Making Sense of Synthesis

Man with face covered in sticky notes

Of the hundreds of South Park characters created by Trey Parker & Matt Stone, the Underpants Gnomes are my unquestioned favorite. The Underpants Gnomes have a plan for profit that they proudly explain to the boys:

South Park underpants gnomes profit plan

It reminds me a lot of the way many people look at how to work with research on an innovation project: We’ll do a bunch of research and the answer will hit us like a lightening bolt in the form of insights. After all, Newton discovered the theory of gravity after an apple fell on his head, right?

Reality is much closer to the concept of the slow hunch Stephen Johnson describes in his book, “Where Good Ideas Come From.” He says that breakthrough ideas almost never come in a sudden stroke of inspiration, and most great ideas actually take a long time to formulate. In fact, Newton’s theory of gravity likely developed because of the years he spent studying the works of Galileo more than anything else. There is much evidence to suggest that Newton greatly embellished if not entirely fabricated his story about the apple.

It’s perfectly understandable why people like to talk about identifying a great opportunity or coming up with great insights as a lightning bolt hitting them. It’s simple. It’s easy to explain. Unfortunately, synthesizing data to recognize a great opportunity is neither.

Digging into all the information from research can be intimidating. There is a ton of data and disparate forms. Knowing where to start is difficult. If you ask people who’ve done this before, you’ll be instructed to “stew with the data,” “marinate with the information,” or simply “wade through it.” All extremely accurate of the immersive feelings associated with synthesis but not particularly helpful in telling you how to dig in or where to start. At that point, all you have to look at is your end goal—identifying an opportunity of that mess of notes and videos and pictures and completed exercises that’s lying on your desk or in your project room. It’s understandable if a grim feeling starts to sink in.

At this point, it’s best to heed the advice of a man who quite probably has never engaged in any type of data synthesis in his life—Mark Twain:

“The secret of getting ahead is getting started. The secret of getting started is breaking your complex overwhelming tasks into small manageable tasks, and then starting on the first one.”

Viewed in this context, breaking down data from research to identify opportunities becomes a series of simple steps that are nothing more than telling stories and making connections.

Task #1: Telling stories of the individuals

Start by telling the stories of the people you met, one at a time. What did they say? What did they do? How did they act? What did their home look like? Be detailed and specific. Stick only to what happened and try to avoid what it means. Simply capturing “what” happened—ideally on Post-It Notes—you’ll have the “pure data” you’ll need in the form of observations.

Task #2: Make connections between the interviews to tell the story of the group

You’ll find similarities and patterns emerging after telling the stories of a few individuals. One of the easiest ways to do it: simply arrange the Post-It Notes into groups and clusters. For example, perhaps you were working on a project about drinking beer. You could create clusters of moments where they drank beer straight out of a can, straight out of a bottle, or chose to pour it in a glass. You might notice that glass drinking happened more often at meal time. These clusters become the core insights that act as the things that both tie the group together and become the foundation of the interview.

Task #3: Make connections between the core insights and your project objectives

The first task has given you a strong grasp over “what happened” in the form of observations. The second task has helped you understand “what it means” in the form of insights. The job now is to identify the opportunity, which is really figuring out “what it means for your project.” This means looking back at the objective for your project and making connections between the insights you’ve uncovered. Some of the insights are merely interesting and have less of a connection to the problem you are trying to solve. Others are more directly linked to your objective. These are the building blocks for your strategy. Additionally, you should have also developed a strong sense of empathy for the people you’ve met throughout this process. You should be able to think like them, to a degree. This is your opportunity to put your empathy to work to identify the real problem. Ideally, this comes in the form of a question to be solved during ideation.

Synthesizing data from research can be a daunting task if viewed in its entirety. It’s difficult to know where to start and how to break it down. However, if viewed as a series of steps of telling stories and making connections, it becomes much more manageable and easier to produce results.


Craig McCarthy

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Craig McCarthy

Director, Strategy