A must-read for anyone who's involved in the process of making things. It will have you questioning the design of just about every man-made object you come across.
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.
To understand products, it is not enough to understand design or technology: it is critical to understand business.
The design principles here, based on psychology, on the nature of human cognition, emotion, action, and interaction with the world, will remain unchanged.
The most important characteristics of good design.
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?
Design is concerned with how things work, how they are controlled, and the nature of the interaction between people and technology.
But most of the problems come from a complete lack of understanding of the design principles necessary for effective human-machine interaction.
We must design our machines on the assumption that people will make errors.
The solution is human-centered design (HCD), an approach that puts human needs, capabilities, and behavior first, then designs to accommodate those needs, capabilities, and ways of behaving.
Good design starts with an understanding of psychology and technology.
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 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).
To be effective, affordances and anti-affordances have to be discoverable—perceivable.
Affordances exist even if they are not visible. For designers, their visibility is critical: visible affordances provide strong clues to the operations of things.
Affordances determine what actions are possible. Signifiers communicate where the action should take place. We need both.
Signifiers are signals. Some signifiers are signs, labels, and drawings placed in the world, such as the signs labeled “push,” “pull,” or “exit” on doors, or arrows and diagrams indicating what is to be acted upon or in which direction to gesture, or other instructions.
Some signifiers are simply the perceived affordances, such as the handle of a door or the physical structure of a switch.
When external signifiers (signs) have to be added to something as simple as a door, it indicates bad design.
Providing physical, logical, semantic, and cultural constraints guides actions and eases interpretation.
Mapping — The relationship between the elements of two sets of things.
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 — Communicating the results of an action
Feedback has to be planned. All actions need to be confirmed, but in a manner that is unobtrusive.
Conceptual model — An explanation, usually highly simplified, of how something works.
Simplified models are valuable only as long as the assumptions that support them hold true.
There are often multiple conceptual models of a product or device.
Mental models, as the name implies, are the conceptual models in people’s minds that represent their understanding of how things work.
The major clues to how things work come from their perceived structure—in particular from signifiers, affordances, constraints, and mappings.
Conceptual models are valuable in providing understanding, in predicting how things will behave, and in figuring out what to do when things do not go as planned.
The Designer’s Model, the User’s Model, and the System Image. The designer’s conceptual model is the designer’s conception of the look, feel, and operation of a product.
System image — What can be derived from the physical structure that has been built (including documentation).
The user’s mental model is developed through interaction with the product and the system image. Designers expect the user’s model to be identical to their own, but because they cannot communicate directly with the user, the burden of communication is with the system image.
Good conceptual models are the key to understandable, enjoyable products: good communication is the key to good conceptual models.
Technology offers the potential to make life easier and more enjoyable; each new technology provides increased benefits. At the same time, added complexities increase our difficulty and frustration with technology.
Design requires the cooperative efforts of multiple disciplines.
If the design team has representatives from all the constituencies present at the same time, it is often possible to reach satisfactory solutions for all the needs.
When people encounter a device, they face two gulfs:
We bridge the Gulf of Execution through the use of signifiers, constraints, mappings, and a conceptual model.
Not all of the activity in the stages is conscious. Goals tend to be, but even they may be subconscious.
The action cycle can start from:
The seven stages provide a guideline for developing new products or services. The gulfs are obvious places to start, for either gulf, whether of execution or evaluation, is an opportunity for product enhancement.
Declarative memory — memory for factual information
Procedural memory — could be factual, but usually recalling activities like how to open a door
Cognition and emotion cannot be separated. Cognitive thoughts lead to emotions: emotions drive cognitive thoughts.
Emotion interacts with cognition biochemically, bathing the brain with hormones, transmitted either through the bloodstream or through ducts in the brain, modifying the behavior of brain cells.
Three levels of processing:
The flow state occurs when the challenge of the activity just slightly exceeds our skill level, so full attention is continually required. Flow requires that the activity be neither too easy nor too difficult relative to our level of skill.
But even when there is no single causal act, that doesn’t stop people from assigning one (see Narrative Fallacy)
Everyone forms stories (conceptual models) to explain what they have observed (e.g. turning the oven to full to heat it quicker, not true).
To fail is to learn: we learn more from our failures than from our successes.
Eliminate all error messages from electronic or computer systems. Instead, provide help and guidance.
Human error usually is a result of poor design: it should be called system error.
If a person performs an inappropriate action, the design should maximise the chance that this can be discovered and then rectified. This requires good, intelligible feedback coupled with a simple, clear conceptual model. When people understand what has happened, what state the system is in, and what the most appropriate set of actions is, they can perform their activities more effectively.
The Seven Stages of Action as Design Aids. Each of the seven stages indicates a place where the person using the system has a question. The seven questions pose seven design themes.
The information that helps answer questions of execution (doing) is feedforward. The information that aids in understanding what has happened is feedback.
The insights from the seven stages of action lead us to seven fundamental principles of design:
Not all of the knowledge required for precise behavior has to be in the head. Knowledge is both in the head and in the world.
Whenever knowledge needed to do a task is readily available in the world, the need for us to learn it diminishes.
People function through their use of two kinds of knowledge:
Memory is knowledge in the head.
The traditional measures of STM capacity range from five to seven, but from a practical point of view, it is best to think of it as holding only three to five.
How well we can ever recover experiences and knowledge from LTM is highly dependent upon how the material was interpreted in the first place.
It has long been known that rehearsal of material—mentally reviewing it while still active in working memory (STM)—is an important component of the formation of long-term memory traces.
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.
How people use their memories and how they retrieve knowledge:
The most effective way of helping people remember is to make it unnecessary. Conscious thinking takes time and mental resources. Experts minimise the need for conscious reasoning.
Natural mappings are those where the relationship between the controls and the object to be controlled (the burners, in this case) is obvious.
Usability is not often thought about during the purchasing process.
Knowledge in the world — perceived affordances and signifiers, the mappings between the parts that appear to be controls or places to manipulate and the resulting actions, and the physical constraints that limit what can be done.
Knowledge in the head — conceptual models; cultural, semantic, and logical constraints on behavior; and analogies between the current situation and previous experiences with other situations.
These four classes of constraints—physical, cultural, semantic, and logical—seem to be universal, appearing in a wide variety of situations. 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.
Physical constraints are made more effective and useful if they are easy to see and interpret, for then the set of actions is restricted before anything has been done.
Each culture has a set of allowable actions for social situations.
Guidelines for cultural behavior are represented in the mind by schemas, knowledge structures that contain the general rules and information necessary for interpreting situations and for guiding behavior.
Semantics is the study of meaning. Semantic constraints are those that rely upon the meaning of the situation to control the set of possible actions.
There are no physical or cultural principles here; rather, there is a logical relationship between the spatial or functional layout of components and the things that they affect or are affected by.
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. The technical name for this method is task analysis.
e.g. starting a car — the driver must have some physical object that signifies permission to use the car.
e.g. Dead man’s switch — requires the operator hold down a spring-loaded switch to enable operation of the equipment
Whereas a lock-in keeps someone in a space or prevents an action until the desired operations have been done, a lockout prevents someone from entering a space that is dangerous, or prevents an event from occurring.
Sometimes everything that is needed cannot be made visible. Enter sound: sound can provide information available in no other way.
Skeuomorphic is the technical term for incorporating old, familiar ideas into new technologies, even though they no longer play a functional role. (e.g. switch designs in UI, engine sounds in electric sports cars)
Root cause analysis — investigate the accident until the single, underlying cause is found.
Why does the root cause analysis stop as soon as a human error is found? If a machine stops working, we don’t stop the analysis when we discover a broken part.
When searching for the reason, even after you have found one, do not stop: ask why that was the case. And then ask why again. Keep asking until you have uncovered the true underlying causes.
Memory lapses can lead to either slips or mistakes, depending upon whether the memory failure was at the highest level of cognition (mistakes) or at lower (subconscious) levels (slips).
Human error — any deviance from “appropriate” behavior.
Slips occur when the goal is correct, but the required actions are not done properly: the execution is flawed.
Action-based slips — the wrong action is performed.
Memory-lapse — memory fails, so the intended action is not done or its results not evaluated.
Tend to occur more frequently to skilled people than to novices because slips often result from a lack of attention to the task. Skilled people tend to perform tasks automatically.
Mistakes occur when the goal or plan is wrong.
Rule-based mistake — new procedures have to be invoked or when simple problems arise, we can characterise the actions of skilled people as rule-based.
Knowledge-based mistake — the problem is misdiagnosed because of erroneous or incomplete knowledge.
Memory-lapse mistakes — take place when there is forgetting at the stages of goals, plans, or evaluation.
We make decisions based upon what is in our memory. But retrieval from long-term memory is actually a reconstruction rather than an accurate record. As a result, it is subject to numerous biases.
Never underestimate the power of social pressures on behavior, causing otherwise sensible people to do things they know are wrong and possibly dangerous.
Hindsight makes events seem obvious and predictable. (see Hindsight Bias)
It is relatively easy to design for the situation where everything goes well, the tricky part is to design for when things go wrong.
Prevention often involves adding specific constraints to actions. (e.g. different vehicle fluids often have different colours so that they can be distinguished.)
Reason’s Swiss Cheese Model of Accidents. Accidents usually have multiple causes, whereby had any single one of those causes not happened, the accident would not have occurred. Unless the holes all line up perfectly, there will be no accident.
We can decrease accidents and make systems more resilient by designing them to have extra precautions against error (more slices of cheese), less opportunities for slips, mistakes, or equipment failure (less holes), and very different mechanisms in the different subparts of the system (trying to ensure that the holes do not line up).
Design redundancy and layers of defence: that’s Swiss cheese.
Good designers never start by trying to solve the problem given to them: they start by trying to understand what the real issues are.
They don’t try to search for a solution until they have determined the real problem, and even then, instead of solving that problem, they stop to consider a wide range of potential solutions.
Designers often start by questioning the problem given to them: they expand the scope of the problem, diverging to examine all the fundamental issues that underlie it. Then they converge upon a single problem statement.
During the solution phase of their studies, they first expand the space of possible solutions, the divergence phase. Finally, they converge upon a proposed solution.
The process of ensuring that people’s needs are met, that the resulting product is understandable and usable, that it accomplishes the desired tasks, and that the experience of use is positive and enjoyable.
This is where the human-centered design process comes into play: it takes place within the double-diamond diverge-converge process.
Understand the nature of the problem.
Research about the customer and the people who will use the products under consideration.
Observing potential customers activities, attempting to understand their interests, motives, and true needs.
Design research supports both diamonds of the design process.
This exercise might be done for both of the double diamonds: during the phase of finding the correct problem, then during the problem solution phase.
Generate numerous ideas. It is dangerous to become fixated upon one or two ideas too early in the process.
Be creative without regard for constraints.
Like prototyping, testing is done in the problem specification phase to ensure that the problem is well understood, then done again in the problem solution phase to ensure that the new design meets the needs and abilities of those who will use it.
The role of iteration in human-centered design is to enable continual refinement and enhancement.
Failure is encouraged. “Fail frequently, fail fast.”
Activity — high-level structure, e.g. go shopping
Task — lower-level component of an activity (e.g. drive to the market, find a shopping basket)
Well-designed devices will package together the various tasks that are required to support an activity, making them work seamlessly with one another, making sure the work done for one does not interfere with the requirements for another.
The day a product development process starts, it is behind schedule and above budget.
The way to handle the time crunch that eliminates the ability to do good up-front design research is to separate that process from the product team: have design researchers always out in the field, always studying potential products and customers. Then, when the product team is launched, the designers can say, “We already examined this case, so here are our recommendations.”
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 — the tendency to add to the number of features of a product, often extending the number beyond all reason.
Jeff Bezos, the founder and CEO of Amazon.com, calls his approach “customer obsessed.” Everything is focused upon the requirements of Amazon’s customers. The competition is ignored, the traditional marketing requirements are ignored. The focus is on simple, customer-driven questions: what do the customers want; how can their needs best be satisfied; what can be done better to enhance customer service and customer value?
Technology changes the way we do things, but fundamental needs remain unchanged.
There is another problem: the general conservatism of large companies. Most radical ideas fail: large companies are not tolerant of failure. Small companies can jump in with new, exciting ideas because if they fail, well, the cost is relatively low.
Incremental — the design is tested, problem areas are discovered and modified, and then the product is continually retested and remodified.
Radical Innovation — Incremental innovation starts with existing products and makes them better. Radical innovation starts fresh, often driven by new technologies that make possible new capabilities.
Although technology is continually introducing new means of doing things, people are resistant to changes in the way they do things.
Consider three simple examples: social interaction, communication, and music. These represent three different human activities, but each is so fundamental to human life that all three have persisted throughout recorded history and will persist, despite major changes in the technologies that support these activities. They are akin to eating: new technologies will change the types of food we eat and the way it is prepared, but will never eliminate the need to eat.
But a business that makes and sells durable goods faces a problem: As soon as everyone who wants the product has it, then there is no need for more. Sales will cease. The company will go out of business.
Ford explained that he wanted to find the parts that were still in good shape. The company could save money if they redesigned these parts to fail at the same time as the others.
Making things fail is not the only way to sustain sales.
In today’s environmentally sensitive world, the full life cycle of the product must be taken into consideration. (see The Circular Design Guide from IDEO)