 Everyone's ready for Mary Papandik's keynote? Yes, lots of excitement. We have three minutes to go, so I'll kill time till then, and then we'll let Mary start at nine. So any questions so far? Anyone in the audience? Nothing. That's good. Hope you guys enjoyed your first day of the conference. Lots of tweets, so that's good. Keep the Twitter streams filled with good and bad stuff. So we learned from this. One other quick thing is we are not actually giving any feedback forms. Those of you who have come for last year's conference probably would have heard about that. We don't do feedback forms, and I want to take a quick minute and talk about why we don't do feedback forms. I've worked for many startup founders where I've kind of got this from them over the years that care about your customers. That is you guys. But don't just keep listening to what they have to say in the feedback forms, because that doesn't help. It was fantastic, actually, because we had about six people walk up to me and give me feedback on a personal level saying, hey, this is what I noticed, and this is what if we can do something about it. I took the time and I explained to them the constraints under which we are working, the kind of challenges we follow. And they were like, immediately, oh, this perfectly makes sense. Now I understand. But had you given this in the feedback form, there's no way for me to kind of explain that, because it's a one-way thing. And now that you've given the feedback, you think you have given me and I'm supposed to fix that next time, or immediately, which doesn't really happen that well. So we really value your feedback, but I don't believe that feedback forms are the way to collect the feedback. So if you guys have any feedback, good, bad, ugly, whatever it is, please feel free to reach out to me. I'll be around, drop me an email, and we'll make sure not that we'll fix it for next year, but we'll fix it today. That's more important, because I'll give the feedback forms at the end of the conference, and it'll take us one year to fix it, because we are not going to do a conference again before one year. So if there's any feedback, please do reach out to me or any of my members of the team and give them the feedback, and we will try and incorporate that right away. But we'll also try and explain you the constraints under which we operate, so you appreciate some of the reasons why some decisions are made. Why are the screens here in front of the stage? The speaker cannot see it. There's a reason for it, which we would love to fix it, but it might not happen right now. But there are other ways to fix it, so just giving you an example. All right, I think I've taken enough of your time. I'll be around. I'll come back after the keynote, but it's an honor and a pleasure to welcome Mary Popendick for the keynote. It's great to be here, Naresh. Mary and Tom, we spent two weeks together about three years ago touring India, and it was fantastic hanging around with them, seeing their perspective. They were only here for two days, but the insights they had about Indian traffic system was mind-blowing. So over to you, Mary. Thank you. Thank you, Naresh. Yeah, Tom observed while we were here that the cars and other vehicles and animals, etc., move around as if they were pedestrians. So the rules here are the rules of pedestrians, and I can see why. So how about, there we go, almost. Linda Rising, who's going to give keynote tonight, so don't miss it, gave a talk called The Agile Mindset at Agile 2011. It was amazing. And she got me and many other people to think about the mindset of people that are working in any environment. And another thing that I used to think about, I worked for 3M for two decades. Took an early retirement leave in 1998. And then I started running into companies where the management system worked differently than the company I had spent most of my career in. And I didn't understand why. We had some interesting ways of thinking about how things are done and how people are managed, which I came to realize were quite healthy. And then I started, as I started working with other companies, running up against a completely different way of looking at how people should behave, why they behave the way they do, how managers should act, that sort of thing. And I wondered for many years, how is it that companies get this kind of crazy mindset? And it didn't take me long to figure out where 3M got its mindset. 3M is a Minnesota company. Minnesota is a state in the U.S. that was pretty much settled by people from Scandinavia. And as I went to Sweden and Norway and other countries like that, I realized that the 3M management system had very strong roots in the way people in the Scandinavian countries think about people management. And it's not an accident that that's the countries that Agile took hold in the fastest. Because the mindset of senior people in companies has a whole lot to do with how things work on the ground. So how come is it that, for example, in most of my country, managers think differently than the company that I grew up in? I ran into an article. Oh, you know what? I first, I'm going to tell you about this article. It was written in 1976. It was written by a guy named, two guys, Jensen and Meckling. It's called The Theory of the Firm. It was the beginning of this thing called the shareholder value theory. The shareholder value, it was published in the Journal of Economics. It has incredible amounts of references and sightings for years upon years. And remember in 1976, for approximately the next quarter of a century, next 25 years, until right around the late 1990s, the concept that the way to run a company is to maximize shareholder value. At least in the US became one of the most fundamental concepts for business behavior. Here's what the article basically said. Now we, as economics, and economics wants to be a science, so it needs to be able to measure things. And in order to measure things like how people behave, you have to make some simplifying assumptions. So the simplifying assumption that was made in that article is that people make decisions that favor their personal economic self-interest. Now when you start with that simplifying assumption, and actually it's not totally wrong, it's just mostly wrong, but if you start with that simplifying assumption, then you get to the concept that managers, they don't own a company. So if somebody owns a company, that's one thing. But people who manage a company for other people can't be trusted to do things that are in the best interests of the owners of the company because where they're going to be looking for is their own economic self-interest. And so therefore, because of that, you have to create a cascading set of measurements to basically focus on increasing the owners, shareholders, economic value. And so you have financial measurements cascading down through every level of the firm, and up at the top you have CEOs who from the mid-1980s until the mid... Oh, I don't know, for the next 15 or 20 years had massive amounts of compensation switched from salary to stock options and their salaries went through the roof. Just amazingly... Now, there's a lot of evidence that the very high salaries of CEOs has nothing to do with long-term stock performance. And what really happens when you focus on shareholder value is a lot of short-term thinking. But that doesn't make that much difference because this theory had so much influence on business practices in the United States. Because of that, it's spread to lots of other countries in the world. It has an incredible amount of impact on business practices, and that's what I was seeing. I was seeing the impact of shareholder value on what it is that happens down on the ground in the trenches with real people. So here's my sort of summary. This is a picture of a cave. And it says, yes, the planet got destroyed, but for a beautiful moment in time, we created a lot of value for shareholders. And you could have said that in 2008 and been pretty close to right. So this concept of shareholder value and its implications, remember, founded on this concept that what people do is look for maximizing their own personal self-interest, has had huge amounts of impact on the mindset of how people think about management in our companies. Now let's go back, because I told you I got a little out of order here, to this concept of minds or mindset. Kahneman, excuse me. Kahneman, yeah. Daniel Kahneman is a Nobel Laureate, and he's written, he's done a lot of research on these simplifying economic assumptions and proven with his research that actually they should be questioned. But he wrote a book called Thinking Fast and Slow just recently, and that book sort of summarizes the idea that we have two kinds of minds, two ways of looking at things. Everybody does. We have what he calls system one and system two minds. And if you take all the literature of people saying, well, we think this way, but on the other hand, we have this opposite idea, he sort of lists the kinds of things that our minds do to us. So he talks about system one. I think it's me being a system one person. And system one is fast thinking. And system two is slow thinking. So system one is reflective, reflexive. So if I'm a little child and I touch a hot stove, I go back real fast. I know really fast that that stove should not be touched. System two is deliberate. So if you ever pause before you do something and just think about it, that's your system two kicking in. System one is responsive, response to what's happening. System two is rational. You analyze and think what's the best thing to do in this situation, what's the most rational thing. And rational in economics tends to mean that simplifying assumption that people will operate in their own economic best interests. So rational means I calculate what's going to give me the most income, what's going to give my family the most income, and that's how I make my decisions. Interestingly enough, system one is where expertise resides. Because when you're expert, you have a sort of innate understanding of how to make stuff happen. You just kind of know. You don't have to be told. When you're a musician, for example, you pick up an instrument and you just plain know how to play it. You don't have to think. When you're a budding musician and you really don't know, you absolutely have to do some analysis. So analysis, interestingly enough, sits over in system two, but expertise sits in system one. You use intuition. I mean, everybody uses intuition here and there. But there's also a lot of people who say, we shouldn't use intuition. It can be wrong. We should use evidence. And there's nothing actually wrong with that either, except sometimes intuition trumps evidence. And other times, evidence trumps intuition. And by the way, it tends to be the experts who know the difference. So then there's habit. System one acts out of habit and system two plans. Good idea to plan, but then again, habit, well, habits can be bad. We want to break some of them, but then again, habits are, you know, if you had no habits, you would have a horrible time getting through a day because there's so much stuff that you do. If you had to think about it all the time, that would just like mess your, you'd not get much done. Tasset knowledge. Stuff that we just know versus explicit knowledge, something that can be explained to others, written down, and made explicit. So system two is explicit. System one is tacit. System one works on autopilot. That's kind of a summary of it. I just kind of do stuff on autopilot. And system two puts you in manual mode. System one, by the way, will override system two. So the most interesting example of that is the sort of standard concept of system one being like, well, let's say our emotions, and it's an elephant. And system two is the rider on top of the elephant directing it where to go, and that's our smarts, yes, our intelligence. Now, it's true that the elephant will go wherever the rider, the driver, asks it to go, directs it to go, unless the elephant decides to go somewhere else. And in which case, there's nothing you can do about it. And we think about that. You have your elephant, and sometimes your mind takes over, but if your emotions take over, there's nothing you can do about it. System two checks up on system one. It's not working all the time because that would be just too exhausting. Instead, every so often it looks and says, is my habit, is my instincts, are they correct? Are they doing the right thing? So system one actually makes most decisions. And the other thing that Kenneman says, which I find quite amusing, is that our system two is basically lazy. So we have these two mindsets, and we think about things in different ways. And what we actually try to do is balance these two systems. You know, if you have a little kid who's going to go across the street, say to play in a park on the other side, you want her to stop when she gets to the street and pause and think, hmm, oh yeah, I'm supposed to worry about traffic. But then when she gets over to the park, you want her to just run around and enjoy herself without worrying too much. So you kind of want both. And each person creates a balance in their mind of how much of intuition, how much of instinct, how much of plans, how much of analysis is the right amount for whichever situation. And that's really not so hard for an individual. But it's kind of hard for a group, especially as groups get bigger, or for a company, especially as companies get bigger. Because now we're not talking about trusting my instincts, which over time I have learned to trust. My expertise, and I know it's boundaries, I'm starting to trust the instincts and expertise of people in my group. And I'm not so sure I'm ready to do that. So companies, big groups, tend to evolve over towards system two thinking and system two direction over time and when they grow. So what that does is it gives us some paradoxes that we have to solve in our companies. And I'm going to talk about some paradoxes that I have observed. And today I'm actually going to go into detail over the couple of them. So we have this one I was mentioning, the concept of self-interest. People make decisions in their own economic self-interest. Or do I care about my community? And do I worry about making sure that the community is successful? In Agile we have an awful lot of people that contribute to the community as a matter of course. Is it in their economic self-interest? Well, not necessarily in the short term. So that's the rational paradox. And then we have another paradox, and this is focus versus exploration. So sometimes we focus on doing whatever it is we're doing now and what happens. The world goes off and has a new invention and we miss out on it. So which is better? So that's the optimization. If you optimize locally, you might miss any movements and change. And then there's the analytic versus intuitive. So I'm analytical or I'm going to make intuitive decisions. That's the design paradox. And then we have thoughtful versus fast. How much thinking do I mean, this is what we've struggled with for years in Suffolk. How much do you think before you get going? That's the speed paradox. And then we have being good versus getting better, which is what Linda's talk was all about and when she did the Agile mindset and that's the perfection paradox. Do I want to be perfect or do I want to spend my time getting better? So if we go into the talk, I hope to have time to cover these two areas this morning. I won't be able to get into the rest. So we talked about the shareholder value theory and the damage that it's done to the company mindsets of an awful lot of companies. So the rational paradox is sort of looks like this. If you've heard of the tragedy of the commons, that's the way it used to be described in economic literature. Tragedy of the commons is we have a beautiful commons area. Great. And because it's so beautiful, we let everybody use it. Now, people are not going to limit their use of that commons area because there's no incentive to limit use to what will keep it beautiful or if you have grazing area or if you have fishing area. How do you limit use so that you don't overgraze, overfish or whatever? And because there is no way to manage that, then we eventually end up with the tragedy of the commons. It becomes a desert or a desolate land. And this was a thought experiment in the late 60s, early 70s. And everybody took it as a given, but it's a theory. And in fact, a lot of economists said it's not a theory that I'm going to believe. And they started doing research into where do we have commons areas in the world that have been successfully maintained for centuries? And here is a place in India where there has been successful irrigation maintained by commons, by a community for many, many centuries. And in this environment of fishing rights, forestry, irrigation, that sort of thing, where fairly large communities have to get together and cooperate to make the commons successful, or otherwise they will not live in a successful community, it actually has been studied by lots of economists. And there are plenty of examples. The person who led the exploration of these different kinds of commons is Eleanor Ulstram. And she also is a Nobel Laureate and died recently. And in a book approximately 1990, she summarized her findings on exploring all of these commons areas. And she said there are plenty of successful self-governing communities in the world. And if you want to create a self-governing community, her points have become sort of the standard by which people say this is what you need to have a self-governing organization or community. First of all, there have to be clearly defined boundaries. If you are going to have a fishing community and you don't want it overfished, then you have boundaries into which no other people except your community members are allowed to fish. There are rules of use that are well matched to the location. Most individuals affected by the rules can be involved in modifying the rules. Community members set up a system for monitoring compliance. So as a group, people keep track that their colleagues are doing the right thing. And there is a system of graduated sanctions. Should you steal more water than you are supposed to from an irrigation system in a drought, your neighbor might say, we have a limit, I think you're going over it. And if you stop, then it's fine. But should you ignore that, then there will be a little bit more aggressive people taking care that you don't take more than your share. There's low-cost conflict resolution available because there will be conflicts. External authorities respect the right of the community to make its own decisions and devise its own rules. And you might have a network of cascading things. Again, going back to fishing, go to Norway. And you might have local fishing groups and then larger fishing groups up through the whole country area. So that's pretty much taken as this is the standard how self-governing communities can survive over time. And in this environment, the tragedy of the commons does not need to hold. Another concept that I like a lot, and that is we have this thought in the agile community that if you have more than like seven or eight or nine people, you can't actually have cooperation. But there's a whole bunch of research that says that's interesting but just plain not true. There's plenty of different group sizes, and if you understand the different kinds of group sizes, you can create things that are much bigger than a group of seven or eight or nine people. So Robin Dunbar is a British researcher, anthropologist who is studying monkeys. And he observed that different size monkeys have different size groupings that are natural to them. Little monkeys have little groups and medium-sized ones have medium-sized groups and big baboons have bigger groups. And he theorized that it's probably because they have to know who's in their group, who's a friend or a relative or somebody they can cooperate with. And based on the size of their, you know, part of their brain where they keep track of relationships, they can only keep track of so many and therefore the little monkeys will have only so many and the bigger ones have a bigger brain and so bigger neocortex so they can actually keep track of more relationships. And then he said, you know, what if we expanded this to humans? You know, theory says we maybe descended from this group of monkeys and baboons and so why not? And then he did the math. And the math said that people should be able to have close relationships, knowing, understanding relationships with about 150 people. Actually, it was 148, but that's close enough to 150 based on the rest of the science. And so that was his theory. The limit is 150. Now, at that time, that was just a theory, but then he started going out looking for groups of 150. And he actually found a bunch of groupings. His group sizes started at an inner circle, a family group of about three to five very close friends or family members. The next would be a sympathy group. You would care if somebody in that group died, for example, or a relative died, maybe 12 to 15, a hunting group. This is one of my favorite sizes of approximately 30 to 50 colleagues who go out hunting together. To accomplish something, to have a goal and make it happen. And I'm going to theorize that maybe that's about how many took to put this conference on. A clan of 150 people. Here we go, there's our 150. And this is a clan. These are either relatives or close associates that you can trust and that you know. You run into somebody and you know their name and you know who's their kid and all of that sort of thing. And then there's larger groups like a tribe of 500 to 2500 and so on. Now, he found that clans actually of 150 are really relatively common. We have most pre-industrial villages did not get bigger than that. And in fact, in the UK, up until Industrial Revolution, villages tended to not be any bigger than 150, except in Kent where they turned out to be 100 for some reason, I don't know. Maybe they had small, I won't say, I won't speculate. But, and then there's the Amish and Hutterite religious communities that have a role that they split at approximately 150. There is most military companies that are approximately 150. University departments, Gorin Associates, a very successful U.S. company that is sort of without a management structure, whole another story. Splits into separate profit and loss business units at 150 because whole bunches of people have noticed that when you get bigger than that people can't keep track of things anymore. Keep track of the other people in their group. And now let's go to this hunting group. I observe in my history that product teams are like 30 to 50. And I've run into that in many places. Most of the products that I worked on are hardware software products. The idea of five to seven people putting one of those products on the market is, you know, a non-starter. And so when you get true cross-functional teams on a product basis, you tend to have more like 30 to 50 which really closely matches what we heard yesterday morning in the keynote. What did we say? Five to ten teams depending on the expertise with one leader. Excuse me. And then we have startup companies, 30 to 50. By the time they get bigger than that they're mostly not a startup anymore. Open source projects. Conference organizations. And what you have in groups this size is a leader who has a vision, an idea of where we're going to go hunting or what we're going to achieve or what our product is going to look like. And that vision coordinates the other people who may then of course be also in some of these smaller subgroup sizes, the sympathy group or inner circle or something like that. So if we think about that, then we have to look at this concept of giving back to the community we live in as a valid economic concept. It actually happens. People do this kind of thing. I want to give you an example. This guy's name is Todd Park. He along with Jonathan Bush started up, well they were consultants. They graduated from Harvard Graduate School. They went to Booz Allen and they were consultants in healthcare. Healthcare is a big growing field. They of course figured they knew everything. That's what a newly minted consultant probably thinks. And so they decided they wanted to be entrepreneurs and they started their own clinic and it almost failed for years because they discovered they didn't actually know as much about running a clinic as they thought they had learned in school. So they learned. And one of the things that they learned was keeping track of medical records was extraordinarily difficult. They switched their company to being an online medical records company for clinics. It became extraordinarily successful. They had a public offering. They made buckets of money. And it's Athena Health. It's still run by Jonathan Bush and they had a really successful IPO. So Todd Park, nice energetic young man but his wife is getting really tired of his long hours. So she encourages him to retire and to move to San Francisco and start a family, which he did. And he started investing in healthcare companies and those were successful. And then he got a call from the U.S. Department of Health and Human Services and said, what don't you like to come and work here as an entrepreneur in residence? And he said, well actually, I don't think I really want to live in Washington, D.C. and there's lots of other reasons, so no. But he got convinced to go out for a trip and he got convinced that it would be a really cool challenge and he finally actually got his wife to agree to move to Washington, D.C. and became the CTO or entrepreneur in residence of HNHS. He didn't have any budget. He didn't have any staff. And the other thing is he had to give up because he had a senior government position. All of his investments in Athena Health and in all of the other companies he'd started up and just get out of that. Economically, very bad move. He certainly wasn't making the kind of money that he would have made with his investments. But he got there and he found some amazing stuff. The databases in HNHS were really cool. Being a big data guy, being a healthcare guy, he could imagine putting those together and making them really do something. So what he decided to do was to give away the data. And he went around HNHS and he rounded up what he calls entrepreneurs. He found plenty of them. You don't work for the government if all you're looking for is your economic self-interest. You actually work because you care about things like health services. And so he found a bunch of people and he also found a model. This is National Oceanic and Atmospheric Administration, our weather data collecting organization in the United States. And some 30 or so years ago, it decided to give away all of its data to the public. And now what we have is all kinds of web apps and stuff just based on using this data which is available for free. And he said, hmm, wouldn't it be cool if we could do that with healthcare data? So he convened a conference of big data people and healthcare people. And he got them all together in 2010 and said, what could we do? And they said, oh, this is cool. The big data guys and the healthcare guys had never met each other and they thought they could do something. So he said, tell you what, I'll give you 90 days and I'll help get some entrepreneurs here in the government to help make data available. Let's see what we can do. And 90 days later, they had 8 or 10 really neat applications complete with business plans and data being released through a website on HNHS. A year later, this grew to a conference of about 50 a one-day conference which is now called the Health Data Palooza. This is one of the apps. It's called Itriage, have it on my cell phone. And whenever I want to know anything about, you know, drug interactions, symptoms, anything that's in the databases, I go there and I can get that information. Perhaps everyone with a business plan for making money. And then another year goes by and he's got a two-day Health Data Palooza 1500 people coming. This is a picture that was painted by an artist for that particular event. And if you zoom in on it, it says I didn't get the memo that this was impossible. And so he kind of did the impossible. By this time, however, he was no longer CTO of HNHS. He had been asked to become CTO of the federal government, which is where he is now. So if you think about this, there's no economic reason why he did this. It's all about giving back to the community that helped make him successful. And it's that kind of behavior that I think is more common, well, should be common in companies that have a lean mindset. So this idea is based on the concept of reciprocity. If I give and contribute, then the community becomes stronger and eventually everybody wins, including me. And this whole concept also can be found in an occasional company that didn't latch on to the shareholder value theory. This concept that if you take good care of employees, they're going to take good care of customers and your company is going to be better off because of it. So Southwest Airlines, those are some of our favorite ones in the U.S. that live by this theory and they are very, very popular amongst customers because of it. And that's not an unusual thing, but it was unusual for companies that were founded before late 90s. When you look at the new startups based on the internet, you find much less of this kind of shareholder value theory behavior and much more of this reciprocity concept. For example, Jeff Bezos at Amazon.com says you can do the math 15 different ways and every time the math tells you you shouldn't lower prices because you're going to make less money. And this is undoubtedly true in the current quarter, even the current year, but I got to believe that it is not true over the decade. And I'm going to have much happier customers if I treat them better over longer period of time. You see this kind of attitude in many of the startup companies that really kind of disappeared at least in our country for a long time. The idea that having customers, employees that are really happy, really promoters of your company really makes your life easier and really makes your success of your company more assured. This is not a common attitude. You don't see a lot of CEOs saying the idea is not to make money over the next quarter or a year, the idea is to set my company up for the long term. But it's those kinds of companies that actually manage to survive over the long term. So there's this concept of loyalty economics. It's Fred Reichhold at Bain and Company did a lot of research on it and over the last say eight years or so has published this concept that there are good profits and there are bad profits. Bad profits are profits that annoy customers. You hold all your cards close and you get as much money as you can. Nuisance fees on airlines for example or anybody that's going to charge you extra money that you really didn't expect. Exploitive pricing. There's a history of in the US of phone operating companies charging all kinds of exploitive fees. So if you're a brand new customer you surely will get a better deal as you come in than loyal customers that have been around for five years or 10 years. Owners contracts contracts that really are going to make sure that you get the most money you possibly can and the most free time you possibly can out of whoever you have the contract with. And when you have this kind of environment what you get is customers who really are not happy. They are what Ryco calls detractors. If somebody asks them I mean if you're the only option they'll stay until there's another option but if somebody asks them do they like your company they'll say uh-uh don't go there. They demoralize employees because employees don't like having to treat customers badly and it undermines this whole economics of long-term thinking that happens to companies that have a long-term perspective on customers like Bezos rather than a short-term perspective. And then on the other hand there's good profits. Okay, where you expose and let everybody know what it is that you're trying to do. And good profits come to you when a customer is happy to pay you because they had a great experience. Because they're just delighted and surprised at what it was that happened when they interacted with your company. And you get top recommendations. Now with the internet things like TripAdvisor and many other kinds of recommendation engines this is becoming really important. This is becoming economically important. But it actually probably was always economically important. It's just easier right now for anybody who's a detractor to let people know they're a fan to let people know. So what happens here? You get promoters, people who love your company. You get energized employees because they like working in that kind of a company. You get sustainable long-term growth. And Wright-Golden's most recent book Ultimate Question 2.0 has actually proven in company after company that adopts this thing called a net promoter score that and does it right not just adopts it but does it right that they get really, truly long-term sustainable growth because they have people who love their company and tell their friends. So the question you ask is, and the only question you ask on a survey is will you recommend product or company to a friend or colleague? So if you're an employee would you recommend your friend work here? If you're a customer would you recommend our product or our service to somebody else? And then you get answers on a scale of 0 to 10 and anybody who gives you a 9 and 10 those are promoters and 8 or 9, 7 or 8, those are neutral people passive and detractors are anybody from 0 to 6 which seems like a broad range but it works out that's probably about right. Now this is just the start. This is just the asking part and as Nuresh just mentioned it doesn't necessarily get anything done and if you don't act and act immediately on this feedback so you ask it you ask it you get lots of people you get a high response rate and you immediately you follow up with this question. So what's the cause of that score? And then the managers in the company personally follow up as fast as they can with detractors and with promoters to find out what they are doing right and wrong and they're using the score of percent promoters minus percent detractors somewhere between minus 1 and 1 to determine whether or not they're creating more promoters or getting rid of detractors and companies that use this right that do immediate follow up that talk with customers and understand the kinds of things that are annoying customers and actually stop doing those things. Finding out what annoys people is not enough. In fact it's almost an insult if you're not going to stop doing it. So those are the kinds of companies that tend to have really long term maybe not short term but long term growth and you actually do have to take some short term hits sometimes to change predatory pricing and that sort of thing in order to create promoters. So to summarize this concept there's a vicious circle that goes on when you start out with the belief that everybody is interested fundamentally in money and because of that that influences your actions. Here here's your personal bonus and that impacts other people vision of us. Ah, man as you said all they're doing is measuring what I do all the time against some you know financial stick and so that causes their kind of actions which says I better spend all my time thinking about how to look good and how to make my numbers great and we get a self-fulfilling prophecy. If we assume people are out for money then we're causing them to be out for money. You can go the other direction too. You can make an assumption and we have a very strong history of this in the agile community and we promoted in a lot of our theories is people actually like we like to fulfill our potential to be able to contribute more like Todd Perk you know other people. And when we have that belief that influences us to trust other people instead of to be suspicious of them and hand them bonuses and then that causes them to think of us more like partners than anything else which then causes usually lots more diligent behavior and what you get in the end is another self-fulfilling prophecy. So the theory is that about 30% of the people in the world they are going to be focusing mostly on their economic gain and about 30% of the world are going to really not care that much and be more like this. And the other 40% you sway by the kind of mindset your company has and the way it treats people and it would be better to have 70% of people who care about making the company successful rather than care about their own personal gain and the only way to get there is to care with a mindset that says what people want is in general the simplifying assumption is to fulfill their potential. So enough on that I am now going to traipse into a little bit on the other thing that I promised you which is the perfection paradox. So the idea here is it's really fun to be good one likes to be perfect but maybe the game isn't perfection maybe the game is getting better. So it's being good versus getting better and the whole concept of the growth mindset that Carol Dwight pioneered in is some people really focus on being good they focus so much on being good that they don't focus on getting better because working to get better means you're not really perfect. And other people really prefer to spend their time getting better. So here is one kind of perfection service level agreements five nines meaning a very small down time over time and this could be considered being close to perfect if you get there or maybe six nines or something like that. But you know it turns out if you get really big there's no way even five nines is good enough. So at Amazon for example there was a guy who happened to be a firefighter who was in this mode of let's get better let's not figure out how we're going to be perfect let's figure out how we can be constantly improving and so he suggested that instead of this that they create events that actually cause their computer data centers to crash on purpose a crash that could take it out for two or three days that if you're not careful could if you're not good could actually impact customer service. Now it's very hard for a management team to say oh sure go ahead take down my data centers and let's see what happens. But being Amazon and Google does this too any company that gets really really large says no matter what the numbers and what the percentage no matter how small it is at scale it's too big. So we have to get better at improving rather than at being really good in the first place. And so the idea is resiliency. How fast can I recover from an error not how few mistakes can I make. Same concept that most emergency response organizations have. And by taking down a data center they learn all kinds of things. Oh guess what we thought that map was over to here but you know it wasn't. Or we thought we would have this backup but it wasn't. Or I couldn't find the procedures fast enough to know what to do. And as people they document what happens they do root cause analysis on any problems centers learn people learn how to respond to emergencies and they get better and better and better at responding when things crash. This whole concept of constantly getting better is when you really are good you worry not so much about being good but how to keep improving. Too many companies too many mindsets of managers and leaders say if we're good that's fine we can relax and we can be comfortable. But there are a few companies that actually have a different attitude. So here is an interesting thing. This is research done by Troy Higgins at Columbia University and he has talked for years and in fact Carol Dweck has based a lot of her work on some of his that people are different in one in an interesting way. There are some people who really worry about what he calls prevention focus safety focus I want my company not to fail I want to be safe and then there's people who focus on aspirational goals promotion I want gain I want to start up a little company and make it grow to be a big success and people who grow up with this prevention focus in mind they really when they get anything presented to them anything and this will be the typical characteristic of a lot of CIOs for example they'll say is it safe not is it interesting is it cool is it maybe a big benefit it's is it safe what is the safest option and then there will be another group of people maybe your entrepreneurs for example when they have an idea they say let's try it let's do it if we try enough paths we're going to find a good one very different attitudes and you'll find people on either side in fact if you go over to the left side you're going to find people who are in many of the emergency response organizations I mean you really do want people in your nuclear power plants for example to be prevention focus so here the idea is duty obligation and interestingly enough when it's all about never failing because it could kill people or whatever then if you have a setback you just try harder because you can't tolerate failure and praise actually causes people to relax and not work quite so hard whereas if you have aspirational goals praise causes people to try all that much harder and setbacks cause discouragement two different personalities and what Troy Higgins says is you need the personality that fits the situation and people grow up with one or the other thing and what you want to do gives them goals that fit their regulatory fit whether it's prevention focus or promotion focus and by the way when you think about it big companies tend to be very much prevention focus thinkers and they have a hard time with anything that's not safe little startups on the other hand tend to be aspirational you know promotion focus goals and they have a hard time worrying too much about being safe even if they grow and get a little big so these kinds of goals actually match corporate philosophies but let's take a very big company that happens to be promotion focus and that would be Intel and way back when 1965 when Gordon Moore published this paper about Moore's law says number of components for integrated circuit on the bottom and up top it says the relative cost manufacturing cost per component and what it does is it sort of looks like this back in 1970 you could put maybe 2300 people in a theater today if you took the entire population of China you could fit it in that theater that's kind of the scale of density that they have seen over the years every year doubling their density now the interesting thing about that is that this has caused the company to have promotion focus goals every year for decades they're always reaching for the next level it's not about being safe it's about doubling the density one more time as impossible as it might seem and that impacts one of the few companies that has other long term issues Gordon Moore published excuse me Andy Grove published an op-ed that says any company that moves its manufacturing out of its home country completely has 10 years before they are no longer able to design what they used to be able to manufacture similarly any company that moves all of its software development away has about 10 years before they can no longer manage that software development locally and what happens here is we're talking about a group in Portland, Oregon where there is a big Intel manufacturing facility which because Andy Grove believes you have to be able to have all of your stuff in a place where you can have cross-functional communication still has a very, very good manufacturing plant but the group I'm talking about is another group in development engineering and their job is here is the development cycle of a chip every two years you roll off another density of chip and as you get towards the end you can see that little circle on silicon that's when the first silicon for the new chip appears and this group PDE their job is to write the software that will test the physical chips and make sure that they don't have any defects in them their whole goal is to keep bad chips from the market so what is that? prevention focus? absolutely prevention focus they're not into inventing new things they're not into all they're into is let's not let a bad chip out there but every two years they have to do twice or three times or four times as much work as they did two years before so they have to constantly improve there's no relaxing so here's where they're working and here is a sequence of chips that Intel has put out and back there in 2007 Patrick one of their guys in PDE noticed that they were burning engineers out like crazy they'd get new guys and they'd have a two year cycle they'd write all the programs they worked day, night and weekend to work even more days, nights and weekends that didn't exist and by the end when PRQ is product release readiness qualification happened everybody would breathe a sigh of relief and all the engineers would say okay now what? and they would be told oh you get to do it again and they would say oh no we don't we're gonna find some other place to work so they were losing a lot of engineers so Patrick decided that there was something that was going to create a sustainable pace and so in 2007 and 2008 they adopted Scrum they had an excellent Scrum trainer they modified the concepts to their environment which is a two year development cycle actually 18 month development cycle and in six months of rapid rapid improvement on the stuff that they do as they have silicon and the nice part about Scrum was it created a sustainable pace to be able to create a steady flow of work make choices as what to do and what not to do give managers an idea of their capacity and allow people at least up until the last six months to work a sustainable work week they also had a lot of other nice benefits that you see when you go into any kind of agile process so it worked well but okay now it's 2009 and now we have another wave of more density and more software needed in order to test that density so just because they were a really good agile organization wasn't good enough so then Patrick went out looking for other people that might give him some more ideas Tom and I happened to go there and we were impressed but we had them do like a value stream map and the value stream map was interesting so for example every two weeks they had six sort of team groups and they'd two weeks, two weeks, two weeks, two weeks and then integrate and I said hmm why don't you start integrating like right after the first two weeks why are you waiting for six weeks and Patrick said well we didn't want to waste time testing and he looked at me and he said that's the wrong answer isn't it I said yes that's the wrong answer so anyway they discovered that maybe they should start integrating right after the first integration and the second thing was their value stream map showed that when they were done because I don't let people stop value stream maps when their job is done you can only step a value stream map when your stuff is delivering value to your customer and their customer is manufacturing so when does manufacturing get value and it turns out it took 45 days manufacturing and I said 45 days for your software to get to manufacturing in the six month period that's like really long and he said well yeah but we have like this really really good manufacturing and there's no way they're going to let our software in unless it's thoroughly tested I says you have a really really good manufacturing plant I've been in a manufacturing plant and I can tell you one thing about a good manufacturing plant and that is every one of them will have a way to pre-qualify vendors all you have to do is ask and ask them what do you need to do so your software can go straight into manufacturing and he said never happen I said I tried and I off I went and they said hmm maybe we should think about this so they did a value stream map and of their software arriving in manufacturing in detail and discovered that this 45 days included only three days of actual testing and the rest was waiting for silicon to arrive or making priorities get up there and stuff like that so we're coming down to the end of this cycle here which is about 2011 and the PDE boss Tim is going to a meeting with his peers and says you know we got a problem we're a couple of months late anybody got a way to speed things up and Tim says I can get you 30 days whoa ok so that was like you can get us 30 days how can you do that he says all I need is 20,000 silicon chips now and they said you got it so he went to the head of manufacturing and he says ok look I got a deal we did some investigation takes you three days to test this but you don't have an easy time getting the chips I get you the chips the manufacturing director says sure sounds like a deal and so their software went into manufacturing in more like three days than 45 and the group got a nice award and they looked really good and stuff was going by this time they were probably the best agile development group I've ever run into but now they have another cycle coming and they have to get better so now it's 2011-2012 right now they're actually doing a pre-RQ for the next level chip and they found out that what they had to do was get three times more software written, validated and delivered in that six months period than they used to do before same number of people no more money how are you going to do it ok so this is constant improvement driven by these amazing targets bad chip into manufacturing so the first thing that they did was they formed a working group of about maybe 30-20% of their people and their leader created very specific targets not three times more productivity it's way too vague exactly which tests are going to have to be created by what schedule at what time, how often do we really have a 3x problem sometimes they didn't, sometimes they had a 5x problem so they broke it down into detailed targets and then they decided that they pretty much gotten everything they could get out of any kind of agile and they decided to go to a thing called lean product development which is actually quite different than lean software development lots of books and conferences in this area and just to summarize it really quickly it is an idea where you're developing over time in this case they had 18 months and your solutions emerge gradually through a series of integrating events and an integrating event coordinates these teams across each other to make sure that by the time they hit the date they have what they call success assured they have put together the necessary stuff to solve the problem and it's sort of like you start out with a bunch of things and you hold integrating event 1, 2, 3 and you narrow down these multiple options to a few options until you get to the solution that's how you spend your time so this is for example what Patrick was working off of he had, you can see across the top we've got, oh across the bottom we've got integrating events 1, 2, 3, 4, 5 and they start with understand need, understand gap establish feasibility for multiple options and measure them and then pick the best solution get it in place and then build it out and then by the end it's time for the silicon to arrive so they did this very diligently for example, just to show you how this works they were using targeted convergence as a consulting firm, that's Brian and Patrick or Brian and Kennedy, Michael Kennedy and Brian was at one of their integrating events and at this integrating event they said we're going to qualify our own software and here's the specs and the idea is that what we're going to do over a weekend is we are going to run 55,000 pieces of silicon through this thing in a 48 hour weekend period, we're going to do that every two weeks and so Brian said well have you tested it and Patrick said well here's the specs like says it can do it you could tell Patrick had never worked with hardware before and so Brian says I'm sorry but if you haven't tested it you don't know anything which is what us hardware folks understand but what was amused when Patrick said he was so surprised so to prove Brian was wrong they took 1500 chips out to the robot and they ran it at speed and guess how many they got done before it broke down, 80 which of course is exactly and Patrick said it took us a year of dinky little improvements before we got that thing reliably running 55,000 chips in 48 hours but they had a year because they did the feasibility test way in advance and by the time that silicon hit they said they had never been more confident that they could do what they needed to do and just going to give you a quick picture of their process you've never seen a process like this before but this is what they developed in order to do it and they're currently running this process reasonably successfully although it turns out they didn't realize it but they actually needed to be five times more productive rather than three so they're still working long hours but start out with a what I'm going to call an infrastructure team this is going to focus on a piece of the infrastructure it'll be a functional team a competency team and they have two weeks to add the next set of capabilities that's necessary for the software over the weekend a system testing team will test that if they find anything there's a day or two to fix it and then they drop that to a module team module team is a cross functional team people from lots of different functions and they then take the technology drops from the different infrastructure teams and merge it into a module that's a piece of software that's going to test a specific silicon configuration and they take a week to do that because they found it's hard to get the modules right so the next weekend they test that they usually find they need to fix it and the thing is by the time they do their final test they can't find any problems or their validation will fail so they have to have known good stuff going into validation no concept that we find defects during validation they don't and so here we go we have a fixed time the next week and then we do a final test and it's validated so it's a five week period now if you take a look at this picture you can see products going through a B C D in two week flows and you can see that the integrate the system test team every other weekend they're doing both an integration test for the technology drop and a module test for the cross functional teams and the opposite week and they're spending full time doing their 48 hour validation and it goes into manufacturing as I said you've never seen something like this before but that's what they do and somebody says what do they do next year I don't know but they'll figure it out so I'm just going to summarize I'm just a tiny bit late here the concept of lean mindset we've we've written a lot of different things with case studies Tom and I have gathered and the thing in common with every case study that we gathered for this book is whatever the group is doing is not something you will read about they're doing something different they're doing something that works in their world they read all the literature have the various consultants come talk to them and then they think for themselves and create new and interesting things that work in their world and to me as far as constantly getting better you have to learn how to make your own decisions so just to summarize we have two different ways of looking at the world everybody does and it's hard when you have a group to get those things together so we have our paradoxes which I mentioned before the first and the last one was what I talked about now what happens is when people hold different mindsets and they're supposed to work together they have to work through what they really believe and so there is things like tension and ambiguity and it takes some time to figure out answers before you get to something that a management group will agree on and eventually you come up with things like cooperation and adaptability and insight and urgency and mastery you come up with those ideas how in a way that works in your company and really there aren't any shortcuts you have to when you have a group that's leading an organization or a group inside of an organization you have to work through the paradox and figure out what's the sweet spot between the two ends of mindsets that works in your world with the group that you have so with that I'm going to say by because there's something starting in 15 minutes and everybody wants to move those things and stuff like that so thanks everybody