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.
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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?
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It is the duty of machines and those who design them to understand people. It is not our duty to understand the arbitrary, meaningless dictates of machines.
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The problem with the designs of most engineers is that they are too logical. We have to accept human behavior the way it is, not the way we would wish it to be.
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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.
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Affordances determine what actions are possible. Signifiers communicate where the action should take place. We need both.
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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.
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Poor feedback can be worse than no feedback at all, because it is distracting, uninformative, and in many cases irritating and anxiety-provoking.
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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.
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For many everyday tasks, goals and intentions are not well specified: they are opportunistic rather than planned. Opportunistic actions are those in which the behavior takes advantage of circumstances. Rather than engage in extensive planning and analysis, we go about the day’s activities and do things as opportunities arise.
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Most innovation is done as an incremental enhancement of existing products.
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A positive emotional state is ideal for creative thought, but it is not very well suited for getting things done. Too much, and we call the person scatterbrained, flitting from one topic to another, unable to finish one thought before another comes to mind. A brain in a negative emotional state provides focus: precisely what is needed to maintain attention on a task and finish it. Too much, however, and we get tunnel vision, where people are unable to look beyond their narrow point of view. Both the positive, relaxed state and the anxious, negative, and tense state are valuable and powerful tools for human creativity and action. The extremes of both states, however, can be dangerous.
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Feedback provides reassurance, even when it indicates a negative result. A lack of feedback creates a feeling of lack of control, which can be unsettling. Feedback is critical to managing expectations, and good design provides this. Feedback—knowledge of results—is how expectations are resolved and is critical to learning and the development of skilled behavior.
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The emotional system is especially responsive to changes in states—so an upward change is interpreted positively even if it is only from a very bad state to a not-so-bad state, just as a change is interpreted negatively even if it is from an extremely positive state to one only somewhat less positive.
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Conceptual models are often constructed from fragmentary evidence, with only a poor understanding of what is happening, and with a kind of naive psychology that postulates causes, mechanisms, and relationships even where there are none.
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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?
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One of my self-imposed rules is, “Don’t criticize unless you can do better.”
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Precision, accuracy, and completeness of knowledge are seldom required. Perfect behavior results if the combined knowledge in the head and in the world is sufficient to distinguish an appropriate choice from all others.
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We only need to remember sufficient knowledge to let us get our tasks done. Because so much knowledge is available in the environment, it is surprising how little we need to learn. This is one reason people can function well in their environment and still be unable to describe what they do.
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The most effective way of helping people remember is to make it unnecessary.
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Conscious thinking takes time and mental resources. Well-learned skills bypass the need for conscious oversight and control: conscious control is only required for initial learning and for dealing with unexpected situations. Continual practice automates the action cycle, minimizing the amount of conscious thinking and problem-solving required to act. Most expert, skilled behavior works this way, whether it is playing tennis or a musical instrument, or doing mathematics and science. Experts minimize the need for conscious reasoning.
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The lack of clear communication among the people and organizations constructing parts of a system is perhaps the most common cause of complicated, confusing designs. 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.
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Standardization is indeed the fundamental principle of desperation: when no other solution appears possible, simply design everything the same way, so people only have to learn once.
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We should treat all failures in the same way: find the fundamental causes and redesign the system so that these can no longer lead to problems.
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Rather than stigmatize those who admit to error, we should thank those who do so and encourage the reporting. We need to make it easier to report errors, for the goal is not to punish, but to determine how it occurred and change things so that it will not happen again.
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We should deal with error by embracing it, by seeking to understand the causes and ensuring they do not happen again. We need to assist rather than punish or scold.
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Avoid criticizing ideas, whether your own or those of others. Even crazy ideas, often obviously wrong, can contain creative insights that can later be extracted and put to good use in the final idea selection. Avoid premature dismissal of ideas.
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I am particularly fond of “stupid” questions. A stupid question asks about things so fundamental that everyone assumes the answer is obvious. But when the question is taken seriously, it often turns out to be profound: the obvious often is not obvious at all. What we assume to be obvious is simply the way things have always been done, but now that it is questioned, we don’t actually know the reasons. Quite often the solution to problems is discovered through stupid questions, through questioning the obvious.
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Good design requires stepping back from competitive pressures and ensuring that the entire product be consistent, coherent, and understandable.
