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.
The best products do not always succeed. Brilliant new technologies might take decades to become accepted. To understand products, it is not enough to understand design or technology: it is critical to understand business.
Affordances define what actions are possible. Signifiers specify how people discover those possibilities: signifiers are signs, perceptible signals of what can be done.
Everyone wants radical innovation, but the truth is, most radical innovations fail, and even when they do succeed, it can take multiple decades before they are accepted. Radical innovation, therefore, is relatively rare: incremental innovation is common.
Two of the most important characteristics of good design are discoverability and understanding.
All artificial things are designed.
Because everything is designed, the number of areas is enormous, ranging from clothes and furniture to complex control rooms and bridges.
Engineers are trained to think logically. As a result, they come to believe that all people must think this way, and they design their machines accordingly. When people have trouble, the engineers are upset, but often for the wrong reason.
Even experts make errors. So we must design our machines on the assumption that people will make errors.
Good design starts with an understanding of psychology and technology. Good design requires good communication, especially from machine to person, indicating what actions are possible, what is happening, and what is about to happen.
Designers need to focus their attention on the cases where things go wrong, not just on when things work as planned.
Cognition and emotion are tightly intertwined, which means that the designers must design with both in mind.
The term affordance refers to the relationship between a physical object and a person (or for that matter, any interacting agent, whether animal or human, or even machines and robots).
Affordances determine what actions are possible. Signifiers communicate where the action should take place. We need both.
The relationship between a control and its results is easiest to learn wherever there is an understandable mapping between the controls, the actions, and the intended result.
Feedback must be immediate: even a delay of a tenth of a second can be disconcerting. If the delay is too long, people often give up, going off to do other activities.
Poor feedback can be worse than no feedback at all, because it is distracting, uninformative, and in many cases irritating and anxiety-provoking.
Too many announcements cause people to ignore all of them, or wherever possible, disable all of them, which means that critical and important ones are apt to be missed.
Feedback must also be prioritized, so that unimportant information is presented in an unobtrusive fashion, but important signals are presented in a way that does capture attention.
The same technology that simplifies life by providing more functions in each device also complicates life by making the device harder to learn, harder to use. This is the paradox of technology and the challenge for the designer.
The difficulties reside in their design, not in the people attempting to use them.
Most of human behavior is a result of subconscious processes.
Cognition and emotion cannot be separated. Cognitive thoughts lead to emotions: emotions drive cognitive thoughts.
Reflective memories are often more important than reality. If we have a strongly positive visceral response but disappointing usability problems at the behavioral level, when we reflect back upon the product, the reflective level might very well weigh the positive response strongly enough to overlook the severe behavioral difficulties (hence the phrase, “Attractive things work better”).
It is easy to design devices that work well when everything goes as planned. The hard and necessary part of design is to make things work well even when things do not go as planned.
Note that knowledge of the rules does not mean they are followed.
What appears good in principle can sometimes fail when introduced to the world.
Knowledge in the world is accessible. It is self-reminding. It is always there, waiting to be seen, waiting to be used.
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.
Remember, any problems you have are probably the design’s fault, not yours.
Constraints are powerful clues, limiting the set of possible actions. The thoughtful use of constraints in design lets people readily determine the proper course of action, even in a novel situation.
A usable design starts with careful observations of how the tasks being supported are actually performed, followed by a design process that results in a good fit to the actual ways the tasks get performed.
Skeuomorphic is the technical term for incorporating old, familiar ideas into new technologies, even though they no longer play a functional role.
Early automobiles looked like horse-driven carriages without the horses (which is also why they were called horseless carriages); early plastics were designed to look like wood; folders in computer file systems often look the same as paper folders, complete with tabs.
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.
We can’t fix problems unless people admit they exist. When we blame people, it is then difficult to convince organizations to restructure the design to eliminate these problems.
Why do people err? Because the designs focus upon the requirements of the system and the machines, and not upon the requirements of people.
Many mistakes arise from the vagaries of human thought, often because people tend to rely upon remembered experiences rather than on more systematic analysis.
The designer should assume that people will be interrupted during their activities and that they may need assistance in resuming their operations.
To understand human error, it is essential to understand social pressure.
One paradox of groups is that quite often, adding more people to check a task makes it less likely that it will be done right. Why? Well, if you were responsible for checking the correct readings on a row of fifty gauges and displays, but you know that two people before you had checked them and that one or two people who come after you will check your work, you might relax, thinking that you don’t have to be extra careful.
The contrast in our understanding before and after an event can be dramatic. The psychologist Baruch Fischhoff has studied explanations given in hindsight, where events seem completely obvious and predictable after the fact but completely unpredictable beforehand.
Put the knowledge required to operate the technology in the world. Don’t require that all the knowledge must be in the head.
The problem I am asked to solve is not the real, fundamental, root problem. It is usually a symptom.
In design, the secret to success is to understand what the real problem is.
It is amazing how often people solve the problem before them without bothering to question it.
A brilliant solution to the wrong problem can be worse than no solution at all: solve the correct problem.
Good designers never start by trying to solve the problem given to them: they start by trying to understand what the real issues are.
How does the product manager keep the entire team on schedule despite the apparent random and divergent methods of designers? Encourage their free exploration, but hold them to the schedule (and budget) constraints. There is nothing like a firm deadline to get creative minds to reach convergence.
Even when we look at widely different cultures, the activities are often surprisingly similar.
Design wants to know what people really need and how they actually will use the product or service under consideration. Marketing wants to know what people will buy, which includes learning how they make their purchasing decisions.
Numerical correlations say nothing of people’s real needs, of their desires, and of the reasons for their activities. As a result, these numerical data can give a false impression of people.
Requirements made in the abstract are invariably wrong. Requirements produced by asking people what they need are invariably wrong. Requirements are developed by watching people in their natural environment.
How can we pretend to accommodate all of these very different, very disparate people? The answer is to focus on activities, not the individual person. I call this activity-centered design.
In theory, there is no difference between theory and practice. In practice, there is.
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.
There is no such thing as the average person.
Design for interests and skill levels. Don’t be trapped by overly general, inaccurate stereotypes.
Complexity Is Good; It Is Confusion That Is Bad
My kitchen looks confusing to you, but not to me. In turn, your kitchen looks confusing to me, but not to you. So the confusion is not in the kitchen: it is in the mind.
When new technologies emerge, there is a temptation to develop new products immediately. But the time for radically new products to become successful is measured in years, decades, or in some instances centuries.
The design of technology to fit human needs and capabilities is determined by the psychology of people. Yes, technologies may change, but people stay the same.
Creeping featurism is the tendency to add to the number of features of a product, often extending the number beyond all reason.
Focus on strengths, not weaknesses. If the product has real strengths, it can afford to just be “good enough” in the other areas.
Good design requires stepping back from competitive pressures and ensuring that the entire product be consistent, coherent, and understandable.
Technology changes the way we do things, but fundamental needs remain unchanged.
Technology changes rapidly, but people and culture change slowly. Change is, therefore, simultaneously rapid and slow.