A basis for better understanding

Editor's note: Greg Chu is principal at KMK Consulting Inc., a Morristown, N.J., research firm.

Once upon a time, design referred largely to the downstream aesthetic and ornamental considerations involved in the creation of physical objects. Over the past half century or so, however, design practitioners and theorists have pushed beyond this limited “posters and toasters” view of design to apply their craft to a range of intangible products of human endeavor and imagination. The Harvard Business Review helped mainstream this expanded perspective of design 10 years ago when it published the article “Design thinking” in which the author, Tim Brown, proclaimed, “Thinking like a designer can transform the way you develop products, services, processes – and even strategy.”

Marketing researchers looking at this enriched concept of design found a lot to like. The emphasis on empathy and customer-centricity in design thinking resonated strongly with them. After all, market researchers and designers are kindred spirits in their commitment to understanding the needs and behaviors of consumers – or, more generally, the users of design. Philosophical affinity in turn paved the way for greater integration of a number of design thinking processes into market research, such as direct observation of consumers in natural environments, co-creation between consumers and marketers and rapid prototyping of product concepts. In some cases, this integration might be better characterized as appropriation of design thinking vocabulary. No one would suggest, for example, that researchers discovered ethnography only with the popularization of direct observation as espoused in design thinking. Nevertheless, design thinking has provided the research industry with additional inspiration in its continuing quest to fine-tune and enhance its relevance to commercial decision-makers.

In the 10 years that have passed since HBR published “Design thinking,” the market research world has seen the memes of design thinking largely displaced by the memes of behavioral economics, a trend no doubt propelled in part by the wave of best-selling books on behavioral economics over the same period, most notably those by Nobel laureates. Today, marketing and market research conference goers find themselves lured by talks on consumer irrationality and System 1 thinking. Marketers are reminded that cognitive biases litter the consumer landscape, either as golden nuggets for the astute or as landmines for the unwitting. While design thinking continues to engage those focused on innovation in product development and business processes, it generally makes little more than cameo appearances in mainstream market research conferences and publications.

Any researcher who has been around the block a few times may be tempted to explain away the shifting fortunes of design thinking as yet another example of the fickleness of market research fashion. He might further argue that design shops and creative agencies are better positioned to commercialize market research as part of design related assignments. Others might assert that the insights into cognitive biases offered by behavioral economics are more relevant to market researchers than the general process frameworks promoted by design-thinking practitioners. But before waving good-bye to design thinking and hopping on the behavioral economics bus, there is value in taking a deeper look at some of the foundational theory underpinning design thinking. Often overlooked by the market research community, this rich body of theory offers us a powerful lens through which to examine and understand consumer psychology and behavior, while complementing and extending the application of behavioral economics in market research.

Five fundamental psychological concepts

One of the foremost theorists of design thinking, Don Norman, introduced five fundamental psychological concepts underlying good design in his work, The Design of Everyday Things (1988). These are affordances, signifiers, constraints, mappings and feedback. While it is impossible to do justice to these concepts in a short article, it is important to note that all possess deep roots in the social sciences. The notion of affordances, for example, which he defines as “the possible interactions between people and the environment,” derives from the Gestalt psychology of James J. Gibson. The notion of signifiers is plucked from semiotic theory, although Norman uses the term in a narrower sense as “any mark or sound, any perceivable indicator that communicates appropriate behavior” in the face of an affordance. According to Norman, a thorough grasp of these five concepts, along with their proper application, leads to discoverability, a key property of good design, for it allows the users of design to discern what “an object does, how it works and what operations are possible.” Ease of discoverability in turn engenders positive user experience and satisfaction.

If the scope of Norman’s discussion of design theory stopped at discoverability, there would already be enough to interest marketing researchers. The relevance of these design concepts to the exploration and assessment of new products or services is clear – not to mention their obvious applications in loyalty and customer experience research. Alongside discoverability, however, he introduces another idea which he describes as the most important of all – that of mental models. These are, in his words, “conceptual models in people’s minds that represent their understanding of how things work.” Designers care about mental models because they affect how people interact with design. Mental models are of interest to us because they can be critical drivers of decision-making and behavior.

Norman provides a simple example of mental models in action. Suppose you enter a cold room and want to warm it up as quickly as possible. You find the room thermostat on the wall. Do you set it to the temperature you ultimately want, all the way up, or somewhere in between? Your decision will depend on your mental model of how the thermostat works. If you imagine the thermostat to be like a valve in which adjustment leads to a continuously variable amount of heat entering the room, you might turn it all the way up. If you imagine the thermostat to be simply an on/off switch that turns on the heat until a set temperature is reached – as is the reality in most cases – you would likely turn the knob just to the desired room temperature. Clearly, your mental model of the thermostat impacts your behavior. 

Are mental models also relevant to artifacts in our environment that are more complex and abstract than simple wall thermostats? Consider the case of health insurance – vitally important to so many but complicated, poorly understood and often blamed for suboptimal health care decision-making on the part of both patients and health care providers. In 2013, as the “affordable insurance exchanges” created by the Affordable Care Act rolled out, a team of researchers published their findings on consumer understanding of health insurance (Loewenstein, et.al.). From the first of the two studies they conducted, these researchers established that only a minority of consumers (14 percent) could demonstrate correct understanding of four basic parameters of health insurance coverage: deductibles, copays, coinsurance and maximum out-of-pocket. In the second and more interesting study, the researchers examined whether behavior could be changed through an insurance policy featuring simpler and clearer incentives for rational health care utilization, effected in part by eliminating deductibles and coinsurance, the two concepts least understood by consumers. Interestingly, in comparison with a traditional insurance plan, this simplified plan showed little impact on health care utilization decisions. The authors explained the result as follows: “One explanation for why we don’t find a striking difference in choices between the traditional and simplified plan may stem in part from the fact that people are already aware that traditional plans incorporate incentives for seeing in-network providers, avoiding the emergency room and taking generic drugs, even if they can’t quantify the consequences of choosing one option over the other.”

While the authors did not use the term “mental model,” their research suggests that consumer health care utilization decisions are driven by a general conceptualization of how insurance plans work and that this conceptualization, once established, may be resistant to the influence of new information – regardless of how clearly this information is conveyed. Much as in the case of the thermostat, the individual’s mental model of health insurance plays an important role in determining behavior. 

Need not be completely accurate 

These two very different examples, one a simple household device and the other, a complex contract, suggest several important properties of mental models. First, it is apparent that mental models need not be completely accurate to be effective. Unless your concept of how a thermostat works is wildly off, you will succeed in warming up the room. Regardless of your grasp of the exact terms of your health insurance, you can avail yourself of its benefits. In either case, you will likely achieve your ends, although you will do so more efficiently if you are possessed of a mental model that more closely aligns with reality. Second, by their very nature, mental models represent a simplification of reality – one that reduces cognitive workload and facilitates decision-making. In this respect, mental models reflect the demands of what is called bounded rationality, a term used to describe our limited cognitive abilities to make optimal decisions in the face of complex problems. Our interactions with the world, then, are guided in part by a panoply of mental models, simplified, incomplete and imperfect conceptualizations of reality which nevertheless allow us to interact with our environment in a satisfactory, if not an optimized or fully rational manner. 

Mental shortcuts 

Behavioral economists are fond of talking about heuristics, those mental shortcuts we use to form judgments and make decisions. Richard Thaler, the most recent behavioral economist to win a Nobel prize, describes heuristics as “simple rules of thumb” used by humans with limited time and brainpower to help them make judgments (Thaler, 2015). Here is where design thinking and behavioral economics begin to overlap – in the complementary and related concepts of mental models and heuristics. Both depend on simplification to work. The mental models which help us navigate our everyday lives are rudimentary schematics that inform our interactions with environmental artifacts, whether physical or conceptual, as well as our interactions with others. Heuristics are simplified cognitive routines; examples of which include relying on more readily accessible information rather than searching for new information or substituting a simpler question for a more difficult question when one has a ready answer for the former. Both mental models and heuristics are essential to our ability to operate in the world, despite the fact that they occasionally lead us to make incorrect judgments or irrational decisions. Herbert Simon, yet another Nobel prize-winning social scientist with deep connections to behavioral economics, summed up this fundamental commonality between mental models and heuristics when he wrote, “Simplification may lead to error but there is no realistic alternative in the face of the limits on human knowledge and reasoning.” (Simon, 1945) It is through the examination of these simplifications, whether expressed as mental models or heuristics, that design thinking and behavioral economics can fuel the generation of deeper psychological insights. 

Market researchers seeking to understand consumer behavior and decision-making would be well-served by keeping one foot in behavioral economics and the other planted firmly in design thinking. Through the lens of heuristics and their associated cognitive biases, behavioral economics alerts us to systematic and predictable patterns in judgment, or misjudgment, that consumers can make. Design thinking, through its emphasis on mental models, grounds these patterns in actual decision-making environments – or, more precisely, in the consumer’s perception of how these environments operate and the possibilities for action they present. 

How behavior can be changed 

But the interests of market researchers are not limited to simply understanding consumer behavior and decision-making. Researchers also seek to develop insights into how behavior can be changed. Here as well, design thinking and behavioral economics converge in a partnership that is more powerful than either one alone. 

In Nudge (2008), Richard Thaler teamed up with Cass Sunstein to explore the theory and application of the “science of choice.” The protagonist in their narrative is the choice architect who leverages a wealth of social science insights to create a context for choice that nudges people in the direction of better decisions. Thaler and Sunstein call this context “choice architecture” and clearly see it as a task for design. It is no accident that the bibliography of Nudge includes Norman’s The Design of Everyday Things. Nor is it surprising that Norman wrote a review of Nudge. When Thaler and Sunstein write that “choice architects can make major improvements in the lives of others by designing user-friendly environments,” they are invoking design thinking. When they discuss choice architecture and nudges, they are channeling affordances and signifiers, two of the five design principles developed by Norman. 

If market researchers are to provide guidance for generating behavioral change at the intersection of design thinking and behavioral economics, a framework for integrating the two domains is needed – ideally one focused on the consumer decision journey. Many such frameworks exist and can be retrofitted to this task. The framework in Figure 1, adapted from veteran ad man Stephen King’s consumer buying process, offers one example. In this framework, mental models are engaged when an individual is confronted with a stimulus demanding judgment or action. Assuming a considered purchase decision, the framework then posits consideration, information-search and choice as sequential steps. The last step in this framework, experience, serves either to strengthen or undermine the consumer’s mental model over multiple iterations of purchase and consumption. At the center of this model are affordances and nudges, which define the environment in which the decision-making process unfolds. Here, affordances represent the complete inventory of what the environment offers the consumer – whether good or bad, perceived or unnoticed. Nudges represent prompts for particular judgments or behaviors. Within the context of marketing, these nudges might take the form of ads, coupons, signage, tweets or blogs. Within the world of design theory, they may be thought of more generally as signifiers, cues to proper interaction with an affordance. Heuristics and cognitive biases attach to any stage of the model but are most commonly referenced in the context of consider and search.

Frameworks like this can serve as high-level blueprints for the construction of robust research programs that drive insight into consumer behavior and provide guidance for eliciting behavioral change. Market research designed to populate these frameworks can, however, be challenging, as the task requires assembling both declarative and procedural knowledge from respondents. Declarative knowledge comprises awareness of facts, opinions and perceptions and self-reports of behavior. Procedural knowledge refers to knowledge utilized in undertaking a specific task. While questionnaires can deliver a reasonable rendering of relevant declarative knowledge from a consumer, they are less suited to extracting procedural knowledge; respondents often have trouble articulating the thought processes they go through in solving problems and may not be fully conscious of what they are doing. In these situations, simulation-based research methods in which the respondent is immersed in a virtual task environment can offer advantages. In such simulations, cognitive interviewing approaches can be used to capture thought processes in-the-moment, rather than from memory. Observation of activities within the simulation can offer insights into heuristics that defy ready verbalization. And manipulation of affordances and nudges within the simulation can help expose the mental models that drive behavior.

A valuable perspective 

A greater appreciation of design thinking offers market researchers a valuable perspective through which to understand consumer choice and behavior. Design thinking for market researchers is much more than ethnography, an empathetic mind-set or a paean to customer centricity. It is an approach to understanding the individual in the context of his environmental niche, including the artifacts and fellow denizens with which he interacts. Design thinking dovetails well with behavioral economics, whose general insights into decision-making and judgment, as understood through heuristics, become actionable when placed within a specific decision-making context or choice architecture. Herein lies the value of design thinking in a world fascinated by behavioral economics: By providing the theoretical basis for understanding and deconstructing existing choice architectures, design thinking provides researchers with the means to guide re-assembly of these architectures in ways that predictably and positively impact consumer behavior.