 100% certain, but what I mean by saying that is extreme certainty. There's almost, well, there was no case where this failed. Right? So far over a collection of roughly a hundred interviews that I've done since this realization and nobody who couldn't recall a book or an influence was any good, and a lot of the people who were good were able to recall with clarity the influences and the books that had taught them a lot. And it's not always books. Sometimes it's bloggers or YouTube channel or it might be an academic paper or white papers, something like that, right? Or an article. It doesn't always have to be books, but the question I ask is books, and that has been probably one of the biggest breakthroughs that I've made so far in trying to recruit and hire really talented people. I have switched from asking questions about outputs and instead ask questions about inputs, because it's very hard to make up someone's name on the spot. It's very hard to make up a book's name on the spot, try and do it. You will fail at it, right? And this is a great way to interview people. So I encourage you, if you have a business and you're hiring people, try to ask questions that relate to the individuals inputs, not their outputs. And then you will start to make leaps and bounds ahead at filtering out the really good people. And this lesson really goes deeper than this. It's not just about how I learned this and improved my recruitment process at my company. It's also about you, cause you might be an employee or you might be an entrepreneur who's just starting out. Or you might be an entrepreneur who's starting out already got some traction, but you don't have any customers yet and you're not ... Well, you've got some customers, but you're not hiring a team yet. Right? And so a lot of people, they always want to know how do I get better? How do I get to that next level? How do I grow? How do I make more money? How do I get smarter? How do I improve? Right? And my answer to you for that question is to focus on your inputs, not outputs. So really take an audit of your inputs, like who are the five people that you spend the most time with? What books have you read? What information do you consume? For example, do you spend most of your time on Facebook and Instagram and YouTube and watching the news on CNN and things like that? Because if you do, then I can guarantee you that your brain is rotting away. It is absolutely rotting and disintegrating at a rapid rate and that the output that is coming out of that is nothing. Your probably delusional, probably spouting off on social media about shit like Donald Trump and flat earth, and all sorts of crap and probably just one of these people that I see on social media that has suffered immense brain decay due to really bad inputs. Right? And it's not really that you're not smart and it's not really that you haven't been lucky. It's mostly that you've been feeding your brain shit and so what you've got is shit. And so really if you want to find the people who are really talented or if you yourself want to become really talented and successful, you have to focus on the inputs. What is going into your brain? Who were the five people you spend the most time with? Who are your mentors? Who are massive influences that have shaped the way you think about and the way you do your work? And what books have you read that have taught you the most? Right? If you can't name books and if you can't name influences in the way that you do your work and everything. If you also don't have mentors and the people, the five people you spend the most time with, if they're not really going anywhere, then this isn't really news, but it will be probably received as news for you right now. You ain't going anywhere, right? You have to make sure that your inputs are good, like raise the average of, raise the like aggregate and talent intelligence level of the five people that you spend the most time with, you will get smarter, right? Stop going on social media and start reading books instead. Stop watching marathon Netflix series and start enrolling in some courses instead. Stop going out and drinking and talking about stupid shit until early hours of the morning and start going to sleep early, and reading, and learning, and growing your mind instead of poisoning it and punishing it, right? And really focus on your inputs because garbage in, garbage out. And this, it doesn't matter what you're looking at in the world anywhere, if it is in the universe and it is observable, even if it's virtual or in atoms or bits, it doesn't matter. This law remains true. And so this is one of those called universal laws and universal principles that you can use, and apply to anything that you want in life. So if you want to get better, focus on your inputs. If you want to find really good people to hire, what are their inputs? Ask them. And if you're trying to help other people get better inputs, always inputs, get them right, outputs will follow. So that's it for this video. I hope you enjoyed it, I hope you learned something. And if you did, just click that like button. And also subscribe to my channel here. I release a video like this once every week on a Tuesday, as well as customer interviews and live stream Q and A's with my customer community. And also let me know what you thought in the comments section below. If you liked it, if you want to give me some feedback or if you've got any questions, just put that in the comment section below. So thanks for watching and I'll see you in the next one soon.

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