Ben Farahmand: Design Research

Showing posts with label Design Research. Show all posts

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.

You may also enjoy reading:

Reflections on Design Research: Framing the Problem

This is the first post in a series of posts I'll be writing about human centered design. I see these posts as a way to help me think about and verbalize what I do by practicing and getting feedback on these essays.

I've been involved in the field of human centered design for the past two and a half years. It's a field that has at its core a meta-level of analysis and synthesis on the design process. A process that many say started at IDEO, and it's a problem solving technique that has greatly shown its impact in Silicon Valley. But there a other design firms, like frog design, which also demonstrate a similar design philosophy.

The design research process is about creating new wisdom for the purpose of designing tools that solve problems people face as they go about their lives and perform their jobs. I think the most important part of the design research process is to figure out how to frame the problem, because in the end, the solution will closely follow the description of the problem. Looking at design at this high level, there are three parts, framing the problem, prototyping a solution, and oscillating between the two states of framing the problem and prototyping a solution.

I've come to understand design research as a way to learn about the world and make sense of the human experience by fashioning and fabricating tools that can probe and structure the information observed about the world. I'll use examples from my thesis to demonstrate and illuminate design research in practice.

One place a human centered designer can start is by performing ethnographic research. This can take the form of interviews, surveys, shadowing, role-playing, etc. One application of ethnographic research is to understand a community, a person, a market, an organization, corporation, etc. This type of research will reveal the community's culture, how the different individuals comprising the culture function autonomously and interactively. This process eventually reveals a problem or opportunity that can be addressed via design.

For example, I engaged with and ethnographically researched the Philadelphia technology startup community for my thesis. I began by doing interviews, which then led to discoveries of challenges and opportunities the community faces. There were two rounds of interviews for my thesis, the first was my initial probe into discovering what the community's problems, challenges, and opportunities. The three major themes discovered revolved around a lack of funding in the Philadelphia region, the need for mentors and advisers who have been entrepreneurs, and each startup's need to figure out how to gain initial traction. The second round of interviews leveraged the knowledge I had gained from the first round of interviews, and I designed a research tool to reveal the community's perspective on resource dispersion. To move my thesis forward, I had to discover where mentors and advisers were located and how they were dispersed throughout the community. Being able to visually map data that's collected in this manner has played a key role in making new connections between information that's normally not connected.

Mapping the Philadelphia Startup Community and the Relationships between different organizations

Another example is observing startups operate and function in their natural environment in order to observe the entrepreneurial culture specific to Philadelphia. To do this, I attended and observed multiple Philly Startup Weekends, observed the Philly Tech Meetup and PSL's Founder Factory, and had the opportunity to help and observe the various startups at the 2012 GoodCompany Ventures program.

Startup Weekend, Mentor Providing Advice

Doing this aided in understanding that mentors/advisers and entrepreneurs can serrendipitiously meet or have planned meetings; eventually, realizing how mentors and advisers may serendipitously interact with entrepreneurs and how mentors and advisers trust and identify each other. At this step in the process, I was finally able to frame the problem for my thesis and I could begin prototyping different solutions (Request for Mentoring, Mentoring Progress Report, and Mentoring System). Also, at this point in my thesis, my thesis began oscillating between prototyping solutions and reframing the problem as I continued to learn from the prototypes I tested.

The next phase of research for my thesis was understanding what goes on during a mentoring/advising session and what goes on before and after the mentor/adviser and entrepreneur meet face-to-face, which eventually will lead to a mentoring system that will benefit entrepreneurs, mentors/advisers, and the organizations that provide mentoring/advising.

You can explore the current draft of my thesis here.

Read the next post in this series here.

You may also enjoy reading:

Design Research: The IDEO Way

The design firm IDEO has been leading the market for the past decade or so. They've perfected their design research methodology and gained a unique position in their market (http://www.businesslistening.com/ideo-product-innovation.php). Design research picks up the ball where conventional research methods fail. Traditional methods compare new ideas to those of the past, and accordingly, it filters out the truly revolutionary and disruptive ideas. These are the ideas that cannot have their economic values directly measured because nothing else like it appears in the market place. I'm assuming most people have heard of conventional research methods like focus groups, data mining, trend analysis, etc. So I'll jump right into the nitty gritty of design research.

Design research insists that the entire group, from engineer to marketer to manufacturer, become intuitively understanding of the product or service being provided. This research process involves the entire group in the brainstorming session. This inclusive methodology paves the way for a holistic perspective and approach to the development process of the product or service (http://www.businesslistening.com/ideo-brainstorming.php). I think the common vocabulary built up by the group during these brainstorming sessions actualizes a lens for the research to be filtered through. The design research that's undertaken will then fall into three categories: generative, evaluative or formative, and predictive (Informing Our Intuition: Design Research For Radical Innovation by Jane Fulton Suri).

-->

Generative design research involves looking to the world around oneself in order to find experiences, patterns, and opportunities that are conducive to innovation. For example, Jane Fulton Suri observes the thoughtless acts people perform in their day-to-day life. She observes the group conformity of placing empty paper cups on a counter only because a few others have conveniently left their cup. Walking along a line on a sidewalk and wrapping our tea bag strings around a cup handle are thoughtless acts that spark innovative opportunities (Thoughtless Acts by Jane Fulton Suri, see also: http://www.thoughtlessacts.com/). Evaluative or formative design research is the continual learning that goes on throughout the entire scope of the project. As new information pours in while the group brainstorms, prototypes, and observes, remaining open to this new information furthers the holistic understanding. Evaluative research can be done in tandem with or sequentially between generative and predictive research. It creates a constant flow between different research methods. Predictive design research considers the business viability of the product or service. If the product or service is truly disruptive, it probably doesn't have a predefined market. This means that “there is tremendous pressure to provide estimates of business potential to guide decision making” regarding the innovation (Informing … Innovation by Suri). The innovation's potential will become clearer as the development team undergoes several iterations of prototypes. The information learned about the deliverable should then be used to further refine the groups intuition. This sets the group on its next iteration of the design process (Figure 1).

IDEO and similar design firms have been destigmatizing intuition as a reliable innovative tool. As undirected as intuition would seem to be appear, it is supported by design research and funneled by the common vocabulary of the group.

It all begins with our cyclical design process

Figure 1: Courtesy of MiD (http://mid.uarts.edu/program/process).

You may also enjoy reading: