In one sense, our actions in the world can be thought of as a series of choices. Are our decisions driven by Logic? By emotion? By something other? If we knew what influenced our decisions, would that help us design better medical products?
In his book, The Business of Choice, Matthew Willcox proposes that the decisions that guide our behavior are based on instinctual responses that have proven advantageous to our survival as a species. This paper will examine that theory, and other hypotheses. By understanding how we respond to stimuli to make choices, we should be able to deliberately design devices to have the physical characteristics that support our instinctual choice mechanisms. It would follow that designing a medical product in that manner would make its use intuitive.
One of the most powerful characteristics that influences how and what we choose is the degree to which something is familiar to us. We have a strong preference for things that we already know. Willcox cites a study by Robert Zajonc that found the more frequently we are exposed to something, the more positive our attitudes toward it become (thus the power of repetitive messaging, which advertisers and propagandists have been exploiting for years). The evolutionary theory is that, as we struggled to survive in the distant past, we felt safe with the things we encountered on a recurring basis that hadn’t harmed us. Familiarity communicates safety.
The Paradox of Innovation
We prefer the familiar, yet we seem to be deluged by messages extoling the virtues of the new and improved. Innovation seems to be what every company bringing a new product to market is in search of. If our preference is for familiar things, why is it that we also seek the new and the innovative? One factor could be simply that we’re curious beings. Another could be that we get bored with sameness. Still another could be that we seem to have a drive to want to continually improve our situation. Acceptable isn’t good enough – how can we make it better, how can we make it perfect?
Wilcox proposes that although we feel safe with the familiar, we’re motivated to seek new things because having access to variety is a good survival strategy – if one resource dries up, we have alternatives. Although we prefer the familiar, we are at the same time attracted to novelty and surprise. Willcox writes that the power of successful advertising is in using familiarity to draw us in, but then providing an unexpected twist that gives us a new perspective.
Still, the power of the familiar is so strong that even if a new way is better, it is very difficult to get people to move from their accustomed ways. The Dvorak keyboard is a classic example. When the typewriter was invented, keys jammed if typing was done too quickly. The key layout was changed to deliberately slow down typist’s speed. Thus we have the “QWERTY” keyboard (the top row alpha characters are QWERTYUIOP – QWERTY for short).
In 1936, Antonin Dvorak developed a layout that increased typing efficiency. Although it’s been shown that the Dvorak keyboard allows people to type faster, the innovation never caught on. The QWERTY keyboard is by far the more familiar arrangement. For anyone to want to switch from it, the reasons would need to be more compelling than the increased speed the Dvorak keyboard offers.
In “The Curse of Innovation: A Theory of Why Innovative New Products Fail in the Marketplace”, John Gourville did an extensive examination of factors that influenced the adoption of new products. He cites Andy Grove, the founder of Intel, as stating that a new product has to offer a 10-times improvement over the existing alternative in order for it to achieve rapid and widespread adoption. Very few innovations will satisfy that requirement.
Gourville found that companies generally overestimated the value their product innovation would have for users. Their products might be innovative, but not to the extent that people would be motivated to move from what they’ve become familiar with. Interestingly, in their paper Managers’ Knowledge of Marketing Principles: The Case of New Product Development, Cierpicki, Wright and Sharp site empirical evidence that indicates the innovation acceptance curve is actually U-shaped: there is high acceptance and market success for products that offer only minor improvement and for products that offer the significant improvement discussed above. Products with an innovation level in the middle are not as successful.
Loss and Gain
In addition to our preference for things we know and are used to, we have a strong aversion to loss. Given a choice between losing a benefit we have and gaining a benefit we don’t yet have, we much prefer keeping our current benefit. Our aversion to loss contributes to the effect of our systematically undervaluing the benefits of an innovation. A loss has a greater negative effect than a gain has a positive effect.
The “endowment” effect also influences how we respond to innovation. It is another factor that bolsters our bias for the familiar. We demand more to give something up than we’re willing to pay to obtain the same thing. The thing we have is part of our endowment, and we place more value on it than a similar thing that is not part of our endowment. Further, we’re more confident in choices we’ve already made. Fear of loss (from having to give up our current benefit) leads us to discount what we could gain from innovation.
In most cases, we judge that the disadvantages of leaving what we know outweigh the advantages of gaining something new. Too many companies start with a new idea believing that people will realize its inherent appeal. The result is often a product that doesn’t have the level of innovation required to get people to move from what they’re already familiar. Emphasizing how a new product is different and better fails to consider and address what people might lose by changing their existing behavior. Understanding what you’re asking people to change, and particularly what you’re asking them to give up by adopting an innovation is a critical but often unasked question.
Obviously, many innovations do succeed in the marketplace. But the high percentage of new product failures (which ranges from 35% to 45% of new product introductions) suggests there is significant opportunity to improve how we evaluate potential user/consumer acceptance before the commitment to launch is made. The messages we receive from media and advertising would suggest that innovation is highly desired. In reality though, that is often not the case. Companies need to be realistic in their assessment of the value an innovation will have for users. Factor loss-aversion into your evaluation.
Impacts on User Research
The pervasiveness of the idea that any innovation is desirable could lead researchers to conduct studies unaware that they might be harboring a bias in favor of the innovation being studied. Bias contributes to false conclusions. There could be an opposite effect at work here also. How many innovative ideas have been scrapped because of studies that produced false results due to participants undervaluing the innovation because of their preference for the familiar and because of the endowment effect? Unfortunately, that can’t be known.
Most user research methods are relatively formal, and create an artificial environment that skews results. The decisions we make are influenced by the context in which they’re made. If the study environment fails to replicate the real-life context, findings will be compromised. The very act of being studied changes how people behave. In fact, when people have to explain a choice, it affects the choice they make. If the study involves a group, group dynamics will play a large role in the results obtained. Our best indicators of what to do in a certain situation come from observing what others are doing. We’re more comfortable going along with the group than going against it. One strong, passionate and vocal member can influence a group to pursue a course they would otherwise not take if each individual were acting on their own.
Because of the biases introduced by an artificial research environment, more accurate results will be obtained if you conduct your study in a more anthropological way – by going into the field and observing behavior in the environments in which the device you are studying is used. We can learn a lot from non-verbal signals. We are adept at decoding subtle movements of facial muscles that can indicate, for example, when someone is content or when they’re frustrated.
Question and answer scenarios have limited value for a number of reasons. The study participant might have reasons for being less than forthright. As we’ve indicated, the act of being studied changes behavior, and being asked to explain a choice could affect the choice we make. Further, (as discussed below in “Heuristics”), we often default to what is easiest to explain, which might not be reflective of our actual motivation.
We make many of our decisions intuitively. People aren’t as rational as they think they are. They don’t have insight into why they do what they do, so asking them to explain their choices will give you questionable data.
Familiarity Enhances Usability
In addition to influencing our preferences, familiarity has an effect on our perception of how usable a medical device is. If familiar user interface elements are missing, we’re forced to figure out how to use the device in ways we’re not accustomed. That makes the task more difficult.
Both hardware interfaces (buttons, knobs, switches, latches, etc.) and graphical interfaces (display screens, icons, on-product instructions) should be designed to incorporate usage cues we have come to understand from long experience. Ignoring established use conventions is one of the main contributors to poor usability. When you are designing any interface, you need to consider carefully whether the visual elements you are using would be recognized by most users as relating to the way they are commonly manipulated.
For example, a plain round form is ambiguous in that it could be a knob that you turn or a button that you push.
Providing an indentation, either physically or graphically, suggests almost universally that it is something to be pushed.
Providing ribs around the perimeter suggests it is something that can be rotated.
These cues are things we’ve learned through experience over time. Because we are used to these types of conventions and they are familiar to us, we don’t need to think very hard about them. Reasoning is a taxing activity, energy wise. We seek to conserve energy, especially cognitive energy, whenever possible. Using commonly-understood form cues enhances usability.
Because decision-making is very taxing in terms of the cognitive energy it takes, we favor decisions that require the least mental effort. In order to conserve cognitive energy, we’ve learned decision-making shortcuts, called heuristics. Heuristics are rules of thumb we instinctively follow. They help us make quick decisions on a preconscious level (in fact, some studies suggest that most of our decisions are actually made before we’re even aware of making them).
In our preference for the familiar, the “recognition” heuristic is at play: we choose what we recognize. In our desire to conserve cognitive energy, a heuristic known as “availability” is at play: we choose what comes to mind most easily – what’s readily available to us. Together, what we recognize and what comes to mind most quickly drives a lot of our decision making. Often we choose not what offers the greatest benefits, but what is easiest to evaluate. Good (usable) design makes things as easy as possible. Easy means requiring the least cognitive effort on the part of the user.
Which of the following do you find easier to decide upon?
- Would you like $10 today or $15 next week?
- Would you like $10 today and $0 next week, or $0 today and $15 next week?
This difference between a hidden-zero framing (A) and an explicit-zero framing (B) was used in a 2014 study done at Stanford University to test aspects of self-control and delayed gratification. The researchers used functional magnetic resonance imaging (fMRI) to study brain activity associated with the decision task. They found less activity with explicit-zero framing, suggesting it required less cognitive effort and made the decision task easier. With explicit-zero framing, a consequence has been made obvious: 10 vs 0, then 0 vs 15. With hidden-zero framing, the possible consequence needs to be developed, which requires more cognitive energy.
Explicit-zero framing provides a ready comparison and a quickly-grasped consequence. Having something to compare against makes decision making easier – we don’t have to imagine the comparison ourselves, it’s already been given. When asking someone to make a choice, the task will be easier if you can supply a comparison that illustrates a consequence.
Our society emphasizes innovation as a desirable characteristic. However, we have a stronger preference for that which is familiar to us. Companies can increase their chances of creating winning products by understanding the dichotomy between the familiar and the innovative to realistically evaluate the chance of product success. Our preference is skewed toward keeping what we already have, versus abandoning it for new potential gain. Innovation needs to offer significant advantage for it to succeed. Reasoning and decision making is taxing. We’ve devised mental shortcuts that help us make choosing between alternatives easier. Using familiar form language in the design of user interfaces (both hardware interfaces and software interfaces) will minimize cognitive load and make products easier and more intuitive to use.
 Zajonc, R.B. (1968) “Attitudinal Effects of Mere Exposure.” Journal of Personality and Social Psychology 9: 1-27.
 Willcox, M. (2015) The Business of Choice. P. 49.
 Willcox, p.46
 Gourville, J.T. (2005) The Curse of Innovation: A Theory of Why Innovative New Products Fail in the Marketplace. P. 25
 Cierpicki, S., Wright, M., Sharp, B. (2000) “Managers’ Knowledge of Marketing Principles: The Case of New Product Development.” Journal of Empirical Generalisations in Marketing Science, January 2000 p. 781
 Gourville, p. 10.
 Gourville, p. 11.
 Wunker, S. (2017) Jobs to be Done. P. 29.
 Willcox, p. 89.
 Cierpicki, p. 778.
 Willcox, p. 184.
 Willcox, p. 182.
 Willcox, pp. 114-115
 Magen, E., Kim, B., Dweck, C., Gross, J.J., McClure, S.M. (2014) “Behavioral and neural correlates of increased self-control in the absence of increased willpower.” Proc Natl Acad Sci 111:9786-9791.