Thickness matters when cooking steak. A rule of thumb is to cook a 2cm-thick piece of steak for 2 minutes for rare, 4 minutes for medium, and 6 minutes for well-done. However, we struggle with guessing how thick a piece of steak is. Seven years ago, I met a clever solution for this problem at a grocery store where there was a manually carved wood plank. Since it shows how professional providers empathize with novice customers, I have shared it with many planers and designers. Recently, I met a similar but more carefully designed wood plank at a different grocery store in Seoul, Korea. According to the website, Gourmet 494 is
a space for food, entertainment and communication, built on the concept of “grocerant” (grocery + restaurant) for the first time in Korea where groceries (food ingredients) and restaurants (food and beverages) come together in one place
Wood plank tells that thickness is difficult for people to evaluate. A specific value (e.g., 2 cm) is hard to tell another value (e.g., 3 cm) because we are not sensitive about it. About this issue, a group of psychologists introduced a concept of General Evaluability Theory about 10 years ago.
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Reference
A central question in psychology and economics is the determination of whether individuals react differently to different values of a cared-about attribute (e.g., different income levels, different gas prices, and different ambient temperatures). Building on and significantly extending our earlier work on preference reversals between joint and separate evaluations, we propose a general evaluability theory (GET) that specifies when people are value sensitive and when people mispredict their own or others’ value sensitivity. The GET can explain and unify many seemingly unrelated findings, ranging from duration neglect to affective forecasting errors and can generate many new research directions on topics ranging from temporal discounting to subjective well-being.
In the section of Nature, the authors wrote the following. According to them, human beings do not seem to have an innate or stable scale to evaluate values on thickness.
Nature refers to whether human beings have an innate and stable physiological or psychological “scale” (reference system) to evaluate values on an attribute. The attribute is inherently evaluable if they do or inherently inevaluable if they do not. Ambient temperature is an example of an inherently evaluable attribute; even without learning or social comparison, we can tell what temperature makes us comfortable and happy and what does not. Other examples include amount of sleep, social isolation, or connectedness. The size of a diamond and the power of a car are examples of inherently inevaluable attributes; without learning or comparison, we would not know how to assess such variables. Of course, some people know how to evaluate diamond size and car power, but such knowledge is learned, not innate. Because people possess innate reference systems for inherently evaluable attributes but not for inherently inevaluable attributes, value sensitivity (without learning or comparison) is higher for inherently evaluable attributes (H1.3). More precisely, people in SE are more sensitive to differences on an inherently evaluable attribute than to differences on an inherently inevaluable attribute, holding their sensitivity to the two types of differences in JE constant; see our discussion of the Mode × Value × Nature interaction later in this article.
It should be noted that classifying a variable as inherently evaluable does not mean that it is immune to the influence of external reference information (such as social comparison); instead, it means that people can evaluate the variable even without such information. Also, inherently evaluable variables are not always associated with basic biological needs—they also include socio-psychological variables, such as loneliness, depression, and sense of achievement. (For details, see Hsee, Yang, Li, & Shen, 2009.)
The author introduces a case in which wooden boards were provided in grocery stores to help customers easily assess the thickness of steaks. In general, people may understand the numerical difference between 2 cm and 3 cm, but they often struggle to accurately perceive that difference in reality. The author explains this phenomenon through General Evaluability Theory (GET). According to GET, people find it difficult to evaluate an attribute when they lack an internal reference standard for it. Therefore, wooden boards that allow consumers to touch and compare actual sizes can help them make more accurate judgments than numerical measurements alone.
I agree with the author’s argument. In fact, I frequently observed a similar phenomenon while working part-time at a family steak restaurant during high school. The steaks served at our restaurant were relatively thin—about 1 cm thick—compared to typical steaks. However, customers rarely asked about the thickness of the meat. Instead, they focused on whether it was sirloin or tenderloin, or on which set menu they should order. I believe this was because customers did not have a clear standard for evaluating steak thickness.
However, this example led me to interpret GET from a slightly different perspective. People may struggle to accurately evaluate not only unfamiliar attributes but also attributes they believe they already understand well. One example was steak doneness. The most popular level of doneness at our restaurant was medium-rare. However, some customers looked at a medium-rare steak and said, “This seems too undercooked,” and asked us to cook it longer. In many cases, they were satisfied once the steak reached medium doneness.
Through this experience, I realized that people do not necessarily evaluate the doneness level itself. Instead, they evaluate it based on their personal preferences. In other words, although the steak clearly met the restaurant’s standard for medium-rare, some customers perceived medium as what medium-rare should be. GET explains that people find it difficult to evaluate an attribute when they lack a reference standard. However, I believe that the same problem can occur even when people do have standards if those standards differ from one another.
For this reason, I would like to propose a new approach for the steak industry. Currently, most restaurants describe levels of doneness using terms such as rare, medium-rare, and medium. However, these labels can be interpreted differently by different people. Instead, just as grocery stores use wooden boards to represent steak thickness, restaurants could display cutaway models showing the actual appearance of each level of doneness before customers place their orders. This would allow consumers to select their preferred doneness much more accurately. For example, if models representing each level of doneness—from rare to well-done—were displayed at the ordering counter, customers could simply point to a model and say, “I’d like my steak cooked like this,” rather than relying on potentially ambiguous terms such as “medium-rare.”
Ultimately, the author’s example demonstrates that people make more accurate judgments when they can compare information directly rather than relying solely on numbers or words. I would add one more point: judgment errors can occur not only when people lack a standard but also when different people use different standards. Therefore, I believe that future service design should go beyond simply providing information and instead focus on creating experiences that allow everyone to understand and evaluate products according to the same standard.