It seems like everybody is talking about Design Thinking these days. In case you havent, design thinking is a methodology that has become very popular in contexts of innovation around the world. Many companies are hiring intensive Design Thinking workshops for their employees to learn to think “out of the box” and with the hope that after a few days using many post-its they will come up with the next great idea that will disrupt the market. But, what do we really know about design thinking? In this article I’ll explain what Design Thinking is and how it relates to social anthropology.
What is Design Thinking?
You’d be surprised how many people talk about Design Thinking without having much knowledge of what it is, or how to put it in action. Literally one could understand Design Thinking as “thinking like a designer”, although it would be sad to believe that designers have a single standarized way of thinking. As Jamer Hunt pointed out at WWNA: Designing the future, “every designer´s method is different. And what is scary is that people want to turn what is a very complex process into a simple one”. That is quite the contrary of what designers do. Above all, designers try different ways, and create by moving towards risky areas of uncertainty. So, if you want to think like designer, maybe you should try avoiding standarized methods.
However, if you want to do the “standarized” Design Thinking, it is also important to understand that it is really not a methodology exclusive to the field of design. This methodology has been nourished by multiple disciplines, and has always bet on interdisciplinarity and collaboration as two of its strengths. One of the disciplines that also plays a rol in this method is anthropology. Is the matter fact, I sometimes like to (provocatively) call it “anthropological thinking” since one of the main attributes of this methodology is its focus on research about people and their contexts.
Brief History of Design Thinking
Although now its trendy in creative offices and innovation departments around the world, this way of working began in the United States in the 1960s. At that time, Richard Buckminster wanted to turn the discipline of design into a science motivated by people’s needs, proposing methodologies to evaluate the design of solutions to complex challenges with a social component (and wicked problems). At the same time, in Scandinavia, a group of designers organized themselves into cooperatives and began to talk about co-design (Yes, 60 years ago there was already a discussion on how to co-design!)
In the 1970s, Herbert Simon, Robert McKim and Nigel Cross – in Stanford University took up these ideas and laid the theoretical foundations of what we now know as Design Thinking. A few years later, also in California, IDEO was born, the design company that has popularized and marketed Design Thinking globally – by the way, they also have been main players in marketing ethnography globally, as they allways worked together with anthropologists.
The standarized model
Today we know Design Thinking as a standarized work method that aims to generate innovative ideas for solving human problems. The most expanded model is that one with 5 steps: Empathize, define, devise, prototype and test.
Which actually, I prefer to represent as a cycle, as one should allways analyze what happens in the testing phase and refine the original data to improve the solutions:
However, there is no single formula or recipe for applying design thinking. For example, the also well known double-diamond approach:
There are different models with variations, and I encourage you to look them up as there is plenty of information out there about all of them.
For this article, I don’t intend to deeply elaborate each of the steps, but just quickly give you an idea on what each step entails:
Empathize: We should always start with an investigation that is intended at learning about the problem or challenge to be solved and the people for whom we will be designing a solution – those who will be impacted by the resulting product/service/technology. Through ethnographic tools such as participant observation, interviews, focus groups and others we go deep into their behaviors, emotions, and contexts. The goal is to avoid a common mistake: building on assumptions. This is the part where anthropologists are crucial. The better this part is done, the more chances to provide solutions that provide real added value to people´s experiences.
Define: In this phase, it is necessary to synthesize the information produced in the empathy phase in order to remain only with that which really sheds light on the challenge or problem. It is very important that the people who have carried out the research also participate in this phase in order to better communicate the results obtained to the rest of the team involved in the project.
Ideate: In this phase, we should get messy. We are not looking for a single answer, as if there is a single answer or “THE perfect solution”. The mindsetshould be that in each context and for each person different solutions can co-exist. So, the more the better. We first brainstorm as many solutions to the problem as we can formulate, moving from divergent thinking (in which many options are devised) to convergent thinking (in which choices are made to get closer to a concept to work on).
Prototype: In this phase, we work hands-on and use our spatial intelligence. The “making process” is another form of thinking and experimenting. It doesnt mean that you are done with the ideation. During this process, we will challenge our ideas and see if it is actually doable, obtaining empirical information about what you need to implement it.
Test: No matter how good your ideas are if you don’t test them by observing them in natural contexts where real users will be interacting with it, you may be creating useless or unstable solutions. That is why we need to test the product or service created to identify improvements. Here, again, you should count with an anthropologist, or at least have the mindset of one. Learn from the users. Listen to them. Be courious. Ask questions.
What does anthropology bring to Design Thinking?
Anthropology has always had an important place in Design Thinking, since the founders of this methodology already included anthropologists in their projects. In many ways these two disciplines are aligned and are a perfect match. Both consider that experience is personal, subjective, and contextual. Both consider that working with assumptions, will lead to same results, and therefore we have to look with neophyte eyes. We have to be curious, to observe and to be surprised by our surrondings. Which leads us to live continuously between the field, the analysis and the synthesis.
Furthermore, including anthropologists in Design Thinking projects will avoid common blunders such as thinking about people in a one-dimensional way, attending only to their quality as “users” or “clients”.
Like many current trends, Design Thinking is plagued with buzzwords (used in English even in non-English speaking contexts; which leads to confussion as many dont even know what the words they are using mean). As we delve a little into its concepts, we will see that many are closely related to social anthropology, and can be powerful concepts:
User Persona = people´s archetypes
Journey maps = cartographies of experiences
Out of the box thinking = Non-hegemonic thinking (or outside the norm)
While anthropologists are known for their ability to visibilize the invisible, ask pertinent questions, and define social problems, designers are dedicated to developing solutions to problems. As Dori Tunstall sings in her D´Anthro rap, “Design transforms values into tangible experiences”. Therefore, if we know how to offer the best of both disciplines, its a perfect match. The value of ethnography in Design Thinking is immeasurable. So, as Jay Hasbrouck would say, it could well be called Ethnographic Thinking!
In Antropología 2.0 we use this methodology for many of our projects. We also accompany other teams when they immerse themselves in a Design Thinking process offering extra support in the empathy and testing phases, which allows them to obtain more rigorous and deep data, commonly called thick data.