Design thinking is a design process that enables us to solve complex problems. It combines deep end-user experience, systems thinking, iterative rapid prototyping and multi-stakeholder feedback to guide us through the successive stages in our design. Design thinking, like complex systems, is interdisciplinary. It cuts across traditional domains by recognizing that everything in our world is designed. Thus, it takes design out of its comfort zone of building chairs and fancy coffee cups to apply it to all areas, from designing effective organizations to creating healthcare and financial services.1
The design process is a bit like blowing up a balloon and then slowly letting all the air out of it again. It requires an initial phase of divergent thinking where we ask expansive questions to explore the full context and many different possible options before having to narrow our vision down upon a single solution and refine it through convergent thinking. But this process is not mechanical. It is more evolutionary, meaning we cannot fully foresee the end product from inception. It emerges, and thus we need to think about the future in an open way. That means having confidence in the possibility that an unknown outcome is feasible, as the whole point of the design process is that we will create something that does not yet exist and thus is unforeseen. But we don’t have to reinvent the design process wheel every time. There are a few broad stages to it, which different people will define in different ways, but we are going to talk about some of the most often identified phases in the design thinking process. They include the stages of researching, ideating, prototyping, and testing. These steps don’t necessarily follow a linear path. They can occur simultaneously and be repeated.
Firstly, the researching phase. What we are doing here is not creating a thing. What we are creating is a solution, which is a solution to a problem that a particular person or people have. Thus, we need to understand the context within which our system will exist and where it lies in relation to other things within that environment. It is only when we see the given context within which a pre-existing version of the system operates that we get a full insight into why it is the way it is, and from this can begin to conceive of an improved solution. When we don’t understand the context then we will be likely to simply go around in circles, reacting to the pre-existing solution. One generation of designers decides that straight lines are the greatest thing, extolling all their virtues, making everything square and rectangular with pointy corners, until the next generation of designers comes along and are now sick of straight lines. So they start a new revolution of curves and rounded corners, until everyone gets tired of all the curves and rediscovers the straight line again and so on.
By understanding the context and the history of the context to a design, we can see its parameters, the advantages, and disadvantages of both extremes and try to find an integrative solution. If we remember that there are always two qualitatively different levels of a complex system, the local and the global, as designers of the system we will be dealing with it primarily on the macro scale. But at the end of the day, everything really plays out on the local level and we need to understand the local context where people interact and live out their lives through these products and services. People can’t always express what exactly the problem is or know exactly what it is they want, so we need deep immersion to piece it together for ourselves, ethnographic studies, customer journey maps, all forms of end-user experience, and, most importantly, empathy. This research phase is a muddy, confusing part of the process that is often bypassed in pursuit of arriving at an end result quickly. However, with these complex engineered systems, it is critical to building a solid foundation with which to move forward on.
If the initial phase of empathy and context understanding is all about the “why”, then ideation is about the “what”. Within these complex systems, there will be multiple stakeholders involved, and we need to consider the perspectives of each one. The solution has to be viable for each of the multiple stakeholders involved, that is, from the human perspective of the end-users that have to live with the finished product, from the economic perspective of the businesses or organizations that are going to deliver the solution, from the technological perspective of what is physically possible – and we might add, from an environmental perspective of what is sustainable given the resources available.
We need to be aware that everyone brings some kind of perspective to this ideation process, and each one of these perspectives will have some kind of filter on it. It is only by identifying and removing these filters that we can truly think outside the box where real innovation happens. One way of achieving this is through collaboration. Design thinking suggests that better answers happen when 5 people work on a problem for a day, rather than having one person working on it for five days. From all these different perspectives, we can come up with what is possible and what is feasible for all. Ideation requires creativity but also rationality, creative thinking to continuously create possibilities, and then analytical thinking to rationalize their viability within the given constraints.
Once we have an idea of what we are building, then we need to know how to build it, and prototyping is the vehicle through which we experiment to discover this. Prototyping can be an art and a craft. It requires practical skills to build and imagination to bridge the gap between a mock-up and the finished product. The idea is to fail early. Many complex systems are big lumpy things like transportation networks. You build them once and then you are stuck with them for many decades. Prototyping offers us a safe environment to keep failing until we succeed.
Lastly, deployment and feedback. Designing something is a lot about learning, and the best learning is supported by experience. Experience in the functioning of a system we are designing, and it can only really be gained by putting it out there into its operating environment because it is only when it is in its finished context that we can gain a full 360-degree view of it. We do this by creating a minimal viable product, the very most basic version of our system that is fully functional and from which we can get real feedback. We can then define key performance metrics and start our accounting of how well it is delivering its functionality. We then iterate on this, gaining feedback each time that goes into our accounting system to see if we are evolving in the right direction. But of course, the design doesn’t stop there. To make the product or service sustainable, we have to integrate this evolutionary mechanism into its full life cycle.