The Design of Everyday Things

by Donald A. Norman

the designer aimed for beauty, not utility. No distracting lines, no visible pillars, no visible hinges. So how can the ordinary user know which side to push on?

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?

Because much of the design is done by engineers who are experts in technology but limited in their understanding of people. “We are people ourselves,” they think, “so we understand people.” But in fact, we humans are amazingly complex. Those who have not studied human behavior often think it is pretty simple. Engineers, moreover, make the mistake of thinking that logical explanation is sufficient: “If only people would read the instructions,” they say, “everything would be all right.”

In design, signifiers are more important than affordances, for they communicate how to use the design.

The continual beeps and alarms of equipment can be dangerous. In many emergencies, workers have to spend valuable time turning off all the alarms because the sounds interfere with the concentration required to solve the problem. Hospital operating rooms, emergency wards. Nuclear power control plants. Airplane cockpits.

Harvard Business School marketing professor Theodore Levitt once pointed out, “People don’t want to buy a quarter-inch drill. They want a quarter-inch hole!” Levitt’s example of the drill implying that the goal is really a hole is only partially correct, however. When people go to a store to buy a drill, that is not their real goal. But why would anyone want a quarter-inch hole? Clearly that is an intermediate goal. Perhaps they wanted to hang shelves on the wall. Levitt stopped too soon. Once you realize that they don’t really want the drill, you realize that perhaps they don’t really want the hole, either: they want to install their bookshelves. Why not develop methods that don’t require holes? Or perhaps books that don’t require bookshelves. (Yes, I know: electronic books, e-books.)

More and more evidence is accumulating that we use logic and reason after the fact, to justify our decisions to ourselves (to our conscious minds) and to others. Bizarre? Yes, but don’t protest: enjoy it.

Modern systems try hard to provide feedback within 0.1 second of any operation, to reassure the user that the request was received. This is especially important if the operation will take considerable time. The presence of a filling hourglass or rotating clock hands is a reassuring sign that work is in progress.

Some studies show it is wise to underpredict—that is, to say an operation will take longer than it actually will. When the system computes the amount of time, it can compute the range of possible times. In that case it ought to display the range, or if only a single value is desirable, show the slowest, longest value. That way, the expectations are liable to be exceeded, leading to a happy result.

Do not blame people when they fail to use your products properly. • Take people’s difficulties as signifiers of where the product can be improved. • Eliminate all error messages from electronic or computer systems. Instead, provide help and guidance. • Make it possible to correct problems directly from help and guidance messages. Allow people to continue with their task: Don’t impede progress—help make it smooth and continuous. Never make people start over. • Assume that what people have done is partially correct, so if it is inappropriate, provide the guidance that allows them to correct the problem and be on their way. • Think positively, for yourself and for the people you interact with.

Knowledge of—what psychologists call declarative knowledge—includes the knowledge of facts and rules. “Stop at red traffic lights.” “New York City is north of Rome.” “China has twice as many people as India.” “To get the key out of the ignition of a Saab car, the gearshift must be in reverse.” Declarative knowledge is easy to write and to teach.

We learn to discriminate among things by looking for distinguishing features. In the United States, size is one major way of distinguishing among coins, but not among paper money. With paper money, all the bills are the same size, so Americans ignore size and look at the printed numbers and images. Hence, we often confuse similar-size American coins but only seldom confuse similar-size American bills. But people who come from a country that uses size and color of their paper money to distinguish among the amounts (for example, Great Britain or any country that uses the euro) have learned to use size and color to distinguish among paper money and therefore are invariably confused when dealing with bills from the United States.

But when the number of secret codes gets too large, memory fails. There seems to be a conspiracy, one calculated to destroy our sanity by overloading our memory. Many codes, such as postal codes and telephone numbers, exist primarily to make life easier for machines and their designers without any consideration of the burden placed upon people.

Our meetings were held in a conference room in the public space of an otherwise secure building. But the toilets were all located inside a secure area. How did we manage? These world-famous, leading authorities on security figured out a solution: They found a brick and used it to prop open the door leading into the secure area. So much for security: Make something too secure, and it becomes less secure.

One method is to transform the digits into meaningful segments (one famous study showed how an athlete thought of digit sequences as running times, and after refining the method over a long period, could learn incredibly long sequences at one glance).

Because retrieval is a reconstructive process, it can be erroneous. We may reconstruct events the way we would prefer to remember them, rather than the way we experienced them. It is relatively easy to bias people so that they form false memories, “remembering” events in their lives with great clarity, even though they never occurred. This is one reason that eyewitness testimony in courts of law is so problematic: eyewitnesses are notoriously unreliable. A huge number of psychological experiments show how easy it is to implant false memories into people’s minds so convincingly that people refuse to admit that the memory is of an event that never happened.

Rote learning creates problems. First, because what is being learned is arbitrary, the learning is difficult: it can take considerable time and effort. Second, when a problem arises, the memorized sequence of actions gives no hint of what has gone wrong, no suggestion of what might be done to fix the problem. Although some things are appropriate to learn by rote, most are not. Alas, it is still the dominant method of instruction in many school systems, and even for much adult training.

is rare that we need to know the answers to complex arithmetic problems with great precision: almost always, a rough estimate is good enough. When precision is required, use a calculator. That’s what machines are good for: providing great precision. For most purposes, estimates are good enough. Machines should focus on solving arithmetic problems. People should focus on higher-level issues, such as the reason the answer was needed.

How many people are involved? It could be any number, but the point is that each adds their bit of knowledge, slowly constraining the choices, recalling something that no single one of them could have done alone. Daniel Wegner, a Harvard professor of psychology, has called this “transactive memory.”

I argued that it is this combination of technology and people that creates super-powerful beings. Technology does not make us smarter. People do not make technology smart. It is the combination of the two, the person plus the artifact, that is smart. Together, with our tools, we are a powerful combination.

three levels of mapping, arranged in decreasing effectiveness as memory aids: • Best mapping: Controls are mounted directly on the item to be controlled. • Second-best mapping: Controls are as close as possible to the object to be controlled. • Third-best mapping: Controls are arranged in the same spatial configuration as the objects to be controlled.

In some cultures, time is represented mentally as if it were a road stretching out ahead of the person. As a person moves through time, the person moves forward along the time line. Other cultures use the same representation, except now it is the person who is fixed and it is time that moves: an event in the future moves toward the person.

With the moving text metaphor, the mouse and the text move in the same directions: move the mouse up and the text moves up. For over two decades, everyone moved the scrollbars and mouse down in order to make the text move up. But then smart displays with touch-operated screens arrived. Now it was only natural to touch the text with the fingers and move it up, down, right, or left directly:

When cars become fully automated, communicating among themselves with wireless networks, what will be the meaning of the red lights on the rear of the auto? That the car is braking? But for whom would the signal be intended? The other cars would already know. The red light would become meaningless, so it could either be removed or it could be redefined to indicate some other condition. The meanings of today may not be the meanings of the future.

In cases of fire, people have a tendency to flee in panic, down the stairs, down, down, down, past the ground floor and into the basement, where they might be trapped. The solution (required by the fire laws) is not to allow simple passage from the ground floor to the basement.

If you can’t put the knowledge on the device (that is, knowledge in the world), then develop a cultural constraint: standardize what has to be kept in the head.

Skeuomorphic is the technical term for incorporating old, familiar ideas into new technologies, even though they no longer play a functional role.

The tendency to stop seeking reasons as soon as a human error has been found is widespread.

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.

An interesting property of slips is that, paradoxically, they tend to occur more frequently to skilled people than to novices. Why? Because slips often result from a lack of attention to the task. Skilled people—experts—tend to perform tasks automatically, under subconscious control. Novices have to pay considerable conscious attention, resulting in a relatively low occurrence of slips.

In the design of airplane cockpits, many controls are shape coded so that they both look and feel different from one another: the throttle levers are different from the flap levers (which might look and feel like a wing flap), which are different from the landing gear control (which might look and feel like a wheel).

Using a bank or credit card to withdraw money from an automatic teller machine, then walking off without the card, is such a frequent error that many machines now have a forcing function: the card must be removed before the money will be delivered. Of course, it is then possible to walk off without the money, but this is less likely than forgetting the card because money is the goal of using the machine.

The most common form of errors in skill-based behavior is slips.

NASA is a neutral body, charged with enhancing aviation safety, but has no oversight authority, which helped gain the trust of pilots. There is no comparable institution in medicine: physicians are afraid that self-reported errors might lead them to lose their license or be subjected to lawsuits. But we can’t eliminate errors unless we know what they are. The medical field is starting to make progress, but it is a difficult technical, political, legal, and social problem.

Thus, novices are more likely to make mistakes than slips, whereas experts are more likely to make slips.

My wife and I follow this convention in driving: when the driver is entering or leaving a high-speed highway, conversation ceases until the transition has been completed. Interruptions and distractions lead to errors, both mistakes and slips.

The Swiss cheese metaphor suggests several ways to reduce accidents: • Add more slices of cheese. • Reduce the number of holes (or make the existing holes smaller). • Alert the human operators when several holes have lined up.

In the United States alone there were roughly 9 million flights in 2012. So, a one-in-a-million chance could translate into nine incidents.

In an airplane, when the automation fails, there is usually considerable time for the pilots to understand the situation and respond. Airplanes fly quite high: over 10 km (6 miles) above the earth, so even if the plane were to start falling, the pilots might have several minutes to respond. Moreover, pilots are extremely well trained. When automation fails in an automobile, the person might have only a fraction of a second to avoid an accident. This would be extremely difficult even for the most expert driver, and most drivers are not well trained.

Engineers and business people are trained to solve problems. Why would anyone ever give them the wrong problem? “Where do you think the problems come from?” I ask. The real world is not like the university. In the university, professors make up artificial problems. In the real world, the problems do not come in nice, neat packages. They have to be discovered. It is all too easy to see only the surface problems and never dig deeper to address the real issues.

Engineers and businesspeople are trained to solve problems. Designers are trained to discover the real problems.

it is useful to ask a pair of people to use it together, one person operating the prototype, the other guiding the actions and interpreting the results (aloud). Using pairs in this way causes them to discuss their ideas, hypotheses, and frustrations openly and naturally.

In theory, there is no difference between theory and practice. In practice, there is.

Moreover, product development takes time even to get started. People are never sitting around with nothing to do, waiting to be called for the product. No, they must be recruited, vetted, and then transitioned off their current jobs. This all takes time, time that is seldom scheduled.

The product has to appeal to the current customer base as well as to expand beyond to new customers. Patents create a minefield for designers and engineers, for today it is almost impossible to design or build anything that doesn’t conflict with patents, which means redesign to work one’s way through the mines.

Designers try hard to determine people’s real needs and to fulfill them, whereas marketing is concerned with determining what people will actually buy. What people need and what they buy are two different things, but both are important. It doesn’t matter how great the product is if nobody buys it.

Designers need to understand their customers, and in many cases, the customer is the person who purchases the product, not the person who actually uses it. It is just as important to study those who do the purchasing as it is to study those who use it.

Why was the HDTV aspect ratio set at 16:9 (or 1.8) if no movies used that ratio? Because engineers liked it: square the old aspect ratio of 4:3 and you get the new one, 16:9.

Norman’s Law of Chapter 6: The day a product development process starts, it is behind schedule and above budget.

Most companies compare features with their competition to determine where they are weak, so they can strengthen those areas. Wrong, argues Moon. A better strategy is to concentrate on areas where they are stronger and to strengthen them even more. Then focus all marketing and advertisements to point out the strong points. This causes the product to stand out