Design thinking is a way of framing and then solving problems based on close and empathetic observation of users or customers. It’s a hot topic right now as companies seek new ways to make innovation happen, and to move beyond other problem-solving approaches such as those offered by Six Sigma. Design thinking forces people to think broadly about user needs and to be generative rather than purely analytical.
Traditional product development often relies on a small team of experts to identify and design a solution, a top-down approach. In contrast, in design thinking, designers observe users and frame the design problem based on what’s learned from those observations. Unlike top-down approaches, design thinking focuses first on making sense of why users act the way they do, similar to what anthropologists do when they study other cultures. Once design problems are identified and framed, then product solutions can be explored. Design thinking can, and in some cases should, be supplemented by quantitative market research.
Rather than frame design thinking as a process, I’ve begun to think about it as a set of skills that we need to develop to support innovation throughout an organization. There are five key skills that I believe matter.
1. The first is for product designers to have empathy for customers. Gaining empathy hinges on good observation skills and understanding not just fundamental use and usability needs, but also the customer’s meaning-based needs. In short, this requires figuring out the story that customers are living in today. The design thinker elicits stories by setting aside her existing assumptions and becoming naïve, asking insightful questions, and trying to understand what customer stories say about their needs. As David Foster Wallace suggests, this requires “seeing the water” in which both they and their customers are swimming.
Gaining empathy hinges on good observation skills and understanding not just fundamental use and usability needs, but also the customer’s meaning-based needs.
2. Next is generating interesting insights. Suppose, for example, that you were observing ATM use. You might conclude that “ATMs should be easier for customers to use”, but this isn’t a terribly interesting insight and is one you could have identified without observation. A more interesting insight might be that people feel unsafe withdrawing money from ATMs when they have their backs turned to the world behind them. The Spanish bank BBVA just revamped their ATMs in part to respond to this fear, turning them sideways so the user can keep an eye on others around him. Interesting insights in turn beget more interesting solutions.
3. Diverging. Brainstorming is certainly one form of diverging, and one that many firms would benefit from practicing more. But, before even starting a brainstorm teams have to diverge around the problem they aim to solve. Charles and Ray Eames’s “Powers of 10” graphically shows what it means to look at a problem at different levels. As I move an order of magnitude further away from the couple picnicking on the Chicago lakefront, I see their situation in very different ways. In our ATM example, I could see the user’s need to interact with the machine itself, a need to get money, a need to pay for dinner, and so on. With each reframing of the problem, I see a different potential set of solutions to that problem.
4. Telling a new and compelling story. Story telling is important throughout the design process. We start by listening closely to the story that customers are telling. Once we’ve figured out the story that customers are living today, we strive to tell a new story. Huggies Pull-ups turned the old story of “I wish I knew how to negotiate toilet training with my toddler” to the new story of “I’m a big kid now!” That story not only motivated the internal R&D organization at Kimberly-Clark, but became the advertising story line as well. Most of the Marketing Requirements Documents we use to communicate from marketing to R&D today fail to tell interesting and compelling stories that inspire the development organization.
5. Engage in learning from failure. Do rapid iteration of new ideas by prototyping quickly. A “make it and break it…quickly” attitude towards product prototyping means that several product design possibilities can be tested quickly and then retired equally quickly if they do not work. Bank of America set up several branches in Atlanta in which it can try out new services or service environments with users. Quickly putting ideas out in front of customers and getting feedback allows the bank to learn what works and doesn’t work, leveraging knowledge from “failures” into new versions of the solutions.
Design research and market research can and should co-exist. However, in the pressure to embrace quantitative and analytical data-based analysis, the risk is that design thinking gets overlooked. Although analytical data can be a goldmine and should remain an essential part of business strategy and decision-making, it does not tell the entire story. The question that innovation managers should be asking themselves is “How do I take analytical data and then go live with people to find out the entire story?” In other words, innovation managers need to learn to “bring life to the numbers.”
In today’s data-abundant business environment, the emphasis on analytical thinking is increasing rather than decreasing. For example, as more and more business activity becomes internet-based, businesses have more data to work with. A purely data-driven approach to understanding customer needs tells you where customers have been and what they have done. However, it does not reveal why the customers did what they did.
The biggest challenge that companies face is using data to form a deep understanding of what customers care about.
The biggest challenge that companies face is using data to form a deep understanding of what customers care about. Focus groups have traditionally been the primary source of qualitative information when companies study user needs. However, focus group research does not provide a whole lot of insight into the context in which customers live. Especially the unspoken norms and the contradictions between what customers say they want and what they actually end up doing.
If I were to speak to senior managers and say, “I want to develop this product,” it’s typical that management would ask to see the data upon which I based my claim. If I were to tell them it’s based on closely observing ten or fifteen customers, they would probably tell me I need to go out and do more homework, i.e. collect additional market research data. While quantitative data is key and should be used, research by Abbie Griffin and John Hauser shows that if a designer goes out and gets to know the needs of twenty to thirty customers using one-on-one interviews, that information will provide about 90% of what you need to successfully shape and develop the right product.
If I were an executive, I would tell the designer to skip the additional “arm’s length” market research surveys and to jump quickly into rapid, small-scale product prototyping. For example, in Japan in the 1980s, they followed a similar approach. Japanese corporations in that era did not believe in doing extensive, large scale market research to determine what their customers needed. Instead, they focused on getting a deep understanding of the customers they knew and then taking new product ideas to a “design factory,” where they inexpensively created and tried out solutions at a small scale. Design thinking, employing rapid prototyping of potential products, exposes customers early to a proposed product. If change is needed, product developers can course-correct early on in the process.
I do not diminish the value of taking an analytical approach, and data should remain a critical and central part of any product development process. However, it’s possible to get a very deep understanding of what direction to steer product development towards by deeply and intimately observing and understanding a relatively small group of target customers.
Co-creation, crowdsourcing and working with lead users are all highly compatible with design thinking. Co-creation entails involving customers directly in the design process, which is part of what rapid prototyping facilitates. Agile development processes similarly provide multiple opportunities to engage customers directly in the design and development process. Crowdsourcing similarly involves the customer in design and development, albeit perhaps in a more arms-length fashion. A web-enabled process, crowdsourcing solicits inputs from a wide range of people into the design of a new technology or solution. Lead users are those who push a product or technology beyond its design limits, often adapting or modifying it to meet their needs. In some industries, lead users are credited with 70% or more of the innovations that happen. Companies in those industries must actively work with and understand lead users to help them imagine advances they might make in their own solutions.
All of these approaches are highly compatible with design thinking, as they provide different ways in which companies can capture understanding of users. In each case, users are invited to bring their own sense of the meaning of alternative solutions to the design process. In this sense, the users are brought into the process directly rather than serving simply as a source of information for a process in which they are less a part.
I started teaching about design at the Haas School of Business in 1993. Back then, we started off with an informative course on design – what designers do and how to work with them. I would call that “Little D” design. It focuses largely on the aesthetics of a solution, its ergonomic and cognitive fit with users. In contrast, design thinking as we teach it today is what I would call “Big D” design. “Big D” design takes a holistic approach to coming up with customer solutions that’s based on observation, empathy, and correctly framing the customers’ problem.
Six Sigma and TQM were becoming increasingly central to corporations and brought with them a focus on variance reduction….students were increasingly taught to understand their customers via metrics rather than via observation.
About the same time I started teaching “Big D” thinking, Six Sigma and TQM were becoming increasingly central to corporations and brought with them a focus on variance reduction. The analytical focus of these methods permeated corporate organizations and business schools; students were increasingly taught to understand their customers via metrics rather than via observation. It seems likely that we’ve let the proverbial pendulum swing too far, and have become overly focused on metrics and variance reduction at the expense of qualitative data and divergent thinking.
The innovation process requires problem finding, problem selecting, solution finding and solution selecting. However, much of the focus in today’s business and engineering programs is on solution finding and selection. Both business and engineering schools – at least in our limited sample to date — attract a large proportion of students who have converging learning styles. These convergers attempt to quickly get to the answer, but are less adept at identifying, framing and re-framing the problem itself. We’re working on teaching business students the skills they need to be better at the problem finding part of the innovation process – empathy, pattern finding, insight generating. But it’s possible that we need to start that teaching much earlier – in high school or before.
Too much focus on metrics and efficiencies can steer a company towards safer product development decisions that result in incremental improvements to existing products. Design thinking teaches us to re-frame questions, which opens up the possibilities for the creation of innovative and radical new product ideas. Six Sigma and TQM absolutely have their place, but it would be best if students and businesses alike were comfortable in all of these methods.
By Melba Kurman
Sara Beckman is on the faculty at the Haas School of Business at University of California, Berkeley where she teaches new product development, design thinking and operations management. Her PhD is in Industrial Engineering, making her a process person at heart. You can reach her at Beckman@haas.berkeley.edu
Melba Kurman is an analyst and speaker with over 15 years of experience in bringing innovative technologies to market. Melba’s commercial and academic work experience gives her unique insight into industry/university research and product development partnerships. She was a product manager for Windows Server at Microsoft and more recently, was responsible for marketing Cornell University’s intellectual property portfolio to industry partners. She is an expert in university technology transfer strategies and challenges. Melba writes the popular Tech Transfer 2.0 blog, and is the president of Triple Helix Innovation, a consulting firm dedicated to improving university and industry innovation partnerships