ybrikman

The main thesis of this book is fantastic: "follow your passion" is bad career advice. "Develop rare, valuable skills" is much better. If people understood that, many of the issues in this country with employment and education would largely take care of themselves. The book is compelling and a very quick read, and I'd recommend it to just about everybody.

The only reason the review is 4 stars instead of 5 is that a) the quality of the writing fluctuates a bit from chapter to chapter, b) the book is a bit repetitive, and c) the final 3 chapters--"develop career capital", "control", and "mission"--seem like a rehash of Dan Pink's "autonomy", "mastery", and "purpose" from the book "Drive".



Some great quotes from the book:


You need to be good at something before you can expect a good job.

The passion hypothesis convinces people that somewhere there’s a magic “right” job waiting for them, and that if they find it, they’ll immediately recognize that this is the work they were meant to do. The problem, of course, is when they fail to find this certainty, bad things follow, such as chronic job-hopping and crippling self-doubt.

Two different approaches to thinking about work: the craftsman mindset, a focus on what value you’re producing in your job, and the passion mindset, a focus on what value your job offers you.

Deliberate practice provides the key to excellence in a diverse array of fields, among which are chess, medicine, auditing, computer programming, bridge, physics, sports, typing, juggling, dance, and music. If you want to understand the source of professional athletes’ talent, for example, look to their practice schedules—almost without exception they have been systematically stretching their athletic abilities, with the guidance of expert coaches, since they were children.

As Ericsson explains, “Most individuals who start as active professionals… change their behavior and increase their performance for a limited time until they reach an acceptable level. Beyond this point, however, further improvements appear to be unpredictable and the number of years of work… is a poor predictor of attained performance.” Put another way, *if you just show up and work hard, you’ll soon hit a performance plateau beyond which you fail to get any better.*” When I first encountered the work of Ericsson and Charness, this insight startled me. It told me that in most types of work—that is, work that doesn’t have a clear training philosophy—most people are stuck. This generates an exciting implication. Let’s assume you’re a knowledge worker, which is a field without a clear training philosophy. If you can figure out how to integrate deliberate practice into your own life, you have the possibility of blowing past your peers in your value, as you’ll likely be alone in your dedication to systematically getting better.

Deliberate practice is often the opposite of enjoyable.

“Do what people are willing to pay for.” Derek made it clear that this is different from pursuing money for the sake of having money. Remember, this is someone who gave away $22 million and sold his possessions after his company was acquired. Instead, as he explained: “Money is a neutral indicator of value. By aiming to make money, you’re aiming to be valuable.”

Strain, I now accepted, was good. Instead of seeing this discomfort as a sensation to avoid, I began to understand it the same way that a body builder understands muscle burn: a sign that you’re doing something right.

Working right trumps finding the right work.

Don’t obsess over discovering your true calling. Instead, master rare and valuable skills.

A quick, practical, actionable read on building MVP's. Borrows heavily from lots of existing sources, so the book feels like an MVP itself, but it works very well, as those sources lend it credibility and serve as wonderful examples. Only downside is the book tends to repeat itself a little bit and is really built to sell the UXPin product, but if you can ignore the marketing message, there is definitely a lot of useful material here.

"The MVP is more than a product, it's a way of thinking."

I do not understand why this is such a popular and beloved book. It starts off pretty interesting, with an engineered disease wiping out much of humanity, and for a while, it seems like a story warning people about the dangers of unchecked science, the evils of modern society, and survival in a post-apocalyptic world. But then, without much warning, the book takes a wild turn into a bunch of religious, superstitious, magical, good-versus-evil nonsense. Instead of telling an interesting tale about humans and choice, it's all the will of god and the devil or angels and demons (or Mother Abigail and Randall Flag) and none of the characters have any real choice. They just _are_ good or evil, they are compelled by dreams and visions to do stuff, and none of them really change or grow in any meaningful way. In short, the plot is complete nonsense.

The book, however, is exceptionally long--close to 1,500 pages long. It's full of unnecessary back stories, tangents, and characterization that is an utter waste, since the characters are just flat, unchanging, stereotypes. And some of the stereotypes are a bit uncomfortable. For example, almost all the women are helpless damsels in distress; the characters with mental retardation have magical abilities to detect evil--oh, and so do the dogs; after the plague, it seems like only a bunch of white folks survive, except for Mother Abigail, a god-fearing sacrificial black woman who is well over 100 years old. The writing is awful. Cheesy puns, terrible analogies, uninteresting prose. And the title and cover make no sense. No one really takes a stand, there is no battle, nothing. Just people surviving, having a religious hallucination, and then an exceptionally predictable and underwhelming "climax". Oh, and then the book drags on unnecessarily for a few more hours.

If you're actually interested in post apocalyptic tales, don't waste your time on the boring, pseudo-religious nonsense of the Stand. Instead, check out The Road, I Am Legend, Oryx and Crake, Children of Men, and World War Z.

A delightful book full of concrete, actionable advice that is perfect for amateurs that want to improve their design skills. This book won't make you a professional designer, but it gives you a vocabulary for thinking about fundamental design principles, including colors, fonts, alignment, repetition, contrast, and proximity. The book includes many examples that show how you can use each of these principles to improve a design step by step. By the time you're done, you've trained your eye a bit, and won't be able to see designs the same way. In fact, within 10 minutes of reading, I was going back to some of my designs and making small improvements.

The only downside is that the book is stronger in some areas than others. For example, the discussion of alignment and grouping is very well done, and has tons of examples to make the ideas stick. However, while the discussion of color theory is very clear, there aren't nearly as many examples, and it's not nearly as obvious how to use the information.

Overall, it's a very quick read that can really help the typical person.


Some good quotes from the book:

Lack of alignment is probably the biggest cause of unappealing documents. Our eyes like to see order; it creates a calm, secure feeling in its clarity. Plus it helps to communicate the information.

Nothing should be placed on the page arbitrarily. Every element should have some visual connection with another element on the page.

Avoid using more than one text alignment on the page (that is, don’t center some text and right-align other text). And please try very hard to break away from a centered alignment unless you are consciously trying to create a more formal, sedate presentation. Choose a centered alignment consciously, not by default.

The most practical thing to remember is that cool colors recede into the background, and warm colors come forward.

One of the most important features of an identity package or branding follows the Principle of Repetition: there must be some identifying image or style that carries throughout every piece.

Typography endows human language with visual form.

A design is in conflict when you set two or more typefaces on the same page that are similar—not really different but not really the same. I have seen countless students trying to match a typeface with one on the page, looking for a face that “looks similar.” Wrong. When you put two faces together that look too much alike without really being so, most of the time it looks like a mistake.

If you have trouble seeing what is wrong with a combination of typefaces, don’t look for what is different between the faces—look for what is similar. It is the similarities that are causing the problem.
The major rule to follow when contrasting type is this: Don’t be a wimp!

Start with the focal point. Decide what it is you want readers to see first.

This book has several very important ideas:

* Even if you aren't professional designer, you still use design everywhere in your life, including how you design your house, your resume, a report, some code, etc.

* Design is all about focusing on people's needs and abilities. You may think you know what those are by the virtue of being a human, but you don't, as most human actions are unconscious. Therefore, to be a good designer, you need to learn some psychology.

* Good design is all about finding the root cause (not just the stated problem) and using an iterative process (there are no failures, just experiments).

* Many of the things we attribute to human error are actually caused by poor design. This is because humans make mistakes _all the time_ and a good design _must_ take this into account.

For these alone, it's worth reading. That said, the book feels a little unfocused and scatter brained. It frequently goes off on tangents, most of which are interesting, but not always relevant to the main points. The book is also repetitive, repeating the same message about bad design, constraints, and culture over and over again.


Some good quotes:

Good design is actually a lot harder to notice than poor design, in part because good designs fit our needs so well that the design is invisible, serving us without drawing attention to itself. Bad design, on the other hand, screams out its inadequacies, making itself very noticeable.

We are all designers in the sense that all of us deliberately design our lives, our rooms, and the way we do things. We can also design workarounds, ways of overcoming the flaws of existing devices.

Two of the most important characteristics of good design are discoverability and understanding. Discoverability: Is it possible to even figure out what actions are possible and where and how to perform them? Understanding: What does it all mean? How is the product supposed to be used? What do all the different controls and settings mean?

All artificial things are designed. Whether it is the layout of furniture in a room, the paths through a garden or forest, or the intricacies of an electronic device, some person or group of people had to decide upon the layout, operation, and mechanisms. Not all designed things involve physical structures. Services, lectures, rules and procedures, and the organizational structures of businesses and governments do not have physical mechanisms, but their rules of operation have to be designed, sometimes informally, sometimes precisely recorded and specified.

Human-centered design is a design philosophy. It means starting with a good understanding of people and the needs that the design is intended to meet. This understanding comes about primarily through observation, for people themselves are often unaware of their true needs, even unaware of the difficulties they are encountering. Getting the specification of the thing to be defined is one of the most difficult parts of the design, so much so that the HCD principle is to avoid specifying the problem as long as possible but instead to iterate upon repeated approximations. This is done through rapid tests of ideas, and after each test modifying the approach and the problem definition. The results can be products that truly meet the needs of people.

A conceptual model is an explanation, usually highly simplified, of how something works. It doesn’t have to be complete or even accurate as long as it is useful.

When people use something, they face two gulfs: the Gulf of Execution, where they try to figure out how it operates, and the Gulf of Evaluation, where they try to figure out what happened [...] The role of the designer is to help people bridge the two gulfs.

We bridge the Gulf of Execution through the use of signifiers, constraints, mappings, and a conceptual model. We bridge the Gulf of Evaluation through the use of feedback and a conceptual model.

Most of us start by believing we already understand both human behavior and the human mind. After all, we are all human: we have all lived with ourselves all of our lives, and we like to think we understand ourselves. But the truth is, we don’t. Most of human behavior is a result of subconscious processes. We are unaware of them.

When we speak, we often do not know what we are about to say until our conscious mind (the reflective part of the mind) hears ourselves uttering the words.

When we perform a well-learned action, all we have to do is think of the goal and the behavioral level handles all the details: the conscious mind has little or no awareness beyond creating the desire to act.

We need to remove the word failure from our vocabulary, replacing it instead with learning experience. To fail is to learn: we learn more from our failures than from our successes. With success, sure, we are pleased, but we often have no idea why we succeeded. With failure, it is often possible to figure out why, to ensure that it will never happen again.
Scientists know this. Scientists do experiments to learn how the world works. Sometimes their experiments work as expected, but often they don’t. Are these failures? No, they are learning experiences. Many of the most important scientific discoveries have come from these so-called failures.

Eliminate all error messages from electronic or computer systems. Instead, provide help and guidance.

Humans err continually; it is an intrinsic part of our nature. System design should take this into account.

Eliminate the term human error. Instead, talk about communication and interaction: what we call an error is usually bad communication or interaction. When people collaborate with one another, the word error is never used to characterize another person’s utterance. That’s because each person is trying to understand and respond to the other, and when something is not understood or seems inappropriate, it is questioned, clarified, and the collaboration continues. Why can’t the interaction between a person and a machine be thought of as collaboration?

Our strengths are in our flexibility and creativity, in coming up with solutions to novel problems. We are creative and imaginative, not mechanical and precise. Machines require precision and accuracy; people don’t. And we are particularly bad at providing precise and accurate inputs. So why are we always required to do so? Why do we put the requirements of machines above those of people?

Seven fundamental principles of design:
1. Discoverability. It is possible to determine what actions are possible and the current state of the device.
2. Feedback.There is full and continuous information about the results of actions and the current state of the product or service. After an action has been executed, it is easy to determine the new state.
3. Conceptual model. The design projects all the information needed to create a good conceptual model of the system, leading to understanding and a feeling of control. The conceptual model enhances both discoverability and evaluation of results.
4. Affordances. The proper affordances exist to make the desired actions possible.
5. Signifiers.Effective use of signifiers ensures discoverability and that the feedback is well communicated and intelligible.
6. Mappings. The relationship between controls and their actions follows the principles of good mapping, enhanced as much as possible through spatial layout and temporal contiguity.
7. Constraints. Providing physical, logical, semantic, and cultural constraints guides actions and eases interpretation.

Never criticize unless you have a better alternative.

When people err, change the system so that type of error will be reduced or eliminated. When complete elimination is not possible, redesign to reduce the impact.

When many people all have the same problem, shouldn’t another cause be found? If the system lets you make the error, it is badly designed. And if the system induces you to make the error, then it is really badly designed. When I turn on the wrong stove burner, it is not due to my lack of knowledge: it is due to poor mapping between controls and burners. Teaching me the relationship will not stop the error from recurring: redesigning the stove will.

Why do people err? Because the designs focus upon the requirements of the system and the machines, and not upon the requirements of people. Most machines require precise commands and guidance, forcing people to enter numerical information perfectly. But people aren’t very good at great precision. We frequently make errors when asked to type or write sequences of numbers or letters. This is well known: so why are machines still being designed that require such great precision, where pressing the wrong key can lead to horrendous results?

In many industries, the rules are written more with a goal toward legal compliance than with an understanding of the work requirements. As a result, if workers followed the rules, they couldn’t get their jobs done.

Good designers never start by trying to solve the problem given to them: they start by trying to understand what the real issues are.

Don Norman's Law of Product Development: The day a product development process starts, it is behind schedule and above budget.

Good designers are quick learners, for today they might be asked to design a camera; tomorrow, to design a transportation system or a company’s organizational structure. How can one person work across so many different domains? Because the fundamental principles of designing for people are the same across all domains. People are the same, and so the design principles are the same.

Every modern innovation, especially the ones that significantly change lives, takes multiple decades to move from concept to company success A rule of thumb is twenty years from first demonstrations in research laboratories to commercial product, and then a decade or two from first commercial release to widespread adoption. Except that actually, most innovations fail completely and never reach the public.

I found this book frustrating. It's has a number of great design insights, but they are mixed with some truly awful advice on what programmers are like and how to build software, that I would hesitate to recommend it to any "business" person (the audience identified in the preface), as the advice in this book may cause more problems than it solves.

Pros:

* Good discussion of how programming is not like manufacturing or building physical goods.
* Love the ideas behind where software design goes wrong. E.g. the needs of a computer and a user are very different, and that trying to satisfy both as a programmer inherently creates conflict; physical device has one concrete use for every part, but software may have different "modes" for each part; physical products have inherent limits on the number of "features", whereas software doesn't; treating the interface as something you slap on later is a recipe for failure.
* The ideas behind using personas, scenarios, and building software to accomplish goals (not tasks) are very powerful.
* I'm a big fan of the concept that software should be "polite" and the examples that go with it.

Cons:

* Treats software as the sole exemplar of bad design. In reality, there is bad design everywhere. Only reason some mechanical systems are better designed is a) they've had way more time to develop those design practices and b) most mechanical devices are much simpler than software systems.
* Claims that computer literacy shouldn't be a requirement of using computers. That's like saying knowing how to read shouldn't be a requirement of using books.
* The author is WAY too dismissive of iterative development and "ship early and often". He claims that a) no good design has ever come from being iterative, b) 1 year release cycles are too fast for meaningful design, and b) software should be built like movies, with a massive "pre-production" phase where you do a huge, detailed, up front design. This is completely counter to everything we've learned about software development in the last 20 years and should be largely ignored. Every single good design is the result of enormous amounts of iteration and every good piece of software has evolved from something much smaller and simpler.
* Repetitive. The first 9 chapters (more than half the book) are about all the things that are wrong with design today. That's a bit too much.
* Very disrespectful of programmers, especially in part 3 of the book. Describes programmers almost as a different species, using lots of stereotypes. In fact, at points, the book seems to use the word "programmer" as a synonym for "someone who is a terrible designer." Even makes the absurd claim that bad UI is just the way nerds are getting revenge against jocks. Seriously?

Overall: skim quickly for the excellent design advice, and ignore all the horrible parts on how to run software projects or what programmers are like.




Good quotes from the book:

Reducing the cost of programming is not the same as reducing the cost of manufacturing. It's more like giving cheap tools to your workers than it is like giving the workers smaller paychecks. The companies that are shipping programming jobs overseas in order to pay reduced salaries are missing the point entirely.

Ironically, the best way to increase profitability in the information age is to spend more.

Treating any aspect of software design and construction as if it were a manufacturing process courts failure.

In all other construction disciplines, engineers plan a construction strategy that craftsmen execute. Engineers don't build bridges; ironworkers do. Only in software is the engineer tasked with actually building the product. Only in software is the “ironworker” tasked with determining how the product will be constructed. Only in software are these two tasks performed concurrently instead of sequentially. But companies that build software seem totally unaware of the anomaly.

I believe that there are two kinds of executives: those who are engineers, and those who are terrified of engineers.

Communications can be precise and exacting while still being tragically wrong.

To be a good programmer, one must be sympathetic to the nature and needs of the computer. But the nature and needs of the computer are utterly alien from the nature and needs of the human being who will eventually use it. The creation of software is so intellectually demanding, so all-consuming, that programmers must completely immerse themselves in an equally alien thought process. In the programmer's mind, the demands of the programming process not only supersede any demands from the outside world of users, but the very languages of the two worlds are at odds with each other.

The process of programming subverts the process of making easy-to-use products for the simple reason that the goals of the programmer and the goals of the user are dramatically different. The programmer wants the construction process to be smooth and easy. The user wants the interaction with the program to be smooth and easy. These two objectives almost never result in the same program.

Playing a violin is extremely difficult but low in cognitive friction because—although a violinist manipulates it in very complex and sophisticated ways—the violin never enters a “meta” state in which various inputs make it sound like a tuba or a bell. The violin's behavior is always predictable—though complex—and obeys physical laws, even while being quite difficult to control. In contrast, a microwave oven has a lot of cognitive friction, because the 10 number keys on the control panel can be put into one of two contexts, or modes. In one mode they control the intensity of the radiation, and in the other they control the duration. This dramatic change, along with the lack of sensory feedback about the oven's changed state, results in high cognitive friction.

I prefer the term interaction design to the term interface design because “interface” suggests that you have code over here, people over there, and an interface in between that passes messages between them. It implies that only the interface is answerable to the users' needs. The consequence of isolating design at the interface level is that it licenses programmers to reason like this: “I can code as I please because an 'interface' will be slapped on after I'm done.” It postpones design until after programming, when it is too late.
Like putting an Armani suit on Attila the Hun, interface design only tells how to dress up an existing behavior.

The number-one goal of all computer users is to not feel stupid

The prodigious gifts of silicon are so overwhelming that we find it easy to ignore the collateral costs. If you are stranded on a deserted island, you don't care much that your rescue ship is a leaky, rat-infested hulk. The difference between having a software solution for your problem and not having any solution is so great that we accept any hardship or difficulty that the solution might force on us.

Most software vendors don't know how to make their programs easy to use, but they sure know how to add features, so that is what they do.

Physical objects, such as my Swiss Army knife, are subject to a natural brake on the proliferation of marginal features. Each new blade or accessory costs money for the manufacturer to build into the knife. The maker of the knife knows this, and each proposed new feature must pass a gauntlet of justification before it makes it into a shipping product. In engineering terms, this is called a _negative feedback loop_, in which intrinsic forces trend toward stability and equilibrium.

Software architect Scott McGregor points out that Gresham's Law—that bad currency drives out good—is also relevant here. If there are two currencies, people will hoard the good one and try to spend the bad one. Eventually, only the bad currency circulates. Similarly, bad schedule estimates drive out good ones. If everybody makes bogus but rosy predictions, the one manager giving realistic but longer estimates will appear to be a heel-dragger and will be pressured to revise his estimates downward.

Most product managers that I have worked with would rather ship a failure on time than risk going late.

It has been said that the way Stalin cleared a minefield was to march a regiment through it. Effective? Yes. Efficient, humanitarian, viable, desirable? No.

I am not saying that you cannot learn from trial and error, but those trials should be informed by something more than random chance and should begin from a well-thought-out solution, not an overnight hack. Otherwise, it's just giving lazy or ignorant businesspeople license to abuse consumers.

It is more costly in the long run to have programmers write the wrong thing than to write nothing at all. This truth is so counterintuitive that most managers balk at the very idea. After code is written, it is very difficult to throw it out. Like writers in love with their prose, programmers tend to have emotional attachments to their algorithms. Altering programs in midstride upsets the development process and wounds the code, too. It's hard on the manager to discard code because she is the one who paid dearly for it, and she knows she will have to spend even more to replace it.

Develop a precise description of our user and what he wishes to accomplish.

The broader a target you aim for, the more certainty you have of missing the bull's-eye. If you want to achieve a product-satisfaction level of 50%, you cannot do it by making a large population 50% happy with your product. You can only accomplish it by singling out 50% of the people and striving to make them 100% happy. It goes further than that. You can create an even bigger success by targeting 10% of your market and working to make them 100% _ecstatic_. It might seem counterintuitive, but designing for a _single user_ is the most effective way to satisfy a broad population.

Giving the persona a name is one of the most important parts of successfully defining one. _A persona without a name is simply not useful_. Without a name, a persona will never be a concrete individual in anyone's mind.

There is an easy way to tell the difference between tasks and goals. Tasks change as technology changes, but goals have the pleasant property of remaining very stable. For example, to travel from St. Louis to San Francisco, my goals are speed, comfort, and safety. Heading for the California gold fields in 1850, I would have made the journey in my new, high-tech Conestoga wagon. In the interest of safety, I would have brought my Winchester rifle. Heading from St. Louis to the Silicon Valley in 1999, I would make the journey in a new, high-tech Boeing 777.

Designing from tasks instead of goals is one of the main causes of frustrating and ineffective interaction.

One important implication of the research is remarkably profound: If we want users to like our software, we should design it to behave like a likeable person. If we want users to be productive with our software, we should design it to behave like a good human work mate. Simple, huh?

The program just doesn't care about me and treats me like a stranger even though I'm the only human it knows.

Although the _code_ may succeed or fail in its ability to handle edge cases, the _product_ will succeed or fail in its ability to handle daily use and necessary cases.

From an interaction designer's point of view, the divisions between hardware and software are inconsequential because they are inconsequential to a user. The user doesn't care which is more expensive to build.

In programming, there is always an infinite variety of ways to solve any given problem. Experienced programmers, as they explore their options searching for the optimum solution, occasionally stumble on a technique that allows them to throw out hundreds—or even thousands—of lines of code. This only happens when the programmer has made a valuable conceptual leap forward. When she can toss out lots of code, her program is getting better. Less code means less complexity, fewer bugs, fewer opportunities for invalid interactions, and easier maintainability. Interaction designers share this sensation. As they explore their options, they discover places where they can dispense with entire screens or discard large and complex dialog boxes. The designer knows that each element of the user interface is a burden on the user. Each button and icon is one more thing that the user must know about, and must work around, to get to what she really wants. Doing more with less is always better.

There is a big difference between _listening to_ and _following_ your customers. Listening is good. It means applying your own filter to what you have heard. Following is bad. It means merely doing what your customers tell you to do.

The customer might have money, but it lacks two vital things: It doesn't have your best, long-term interests at heart, and it doesn't know how to design your product.

There is a lot of interesting content in this book, but I'm not sure it actually made me more creative. The writing is _slightly_ meandering and academic in style, a bit like a research survey paper, but the content within is genuinely valuable. Just the idea of thinking about *how* you come up with a solution (visual thinking, mathematical thinking, deduction, induction, etc), rather than what the solution turns out to be, is a pretty powerful exercise. The list of blocks that get in the way of creative thinking are also useful, and the discussion of the psychology around them is fascinating, but I walked away without a keen awareness of how to get past all of these blocks, other than brainstorming and making lists. That said, perhaps the most powerful aspect of the book is to treat creativity as a skill, and one that can be honed, and perhaps the mere awareness of that fact will be enough to get better over time.

Some good quotes from the book:

We have a one-watt mind in a megawatt world. We cannot process all of the data available to us in raw form. The mind, therefore, depends heavily on structures, models, and stereotypes.

The natural response to a problem seems to be to try to get rid of it by finding an answer--often taking the first answer that occurs and pursuing it because of one’s reluctance to spend the time and mental effort needed to conjure up a richer storehouse of alternatives from which to choose.

Perceptual blocks are obstacles that prevent the problem-solver from clearly perceiving either the problem itself or the information needed to solve the problem.

Once a label (professor, housewife, black, chair, butterfly, automobile, laxative) has been applied, people are less likely to notice the actual qualities or attributes of what is being labeled.

(From New Think by Edward de Bono):
Logic is the tool that is used to dig holes deeper and bigger, to make them altogether better holes. But if the hole is in the wrong place, then no amount of improvement is going to put it in the right place. No matter how obvious this may seem to every digger, it is still easier to go on digging in the same place than to start all over again in a new place. Vertical thinking is digging the same hole deeper; lateral thinking is trying again elsewhere.

Fear to make a mistake, to fail, or to take a risk is perhaps the most general and common emotional block. Most of us have grown up rewarded when we produce the “right” answer and punished if we make a mistake. When we fail we are made to realize that we have let others down (usually someone we love). Similarly we are taught to live safely (a bird in the hand is worth two in the bush, a penny saved is a penny earned) and avoid risk whenever possible. Obviously, when you produce and try to sell a creative idea you are taking a risk: of making a mistake, failing, making an ass of yourself, losing money, hurting yourself, or whatever.

In a sense, problem-solving is bringing order to chaos. A desire for order is therefore necessary. However, the ability to tolerate chaos is a must.

If you analyze or judge too early in the problem-solving process, you will reject many ideas. This is detrimental for two reasons. First of all, newly formed ideas are fragile and imperfect--they need time to mature and acquire the detail needed to make them believable. Secondly, as we will discuss later, ideas often lead to other ideas.

You should allow the mind to struggle with problems over time. Incubation is important in problem-solving. It is poor planning not to allow adequate time for incubation in the solution of an important problem. It is also important to be able to relax in the midst of problem-solving. Your overall compulsiveness is less fanatical when you are relaxed, and the mind is more likely to deal with seemingly “silly” combinations of thoughts. If you are never relaxed, your mind is usually on guard against non-serious activities, with resulting difficulties in the type of thinking necessary for fluent and flexible conceptualization.

Arthur Koestler was an important writer who among other topics, treated conceptualization. In an essay, “The Three Domains of Creativity”, he identified these “domains” as artistic originality (which he called the “ah!” reaction), scientific discovery (the “aha!” reaction), and comic inspiration (the “haha!” reaction). He defined creative acts as the combination of previously unrelated structures in such a way that you get more out of the emergent whole than you have put in. He explained comic inspiration, for example, as stemming from “the interaction of two mutually exclusive associative contexts.” As in creative artistic and scientific acts, two ideas have to be brought together that are not ordinarily combined. This is one of the essentials of creative thinking. In the particular case of humor, according to Koestler, the interaction causes us “to perceive the situation in two self-consistent but habitually incompatible frames of reference.” [...] The critical point of interest here is that a similar reaction (laughter) may greet an original idea. A concept may be so contrary to the logical progress of the problem solution, precedent, or common intuition, that it may cause laughter. In fact any answer to a problem releases tension. Your unbelievably insightful solution to a problem may therefore be greeted with giggles and hoots, not only from others but even from yourself.

The Introduction to Process Notebook, also by Interaction Associates, summarized the situation as follows:
Just as we use physical tools for physical tasks, we employ conceptual tools for conceptual tasks. To familiarize yourself with a tool, you may experiment with it, test it in different situations, and evaluate its usefulness. The same method can be applied to conceptual tools. Our ability as thinkers is dependent on our range and skill with our own tools.

We learn as we grow older that it is good to be smart. Smartness is often associated with the amount of knowledge we possess. A question is an admission that we do not know or understand something. We therefore leave ourselves open to suspicion that we are not omniscient. Thus, we see the almost incredible ability of students to sit totally confused in a class in a university that costs thousands of dollars a year to attend and not ask questions. Thus, we find people at cocktail parties listening politely to conversations they do not understand, and people in highly technical fields accepting jargon they do not understand.

A camel is a horse designed by committee.

In authoritative systems individuals attempt to perform well according to their job descriptions. But how many job descriptions contain the phrase “take risks”?

It is not too difficult in any large organization to find people whose job is to prevent mistakes.

Bob Sutton, an organizational behavior professor at Stanford, is fond of saying that non-innovative companies reward success, punish failure, and accept inaction. Innovative companies reward both success and failure (assuming it follows a valiant attempt) and punish inaction.

As an engineer, this book makes me happy. A great discussion of how to break *any* problem down into quantifiable metrics, how to figure out which of those metrics is valuable, and how to measure them. The book is fairly actionable, there is a complementary website with lots of handy excel tools, and there are plenty of examples to help you along. The only downside is that this is largely a stats book in disguise, so some parts are fairly dry and a the difficulty level jumps around a little bit. If you make important decisions, especially in business, this book is for you.

Some great quotes:

Anything can be measured. If a thing can be observed in any way at all, it lends itself to some type of measurement method. No matter how “fuzzy” the measurement is, it’s still a measurement if it tells you more
than you knew before. And those very things most likely to be seen as immeasurable are, virtually always, solved by relatively simple measurement methods.

Measurement: a quantitatively expressed reduction of uncertainty based on one or more observations.

So a measurement doesn’t have to eliminate uncertainty after all. A mere _reduction_ in uncertainty counts as a measurement and possibly can be worth much more than the cost of the measurement.

A problem well stated is a problem half solved.
—Charles Kettering (1876–1958)

The clarification chain is just a short series of connections that should bring us from thinking of something as an intangible to thinking of it as a tangible. First, we recognize that if X is something that we care about, then X, by definition, must be detectable in some way. How could we care about things like “quality,” “risk,” “security,” or “public image” if these things were totally undetectable, in any way, directly or indirectly? If we have reason to care about some unknown quantity, it is because we think it corresponds to desirable or undesirable results in some way. Second, if this thing is detectable, then it must be detectable in some amount. If you can observe a thing at all, you can observe more of it or less of it. Once we accept that much, the final step is perhaps the easiest. If we can observe it in some amount, then it must be measurable.

Rule of five: There is a 93.75% chance that the median of a population is between the smallest and largest values in any random sample of five from that population.

An important lesson comes from the origin of the word experiment. “Ex- periment” comes from the Latin ex-, meaning “of/from,” and periri, mean- ing “try/attempt.” It means, in other words, to get something by trying. The statistician David Moore, the 1998 president of the American Statistical Association, goes so far as to say: “If you don’t know what to measure, measure anyway. You’ll learn what to measure.”

Four useful measurement assumptions:
1. Your problem is not as unique as you think.
2. You have more data than you think.
3. You need less stated that you think.
4. And adequate amount of new data is more accessible than you think.

Don’t assume that the only way to reduce your uncertainty is to use an impractically sophisticated method. Are you trying to get published in a peer-reviewed journal, or are you just trying to reduce your uncertainty about a real-life business decision? Think of measurement as iterative. Start measuring it. You can always adjust the method based on initial findings.

In business cases, most of the variables have an "information value" at or near zero. But usually at least some variables have an information value that is so high that some deliberate measurement is easily justified.

While there are certainly variables that do not justify measurement, a persistent misconception is that unless a measurement meets an arbitrary standard (e.g., adequate for publication in an academic journal or meets generally accepted accounting standards), it has no value. This is a slight oversimplification, but what really makes a measurement of high value is a lot of uncertainty combined with a high cost of being wrong. Whether it meets some other standard is irrelevant.

When people say “You can prove anything with statistics,” they probably don’t really mean “statistics,” they just mean broadly the use of numbers (especially, for some reason, percentages). And they really don’t mean “anything” or “prove.” What they really mean is that “numbers can be used to confuse people, especially the gullible ones lacking basic skills with numbers.” With this, I completely agree but it is an entirely different claim.

The fact is that the preference for ignorance over even marginal reductions in ignorance is never the moral high ground. If decisions are made under a self-imposed state of higher uncertainty, policy makers (or even businesses like, say, airplane manufacturers) are betting on our lives with a higher chance of erroneous allocation of limited resources. In measurement, as in many other human endeavors, ignorance is not only wasteful but can be dangerous.

If we can’t identify a decision that could be affected by a proposed measurement and how it could change those decisions, then the measurement simply has no value.

The lack of having an exact number is not the same as knowing nothing.

The McNamara Fallacy: The first step is to measure whatever can be easily measured. This is OK as far as it goes. The second step is to disregard that which can’t easily be measured or to give it an arbitrary quantitative value. This is artificial and misleading. The third step is to presume that what can’t be measured easily isn’t important. This is blindness. The fourth step is to say that what can’t easily be measured really doesn’t exist. This is suicide.

First, we know that the early part of any measurement usually is the high-value part. Don’t attempt a massive study to measure something if you have a lot of uncertainty about it now. Measure a little bit, remove some uncertainty, and evaluate what you have learned. Were you surprised? Is further measurement still necessary? Did what you learned in the beginning of the measurement give you some ideas about how to change the method? Iterative measurement gives you the most flexibility and the best bang for the buck.

This point might be disconcerting to some who would like more certainty in their world, but everything we know from “experience” is just a sample. We didn’t actually experience everything; we experienced some things and we extrapolated from there. That is all we get—fleeting glimpses of a mostly unobserved world from which we draw conclusions about all the stuff we didn’t see. Yet people seem to feel confident in the conclusions they draw from limited samples. The reason they feel this way is because experience tells them sampling often works. (Of course, that experience, too, is based on a sample.)

Anything you need to quantify can be measured in some way that is superior to not measuring it at all.
—Gilb’s Law

A pretty convincing argument for why large, established companies struggle to keep up with disruptive innovations. It turns out that the very things that make those companies dominant in an existing market work against them when considering new markets. As the pace of disruption accelerates, the lessons in this book become more and more important.

Less convincing are the solutions the book proposes and, at an even more basic level, how to distinguish between what the book calls "sustaining innovations" and "disruptive innovations". It seems that the definitions rely on hindsight (ie, a disruptive innovation is one that turns out to, uh, disrupt the leaders) and are not particularly predictive. And since the solutions the book proposes only work for the disruptive ones, this is a rather big weakness.

Still, the book is worth reading for building your awareness and vocabulary around these issues. The writing is a bit dry and academic-sounding, but there are plenty of good examples that, if you've ever worked at a large company, will feel all-too-familiar.



Some good quotes from the book:


First, disruptive products are simpler and cheaper; they generally promise lower margins, not greater profits. Second, disruptive technologies typically are first commercialized in emerging or insignificant markets. And third, leading firms’ most profitable customers generally don’t want, and indeed initially can’t use, products based on disruptive technologies. By and large, a disruptive technology is initially embraced by the least profitable customers in a market. Hence, most companies with a practiced discipline of listening to their best customers and identifying new products that promise greater profitability and growth are rarely able to build a case for investing in disruptive technologies until it is too late.

While managers may think they control the flow of resources in their firms, in the end it is really customers and investors who dictate how money will be spent because companies with investment patterns that don’t satisfy their customers and investors don’t survive. The highest-performing companies, in fact, are those that are the best at this, that is, they have well-developed systems for killing ideas that their customers don’t want. As a result, these companies find it very difficult to invest adequate resources in disruptive technologies—lower-margin opportunities that their customers don’t want—until their customers want them. And by then it is too late.

With few exceptions, the only instances in which mainstream firms have successfully established a timely position in a disruptive technology were those in which the firms’ managers set up an autonomous organization charged with building a new and independent business around the disruptive technology. Such organizations, free of the power of the customers of the mainstream company, ensconce themselves among a different set of customers—those who want the products of the disruptive technology.

In dealing with disruptive technologies leading to new markets, however, market researchers and business planners have consistently dismal records. In fact, based upon the evidence from the disk drive, motorcycle, and microprocessor industries, reviewed in chapter 7, the only thing we may know for sure when we read experts’ forecasts about how large emerging markets will become is that they are wrong.

Simply put, when the best firms succeeded, they did so because they listened responsively to their customers and invested aggressively in the technology, products, and manufacturing capabilities that satisfied their customers’ next-generation needs. But, paradoxically, when the best firms subsequently failed, it was for the same reasons—they listened responsively to their customers and invested aggressively in the technology, products, and manufacturing capabilities that satisfied their customers’ next-generation needs. This is one of the innovator’s dilemmas: Blindly following the maxim that good managers should keep close to their customers can sometimes be a fatal mistake.

My findings consistently showed that established firms confronted with disruptive technology change did not have trouble developing the requisite technology [...] Rather, disruptive projects stalled when it came to allocating scarce resources among competing product and technology development proposals [...] Sustaining projects addressing the needs of the firms’ most powerful customers [...] almost always preempted resources from disruptive technologies with small markets and poorly defined customer needs.

Successful companies want their resources to be focused on activities that address customers’ needs, that promise higher profits, that are technologically feasible, and that help them play in substantial markets. Yet, to expect the processes that accomplish these things also to do something like nurturing disruptive technologies—to focus resources on proposals that customers reject, that offer lower profit, that underperform existing technologies and can only be sold in insignificant markets—is akin to flapping one’s arms with wings strapped to them in an attempt to fly. Such expectations involve fighting some fundamental tendencies about the way successful organizations work and about how their performance is evaluated.

One of the dilemmas of management is that, by their very nature, processes are established so that employees perform recurrent tasks in a consistent way, time after time. To ensure consistency, they are meant not to change—or if they must change, to change through tightly controlled procedures. This means that the very mechanisms through which organizations create value are intrinsically inimical to change.

In order for a $40 million company to grow 25 percent, it needs to find $10 million in new business the next year. For a $40 billion company to grow 25 percent, it needs to find $10 billion in new business the next year. The size of market opportunity that will solve each of these companies’ needs for growth is very different. As noted in chapter 6, an opportunity that excites a small organization isn’t big enough to be interesting to a very large one. One of the bittersweet rewards of success is, in fact, that as companies become large, they literally lose the capability to enter small emerging markets.

Disruptive technology should be framed as a marketing challenge, not a technological one.

A superb book that presents convincing arguments, great stories, great research, great analogies, and highly actionable advice on how to communicate ideas in a way that will "stick". That is, in a way that will make people remember your ideas and act on them. In fact, the book uses its own advice to convey its ideas, and, uh, well, it stuck. I wish I had read it long ago. I wish everyone would read it, as it would improve the average quality of communication significantly.

Some good quotes from the book:


PRINCIPLE 1: SIMPLICITY
How do we find the essential core of our ideas? [...] Proverbs are the ideal. We must create ideas that are both simple and profound. The Golden Rule is the ultimate model of simplicity: a one-sentence statement so pro- found that an individual could spend a lifetime learning to follow it.

PRINCIPLE 2: UNEXPECTEDNESS
How do we get our audience to pay attention to our ideas, and how do we maintain their interest when we need time to get the ideas across? We need to violate people's expectations. [...] For our idea to endure, we must generate interest and curiosity. [...] We can engage people's curiosity over a long period of time by systematically "opening gaps" in their knowledge—and then filling those gaps.

PRINCIPLE 3: CONCRETENESS
How do we make our ideas clear? We must explain our ideas in terms of human actions, in terms of sensory information. [...] Naturally sticky ideas are full of concrete images—ice-filled bathtubs, apples with razors—because our brains are wired to remember concrete data.

PRINCIPLE 4: CREDIBILITY
How do we make people believe our ideas? [...] Sticky ideas have to carry their own credentials. We need ways to help people test our ideas for themselves—a "try before you buy" philosophy for the world of ideas.

PRINCIPLE 5: EMOTIONS
How do we get people to care about our ideas? We make them feel something. [...] We are wired to feel things for people, not for abstractions.

PRINCIPLE 6: STORIES
How do we get people to act on our ideas? We tell stories. [...] Research shows that mentally rehearsing a situation helps us perform better when we encounter that situation in the physical environment. Similarly, hearing stories acts as a kind of mental flight simulator, preparing us to respond more quickly and effectively.

To summarize, here's our checklist for creating a successful idea: a Simple Unexpected Concrete Credentialed Emotional Story. A clever observer will note that this sentence can be compacted into the acronym SUCCESs.

This is the Curse of Knowledge. Once we know something, we find it hard to imagine what it was like not to know it. Our knowledge has "cursed" us. And it becomes difficult for us to share our knowledge with others, because we can't readily recreate our listeners' state of mind.

Had John F. Kennedy been a CEO, he would have said, "Our mission is to become the international leader in the space industry through maximum team-centered innovation and strategically targeted aerospace initiatives."

Highly creative ads are more predictable than uncreative ones. It's like Tolstoy's quote: "All happy families resemble each other, but each unhappy family is unhappy in its own way." All creative ads resemble one another, but each loser is uncreative in its own way.

If you say three things, you don't say anything.

To be surprising, an event can't be predictable. Surprise is the opposite of predictability. But, to be satisfying, surprise must be "post-dictable." The twist makes sense after you think about it, but it's not something you would have seen coming.

So, a good process for making your ideas stickier is: (1) Identify the central message you need to communicate—find the core; (2) Figure out what is counterintuitive about the message —i.e., What are the unexpected implications of your core message? Why isn't it already happening naturally? (3) Communicate your message in a way that breaks your audience's guessing machines along the critical, counterintuitive dimension. Then, once their guessing machines have failed, help them refine their machines.

Curiosity, he [Loewenstein] says, happens when we feel a gap in our knowledge. Loewenstein argues that gaps cause pain. When we want to know something but don't, it's like having an itch that we need to scratch. To take away the pain, we need to fill the knowledge gap. We sit patiently through bad movies, even though they may be painful to watch, because it's too painful not to know how they end.

To make our communications more effective, we need to shift our thinking from "What information do I need to convey?" to "What questions do I want my audience to ask?"

Abstraction demands some concrete foundation. Trying to teach an abstract principle without concrete foundations is like trying to start a house by building a roof in the air.

Memory, then, is not like a single filing cabinet. It is more like Velcro. If you look at the two sides of Velcro material, you'll see that one is covered with thousands of tiny hooks and the other is covered with thousands of tiny loops. When you press the two sides together, a huge number of hooks get snagged inside the loops, and that's what causes Velcro to seal. Your brain hosts a truly staggering number of loops. The more hooks an idea has, the better it will cling to memory. Your childhood home has a gazillion hooks in your brain. A new credit card number has one, if it's lucky.

Novices perceive concrete details as concrete details. Experts perceive concrete details as symbols of patterns and insights that they have learned through years of experience. And, because they are capable of seeing a higher level of insight, they naturally want to talk on a higher level. They want to talk about chess strategies, not about bishops moving diagonally.

Caples says companies often emphasize features when they should be emphasizing benefits. "The most frequent reason for unsuccessful advertising is advertisers who are so full of their own accomplishments (the world's best seed!) that they forget to tell us why we should buy (the world's best lawn!)." An old advertising maxim says you've got to spell out the benefit of the benefit. In other words, people don't buy quarter-inch drill bits. They buy quarter-inch holes so they can hang their children's pictures.

This finding suggests that it may be the tangibility, rather than the magnitude, of the benefits that makes people care. You don't have to promise riches and sex appeal and magnetic personalities. It may be enough to promise reasonable benefits that people can easily imagine themselves enjoying.

How can we make people care about our ideas? We get them to take off their Analytical Hats. We create empathy for specific individuals. We show how our ideas are associated with things that people already care about. We appeal to their self-interest, but we also appeal to their identities—not only to the people they are right now but also to the people they would like to be

We cannot simply visualize the story on a movie screen in our heads; we must somehow simulate it, complete with some analogue (however loose) to the spatial relationships described in the story. These studies suggest that there's no such thing as a passive audience. When we hear a story, our minds move from room to room. When we hear a story, we simulate it.

Stories are like flight simulators for the brain. Hearing the nurse's heart-monitor story isn't like being there, but it's the next best thing.

The problem is that when you hit listeners between the eyes they respond by fighting back. The way you deliver a message to them is a cue to how they should react. If you make an argument, you're implicitly asking them to evaluate your argument—judge it, debate it, criticize it—and then argue back, at least in their minds. But with a story, Denning argues, you engage the audience—you are involving people with the idea, asking them to participate with you.

There is a curious disconnect between the amount of time we invest in training people how to arrive at the Answer and the amount of time we invest in training them how to Tell Others. It's easy to graduate from medical school or an MBA program without ever taking a class in communication. College professors take dozens of courses in their areas of expertise but none on how to teach. A lot of engineers would scoff at a training program about Telling Others.

For an idea to stick, for it to be useful and lasting, it's got to make the audience:
1. Pay attention
2. Understand and remember it
3. Agree/Believe
4. Care
5. Be able to act on it

Very quick read, but not a particularly good one. The advice is extremely simplistic, bordering on platitudes, and much of it is not particularly actionable. A lot of it simply does not apply to *many* companies: e.g. building for yourself is all it takes to find a market (tell that to the many engineers who built something that *only* they would want), everything can be self-funded (many business cannot), everyone should give away all of their data for free (unless, of course, data is your differentiator, which it is for many companies).

It's not all bad, of course. The advice on design is actually quite good, mostly because it sticks with very concrete details: e.g. avoid too many preferences/settings in an app, design for regular, blank, and error states, copywriting is part of the design, and that your app has a voice. And some of the quotes from third parties are decent too.

Overall, there is some good stuff in this book, but it doesn't do a very good job of presenting it.


Some quotes that I liked:

Build half a product, not a half-ass product

The best designers and the best programmers aren’t the ones with the best skills, or the nimblest fingers, or the ones who can rock and roll with Photoshop or their environment of choice, they are the ones that can determine what just doesn’t matter. That’s where the real gains are made. Most of the time you spend is wasted on things that just don’t matter. If you can cut out the work and thinking that just don’t matter, you’ll achieve productivity you’ve never imagined.

Another reason to design first is that the interface is your product. What people see is what you’re selling. If you just slap an interface on at the end, the gaps will show.

Design for regular, blank, and error states.

The customer decides if an application is worthy at this blank slate stage – the stage when there’s the least amount of information, design, and content on which to judge the overall usefulness of the application. When you fail to design an adequate blank slate, people don’t know what they are missing because everything is missing.

Copywriting is interface design. Great interfaces are written. If you think every pixel, every icon, every typeface matters, then you also need to believe every letter matters.

Encourage programmers to make counteroffers.You want to hear: “The way you suggested will take 12 hours. But there’s a way I can do it that will only take one hour. It won’t do x but it will do y.”

Lorem ipsum changes the way copy is viewed. It reduces text-based content to a visual design element – a shape of text – instead of what it should be: valuable information someone is going to have to enter and/or read. Dummy text means you won’t see the inevitable variations that show up once real information is entered. It means you won’t know what it’s like to fill out forms on your site. Dummy text is a veil between you and reality.

Think of your product as a person. What type of person do you want it to be? Polite? Stern? Forgiving? Strict? Funny? Deadpan? Serious? Loose? Do you want to come off as paranoid or trust- ing? As a know-it-all? Or modest and likable? Once you decide, always keep those personality traits in mind as the product is built. Use them to guide the copywriting, the interface, and the feature set. Whenever you make a change, ask yourself if that change fits your app’s personality. Your product has a voice – and it’s talking to your customers 24 hours a day.

This book is a mixed bag. There are a few really good blog posts and essays in here. In particular, all the ones from Paul Graham are *superb* (as usual), Peter Thiel's discussion of distribution is excellent, and there is a great chapter on the basics of fundraising and investors. The other essays are not quite as good. The one on "what is web 2.0" feels a bit dated. There is one chapter that's just the wikipedia entry on Lean Startups (lol). One chapter looks like it was originally a slide deck and is not pleasant to read. Overall, there is too much focus on the fundraising and investor aspects of startups, which is not too surprising, since the book was put together by an VC firm. At least it's a quick read and free.



Some good quotes from the book:

=== Tim O'Reilly

Hyperlinking is the foundation of the web. As users add new content, and new sites, it is bound in to the structure of the web by other users discovering the content and linking to it. Much as synapses form in the brain, with associations becoming stronger through repetition or intensity, the web of connections grows organically as an output of the collective activity of all web users.

=== Taylor Davidson

Building financial models can still be valuable, if you remember one thing: the model doesn’t matter, the thought process does.


In the end, the most important thing isn’t a really detailed financial model – it’s having a grasp of what the major influencing factors are on your model (hint: sales and growth) and then getting some kind of data that helps you accurately predict these variables.

=== Felix Salmon

VCs and angels may talk about changing the world, but their business model rests on a more prosaic calculation: Buy low, sell high. They invest in companies they think will become more valuable, so they can sell their stake for a sizable profit. From the time that VCs invest in a company, they have five years—10 at the most—to sell their entire position, hopefully for many times more than their original investment. After that, it doesn’t matter to them whether the company survives a year or a century.

To put it another way, the VC model is based on creating wealth for investors, not on building successful businesses. You buy into a company early on and sell out a few years later; if you pick well, you can make lots of money. But your profits don’t accrue to the company itself, which could implode after your exit for all you care. Silicon Valley is full of venture capitalists who have become dynastically wealthy off the backs of companies that no longer exist.

=== Paul Graham, talking to high schoolers

When I ask people what they regret most about high school, they nearly all say the same thing: that they wasted so much time. If you’re wondering what you’re doing now that you’ll regret most later, that’s probably it.


The most powerful sort of aptitude is a consuming interest in some question, and such interests are often acquired tastes. A distorted version of this idea has filtered into popular culture under the name “passion.” I recently saw an ad for waiters saying they wanted people with a “passion for service.” The real thing is not something one could have for waiting on tables. And passion is a bad word for it. A better name would be curiosity.


Curiosity turns work into play. For Einstein, relativity wasn’t a book full of hard stuff he had to learn for an exam. It was a mystery he was trying to solve. So it probably felt like less work to him to invent it than it would seem to someone now to learn it in a class.


The only real difference between adults and high school kids is that adults realize they need to get things done, and high school kids don’t. That realization hits most people around 23. But I’m letting you in on the secret early. So get to work. Maybe you can be the first generation whose greatest regret from high school isn’t how much time you wasted.


The second biggest regret was caring so much about unimportant things. And especially about what other people thought of them. I think what they really mean, in the latter case, is caring what random people thought of them. Adults care just as much what other people think, but they get to be more selective about the other people. I have about thirty friends whose opinions I care about, and the opinion of the rest of the world barely affects me. The problem in high school is that your peers are chosen for you by accidents of age and geography, rather than by you based on respect for their judgement.

The first half of this book is gold. It kicks off with the diffusion of innovations theory and a characterization of innovators, early adopters, early majority, late majority, and laggards. It goes through lots of concrete strategy on how to market to each of these groups, how different they are, and why there is a tricky chasm between the two early adopter groups and everyone else. The lessons here go beyond marketing a product and are just as useful in other contexts, such as how to convince people at your own company to do something. The writing is clear, keeps jargon to a minimum, and has lots of good analogies and even a few good jokes.

As you get into the second half of the book, it runs out of steam. Or, to be fair, perhaps it just wasn't what I was looking for. It starts to go into detailed tactics, and at this level of detail, the book really shows its age. Many of the companies and technologies it uses as examples are long gone. Worse yet, some of the advice doesn't make sense any more. For example, the book describes the Internet as an up and coming technology you might want to pay attention to. The book also shies away from any sort of data or talking to real customers in favor of intuition and experience. This may be the right decision in some scenarios, but with the data access and analysis we have today, it's not always a good trade-off.

In short, well worth reading the first few parts to wrap your head around the different customer segments and how your marketing tactics have to change as you capture more of the market, but consider skipping the rest.


Some good quotes from the book:

Innovators pursue new technology products aggressively. They sometimes seek them out even before a formal marketing program has been launched. This is because technology is a central interest in their life, regardless of what function it is performing.


Early adopters, like innovators, buy into new product concepts very early in their life cycle, but unlike innovators, they are not technologists. Rather they are people who find it easy to imagine, understand, and appreciate the benefits of a new technology, and to relate these potential benefits to their other concerns.
[...]
The early majority share some of the early adopter’s ability to relate to technology, but ultimately they are driven by a strong sense of practicality. They know that many of these newfangled inventions end up as passing fads, so they are content to wait and see how other people are making out before they buy in themselves.
[...]
The late majority shares all the concerns of the early majority, plus one major additional one: Whereas people in the early majority are comfortable with their ability to handle a technology product, should they finally decide to purchase it, members of the late majority are not. As a result, they wait until something has become an established standard, and even then they want to see lots of support and tend to buy, therefore, from large, well-established companies.
[...]
Finally there are the laggards. These people simply don’t want anything to do with new technology, for any of a variety of reasons, some personal and some economic. The only time they ever buy a technological product is when it is buried so deep inside another product—the way, say, that a microprocessor is designed into the braking system of a new car—that they don’t even know it is there.


What the early adopter is buying [...] is some kind of change agent. By being the first to implement this change in their industry, the early adopters expect to get a jump on the competition, whether from lower product costs, faster time to market, more complete customer service, or some other comparable business advantage. They expect a radical discontinuity between the old ways and the new, and they are prepared to champion this cause against entrenched resistance. Being the first, they also are prepared to bear with the inevitable bugs and glitches that accompany any innovation just coming to market.

By contrast, the early majority want to buy a productivity improvement for existing operations. They are looking to minimize the discontinuity with the old ways. They want evolution, not revolution. They want technology to enhance, not overthrow, the established ways of doing business. And above all, they do not want to debug somebody else’s product. By the time they adopt it, they want it to work properly and to integrate appropriately with their existing technology base.


Marketing professionals insist on market segmentation because they know no meaningful marketing program can be implemented across a set of customers who do not reference each other. The reason for this is simply leverage. No company can afford to pay for every marketing contact made. Every program must rely on some ongoing chain-reaction effects—what is usually called word of mouth. The more self-referencing the market and the more tightly bounded its communications channels, the greater the opportunity for such effects.


When pragmatists buy, they care about the company they are buying from, the quality of the product they are buying, the infrastructure of supporting products and system interfaces, and the reliability of the service they are going to get. In other words, they are planning on living with this decision personally for a long time to come. (By contrast, the visionaries are more likely to be planning on implementing the great new order and then using that as a springboard to their next great career step upward.) Because pragmatists are in it for the long haul, and because they control the bulk of the dollars in the marketplace, the rewards for building relationships of trust with them are very much worth the effort.


Most companies fail to cross the chasm because, confronted with the immensity of opportunity represented by a mainstream market, they lose their focus, chasing every opportunity that presents itself, but finding themselves unable to deliver a salable proposition to any true pragmatist buyer. The D-Day strategy keeps everyone on point—if we don’t take Normandy, we don’t have to worry about how we’re going to take Paris.


Positioning is the single largest influence on the buying decision. It serves as a kind of buyers’ shorthand, shaping not only their final choice but even the way they evaluate alternatives leading up to that choice. In other words, evaluations are often simply rationalizations of pre-established positioning.

Here there is one fundamental key to success: When most people think of positioning in this way, they are thinking about how to make their products easier to sell. But the correct goal is to make them easier to buy.

A good book to learn how to develop, market, and sell products as a startup. Makes a very convincing case for why the product development, marketing, and sales practices used in a big, established company will not work in a new venture trying to grab a foothold. Reasonably clear guide on the proper way to do it in such an uncertain environment, including lots of great questions to ask yourself (as a startup employee) and your customers.

Downsides to the book are that parts of it feel a little dragged out and repetitive and some of the advice is only useful for enterprise and B2B products and not consumer products. Also, parts of the book can be a bit egotistical. The Creation of Adam from the Sistine Chapel ceiling on the cover? "Epiphany" in the title? The first chapter talking about the "hero journey" of a founder? Bleh.

Some fun quotes from the book:

The surprising fact is that companies large and small, established corporate giants as well as brand new startups, fail in 9 out of 10 attempts to launch their new products.

The difference between the winners and losers is simple. Products developed with senior management out in front of customers early and often - win. Products handed off to a sales and marketing organization that has only been tangentially involved in the new Product Development process lose. It's that simple.

To begin with, the Product Development diagram completely ignores the fundamental truth about startups and all new products. The greatest risk—and hence the greatest cause of failure—in startups is not in the development of the new product but in the development of customers and markets. Startups don't fail because they lack a product; they fail because they lack customers and a proven financial model.

Broadly speaking, Customer Development focuses on understanding customer problems and needs, Customer Validation on developing a sales model that can be replicated, Customer Creation on creating and driving end user demand, and Company Building on transitioning the organization from one designed for learning and discovery to a well-oiled machine engineered for execution.

A startup begins with a vision: a vision of a new product or service, a vision of how the product will reach its customers, and a vision of why lots of people will buy that product. But most of what a startup's founders initially believe about their market and potential customers are just educated guesses. To turn the vision into reality (and a profitable company), a startup must test those guesses, or hypotheses, and find out which are correct. So the general goal of Customer Discovery amounts to this: turning the founders' initial hypotheses about their market and customers into facts. And since the facts live outside the building, the primary activity is to get in front of customers. Only after the founders have performed this step will they know whether they have a valid vision or just a hallucination.

I ask them [my customers], "If the product were free, how many would you actually deploy or use?" The goal is to take pricing away as an issue and see whether the product itself gets customers excited. If it does, I follow up with my next question: "Ok, it's not free. In fact, imagine I charged you $1 million. Would you buy it?" While this may sound like a facetious dialog, I use it all the time. Why? Because more than half the time customers will say something like, "Steve, you're out of your mind. This product isn't worth more than $250,000." I've just gotten customers to tell me how much they are willing to pay. Wow.

What if a customer tells you the issues you thought were important really aren't? Realize you've just obtained great data. While it may not be what you wanted to hear, it's wonderful to have that knowledge early on. Do not, I repeat, do not, try to "convince" customers they really have the problems you describe. They are the ones with the checkbooks, and you want them to convince you.

Can you reduce your business to a single clear, compelling message that says why your company is different and your product worth buying? That's the goal of a value proposition (sometimes called a unique selling proposition).

A company creating a new market is a radically different type of company than one entering or reframing an existing market. While there are no market-share battles with competitors, there are also no existing customers. If there are no existing customers, then even an infinite demand creation budget at the point of product launch will not garner market share. Creating a new market is about long-term customer education and adoption.

Startups creating new markets will not create a market of substantial size to generate a profit until three to seven years from product launch. This sobering piece of data is derived from looking at the results of hundreds of high-tech startups in the last twenty years.

One way to nurture maturity is to transition the "superstars" found in every corner of a startup into coaches and role models. When the company was a small startup, it looked for those world-class individuals who were ten times more productive than average. Now, when you need to scale and grow, you'll find there are not enough superstars in the job market to match the caliber of your existing staff. In a traditional startup, as processes, procedures, and rules begin to get added, jobs are redefined so "average" hires can do them. The superstars, who tend to be individualist and iconoclastic, look at all this with dismay, lamenting "the company is going downhill." Like the elves in the Lord of the Rings stories, they realize that their time has passed and quietly disappear by leaving the company. One way to keep and motivate superstars is to integrate them into larger teams as role models and coaches. If they can teach, make them coaches. If they prefer isolation, let them be revered role models. And if they are outspoken, they can become the voices in the wilderness that will sometimes be prophetic—as long as your culture protects the mavericks.

A good look at the irrational decisions we make every day. Knowing when we get things wrong is helpful in a wide range of areas: knowing how to market a product, how to be a more conscious consumer, how to ask people for help, how to make a diet successful, and how to enjoy food and wine more.

Some good quotes:

Humans rarely choose things in absolute terms. We don’t have an internal value meter that tells us how much things are worth. Rather, we focus on the relative advantage of one thing over another, and estimate value accordingly. (For instance, we don’t know how much a six-cylinder car is worth, but we can assume it’s more expensive than the four-cylinder model.)

One thing Rapp has learned is that high-priced entrées on the menu boost revenue for the restaurant—even if no one buys them. Why? Because even though people generally won’t buy the most expensive dish on the menu, they will order the second most expensive dish. Thus, by creating an expensive dish, a restaurateur can lure customers into ordering the second most expensive choice (which can be cleverly engineered to deliver a higher profit margin).

We not only tend to compare things with one another but also tend to focus on comparing things that are easily comparable—and avoid comparing things that cannot be compared easily.

This, then, is what we call arbitrary coherence. Initial prices are largely “arbitrary” and can be influenced by responses to random questions; but once those prices are established in our minds, they shape not only what we are willing to pay for an item, but also how much we are willing to pay for related products (this makes them coherent).

You’re walking past a restaurant, and you see two people standing in line, waiting to get in. “This must be a good restaurant,” you think to yourself. “People are standing in line.” So you stand behind these people. Another person walks by. He sees three people standing in line and thinks, “This must be a fantastic restaurant,” and joins the line. Others join. We call this type of behavior herding. It happens when we assume that something is good (or bad) on the basis of other people’s previous behavior, and our own actions follow suit.

If we can’t rely on the market forces of supply and demand to set optimal market prices, and we can’t count on free-market mechanisms to help us maximize our utility, then we may need to look elsewhere. This is especially the case with society’s essentials, such as health care, medicine, water, electricity, education, and other critical resources. If you accept the premise that market forces and free markets will not always regulate the market for the best, then you may find yourself among those who believe that the government (we hope a reasonable and thoughtful government) must play a larger role in regulating some market activities, even if this limits free enterprise. Yes, a free market based on supply, demand, and no friction would be the ideal if we were truly rational. Yet when we are not rational but irrational, policies should take this important factor into account

Zero is not just another discount. Zero is a different place. The difference between two cents and one cent is small. But the difference between one cent and zero is huge! If you are in business, and understand that, you can do some marvelous things. Want to draw a crowd? Make something FREE! Want to sell more products? Make part of the purchase FREE!

As Margaret Clark, Judson Mills, and Alan Fiske suggested a long time ago, the answer is that we live simultaneously in two different worlds—one where social norms prevail, and the other where market norms make the rules.

As we learned in our experiments, cash will take you only so far—social norms are the forces that can make a difference in the long run. Instead of focusing the attention of the teachers, parents, and kids on test scores, salaries, and competition, it might be better to instill in all of us a sense of purpose, mission, and pride in education.

It may be that our models of human behavior need to be rethought. Perhaps there is no such thing as a fully integrated human being. We may, in fact, be an agglomeration of multiple selves. Although there is nothing much we can do to get our Dr. Jekyll to fully appreciate the strength of our Mr. Hyde, perhaps just being aware that we are prone to making the wrong decisions when gripped by intense emotion may help us, in some way, to apply our knowledge of our “Hyde” selves to our daily activities.

Much of our life story can be told by describing the ebb and flow of our particular possessions—what we get and what we give up. We buy clothes and food, automobiles and homes, for instance. And we sell things as well—homes and cars, and in the course of our careers, our time.

Our propensity to overvalue what we own is a basic human bias, and it reflects a more general tendency to fall in love with, and be overly optimistic about, anything that has to do with ourselves. Think about it—don’t you feel that you are a better-than-average driver, are more likely to be able to afford retirement, and are less likely to suffer from high cholesterol, get a divorce, or get a parking ticket if you overstay your meter by a few minutes? This positivity bias, as psychologists call it, has another name: “The Lake Wobegone Effect,” named after the fictional town in Garrison Keillor’s popular radio series A Prairie Home Companion. In Lake Wobegone, according to Keillor, “all the women are strong, all the men are good-looking, and all the children are above average.”

Some years ago, two very perspicacious researchers, Marian Friestad and Peter Wright, suggested that people in general are starting to understand that the offers companies put before us are in their best interest and not ours. As a consequence, we’ve become more distrustful—not only of those who are trying to swindle us but of everyone.

Pros:

* Some parts of the book are inspiring. The author has, indeed, done some cool sh*t.
* Good insight into human psychology and how to communicate effectively. Some of these ideas are obvious, but it's easy to forget them in certain contexts, such as in an email or when asking for a favor. Examples:
** All relationships must be mutually beneficial.
** When convincing someone, make sure to talk about "we", not "I". Present a "shared" vision for the future.
** Everyone wants to be heard, so always give people an opportunity to share something about themselves.
** Avoid small talk. Instead of asking about the weather, ask people about their dreams, their vision, and what excites them.
** If you make people feel like experts, they will go out of their way to help you.
** Always try to make people laugh.
** Always smile.
** People love free food.

Cons:

* The book has a tendency to sound a little too much like an infomercial crossed with a self-help seminar.
* Occasionally, the book crosses the line from inspiring to self-promotional.
* A few chapters are a bit hand wavy and naive, such as the one on exercise and diet.

Some good quotes:

Business plans don't raise dollars, people do.

Hire slow, fire fast. I can’t stress that enough. No one has ever said that they fired somebody too soon.

We achieve being through doing. The notion that your most authentic self will come through simply by doing the things you love absolutely captivated me. It means that you will simply be exactly who you want to be when you start acting that way.