Introduction System Engineering

I'll teach Young's modules how to measure or I'll teach something else. Rarely will he say I'm going to educate the students for their future. Now, you may say in both a parable and that story, that, of course, the bigger goal was always understood. I doubt that you really believe it. Most of the time, people are soul meshed in the details, they fail to see the bigger picture. It is the essence of bureaucracy. The bureaucrat does his job in front of his face the way he sees it. He does not see the larger function of the whole organization. It's very common. Well, systems engineering is attempt to look at the whole as a whole at all times. That's what system engineering is. Its attempt to look at the whole as a whole and not make these foolish mistakes of trying to think it's the details. Now, it's not easy to be a system engineer. It's very hard. But big science has been very, very popular, a large group of people have learned how to say the right words. But you're familiar with people who know how to tell you all about how to play tennis. But they themselves can't play a good game. The same assessment hearing: you don't pay attention to the person's words, you judge them by what they produce. And there are very few actual good systems engineering, but there are larger people who could say all the words. So I clame to you, the problem is very, very difficult. You know what you want to do perfectly well, but you cannot do it. And you may be surprises, so I'm going to try right on a whole bunch of you. You know, you're here to get an education. You know, the people paying the bill, the teachers and you yourselves all believe the education is going do some good in your future career. Otherwise, we would be doing it. You know, it's an education. Nevertheless, every term you cram, at the end of term, you know, that is counterproductive to your education. You know, the same effort spent all along the way reasonably should be what you're doing. And cramming is counterproductive is simply cram as much stuff in, which tends to fade out properly. It's very poor policy. You know it. But you can't stop cramming. You try to get the grades turn by turn by term, course by course by course, without looking at the whole picture. Thus I say, you know what the system is trying to do. [00:02:50]Namely produced, [0.0s] educated person. But you can not follow your own rules. You practice inefficient, counterproductive techniques which go against the system. That's why system engineering is so damnably hard.

You know and believe, but can’t follow your own rules

You may perfectly well know and believe, but you can't follow your own rules. That's the tough thing. System Engeering and is it the attempt to keep at all times the larger goals in mind and it translate to local action into global actions. But there is not a single larger picture. It's one of the many troubles. Take, for example, I told you I first got control of a digital computer at Bell Labs. I thought my task was to get the maximum number of computation done per day. What better? Keep the machine busy, get the number you ground out. Don't stall around all of my machines stand idle. By God, they are there to be used. After a while, it dawned on me that it was really important to do important computations. And not important ones it didn't matter. My problem was to find the important computations. Goes which would matter to Bell Labs and they will avoid those who would dump. Now I was in research department - math department - so I actually started in the math department. But I began to look at the research department. Well, now, if the research department were going to use a machine efficiently in those days, it gradually dawned on me the scientists had to ask the right questions. Otherwise, the problems are no good. How will ever write to write questions? How will I know? Ask them. Write them down wherever you want. Answer, probably only if they come their terms with a machine and learn how to run it themselves. The machines were so different that they're not hand calculations. So I had to set out a method of programing that is so easy that the staff would have to learn how to run the machine, to learn how to do simple computation or what machine computation meant against hand calculation. It's a different business. Well, after a while it dawned on me that I was not only employed by math department and the research department, I was employed by Bell Labs.

Breadth of engineering

Therefore, part of my problem was to provide a service for the whole of engineering to find out what computers could do with the breadth of engineering. I also began to realize my task was not to do the computation, it was more to find out what could be done, show people how to do it and let them build on what I had found out. My task was really not to compute, but to find out how [00:05:35]Puccini [0.0s] should be used. Well, above Bell Labs, there was AT&T in West Reluctant. What about them? What about whole scientific world? What about the whole world? I have obligations to all those levels and the obligations are short term, relatively long term and very long term. Very different obligations, again. To get some computation done today or find out how to do computing in some area, so we can do it tomorrow. I have all those conflicts. I have a job as a total system and you can't say where the boundary is any one moment, but that's the real position I was in. And that's the position you were in almost all the time. Now, it was very easy, I said, to say the right words in systems engineering, [00:06:25]you even say of yourself; [0.7s] it is very hard to practice it. I found myself in constant conflict, worrying about doing the right thing, and I spending too much time on the immediate vs. the long term, or am I spending too much to long term and not immediate. Am I not educating people adequately besides getting answers? What abouts effect AT&T? Had we not better do think get AT&T alerted that machines are coming along? Have we not obligations in many other directions? I had to balance these things. It was not an easy task. Now the first rule of system engineering is one which you won't believe: if you optimize a component, you probably ruined the system behavior. That sounds very strange. I've got system of a whole bunch of components. I make one better. The system performance goes down. So this is very hard to believe. I'll tell you a dramatic story with regard to a differential analyzer. I had inherited a differential analyzer. I've gotten it because the original guy was so incompetent. I could bottom look better up as he did it and I did so well. We had so many problems. Gradually, we needed another machine both so we could couple the two together to get bigger problems done, and B, so we could do more problems because we are now overloaded. Well, we couldn't buy them commercially because they weren't quite good enough. So we had to have more [00:07:50]M9 gun directories condemn [1.0s] and built on the shop floor [00:07:54]equipment. And I'm took over to [2.9s] look at his acceptance tests or move all over my place.

Equations y(0)= 1

I get a friend of mine to look at the system with me and I tried at first a well-known equation: why is zero equals one? Why prime of zero equals zero, who's solution, you know, is the sine. And the derivative is a cosine. If you plot the sine against the cosine, you should get a circle. And how well they'll circle close on itself, time after time after time, tells you how accurate the machine is. Well, we patch of the first and it doesn't run. That must be one bad component in some someplace, so we pick some other components and tried again. Didn't work. After two or three tries, my friend admits something was wrong. We call in the guys who sampled it, pointed out to them that something was wrong; they had to admit there was something wrong. And so my friend and I watched. And we finally got bored watching, so we were at the lunch. We came back from lunch. They had found the trouble. Yes, they put it in better amplifiers. Much better amplifiers than the ones I had. What they had not done was put an adequate ground. What was happening is the leakage through the inadequate ground from one amplifier to another was wrecking the whole system. All they had to do was put it in a really heavy copper bar, and then the thing ran. Now, here's a machine where all components are independent and still improving a component ruined the system behavior. I know it sounds strange. You'll say: well, that's unique one. No, it's not. It's very, very common. It's very common that when you improve a component the system goes to hell. Now, let me give you some examples.

Mathematical reform

Again, take mathematical reform. We've had it in 30 or 40 years our reform of the caculus. What they do is have some idea, like use computers or something else. And they do that. They never, never ask themselves what is a total mathematical education. Now, the mathematic is sophisticated. You certainly know math conduction - as you all know, complex numbers and so on. But what happens in these things? In complex numbers, you meet them at high school hours when you hit a quadratic. And then I say, holy dread, they are avoided. Calculus never mentioned some. Geometry, never mentioned some. Until you come to linear algebra. And there, well into the thing, when you suddenly hit complex eigenvalues and complex eigenvectors, you meet them again. Now you're facing two difficult concepts: complex numbers and eigenvalues and eigenvectors. And is it a wonder that this students go apart? Don't know what's going on? No. You never tried to teach two complicated things at one time. But there they do. Because they did not stop and think. Yes, we must deliberately give the reinforcement steadily on complex numbers. So when we come to this point, they will understand them. The same thing happens in math conduction. You told a couple of times, then for a long while you never meet it. And finally, if you take computer science, you'll [00:11:28]beat [0.0s] it frequently. And you find other words down there. It's a basic tool for answering the question, how under your mathematical traditions, can I prove something for all cases? It's a fundamental method of reasoning as important that you understand both what it can do and what it cannot do.

linear algebra

Well, they don't do that. They don't look at it. What they have done instead is they've optimized calculus and they've optimized linear algebra and they've optimized other courses. As a result, you don't have a decent mathematical education. Now, their excuse is quite simple. The whole problem, namely what is a mathematical education, is too big to think about. Therefore, let's do what we can do. That's a typical tactician. They will not stop and think. Now, the same thing happens of most of us in this factory. I don't think you would ever get out of this school, a statement of what the educated output is supposed to be. If we don't know what the output is supposed to be, how the hell are we supposed to do a good job - with difficulty? This is one, again, example of the failure to look at the system and the consequent trouble. So I began to think about the history of systems engineering. The earliest example I know is between 12 and 14 hundred in the arsenal at a... at Venice. They had a line coming down to [00:12:56]bruce the ships, the mast came in, the sails came on, the orders came on, this came on. [3.9s] And a trained crew was there, they got in the boat and left. This early example of just in time. Just in time the mast was there, just done this sail was there just in time the orders were there, just in time the trained crew was there. That is an example of systems engineering. They knew the system, they knew the problem, and they looked at the whole problem. How do I keep a fleet going? It's more common now, but that's the first rocket fired in history. Now, you may say that the railroads were systems. Yes, but that does not mean, I think, that you can look and say the guys who built the railroads understood the system. While I read the history, I doubt that they did. They saw the locomotive, they saw the cars, they saw the rails. They did not think of the system as a system. They simply patched piece here, a piece there. The first real system engineerings [00:14:02]enrolls [0.0s] in large at modern times is the telephone company. They were in a very funny position. They not only design at through [00:14:13]West like [0.2s] manufactured, but they operated it.

There’s a big difference between making something and selling it to someone else and running it yourself

Now there's a big difference between making something [00:14:19]as selling it to [0.4s] somebody else and running it yourself. A tremendous difference. Suddenly, reliability, other things or maintainability, become very, very large because you're going to have to do it. At it since it's the same organization, it enters into design. Now, I have to tell you something about the telephone business would probably never occurred to you. It's called the diseconomies of scale. You're used to the economy of scale. If you were to build 10 one, they want to build 100, you gain economy by scale. But now consider the telephone business. We have 10 subscribers. Eleven one comes in. Eleven one's got to connect the other 10. A 12th one comes in. At twelve one's gotta be connected to 11 other people. The more people are the more cross connections [00:15:11]that [0.0s] I must produce. It is a job which is very you do what you got to people. It is very hard to do when you got 2 hundret million. They had that peculiar problem of the diseconomies of scale. The bigger they got, the relatively harder it is to do the job, not the easier it is. So they had to pay attention to system design. I will say, by enlarge, they have done pretty shrewdly. In fact, they've done it so shrewdly now that most of you haven't got much idea. You pushed the buttons there and you get connected. Haven't much idea what happens behind it. They've got big elaboritely system going there, a very complicated one, probably the most complicated thing built still to this day. Every central office has well above a million buys with structure. Used to be mechanical, we've gotten into computers. But we face the problem. How do you produce? I being lines of code. Twice a week or oftener when no two central office are in the same place at the same time or doing the same function. Central offices don't do the same thing. Someone will have different calling habits.

Different design criteria to meet

The one's in the cities, you have different call inhabit than you have in the country. You have different design criteria to meet. And therefore the software must be different. They face these problems and by enlarge, you know, it works. It works better electric distribution, because when the power fails, you grab the telephone and suppose you call this help. Hey, the power's out. You think of me the other way around, would you? But nope, that's were it goes, it's pretty good. Now, I don't pretend to answer the question of how it was that I, who was a classically trained, pure mathematician, became a system engineer. But I'll give you some steps all along the way. As a junior, when I went to Chicago, Robert Hutchins, the radical president of Chicago, was in charge. And the rule was, you got a degree when you passed nine courses in your major field and six in the minor. It didn't matter what grade you got along the way. You had to know the stuff at the end of your senior year. You had to know the nine course in mathematics. Well, that makes you study a little differently. When you are told you're not passing course by course, you're gonna know the whole as a whole on an exam then and your mind, if you're going to the hole, is all there. It makes you think a little different, it makes you study different. The next big episode was at Los Alamos. I think when, of course, you do it, partly when you get to your doctor's degree, also you begin to study the problem of how you go to [00:18:01]your patch over all. [0.0s] At Los Alamos, we knew we were building a bomb. The whole bunch of us were building one bomb. All the parties must work together and it must fit in a bomb bay and we better get it done before the enemy who was working on it gets it, because if he gets there first, we're through. We knew we're working on a single one design, one single system. That made a big impression on me. I'm going to Bell Labs. I learned a great deal more. I told you about two episodes of computing. They gave me other ones. why I saw the nature of a system. I saw how when people did not see the system as a whole, they did counterproductive things. And that was very bad. I [00:18:48]better mean, [0.2s] Nike missiles.

designing mistakes

I saw again and again we were designing missile system. I'll come back then a little later. Now, another point connected. I first learned with Nike missiles, when we put the test shots out to [00:19:06]are required to win. [0.5s] I wasn't involved directly, but I was back home involved. I didn't go out to watch him. What the heck. Why go out there for watch somebody go off, bang in the sky? I found that there were field changes going out even as we were installing the plan to do the job. I didn't really realize how much a system is constantly being adjusted and change, it fitted here and there, and how field changes keep coming in even after the thing is accepting, sometimes further field changes come through. I made me think a lot. Now I come up with the second criteria. Part of the system engineering job is to prepare for changes so that when they occur, you can make them gracefully. Furthermore, if you do it that way, even as you're doing your research and developing the thing when you get new ideas. If you've built it flexibly, you can. This flexibility I didn't appreciate for a long while, but glad you came to realization. That's why I like when you draw black boxes. Then to some extent you can modify black boxes whether they effect, affecting the whole system, but you also cannot. I saw that on watching doing calculation [00:20:27]where [0.0s] people. [00:20:28]had this like, [2.2s] look, there's no use putting a wide bandwidth processing circuit here. Went back there. You're right. Our data hasn't got that bandwidth or those severals have got the bandwidth.

flow of the information

There's no use providing bandwidth a little bit more, yes, but ten times as much, forget it. We have to look at how the flow of the information go through. How much information is there? How will it be used? We have to think about these things carefully and not overdesign one part, underdesigned another. So I began to understand these things from experience. Now, I've got another rule. The closer you hit this designing conditions, the worse it overload, to take the extreme example. Think of a bridge built to support 30 tons. Exactly 30 tons. Optimally designed. Well, 30 tons of one pound. It falls down. Take a central office. We optimally designed it for the maximum load. What happens when you exceed load? The whole thing is crashing down. You caqn practically no [00:21:35]trents, [0.0s] nothing through it. So one of the parts of design is graceful degradation, when you exceed design specifications. The bridge sags a bit more. We don't carry quite such a load, but we don't collapse immediately on a central office. Graceful degradation of a system under overload is essential. Now, [00:21:58]suspend year, [0.5s] I told you is discussed by lots of people and almost nobody knows anything. But there is a set of notes written by my friend Bob Westermann, which were never published, but which I have a copy. And I've used parts of it. He's the only guy I really think understands systems engineering very well. Then it's called "One Man's Systems Engineering" written back in seventy five, so this is, in ninety five, twenty years ago. If I take the title only, "one man system engineering", what is system engineering on the objective.

What does a system engineer do?

What does a system engineer do? The framework of systems engineering, organization of systems engineering, objectives and policymakers are the methodologies of systems engineering, evaluation and, common or uncommon sense, and the ending [00:22:50]onvoy. [0.0s] Now he believes that the group is a basis for system engineering. I had, well we work with computers, essentially do a singlehanded, there weren't people around in my location. There were people spred around at that state, so we got together technical meetings. But fundamentally, there weren't people understood about computing. And I had to do systems engineering by myself. And I ran into [00:23:17]old [0.0s] troubles. It's hard to do it, but I tend to be more than he does. But he had bigger problems and he did not only military jobs, but Bell-Lab jobs, and he did a lot of them. He believes that specialists brought together to form a team is the basis. But he also maintains that unless you let them go back to their specialty, to keep their talents sharpened up, it will fail. And he apparently went through a period when, because he was part of a team which could solve all kinds of problems, they were constantly asked to put out fires. And they couldn't maintain their skills. So one of the thinks I think about systems engineering is that the people with various skills must be given free time, now and then, to go back and sharpen up their skills and their various tactical areas. They cannot be kept on system job one after another have nothing. They will lose or underlying skill. But management will not appreciate that point at all. They've got another crisis.

System engineering job is never done

Now we belief that system engineering job is never done. One reason is that the presence of a solution changes the problem. I had to give you my favorite example. I came to believe that what I should provide in computing service was regular, reliable service. Particularly, short times for debugging programs. And those days you put the program on a machine and you got the answer back. You've got your terminals, which does the same trick that I want to do. So I set aside an hour and a morning, an hour and afternoon for short problems, up to three minutes. And if you have to add five minutes above that - off. No matter how much is it: "I will have the answer in two minutes more" - forget it. Well, what some people do with terminal problems, they've broken three parts. They did one third somewhere else - they walked out the office, of computer room, somebody else came in with the next piece and somebody came the next piece and bingo, they got the thing done. At a far greater workload on me, they were optimizing their personal production. My problem was to optimize the production of Bell Laboratories. And one of the first things you find out in systems engineering is this classical conflict: the individual's idea of what they want individually and what you're trying to do. The system as a whole comes head on in conflict. And when you change the rules to design for our system optimization as a whole, they change their strategy throughout the optimization in small. For example, take how much you people have changed your plans as various rules for selection have been made. When management changed the rule for promotion, you change your behavior to fit. Not that you think that will do best for the company as a whole or the organization, you think is best for you. You continue to try and optimize your best response to the system every time the system changes. Therefore, systems engineering's job is never done. The moment you put in a new system that people react differently. And so you got to design again. Second place, what happens what you design, you evaluate, you don't like it and come back and goaround the circle: design, evaluation; quite happily, until somebody says, "hey, we've got to have a product". And some people with more [00:26:38]nerve and methylation [0.4s] says that's the deadline. We're starting this building tomorrow. And so you commit yourself to a design which you think if you were left another six months, you could do better. It's not surprising, therefore, the product when it's finally produced is not optimal. Their design, evaluation and modification cycle is broken somewhere, because it has to be. Imitations like me and the math [00:27:08]Barba [0.0s] wouldn't have had the nerve to do it. Engineers are needed to stop the process and get it on the track. It's a very hard thing to do. Now, Westermann believes, as I do, that the client has some knowledge of the symptoms of his trouble. But he doesn't know the cause. Probably. Your problem is to find out why he has this happening. Your problem is the same as the doctors.

A doctors job is solving the problem

You go to the doctor with the runny nose, the doctors problems to find out why. He can give you something to stop the runny nose. But that's not the problem. Now the customer is suffering and wants relief. He wants to relieve immediately from his symptoms. But, you know, you'd better find out what the cause is. So you cure the cause and not the symptoms. Well, this starts very beginning: the trouble with the customer and the systems engineer. The systems engineer has got some rights, but the customer has also. A customer, after all, is a man who is suffering. He wants relief. Now! He wants a missile tomorrow, shoot down those damn planes which come over. He doesn't want something designed in 40 some weeks. So he is like me, quite demanding. Well, let's have this extra, now. Never mind all this analysis. Get me a solution.

The system engineer is in the same position of the doctor; knows the issue, but not the cause.

And the system engineer isn't the position of the doctors [00:28:42]AI. [0.0s] This guy knows the symptoms. He doesn't know the cause. He doesn't really understand his problem. And part of this system, man, your job is to try to uncover the underlying problem. That it takes time to do this. It's the time consuming. Now, just as there's no definite system within which the solutions are found, the boundaries of the problem are likewise elastic. What the hell a solution is going to be, is variable. And I suppose the hardest system engineering is the acceptance that there is neither a definite problem nor a definite solution. That just isn't the thing which you were taught in school. Definite, probably definite answer. The answer is six. No. Now, can the school do anything about the fact that they teach you no system engineering [00:29:30]worth match? [0.0s] The answer is: I think no. Attractive as the idea is, of a laboratory course in system engineering, it can't be done. For example, consider my problem in Bell Labs in computing. I had to know the kind of people who were in physics who I was going to educate. How educated were? How much are they willing to learn computing? How can I lure them into it? I had to understand as a spit out the kind of people were go into what kind of jobs. I had, understand the [00:29:59]ethos [0.0s] of the whole organization. How much duress can you apply the organization? How much must be by consent? There's enormous amount of difficulty. And you, until you understand those elastic cut back obligations that people are gonna do the job in a field. It's all very well-designed, something in the laboratory which works beautifully under laboratory conditions with laboratory maintenance. But out in the field and real work conditions, it goes to hell rapidly. Because the people on the field are in a hurry, there are difficult conditions and they aren't well trained. Well, I've watched it happen to many more companies than mine because I didn't see it very hap..., very, very often in Bell Labs.

Different styles

I saw it happen elsewhere, where what worked in the labs doesn't work in the field. The people are different. They've got different styles. They've got different habits. They've got into work conditions. And what you can get done, you can't, for example, [00:30:53]to hire where our organization people work overtime without fussing and lobar argument, low morale organization. [7.2s] They're in at eight, but they all were drinking coffee and if a.. if you're gonna quit at five, at four thirty there are already prepared to quit. To get ready to leave allright at five o'clock. Well, in an emergency, they still do it. A hybrid organization. They behave differently. They come in and buckle down and get the job done. Well, you have to understand what is the organization's goal to maintain the stuff? How is it going to be done? These are not easily taught in lab class. Furthermore, the university doesn't have a faculty to do it. So I don't think it can be done. I think it has to be done the way the Westermann said. You take people into a system group. They live with a systems group. They learn by osmosis. And also, he believes, which is hard to do, you throw the older people out of the systems group to make room for the young. Now, some, even a sister group for some years is still doing fairly well, doesn't like being thrown out to take some young punk in who doesn't know what you've got to do, that. You've gotta get rid of the older guys and get the younger ones and keep the system going. You learn it by osmosis, by doing many a job you learn by doing like bicycle riding. You learn by doing. You learn system engineering by doing it. And I don't think there's any other way you'd learn it. Much as I appreciate you now, it's a very hard business to learn. Now, if you look back at these lectures, I maintain a fair amount has been this way, which I seem to be a dedicated systems engineer. I seem to look at the system as a whole. I say I can't control why I did it. But there I am. And these notes have been an attempt to show you the bigger system all the way along the way as best I could. But I really can't. You have to experience to know it. System engineering, if you don't mind expression, is like sex. You can take a boy of 40 and let him read all the books you want. He isn't going to know what sex is and when he has some experience, he still may not know what happened. Even if you take a person through a system design, it may not be they ever really understood what happened. But the only hope, I think, is to give them direct hands-on experience to find out. I don't think you'd learn from reading books. Anymore you learn sex books. Yeah, you learn something about sex, but you really won't learn what it is. Now, let me close this, my observation about this business.

The wrong problem solved exactly right

I have seen many times the wrong problem solved, exactly right. They didn't listen to the customers agony. Or that perhaps they listened to the symptoms but did not find the cause. And so I will patch their symptoms, someother ones broke out elsewhere. This is wrong... The nice solution to the wrong problem isn't very good. I would say, loosely speaking, is better you have a poor solution to the right problem than a good solution to the wrong problem. And that means you get down somewheres near the bottom of what is the problem. Now, the problem always changes. There isn't any problem. And to give you an illustration, now, let's take my experience with Nike. Well, I got involved in search shortly after I came to Bell Labs. I was computing [00:34:30]through reject [0.5s] reasoning, the problem was fundamentally, we're going to build something which will shoot down an incoming plane, given altitudes, given speeds, so on, given maneuverability, we got those estimates of what they will be when we get a system built, which course we don't know. But we estimate those things. What else? Who's how fast? What maneuverability? We're trying to shoot down when it wasn't your plane. Well, we get it done. And sure enough, we take out the quadroon. One plane flies cross a drone. Pretty much it. How do we know? Pretty much the right time. Boom. We shoot it down. One shot. Does that proof the system works? I don't know. All I can tell you is when they flew the film back and I was there quickly watching the film and think well off, I think things and there was a big explosion at the sky and parts fall out. We all plodders shout "Hooray". But, one single shot, no one is coming by, how good was the test? It wasn't much. Well, let's go up. We now come to, shall we say, defense of cities. How many batteries around New York? How many around [00:35:44]Podoko. [0.0s] And how do we coordinate? Well, how do we coordinate? We can't have each one operating independently, because in six of them all in the same area playing, the other airplane is going to be free. Clearly, we've got a totally different problem now of coordinating the guns around the city or on a ship or any place else. We've got to coordinate the group as a whole. It no longer becomes shooting down one airplane by one missile. It now becomes defense against a fleet of targets. And the question of how long can you average fired and guided in the end? How quick can you launch another one to get you another guy further back? All these things have to enter into it. Well, we work on that for a while. We get that system going. So we have systems of missiles now. And now we come down to the cities. What cities do you defend? Well, you think long enough and you will say, huh? We must leave no undefended target where you could do a great deal of damage. The enemy can do damage. We must make every bit of damage to the enemy equally painful to the enemy. That's what it really is. That's what the Nike missile is, an attempt, its an attempt to make every possible target equally difficult to do us damage. More dangerous things to be lost, more [00:37:13]suffended. [0.0s] Something you don't matter, for example a farm in Kansas, well, or if they destroy a farm in Kansas, you don't mind. They destroyed the capital of Washington D.C., you do mind more. You defend according to the value put on it, but you try to leave all targets equally defended. Now you see how enormous a difference that is, from what we started out, namely to shoot down one plane. You see the solution, each stage brought the new problem, and that is the nature of systems engineering, its never done. When you deliver in the system as an action for while, now, the problem becomes deeper. And you see how in this case, depth was achieved down to fundamentals. Now, we could not have thought that simple answer. Every target must be defended equally, when we first began. Shoot down that airplane coming in at that rate with that maneuverability. That is what makes systems engineering so difficult and why it is never done. It's an endless sequence around, around and around. And pretty soon you get people out of it because they're simply tired of it. I got tired Nike problems after a while and went off and did other things. Other people carried on. But it's an unending task when you do undertake systems engineering. Let me say again. But I should didn't, don't think I said well enough. It's the patient or the customer who has the agony. He's got the pain. You do have to listen to him, but you got to also put more in. You must try to find the cause. Same as a doctor. The doctor may have a great deal of trouble, so he may for a while give you some drugs to alleviate the symptoms. But if he's a conscientious doctor, he just doesn't relieve the symptoms, he tries to find the cause and finally do something about it. So I have nothing against relieving your symptoms. But really, if there's nothing else you can do. But that's not a systems engineering job. The system engineering job is to find out what the nature problem is.

Each time you get a solution, your understanding should be deeper

And each time you get a solution, you're understanding the problem should be deeper. You go round again. This system is [00:39:37]steeper, still. [0.0s] It's a difficult problem. For [00:39:41]allowance [0.0s] you come back to work. My favorite wanted for last, say, 18 years or so. What is the educated person? It's a changing thing in the first place. But it's very, very difficult to get anybody to say much about what is the target. The complaint is that we've got a bunch of people can't do this, this and this. Yes. They can't really get to this idea. We know all the complaints. We don't really have a clear picture what we're trying to do. It's one thing in... to tell their business, although even there is a little difficult sometimes to decide between supplying service and cheap service. We've done several things which we know re... not popular, for example, in my Mother's Day, in my childhood, you picked up a phone. There was a lady out there. "Number, please". And she did a lot of other things as well. She was a human being. Now you have great trouble getting a human being on a telephone system. You punch buttons to that, an so on, yes, if you want one punch, if you want this punch button one. If you want that punch button, two. And so on. Bing, bing, bing. A half the time when you think giving a voice you want. And that's stopped popular with people. People would like to haven't it. But that having real human beings there is very, very expensive. So what we've done, we've mechanize a thing and we've produced a different kind of solution, which isn't always popular. And in some quarters, my mind, I wonder, whether the telephone company has done the right thing or whether it has gone too far automating and not enough charge a little bit more, but give you a little more [00:41:19]humanity [0.0s] service. I want to close my exact aspect. The trouble in system engineering is, you are also required to think about the human beings. If you don't think about the human beings who are doing the job, it doesn't go around very well. My failure to notice when I put it in a short test times that they were prompted by changes, change of strategies. And I forgot the human beings were all eager to optimize their performance on their problem. I didn't care one bit about the systems of how much competing was done for the whole of Bell Labs. My problem was the whole. There's another individual one. And you will find through out system engineering the conflict between the individual and the group... is gonna be solved. Now, solving group completely is not satisfactory because it turns out to be inhumane. You have to let the people get away with some things now and then. You have to let people....