Do you face the challenge of describing study results to audience members with varied levels of familiarity of the topic at hand? Do you wonder how best to present your analyses when some individuals have sophisticated understandings of the methodologies employed, and others are interested solely in findings and recommendations? One piece of advice to successfully navigate the disparate needs and expectations of colleagues and stakeholders is to make data relatable by sharing the stories of the data before
focusing on the actual data.
This suggestion was offered by Lee LeFever, founder of Common Craft and author of The Art of Explanation, who spoke with eAIR about ways in which institutional researchers can make data and analyses easier to understand while maintaining defensibility.
Lee offers advice for institutional researchers about explanations, data, and reaching every member of the audience.
The Difficulty of Achieving Clarity
Like anything, clarity can take a number of forms. To a scientist, for example, clarity may come from testing a hypothesis and understanding the key data. To an accountant, it may be through a balance sheet. For a journalist, it may come from primary sources. On an individual level, achieving clarity is something we can do with confidence.
The problem occurs when it’s our job to share that clarity with others. This requires a change in perspective because clarity relies on communication more than data. The clearest data in the world may be useless if they’re not communicated in a clear and understandable way.
Unfortunately, when an idea is clear in our minds, it becomes difficult to imagine what it’s like to learn the idea for the first time. We find it easy to assume others understand the language and examples that work for us. The Heath brothers, in their book Made to Stick (Random House, 2007), call this the Curse of Knowledge. Our knowledge can cause us to make incorrect assumptions about the knowledge of others, and when our assumptions are wrong, something detrimental happens—our audience begins to lose confidence and tune out.
We can work toward more clarity by realizing that we’re cursed, and must think differently about the audience in order to relate information in a clear manner. We have to empathize and try to imagine what it’s like in their shoes. This may mean taking a step back and discussing the big picture, building context, and being conscious about the language we use. It may also mean thinking through how to build confidence step-by-step so our audience stays engaged.
Less is More: Removing Details to Improve Clarity
Nearly everything in explanation is circumstantial. There isn’t a specific formula for knowing what details to remove because every situation and audience is different. However, from my experience, less is often more.
The key to selecting the right details is to consider your goals. I advocate the goal of understanding—of intentionally crafting your communication to be understandable to your audience. This is fundamentally different from making it 100 percent technically accurate and defensible. When understanding is the goal, you can work more in the abstract. You can present big, reasonable ideas and invite your audience to see not just the data, but why the idea makes sense or why they should care. Through this lens, you may find that many details can be removed, summarized, or exchanged for analogies or stories that help make the data more useful, interesting, and above all: relatable.
Maintaining Defensibility with Less
It’s a horrible feeling to have someone you respect poke holes in information you present. Maybe the head of your program questions an assumption you make in a paper. Maybe the chair of the board calls you out for missing an important detail. We’re wired for avoiding these situations and are rewarded for presenting information in a way that is defensible and technically accurate. We learn to achieve
defensibility through data and details. We cover every base because in much of life, defensibility matters.
But this need for defensibility can also be a problem when your job is to make an idea or data understandable for someone who is hearing it for the first time. Unlike your program director or the chairperson, these people have very different needs, and your perspective must change if understanding is the goal.
Sometimes this involves a trade-off. To be understandable to an audience of curious learners, you may have to give up a little technical accuracy. You may have to skip some details that seem important to you in order to provide them a way to see the big picture and feel confident.
You can think about it this way: your goal is to make someone care about your ideas. Until they care, the details and data won’t matter. They won’t know enough to poke holes. A focus on understanding becomes the priority. Once they understand your idea, they’ll be motivated to keep learning, and that’s when you can really show them how great an idea can be—and how defensible it is.
The Diminishing Return of Information Overload
From the perspective of a researcher, the truth is in the data. By sharing the details of the data and accounting for exceptions and confounders, for example, researchers can present accurate and useful information that stands up to the questions and analyses of their peers.
Within the insulated world of research, this can work and can be rewarded. But outside of the research world, a different perspective is required. The audience is typically not in a position to poke holes in your assumptions. They don’t necessarily care about the exceptions. They only want to understand why they should care. Details won’t help this audience.
Ask yourself this question when you’re communicating data: Is this information for my peers or for another audience? If it’s another audience, you must switch gears and realize that more details and data come with diminishing returns. Different audiences have different needs.
A Perfect Use for (Imperfect) Analogies
Sigmund Freud famously said, “It is true, analogies decide nothing, but they make one feel more at home.” I love that quote because it recognizes the inherent problem with analogies—they are imprecise. It is rarely possible to find an analogy that stands up to the impeccable standards of many researchers. But are they useful and powerful in relating ideas? I think so.
Consider some of the great scientific discoveries, like Einstein’s theory of relativity. In my experience, there are two ways to understand it. The first is to have an education in physics. With the proper training, we can see the theory’s details at work. For physicists, this is likely the most powerful way to understand it. But everyone else requires something different—the details don’t work.
Thankfully, Einstein often used an analogy that provided a layperson an imprecise, yet useful way to see the big picture of relativity. The most famous is likely the train analogy, where relativity and simultaneous events are explained using people, lightning, and trains—all real and familiar things. This provides a way for non-physicists to develop a basic, yet imprecise understanding that could lead to more learning.
While you may not need to explain relativity, you may find that simple, familiar examples and analogies can be used to help your audience see why data matter and why they should care.
Lee LeFever will speak at the 2014 AIR Forum in Orlando, Florida. Visit the Common Craft website for more information about Lee, the work of Common Craft, and The Art of Explanation. Interview by Leah Ewing Ross.