Reflections on Design Research: Framing the Problem, Part 2

Re-reading my previous post about design research and how I described what it means for a human centered designer to frame a problem in the context of a community, I realized I needed to break down the different steps involved in framing a problem. Just as I did with my previous post, I'll use examples from my thesis to show the different steps, but this time I'll also reference several design texts. This will build up a language to describe design research and its role within the design process.

A theme in design research is to understand the relationships between different problems. Understanding how problems are connected by using visual mapping techniques can greatly aid in sense-making and communication. Communicating the interconnectedness of each problem, challenge, and opportunity allows for a deeper level of research that will shed light on the root of the problems you're tackling. Designers call these types of problems, wicked problems, because there is no single, simple, or straightforward solution. Instead, the solution takes on the form of a system of solutions, which tackles a system of problems. Sometimes prototyping and testing each solution within a system is a start. However, each solution for each respective problem is not enough, because a solution by itself does not anticipate the difficulties of interacting with other solutions. Thus, a systemic perspective of the interaction of solutions is necessary.

For example, after I finished my first round of interviews for my thesis, I became aware of three major challenges for the Philadelphia startup ecosystem. These three major areas included a disconnect between mentors and entrepreneurs, a lack of funding in the Philadelphia startup ecosystem, and the entrepreneur's concern with traction.

I then learned the relationship between these various themes that surfaced after I organized the data I gathered. The relationship is the following: if startups need funding, traction is usually required and having a mentor may prove to be a first point of traction. This is a valuable insight, but was not enough to justify focusing on mentors. Around the same time of these interviews, I came across a report published by the Startup Genome, which discovered two important pieces of information:

(1) "Hands-on help from investors have little or no effect on the company's operational performance. But the right mentors significantly influence a company's performance and ability to raise money."

(2) "Founders that learn are more successful. Startups that have helpful mentors, track performance metrics effectively, and learn from startup thoughts leaders raise 7x more money and have 3.5x better user growth."

These two key pieces of information pointed towards mentoring as a vital opportunity, challenge, and problem that required some sort of solution. Solving mentoring would then indirectly solve traction and funding because of these relationships between traction, mentors, and funding.

In his book, Exposing the Magic of Design, Jon Kolko presents three major steps: making meaning out of data, experience frameworking, and empathy and insight. Roger Martin, in The Design of Business, calls these same steps the knowledge funnel, when you're going from a mystery to a heuristic to an algorithm. These are all about discovering problems and solutions, and the important part of finding the problem is correctly understanding the relationships between different problems. If you take a look at the example I provided above from my thesis, the example shows the organization of data points into a heuristic, as Martin would call it, and making meaning out of data, from Kolko's perspective.

Making meaning out of data is the step you take when you've already completed a round of data collection and are working to find themes and structure to interpret the collected data.

Giving form to the data and finding patterns is messy!


Organizing and re-organizing the data reveals structures and relationships between groups of data.

From the previous example about traction, funding, and mentoring, getting to that finalized, clean, and communicable state takes time and requires an open space outside of your laptop. Kolko describes the need for using the physical format over the digital as a way to permit easy manipulation of individual pieces of data. Otherwise, hording the various pieces of collected data in a digital format imposes a file and folder hierarchy that may prevent insights to be gained.

More examples and thoughts about the design process to come in part 3 of this series.

To read the current draft of my thesis, go here.


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