Traditionally these are questions for philosophy, but philosophy is dead. Philosophy has not kept up with modern developments in science, particularly physics. Scientists have become the bearers of the torch of discovery in our quest for knowledge. The purpose of this book is to give the answers that are suggested by recent discoveries and theoretical advances. They lead us to a new picture of the universe and our place in it that is very different from the traditional one, and different even from the picture we might have painted just a decade or two ago.
According to the traditional conception of the universe, objects move on well-defined paths and have definite histories. We can specify their precise position at each moment in time. Although that account is successful enough for everyday purposes, it was found in the 1920s that this “classical” picture could not account for the seemingly bizarre behavior observed on the atomic and subatomic scales of existence. Instead it was necessary to adopt a different framework, called quantum physics. Quantum theories have turned out to be remarkably accurate at predicting events on those scales, while also reproducing the predictions of the old classical theories when applied to the macroscopic world of daily life. But quantum and classical physics are based on very different conceptions of physical reality.
We will explain Feynman’s approach in detail, and employ it to explore the idea that the universe itself has no single history, nor even an independent existence. That seems like a radical idea, even to many physicists. Indeed, like many notions in today’s science, it appears to violate common sense. But common sense is based upon everyday experience, not upon the universe as it is revealed through the marvels of technologies such as those that allow us to gaze deep into the atom or back to the early universe.
To deal with such paradoxes we shall adopt an approach that we call model-dependent realism. It is based on the idea that our brains interpret the input from our sensory organs by making a model of the world. When such a model is successful at explaining events, we tend to attribute to it, and to the elements and concepts that constitute it, the quality of reality or absolute truth. But there may be different ways in which one could model the same physical situation, with each employing different fundamental elements and concepts. If two such physical theories or models accurately predict the same events, one cannot be said to be more real than the other; rather, we are free to use whichever model is most convenient.
Model-dependent realism, mental models
M-theory is not a theory in the usual sense. It is a whole family of different theories, each of which is a good description of observations only in some range of physical situations. It is a bit like a map. As is well known, one cannot show the whole of the earth’s surface on a single map. The usual Mercator projection used for maps of the world makes areas appear larger and larger in the far north and south and doesn’t cover the North and South Poles. To faithfully map the entire earth, one has to use a collection of maps, each of which covers a limited region. The maps overlap each other, and where they do, they show the same landscape. M-theory is similar. The different theories in the M-theory family may look very different, but they can all be regarded as aspects of the same underlying theory. They are versions of the theory that are applicable only in limited ranges—for example, when certain quantities such as energy are small. Like the overlapping maps in a Mercator projection, where the ranges of different versions overlap, they predict the same phenomena. But just as there is no flat map that is a good representation of the earth’s entire surface, there is no single theory that is a good representation of observations in all situations.
The Mp is Not the Terrain
Today most scientists would say a law of nature is a rule that is based upon an observed regularity and provides predictions that go beyond the immediate situations upon which it is based.
General and broadly applicable
Because it is so impractical to use the underlying physical laws to predict human behavior, we adopt what is called an effective theory. In physics, an effective theory is a framework created to model certain observed phenomena without describing in detail all of the underlying processes.
There is no picture- or theory-independent concept of reality. Instead we will adopt a view that we will call model-dependent realism: the idea that a physical theory or world picture is a model (generally of a mathematical nature) and a set of rules that connect the elements of the model to observations. This provides a framework with which to interpret modern science.
We make models in science, but we also make them in everyday life. Model-dependent realism applies not only to scientific models but also to the conscious and subconscious mental models we all create in order to interpret and understand the everyday world. There is no way to remove the observer—us—from our perception of the world, which is created through our sensory processing and through the way we think and reason. Our perception—and hence the observations upon which our theories are based—is not direct, but rather is shaped by a kind of lens, the interpretive structure of our human brains.
Mental Models, Galilean Relativity
A model is a good model if it: Is elegant, Contains few arbitrary or adjustable elements, Agrees with and explains all existing observations, Makes detailed predictions about future observations that can disprove or falsify the model if they are not borne out.
Another of the main tenets of quantum physics is the uncertainty principle, formulated by Werner Heisenberg in 1926. The uncertainty principle tells us that there are limits to our ability to simultaneously measure certain data, such as the position and velocity of a particle. According to the uncertainty principle, for example, if you multiply the uncertainty in the position of a particle by the uncertainty in its momentum (its mass times its velocity) the result can never be smaller than a certain fixed quantity, called Planck’s constant. That’s a tongue-twister, but its gist can be stated simply: The more precisely you measure speed, the less precisely you can measure position, and vice versa.
In other words, nature does not dictate the outcome of any process or experiment, even in the simplest of situations. Rather, it allows a number of different eventualities, each with a certain likelihood of being realized.
Given the state of a system at some time, the laws of nature determine the probabilities of various futures and pasts rather than determining the future and past with certainty.
Quantum physics tells us that no matter how thorough our observation of the present, the (unobserved) past, like the future, is indefinite and exists only as a spectrum of possibilities. The universe, according to quantum physics, has no single past, or history. The fact that the past takes no definite form means that observations you make on a system in the present affect its past.
Electric and magnetic forces are far stronger than gravity, but we don’t usually notice them in everyday life because a macroscopic body contains almost equal numbers of positive and negative electrical charges. This means that the electric and magnetic forces between two macroscopic bodies nearly cancel each other out, unlike the gravitational forces, which all add up.
Maxwell’s equations dictate that electromagnetic waves travel at a speed of about 300,000 kilometers a second, or about 670 million miles per hour. But to quote a speed means nothing unless you specify a frame of reference relative to which the speed is measured. That’s not something you usually need to think about in everyday life. When a speed limit sign reads 60 miles per hour, it is understood that your speed is measured relative to the road and not the black hole at the center of the Milky Way. But even in everyday life there are occasions in which you have to take into account reference frames. For example, if you carry a cup of tea up the aisle of a jet plane in flight, you might say your speed is 2 miles per hour. Someone on the ground, however, might say you were moving at 572 miles per hour. Lest you think that one or the other of those observers has a better claim to the truth, keep in mind that because the earth orbits the sun, someone watching you from the surface of that heavenly body would disagree with both and say you are moving at about 18 miles per second, not to mention envying your air-conditioning.
Electromagnetic forces are responsible for all of chemistry and biology.
The histories that contribute to the Feynman sum don’t have an independent existence, but depend on what is being measured. We create history by our observation, rather than history creating us. The idea that the universe does not have a unique observer-independent history might seem to conflict with certain facts we know. There might be one history in which the moon is made of Roquefort cheese. But we have observed that the moon is not made of cheese, which is bad news for mice. Hence histories in which the moon is made of cheese do not contribute to the present state of our universe, though they might contribute to others. That might sound like science fiction, but it isn’t.
What makes this universe interesting is that although the fundamental “physics” of this universe is simple, the “chemistry” can be complicated. That is, composite objects exist on different scales. At the smallest scale, the fundamental physics tells us that there are just live and dead squares. On a larger scale, there are gliders, blinkers, and still-life blocks. At a still larger scale there are even more complex objects, such as glider guns: stationary patterns that periodically give birth to new gliders that leave the nest and stream down the diagonal.
One can define living beings as complex systems of limited size that are stable and that reproduce themselves.
M-theory is the unified theory Einstein was hoping to find. The fact that we human beings—who are ourselves mere collections of fundamental particles of nature—have been able to come this close to an understanding of the laws governing us and our universe is a great triumph. But perhaps the true miracle is that abstract considerations of logic lead to a unique theory that predicts and describes a vast universe full of the amazing variety that we see. If the theory is confirmed by observation, it will be the successful conclusion of a search going back more than 3,000 years. We will have found the grand design.
What I got out of it
Hawking does a brilliant job of making many of these complex and scary topics manageable and approachable – from M-theory to quantum physics and string theory
This book is a belated answer to Tom Watson’s probing questions as to why programming is hard to manage…Briefly, I believe that large programming projects suffer management problems different in kind from small ones, due to division of labor. I believe the critical need to be the preservation of the conceptual integrity of the product itself. These chapters explore both the difficulties of achieving this unity and methods for doing so. The later chapters explore other aspects of software engineering management….The Mythical Man-Month is only incidentally about software but primarily about how people in teams make things. There is surely some truth in this
A rule of thumb, I estimate that a programming product costs at least three times as much as a debugged program with the same function…Programming system component costs at least three times as much as a stand-alone program of the same function.
First, one must perform perfectly. The computer resembles the magic of legend in this respect, too. If one character, one pause, of the incantation is not strictly in proper form, the magic doesn’t work. Human beings are not accustomed to being perfect, and few areas of human activity demand it. Adjusting to the requirement for perfection is, I think, the most difficult part of learning to program. Next, other people set one’s objectives, provide one’s resources, and furnish one’s information. One rarely controls the circumstances of his work, or even its goal. In management terms, one’s authority is not sufficient for his responsibility. It seems that in all fields, however, the jobs where things get done never have formal authority commensurate with responsibility. In practice, actual (as opposed to formal) authority is acquired from the very momentum of accomplishment. The dependence upon others has a particular case that is especially painful for the system programmer. He depends upon other people’s programs. These are often maldesigned, poorly implemented, incompletely delivered (no source code or test cases), and poorly documented. So he must spend hours studying and fixing things that in an ideal world would be complete, available, and usable. The next woe is that designing grand concepts is fun; finding nitty little bugs is just work. With any creative activity come dreary hours of tedious, painstaking labor, and programming is no exception.
The challenge and the mission are to find real solutions to real problems on actual schedules with available resources.
More software projects have gone awry for lack of calendar time than for all other causes combined. Why is this cause of disaster so common? First, our techniques of estimating are poorly developed. More seriously, they reflect an unvoiced assumption which is quite untrue, i.e., that all will go well. Second, our estimating techniques fallaciously confuse effort with progress, hiding the assumption that men and months are interchangeable.
Key point – men and months are not interchangeable, but we make assumptions that they are
Fifth, when schedule slippage is recognized, the natural (and traditional) response is to add manpower. Like dousing a fire with gasoline, this makes matters worse, much worse. More fire requires more gasoline, and thus begins a regenerative cycle which ends in disaster.
For the human makers of things, the incompletenesses and inconsistencies of our ideas become clear only during implementation. Thus it is that writing, experimentation, “working out” are essential disciplines for the theoretician.
The second fallacious thought mode is expressed in the very unit of effort used in estimating and scheduling: the man-month. Cost does indeed vary as the product of the number of men and the number of months. Progress does not. Hence the man-month as a unit for measuring the size of a job is a dangerous and deceptive myth. It implies that men and months are interchangeable.
The bearing of a child takes nine months, no matter how many women are assigned. Many software tasks have this characteristic because of the sequential nature of debugging.
Since software construction is inherently a systems effort—an exercise in complex interrelationships—communication effort is great, and it quickly dominates the decrease in individual task time brought about by partitioning. Adding more men then lengthens, not shortens, the schedule.
For some years I have been successfully using the following rule of thumb for scheduling a software task: 1/3 planning 1/6 coding 1/4 component test and early system test 1/4 system test, all components in hand.
Programming managers have long recognized wide productivity variations between good programmers and poor ones. But the actual measured magnitudes have astounded all of us. In one of their studies, Sackman, Erikson, and Grant were measuring performances of a group of experienced programmers. Within just this group the ratios between best and worst performances averaged about 10:1 on productivity measurements and an amazing 5:1 on program speed and space measurements! In short the $20,000/year programmer may well be 10 times as productive as the $10,000/year one. The converse may be true, too. The data showed no correlation whatsoever between experience and performance. (I doubt if that is universally true.)
I have earlier argued that the sheer number of minds to be coordinated affects the cost of the effort, for a major part of the cost is communication and correcting the ill effects of miscommunication (system debugging). This, too, suggests that one wants the system to be built by as few minds as possible.
The dilemma is a cruel one. For efficiency and conceptual integrity, one prefers a few good minds doing design and construction. Yet for large systems one wants a way to bring considerable manpower to bear, so that the product can make a timely appearance. How can these two needs be reconciled? Mills’s Proposal A proposal by Harlan Mills offers a fresh and creative solution. Mills proposes that each segment of a large job be tackled by a team, but that the team be organized like a surgical team rather than a hog-butchering team. That is, instead of each member cutting away on the problem, one does the cutting and the others give him every support that will enhance his effectiveness and productivity.
Even though they have not taken centuries to build, most programming systems reflect conceptual disunity far worse than that of cathedrals. Usually this arises not from a serial succession of master designers, but from the separation of design into many tasks done by many men. I will contend that conceptual integrity is the most important consideration in system design. It is better to have a system omit certain anomalous features and improvements, but to reflect one set of design ideas, than to have one that contains many good but independent and uncoordinated ideas.
The purpose of a programming system is to make a computer easy to use…Because ease of use is the purpose, this ratio of function to conceptual complexity is the ultimate test of system design. Neither function alone nor simplicity alone defines a good design. This point is widely misunderstood. As soon as ease of use is held up as the criterion, each of these is seen to be unbalanced, reaching for only half of the true goal. Ease of use, then, dictates unity of design, conceptual integrity. Conceptual integrity in turn dictates that the design must proceed from one mind, or from a very small number of agreeing resonant minds.
Architecture must be carefully distinguished from implementation. As Blaauw has said, “Where architecture tells what happens, implementation tells how it is made to happen.”
Not trivial, however, is the principle that such mini-decisions be made consistently throughout.
In most computer projects there comes a day when it is discovered that the machine and the manual don’t agree. When the confrontation follows, the manual usually loses, for it can be changed far more quickly and cheaply than the machine.
The project manager’s best friend is his daily adversary, the independent product-testing organization. This group checks machines and programs against specifications and serves as a devil’s advocate, pinpointing every conceivable defect and discrepancy. Every development organization needs such an independent technical auditing group to keep it honest.
The second reason for the project workbook is control of the distribution of information. The problem is not to restrict information, but to ensure that relevant information gets to all the people who need it.
The purpose of organization is to reduce the amount of communication and coordination necessary; hence organization is a radical attack on the communication problems treated above.
The means by which communication is obviated are division of labor and specialization of function.
On larger projects it is very rarely workable, for two reasons. First, the man with strong management talent and strong technical talent is rarely found. Thinkers are rare; doers are rarer; and thinker-doers are rarest.
Practice is the best of all instructors. —PUBLILIUS
Experience is a dear teacher, but fools will learn at no other. —POOR RICHARD’S ALMANAC
The linear extrapolation of such sprint figures is meaningless. Extrapolation of times for the hundred-yard dash shows that a man can run a mile in under three minutes.
Fostering a total-system, user-oriented attitude may well be the most important function of the programming manager.
First, writing the decisions down is essential. Only when one writes do the gaps appear and the inconsistencies protrude. The act of writing turns out to require hundreds of mini-decisions, and it is the existence of these that distinguishes clear, exact policies from fuzzy ones.
Chemical engineers learned long ago that a process that works in the laboratory cannot be implemented in a factory in only one step. An intermediate step called the pilot plant is necessary to give experience in scaling quantities up and in operating in nonprotective environments. For example, a laboratory process for desalting water will be tested in a pilot plant of 10,000 gallon/day capacity before being used for a 2,000,000 gallon/day community water system.
In most projects, the first system built is barely usable. It may be too slow, too big, awkward to use, or all three. There is no alternative but to start again, smarting but smarter, and build a redesigned version in which these problems are solved. The discard and redesign may be done in one lump, or it may be done piece-by-piece. But all large-system experience shows that it will be done. Where a new system concept or new technology is used, one has to build a system to throw away, for even the best planning is not so omniscient as to get it right the first time. The management question, therefore, is not whether to build a pilot system and throw it away. You will do that. The only question is whether to plan in advance to build a throwaway, or to promise to deliver the throwaway to customers. Seen this way, the answer is much clearer.
Structuring an organization for change is much harder than designing a system for change.
Things are always at their best in the beginning,” said Pascal. C. S. Lewis has stated it more perceptively: That is the key to history. Terrific energy is expended—civilizations are built up—excellent institutions devised; but each time something goes wrong. Some fatal flaw always brings the selfish and cruel people to the top, and then it all slides back into misery and ruin. In fact, the machine conks. It seems to start up all right and runs a few yards, and then it breaks down.
A good workman is known by his tools. —PROVERB
The most pernicious and subtle bugs are system bugs arising from mismatched assumptions made by the authors of various components.
Many poor systems come from an attempt to salvage a bad basic design and patch it with all kinds of cosmetic relief. Top-down design reduces the temptation. I am persuaded that top-down design is the most important new programming formalization of the decade.
Add one component at a time. This precept, too, is obvious, but optimism and laziness tempt us to violate
Lehman and Belady offer evidence that quanta should be very large and widely spaced or else very small and frequent. The latter strategy is more subject to instability, according to their model. My experience confirms it: I would never risk that strategy in practice.
How does one control a big project on a tight schedule? The first step is to have a schedule. Each of a list of events, called milestones, has a date. Picking the dates is an estimating problem, discussed already and crucially dependent on experience. For picking the milestones there is only one relevant rule. Milestones must be concrete, specific, measurable events, defined with knife-edge sharpness. It is more important that milestones be sharp-edged and unambiguous than that they be easily verifiable by the boss. Rarely will a man lie about milestone progress, if the milestone is so sharp that he can’t deceive himself. But if the milestone is fuzzy, the boss often understands a different report from that which the man gives. Sharp milestones are in fact a service to the team, and one they can properly expect from a manager. The fuzzy milestone is the harder burden to live with. It is in fact a millstone that grinds down morale, for it deceives one about lost time until it is irremediable. And chronic schedule slippage is a morale-killer.
The preparation of a PERT chart is the most valuable part of its use. Laying out the network, identifying the dependencies, and estimating the legs all force a great deal of very specific planning very early in a project. The first chart is always terrible, and one invents and invents in making the second one.
Most of the big last gains in software productivity have come from removing artificial barriers that have made the accidental tasks inordinately hard, such as severe hardware constraints, awkward programming languages, lack of machine time. How much of what software engineers now do is still devoted to the accidental, as opposed to the essential? Unless it is more than 9/10 of all effort, shrinking all the accidental activities to zero time will not give an order of magnitude improvement. Therefore it appears that the time has come to address the essential parts of the software task, those concerned with fashioning abstract conceptual structures of great complexity. I suggest:
Exploiting the mass market to avoid constructing what can be bought.
Using rapid prototyping as part of a planned iteration in establishing software requirements.
Growing software organically, adding more and more function to systems as they are run, used, and tested.
Identifying and developing the great conceptual designers of the rising generation.
The gap between the best software engineering practice and the average practice is very wide—perhaps wider than in any other engineering discipline. A tool that disseminates good practice would be important.
The development of the mass market is, I believe, the most profound long-run trend in software engineering. The cost of software has always been development cost, not replication cost. Sharing that cost among even a few users radically cuts the per-user cost. Another way of looking at it is that the use of n copies of a software system effectively multiplies the productivity of its developers by n. That is an enhancement of the productivity of the discipline and of the nation.
No other part of the conceptual work is so difficult as establishing the detailed technical requirements, including all the interfaces to people, to machines, and to other software systems. No other part of the work so cripples the resulting system if done wrong. No other part is more difficult to rectify later. Therefore the most important function that software builders do for their clients is the iterative extraction and refinement of the product requirements. For the truth is, the clients do not know what they want. They usually do not know what questions must be answered, and they almost never have thought of the problem in the detail that must be specified.
I would go a step further and assert that it is really impossible for clients, even those working with software engineers, to specify completely, precisely, and correctly the exact requirements of a modern software product before having built and tried some versions of the product they are specifying. Therefore one of the most promising of the current technological efforts, and one which attacks the essence, not the accidents, of the software problem, is the development of approaches and tools for rapid prototyping of systems as part of the iterative specification of requirements. A prototype software system is one that simulates the important interfaces and performs the main functions of the intended system, while not being necessarily bound by the same hardware speed, size, or cost constraints. Prototypes typically perform the mainline tasks of the application, but make no attempt to handle the exceptions, respond correctly to invalid inputs, abort cleanly, etc. The purpose of the prototype is to make real the conceptual structure specified, so that the client can test it for consistency and usability.
Incremental development—grow, not build, software. I still remember the jolt I felt in 1958 when I first heard a friend talk about building a program, as opposed to writing one. In a flash he broadened my whole view of the software process. The metaphor shift was powerful, and accurate. Today we understand how like other building processes the construction of software is, and we freely use other elements of the metaphor, such as specifications, assembly of components, and scaffolding. The building metaphor has outlived its usefulness. It is time to change again. If, as I believe, the conceptual structures we construct today are too complicated to be accurately specified in advance, and too complex to be built faultlessly, then we must take a radically different approach. Let us turn to nature and study complexity in living things, instead of just the dead works of man. Here we find constructs whose complexities thrill us with awe. The brain alone is intricate beyond mapping, powerful beyond imitation, rich in diversity, self-protecting, and self-renewing. The secret is that it is grown, not built. So it must be with our software systems. Some years ago Harlan Mills proposed that any software system should be grown by incremental development. That is, the system should first be made to run, even though it does nothing useful except call the proper set of dummy subprograms. Then, bit by bit it is fleshed out, with the subprograms in turn being developed into actions or calls to empty stubs in the level below. I have seen the most dramatic results since I began urging this technique on the project builders in my software engineering laboratory class. Nothing in the past decade has so radically changed my own practice, or its effectiveness. The approach necessitates top-down design, for it is a top-down growing of the software. It allows easy backtracking. It lends itself to early prototypes. Each added function and new provision for more complex data or circumstances grows organically out of what is already there. The morale effects are startling. Enthusiasm jumps when there is a running system, even a simple one. Efforts redouble when the first picture from a new graphics software system appears on the screen, even if it is only a rectangle. One always has, at every stage in the process, a working system. I find that teams can grow much more complex entities in four months than they can build. The same benefits can be realized on large projects as on my small ones.
The differences are not minor—it is rather like Salieri and Mozart. Study after study shows that the very best designers produce structures that are faster, smaller, simpler, cleaner, and produced with less effort. The differences between the great and the average approach an order of magnitude.
My first proposal is that each software organization must determine and proclaim that great designers are as important to its success as great managers are, and that they can be expected to be similarly nurtured and rewarded. Not only salary, but the perquisites of recognition—office size, furnishings, personal technical equipment, travel funds, staff support—must be fully equivalent. How to grow great designers? Space does not permit a lengthy discussion, but some steps are obvious:
Systematically identify top designers as early as possible. The best are often not the most experienced.
Assign a career mentor to be responsible for the development of the prospect, and keep a careful career file.
Devise and maintain a career development plan for each prospect, including carefully selected apprenticeships with top designers, episodes of advanced formal education, and short courses, all interspersed with solo design and technical leadership assignments.
Provide opportunities for growing designers to interact with and stimulate each other.
Turski and I both insist that pipe-dreaming inhibits forward progress and wastes effort.
Capers Jones, writing first in a series of memoranda and later in a book, offers a penetrating insight, which has been stated by several of my correspondents. “NSB,” like most writings at the time, was focused on productivity, the software output per unit of input. Jones says, “No. Focus on quality, and productivity will follow.” He argues that costly and late projects invest most of the extra work and time in finding and repairing errors in specification, in design, in implementation. He offers data that show a strong correlation between lack of systematic quality controls and schedule disasters. I believe it.
Representation is the essence of programming.
Fixing a defect has a substantial (20 to 50 percent) chance of introducing another.
Vyssotsky: “I have found it handy to carry both ‘scheduled’ (boss’s dates) and ‘estimated’ (lowest-level manager’s dates) dates in the milestone report. The project manager has to keep his fingers off the estimated dates.”
The subsystem boundaries must be at those places where interfaces between the subsystems are minimal and easiest to define rigorously.
Featuritis. The besetting temptation for the architect of a general purpose tool such as a spreadsheet or a word processor is to overload the product with features of marginal utility, at the expense of performance and even of ease of use. The appeal of proposed features is evident at the outset; the performance penalty is evident only as system testing proceeds. The loss of ease of use sneaks up insidiously, as features are added in little increments, and the manuals wax fatter and fatter.
If one believes, as I have argued at many places in this book, that creativity comes from individuals and not from structures or processes, then a central question facing the software manager is how to design structure and process so as to enhance, rather than inhibit, creativity and initiative. Fortunately, this problem is not peculiar to software organizations, and great thinkers have worked on it. E. F. Schumacher, in his classic, Small is Beautiful: Economics as if People Mattered, proposes a theory of organizing enterprises to maximize the creativity and joy of the workers. For his first principle he chooses the “Principle of Subsidiary Function” from the Encyclical Quadragesimo Anno of Pope Pius XI: It is an injustice and at the same time a grave evil and disturbance of right order to assign to a greater and higher association what lesser and subordinate organizations can do. For every social activity ought of its very nature to furnish help to the members of the body social and never destroy and absorb them. . . . Those in command should be sure that the more perfectly a graduated order is preserved among the various associations, in observing the principle of subsidiary function, the stronger will be the social authority and effectiveness and the happier and more prosperous the condition of the State.
What I got out of it
The importance of thinking in parallel vs. series, adding margins of safety (things always go wrong, so do you bake that into your assumptions or do you pay for it dearly at a later point?), adding more software developers generally makes projects even later, as few minds as possible to make the system easy to use (top-down design one of the most important aspects to consider), the importance of testing and iteration at every step along the process (grow, don’t build software), sharp rather than fuzzy milestones
Focusing on work-life balance leads to daily rituals which feeds intentions and goals which helps with downtime and creativity. It is a beautiful, virtuous cycle. Schedule time for your creative projects, make creativity habitual by forming positive associations with it, deepen your ocmmitment by identify what you want to create, step back to take care of yourself and get perspective on your work
Although I like to remain receptive and flexible when it comes to the bigger picture, I show up daily for my creative projects. I focus on a “slow and steady” approach to write for an hour or two a day. I don’t fixate on how much I write during that period. I put in the time and don’t worry too much about the results, because I’ll be there again tomorrow. This sort of simmering has worked well for me because, practically speaking, there is only so much time I can spend on a specific project before burning out, and moving between things keeps me fresh. If I stock to one thing for too long, that’s when I start checking social media or reading the news, or otherwise lose focus. I lift weights with my friend John Sharian, who works as an actor. One day he pointed out that if you stop between repetitions, it’s harder to get going again because you’re beginning from a dead spot. He suggested creating a rhythm. I’ve thought of how this relates to my creative work: I do a lot of projects at once so I can move between things with fewer stops. Exercise offers a good metaphor for creativity. You get inspired one day and go for a run. The next day you shock yourself by shaking off the hesitation and getting off the couch again. Then you keep doing it, eventually without even thinking about it. You no longer need to psych yourself out; it just happens. You made it happen, and then you keep making it happen.
What I got out of it
Beautiful book with some great exercises and questions to help you figure out a system and routine to improve your creativity
In our view, 3 characteristics indicate quality. These are strong, predictable cash generation; sustainably high returns on capital; and attractive growth opportunities. Each of these financial traits is attractive in its own right, but combined, they are particularly powerful, enabling a virtuous circle of cash generation, which can be reinvested at high rates of return, begetting more cash, which can be reinvested again.
One of our favorite explanations of quality appears in Zen and the Art of Motorcycle Maintenance, in which Phaedrus tells his student “…even though Quality cannot be defined, you know Quality is!”
The value any business creates, listed or not, is determined by the rate at which it deploys incremental capital
The very best companies enjoy a diversified set of growth drivers through ingenuity in the design of products, pricing, and product mix
Security by obscurity – an obscure industry, even one with appealing economic characteristics, tends to face lower disruption risk, making attractive industry structures more durable
Assurance benefits are often based on reputation. A reputation of high quality or reliability is earned over time. To compete with reputation is almost impossible, no matter how much money is staked on it
Some key characteristics or industries of quality companies
Market share gainers
Global capabilities and leadership
What I got out of it
A good look at a dozen or so companies and how they can be defined as “quality”
Innovation is simply the rearranging of elements to create something unlikely that is better or takes less energy to accomplish a task
Innovation is one of most important yet least understood human phenomenon. It allows us to leverage other people’s skills and time so that we can specialize yet enjoy a broad diversity of products and services. This process makes us more interdependent and globalized
Invention is taking somethings from 0 to 1. Innovation is the incremental progress to make something reliable and widespread. Many inventors think they are building something for the wealthy, a luxury item. Innovators then take that idea and refine it, bringing it to the masses
Simultaneous invention appears to be the norm as technologies, thought, and idea coalesce into a more probable state
Use often precedes understanding. This is common and to be expected
The Wright brothers innovated perfectly – with little money, few preconceived notions, not reliant on any government or regulation, iterating quickly
A common pattern in innovation is looking to other fields for inspiration
Something can seem inevitable in hindsight but totally mysterious in the present. This is a surprising finding of invention
Dense human populations seem to serve as a catalyst for invention and innovation. Without it, specialization can’t occur which doesn’t allow progress to be made – at least not nearly as rapidly. A good counterpoint seems to lie in Tasmania. They became increasingly isolated and actually lost a lot of the technology their ancestors had originally come with when they landed on the island. Globalization and trade Spurs goods and ideas, where we can learn from each other. Innovation is a collective phenomenon that occurs between and not within brains
Geoffrey West, Scale
The main ingredient and secret sauce that spurs innovation is freedom – freedomfromregulation, freedomfromover restrictive laws and boundaries, freedomtopursue your dream and more
What I got out of it
Fascinating book that helps tie together patterns of invention and innovation across history and industries
Ridley takes one gene at a time and makes it a chapter – diving into how genes work and affect is
Genome contains information from both our recent and far distant past. It has clues to questions that help highlight why we do certain things and have certain characteristics – an autobiography of our species
Life is a slippery term to try to pin down but it requires the ability to replicate and the ability to create order
A reduction in entropy
Shannon’s Information Theory is more helpful for understanding life than mountains of knowledge from biology and chemistry
The importance of being multidisciplinary
Genes contain the recipe for both anatomy and behavior. The code for how to make proteins which enable and allow for nearly everything that happens in the human body
The discovery by Watson and Crick of the double helix DNA structure and that it was the language by which genes express themselves to form proteins was the most momentous scientific discovery of the 20th century, maybe the whole millennium
Intelligence has a large component which is inherited but it is important to remember that heritability does not mean immutability.
Our genes contain a history of infectious disease showing us our ancestors survived or were able to cope with the disease better than others
Our genes are linked filled with parasitic clusters of DNA – sometimes they have disastrous consequences but most often they have no noticeable impact
Lower levels of serotonin are associated with alphas, but this is an effect, not a cause. The alpha’s view of themselves and their position in the pack raises or lowers their serotonin levels. Leaders are in fact calmer, less aggressive than lower-status people in the same group. They tend to be better at reconciliation and remaining calm under pressure
Although genes have a tremendous impact on us, behavior is a great determinant as well. Behavior impacts genes as much as genes impact behavior. The psychological drives the physical. Hormones and chemical makeup changes based on how much control you have in your life, your status and stress, and much more
An ability to metabolize alcohol it’s linked to ancestors in regions that had consistently clean drinking water such as Native Americans. European’s ancestors lived in dirty cities, where the only safe liquids were fermented or boiled and therefore they had to develop the ability to metabolize alcohol relatively quickly.
People who have the ability to digest milk share one common ancestral similarity – their ancestors herded cows and sheep. This is a fascinating discovery that shows how cultural changes (a pastoral lifestyle) lead to evolutionary changes the genetic ability to digest lactose
Instinct is genetically determined behavior whereas learning is behavior modified by experience. Learning slowly gives way to instinct
Genetic diagnosis followed by conventional treatment is likely genetics’ biggest boom to medicine today
It is so important to note that genetic determinism is not fatalism. You may be predisposed today some condition or intuition, but it does not mean you have no say
What I got out of it
Deep dive into how the genome works – some interesting mechanical / logistical things that I hadn’t heard of before
This book presents neither a theory of behavior nor a set of generalizations that explain why people behave as they do. Nor does it describe their behavior. Nor is it another of the increasing number of efforts to mathematize or formalize the study of human behavior. What this book does attempt to do is provide a way of looking at human behavior as systems of purposeful (teleological) events…A purposeful system is of a qualitatively higher order than is a goal-seeking system: it can pursue objectives. A goal-seeking system selects its course of action only with respect to a goal – the outcome that can occur in the situation with which it is confronted. A purposeful system can choose courses of action with respect to a criterion, an objective, which is not necessarily a possible outcome in the period considered, but is a possible outcome of future situations of which the current situation’s outcomes are potential coproducers. If a purposeful system fails to achieve its goal in one situation, it may change its goal in order to better pursue the same objective. If a system consistently sacrifices its goals for the sake of its objectives, we can be sure it is a purposeful system
We began construction of a conceptual system in Chapter 2 by assuming the meanings of a few logical, temporal, and spatial concepts, and we used them to define concepts of mechanics and physics. Thus, starting with concepts taken from the formal sciences, we developed a few central concepts of the physical sciences and, using them, then proceeded to the behavioral sciences. The order of this development reflects the commonly held belief that the concepts of science, and hence the sciences themselves, are hierarchical in nature. The concepts of the formal and physical sciences are believed to be fundamental in some sense, and the concepts of the behavioral sciences are believed to be derived from them…We believe that all the concepts of science are interdependent, and therefore illumination of the meaning of any member of the system of scientific concepts can illuminate to varying degrees, each of the other concepts in the system. As we have noted earlier, historical ordering is often confused with logical or epistemological ordering. We do not take the concepts we begin with to be basic in any way, but rather we maintain that they are definable in terms of the concepts derived from them. To show that this is the case is not to close a vicious cycle, but to complete a cycle in which the initial concepts are enriched. It opens the way for another such cycle in which the meanings of all the concepts can be further enhanced.
Logic – the art of thinking and reasoning in strict accordance with the limitation and incapacities of the human misunderstanding. – The Devil’s Dictionary
While acknowledging that disciplinary segmentation evolved as a way of coping with the complexity of the universe and the study of it, systems theorists challenge the presumption that the world is best understood by segmenting our investigation of it into discrete disciplinary areas, each of which specializes in a particular perspective, level of analysis, or phenomena. Systems theorists argue that such an approach may not be the most appropriate one for meaningfully addressing the complexity of life, and also point to the limitations this structure imposes on the advancement of general and integrative knowledge. Perhaps, one of the most tangible manifestations of this problem can be seen in the curriculum of the average undergraduate student, which offers up a biological view of life in the first hour, a psychological view second hour, a communication view third hour, sociological fourth, political science fifth, and so on, as if human behavior could be best comprehended when compartmentalized in such a manner.
Philosophy’s principal function in the nineteenth century was to synthesize the findings of the various scientific disciplines into one cohesive body of knowledge about natural phenomena. The biggest barrier to such synthesis is the difference between living and nonliving systems, not just the diversity of disciplines
Nature does not come to us in disciplinary form. Phenomena are not physical, chemical, biological, and so on. The disciplines are the ways we study phenomena; they emerge from points of view, not from what is viewed. Hence the disciplinary nature of science is a filing system of knowledge. Its organization is not to be confused with the organization of nature itself…In brief, the need to assemble knowledge of our world into one cohesive view derives from the necessity to take it apart in order to penetrate it in depth.
System: a set of interrelated elements, each of which is related directly or indirectly to every other element, and no subset of which is unrelated to any other subset. Hence, a system is composed of at least 2 elements and a relation that holds each of its elements and at least one other element in the set. The elements form a completely connected set that is not decomposable into unrelated subsets. Therefore, although a system may itself be part of a larger system it cannot be decomposed into independent subsystems
Abstract system – a system all of whose elements are concepts
Concrete system – a system at least two of whose elements are objects
Another major aspect of the individuality of a system is its response capabilities or aptitudes. In considering psychological systems we use the terms in this connection – knowledge, understanding, and intelligence. The first two terms have received more attention from philosophers than from psychologists, but intelligence has been a major preoccupation of psychologists. The meaning of these concepts and the difference among them is far from clear in either ordinary or technical usage. Knowledge – awareness or possession of a fact or state of affairs and/or the possession of a practical skill. Understanding implies something deeper than knowledge – apprehending the meaning or significance of what is known, responsiveness to whatever affects efficiency. Intelligence has to do with the rate at which a subject can learn (learning is the increase in degree of knowledge or understanding over time)
Ideal – an outcome that can never be obtained but can be approached without limit
Purposeful choices come from perception, consciousness (the perception of the mental state of another or oneself), and memory
Models are used because they are easier to manipulate than reality itself. This usually arises from the fact that the images and concepts that make up the models are usually easier to manipulate than is reality, and from their being usually simpler than reality
An individual believes in the existence of things only when he believes they make a difference in his pursuit of his goals. Hence, any attempt to define what is meant by an individual’s belief in the existence of a thing should make reference to the outcome that he seeks (to his purposeful state)
Hypothesis – a belief (which has some doubt associated with it) in the past, present, or future existence of something that has never been perceived
A purposeful individual has 3 different ways of disposing of a problem: dissolution, resolution, and solution
An individual who has a problem can change his intentions so that his dissatisfaction dissolves. It is the removal (production of the subsequent absence) of a problem situation by a purposeful individual who is in it, by a change in that individual’s intentions
Resolution of a problem – the removal of a problem situation by a purposeful individual who is in it, by an arbitrary choice
Solving a problem requires answering two questions – what alternatives are available and which one is best or good enough
Thought is conscious inference. Intuition is unconscious inference
The relation of instrumentality is inherent in the relation between a purposeful system and its purposeful elements. A system must be either variety increasing or variety decreasing
Organisms and organizations are fundamentally different. Both organisms and organizations are purposeful systems, but organisms do not contain purposeful elements. The elements of an organism may be functional, goal-seeking, or multi-goal-seeking, but not purposeful. In an organism only the whole can display will; none of its parts can. Because an organism is a system that has a functional division of labor it can also be said to be organized. Its functionally distinct parts are called organs. Their functioning is necessary but not sufficient for accomplishment of the organism’s purpose(s)
Many wise men have observed that there is more satisfaction in pursuing an end than in attaining it; to play a game well yields more satisfaction than does winning it. Also, some have observed that the researcher’s and manager’s objective is not so much to solve problems as it is to create more challenging and important problems to work on by solving the one at hand. This is to say that the continuous pursuit of more desirable ends is an end in itself, and hence that the attainment of a specific end can be conceptualized as a means to such pursuit. Such observations suggest that a pervasive objective of man and the social systems of which he is a part is the successful pursuit of increasingly desirable objectives. If this is so, then it is reasonable for man and the social systems of which he is part to formulate objectives that can be pursued without end but can be continually approached. Man seeks objectives that enable him to convert the attainment of every goal into a means for the attainment of a new and more desirable goal. The ultimate objective in such a sequence cannot be obtainable; otherwise its attainment would put an end to the process. And end that satisfies these conditions is an ideal. Ideal pursuit can provide cohesiveness and continuity to extended and unpredictable processes, to life and history. Thus the formulation and pursuit of ideals is a means by which man puts meaning and significance into his life and into the history of which he is a part. It also provides the possibility of deriving satisfaction from a life that must end but that can contribute to a history that may not.
The distinction between knowledge and wisdom is important. Knowledge is a means-oriented concept. Wisdom is end- as well as means-oriented. Knowledge is more common than wisdom.
What I got out of it
Thought provoking book and exciting to go deeper on systems thinking and how you can apply it to your day to day life. The idea of dissolving a problem (rather than solving it) is enticing and vibes with the path of least resistance. The idea that organisms’ various parts don’t themselves have purpose but only the whole is important to remember, whereas the constituents of an organization each have their own purpose
System is more than just a concept. It is an intellectual way of life, a worldview, a concept of the nature of reality and how to investigate it – a weltanschauung
A system is a set of two or more elements that satisfies the following 3 conditions: 1) the behavior of each element has an effect on the behavior of the whole, 2) the behavior of the elements and their effects on the whole are interdependent, 3) however subgroups of the elements are formed, each has an effect on the behavior of the whole and none an independent effect on it. A system, therefore, is a whole that cannot be divided into independent parts..The essential properties of a system taken as a whole derive from the interactions of its parts, not their actions taken separately. Therefore, when a system is taken apart it loses its essential properties. Because of this – and this is the critical point – a system is a whole that cannot be understood by analysis.
If each part of a system, considered separately, is made to operate as efficiently as possible, the system as a whole willnotoperate as effectively as possible. For example, if we took the highest quality parts from various cars and put them all together into a new car, we would not even obtain an automobile because the parts would not fit together. Even if they did, they would not work well together. The performance of a system depends more on how its parts interact than on how they act independently of each other. Understanding proceeds from the whole to its parts, not from the parts to the whole as knowledge does.
We must always be concerned with 3 levels of purpose: the purposes of the system, of its parts, and of the system of which it is part, the suprasystem
Systems are either variety-increasing or variety-decreasing relative to the behavior of its parts. A prison is variety-decreasing whereas a library is variety-increasing. The most variety-decreasing type of social system is one we call a bureaucracy. A bureaucracy is an organization whose principal objective is to keep people busy doing nothing. They tend to mechanize procedures, thereby reducing choice
The best system designer is one who knows how to beat any system that others design. A smart sytem can use knowledge of how it can be beat to redesign itself to reduce or eliminate that kind of beating (use of countermeasure teams helps as well)
No system is as smart as some of the people it serves
Reactive planning has two major deficiencies. First, it is based on the mistaken assumption that if one gets rid of what one does not want, one gets what one wants. This assumption can be seen as false by anyone who turns on a television set and gets a program he or she does not want. Preactive planners focus on increasing their ability to forecast changes that will occur. Interactive planners focus on increasing their ability to control or influence change or its effects, and to respond rapidly and effectively to changes they cannot control, thereby decreasing their need to forecast. Reactive planning is primarily concerned with removal of threats; preactive planning is concerned with exploitation of opportunities. Interactive planning is concerned with both equally but it assumes that threats and opportunities are created when an organization does as well as by what is done to it. In planning, breadth is more important than depth, and interactions are more important than actions. Planning cannot be siloed or independent, all levels should be planned for simultaneously and interdpendently. When the principles of coordination and integration are combined the holistic principle is obtained: every part of an organization at every level should plan simultaneously and interdependently. The concept of all-over-at-once planning differs significantly from both reactive bottom-up and preactive top-down planning
With tongue in cheek, we can say that successful long-term planning involves, among other things uncovering the inevitable, determining how to exploit it, and taking credit for having brought it about
One way to obtain control over the future is to reduce the variations one might expect in the behavior of essential parts of the system or its environment
There are 4 ways of treating problems
Absolve – ignore it and hope it will go away or solve itself
Resolve – do something that yields an outcome that is good enough, that satisfies. Try to identify the cause of the problem, remove or suppress it, and thereby return to a previous state (clinical approach)
Solve – do something that yields the best possible outcome, that optimizes. Rely heavily on experimentation and quantitative analysis (research)
Dissolve – elimiante the problem by redesigning the system that has it. Idealize and approximate an ideal system and thereby do better in the future than the best that can be done now
Educators make little or no effort to relate the bits and pieces of information they dispense. Subject matters are kept apart. A course in one subject seldom uses or even refers to the content of another…Such compartmentalization reinforces the concept that knowledge is made up of many unrelated parts. But it is only by grasping the relationship between these parts that information can be transformed into knowledge, knowledge into understanding, and understanding into wisdom…Emphasis on separateness of subjects was characteristic of the Machine Age. Emphasis on relationships and interactions is characteristic of the Systems Age. Machine Age education is disintegrating; that of the Systems Age should be integrating.
Teachers cheat to stay in the system; students, to get out of it
Formal education denies the effectiveness of learning processes that take place out of class or school. Most learning takes place without teaching, but schools are founded on teaching, not learning. Therefore, the Systems Age education should focus on the learning process, not the teaching process. In the Systems Age school children should be motivated to learn whatever they ought to learn but never forced to learn what they do not want to. When students want to learn something or the need for learning it becomes apparent to them, they will learn it
Industrial Age education is variety-decreasing, but individuality should be preserved at all costs. Uniformity and conformity are anathema to progress
It is artificial counterproductive to separate play, formal education, and work
Systems Age education should be organized as a continuing, if not a continuous, process.
Systems Age education should be carried out by either educational systems that can and do learn and adapt. It should facilitate a student’s learning what he wants and needs to learn, enable him to learn more efficiently, and motivate him to want to learn, particularly those things he needs in order to satisfy his own desires and to be socially useful
Some subjects are best learned by teaching them to oneself, some subjects are best learned by teaching them to others, some skills are best learned through demonstration and instruction by one who already has it
Awareness of questions that have either not been asked or answered and synthesis of those answers that are available are best attained in seminar discussions guided by one steeped in the relevant area
Many students are best motivated to learn and best learn how to do so in attempting to solve real problems under real conditions with the guidance of one who is already so motivated and who knows how to learn
A major deficiency in formal education lies in its formality
Small groups of 3-5 students can be organized into learning cells in which they teach each other different subjects or different parts of the same subject.
Closed-book examinations – the type most frequently used – are poor tests of knowledge or understanding because they are not like real-life situations in which a person’s knowledge and understanding are tested and evaluated. They are primarily tests of memory. In real life, we are evaluated by how well we get jobs done.
I believe it is not nearly as important that a student learns any particular subject as it is that he learns how to learn and how to enjoy doing so. Subjects, disciplines, and even professions are convenient ways of labeling and filing knowledge. But the world is not organized in the same way as our knowledge of it is. There are no physical, chemical, biological, psychological, sociological, or other unidisciplinary problems. The disciplines and subjects are not different parts of the world; they are different ways of looking at the world. Hence, any problem can be looked at form the point of view from any discipline. For example, a doctor may see an elderly woman’s lack of good health as a consequence of her weak heart; an architect may see it as deriving from her having to walk up 3 flights of stairs to her inadequate apartment; an economist may see it as due to her lack of income; and a sociologist as a consequence of her family’s indifference. Progress comes from creative reorganization of what we already know as from discovery of new things. Therefore, we should not imbed our current wants of knowledge in students’ minds as fixed categories. They should be encouraged to oranize their learning in ways that best serve them, not us. Because what one learns is not nearly as important as learning how to leanr, and because questions are at least as important as answers, students should be free to design their own curricula
An ounce of information is worth a pound of data. An ounce of knowledge is worth a pound of information. An ounce of understanding is worth a pound of knowledge
Information is contained in descriptions, answers to questions that begin with such words as who, what, when, where, and how many. Knowledge is conveyed by instructions, answers to how-to questions. Understanding is conveyed by explanations, answers to why questions
Effectiveness is evaluated efficiency. It is efficiency multiplied by value, efficiency for a valued outcome. Intelligence is the ability to increase efficiency; wisdom is the ability to increase effectiveness
There are as many realities as there are minds contemplating them. Learning how to determine what points of view will produce the best treatment should be, but seldom is, an essential part of education
Academic departments and curricula do not organize knowledge; they organize teachers and disorganize knowledge. It is important for students to realize that the best place to deal with a problem is not necessarily where the problem appears. For example, we don’t try to treat headaches with brain surgery, but by swallowing a pill
What’s wrong with teaching? Four things are wrong with teaching. 1) More concerned with transmitting than receiving (although talking to others is a good way to find out what we think, it is often a very poor way of learning what they think). 2) it assumes ignorance on the part of the students. 3) it discourages, if not kills, creativity. 4) it normally uses tests and examinations to determine what students have learned, and they do not do so effectively.
The less we expect from others, the less we are likely to get from them
It is particularly important for managers to understand that correlation and regression analyses cannot establish causal relationships – only experiments can do that
First, we shall consider science as a process of inquiry; that is, as a procedure for a) answering questions, b) solving problems, and c) developoing more effective procedures for answering questions and solving problems. Science is also frequently taken to be a body of knowledge. We shall concentrate, however, on the process which generates this knowledge rather than on the knowledge itself.
Scientific progress has been two dimensional. First, the range of questions and problems to which science has been applied has been continuously extended. Second, science has continuously increased the efficiency with which inquiry can be conducted. The products of scientific inquiry then are 1) a body of information and knowledge which enables us better to control the environment in which we live, and 2) a body of procedures which enables us better to add to this body of information and knoweldge. science both informs and instructs. The body of information generated by science and the knowledge of how to use it are two products of science
The phases of research – observation, generalization, experimentation
Research in 6 phases – formulating the problem, constructing the model, testing the model, deriving a solution from the model, testing and controlling the solution, implementing the solution
As the rate of change increases, the complexity of the problems that face us also increases.
Analysis focuses on structure; it reveals how things work. Synthesis focuses on function; it reveals why things operate as they do. Therefore, analysis yields knowledge; synthesis yields understanding. The former enables us to describe; the latter, to explain.
There are 3 basic types of systems and models of them: deterministic (neither parts nor the whole are purposeful), animated (the whole is purposeful but the parts are not), social (parts and whole are purposeful). All are contained in ecological systems – some of whose parts are purposeful but not the whole
Henry Ford’s phenomenal success in the creation of a mechanistic mass production system marked the beginning of the production era but contained the seeds of its demise. He failed to appreciate the potentiality of the process he initiated when he said, in effect, “they can have any color they want as long as it is black.” This gave Alfred Sloan of General Motors the opportunity to gain domination of the market.
To grow is to increase in size or number. To develop is to increase one’s ability and desire to satisfy one’s own needs and legitimate desires and those of others. A legitimate desire is one that, when satisfied, does not impede the development of anyone else. Development is an increase in capability and competence. Development is better reflected in quality of life than in standard of living.
To learn is to increase one’s efficiency in the pursuit of a goal under unchanging conditions
The principal objective of a contract should be to ensure terminal satisfaction of both parties
Whatever else creativity implies, it implies production of the unexpected. It is the unexpected that produces the quantum leaps in development and quality of life
Wisdom is the ability to see the long-run consequences of current actions, the willingness to sacrifice short-run gains for larger long-run benefits, and the ability to control what is controllable and not to fret over what is not. Therefore, the essence of wisdom is concern with the future. It is not the type of concern with the future that the fortune teller has; he only tries to predict it. The wise man tries to control it. Planning is the design of a desired future and of effective ways of bringing it about. It is an instrument that is used by the wise, but not by the wise alone. When conducted by lesser men it often becomes an irrelevant ritual that produces short-run peace of mind, but not the future that is longed for.
Unless the adoption of a mission statement changes the behavior of the firm that makes it, it has no value. It should differentiate it from other companies, a mission statement should define the business that the company wants to be in, not necessarily is in, should be relevant to all the firm’s stakeholders, should be exciting and inspiring, does not have to appear to be feasible, only desirable
Good management follows the 5 C’s: Competence, Communicativeness, Concern, Courage, Creativity. The greatest of these is creativity – the creative manager makes his own breaks
Chase, Chance, and Creativity
Beauty is that property of the works and workings of man and Nature that stimulates new aspirations and commitments to their pursuit. No wonder we say of a solution to a problem that inspires us, “it is beautiful.”
A wrong solution to the right problem is generally better than the right solution to the wrong problem, because one usually gets feedback that enables one to correct wrong solutions, but not wrong problems. Wrong problems are perpetuated by right solutions to them.
The personality of a child added to a family tends to be formed so as to increase the stability of the family
Many people fail to realize that there are two kinds of power – power over and power to. Power over is authority and command, whereas power to is the ability to implement
Most of us who have suffered from an information overload are aware of the fact that when the amount of information exceeds a certain amount, a supersaturation point, both the amount and percentage of it that we try to absorb decreases. We give up hope of being able to keep up and abandon our efforts to do so. The more we get beyond this point the less we use.
It has long been known in science that the less we understand something, the more variables we require to explain it. Therefore, the manager who is asked what information he needs to control something he does not fully understand usually plays it safe and says he wants as much information as he can get
Style has to do with the satisfaction we derive from what we do rather than what we do it for
Stakeholder view of the firm – one stakeholder group, larger than all the others combined, is almost always ignored, future generations. They may be the ones most seriously affected by what is done today. How can their interests be taken into account when we do not know what their interests will be? We do know one thing about future generations: they will be interested in making their own decisions, not in having had us make their decisions for them. This requires keeping their options open
The difference between the amount of resources consumed by a corporation and the amount of consumption it makes possible is the amount of wealth it creates
The principal responsibility of managers is to create an environment and conditions under which their subordinates and do their jobs as effectively as their capabilities allow. It is not to supervise them. That is, the principal responsibility of a manager is to manage over and up, not down, to manage the interactions of their units with the rest of the organization and its environment, not to manage the actions of their subordinates. If subordinates require supervision beyond an initial break-in period, they should be replaced by persons who do not require it
What I got out of it
A brilliant thinker who makes the complex simple – especially liked what he had to say about education and solving – resolving – dissolving problems