Storytelling Through Data AnalyticsQ&A with Mico Yuk, chief data evangelist at Count and keynote speaker for the 2022 SOA ImpACT Conference September 2022
Although there is so much data available, it is a constant challenge to make use of it. Distilling data into a compelling story and then communicating it can be daunting, yet it’s a worthwhile application of actuarial expertise. Storytelling using visuals and narratives to communicate insights from a data set is a key skill vital to fostering decision-making and motivating actions.
Mico Yuk teaches the verbal, written and visual art of data storytelling to drive action and create business value. She is the chief data evangelist at Count, a London-based hyperdata collaboration platform, and creator of the BI Data Storytelling Framework. As our keynote speaker for the 2022 SOA ImpACT Conference, Yuk will share three key techniques to kick off your data storytelling journey.
Joe Wurzburger, FSA, MAAA, CAE, SOA managing director of Strategy and Innovation, spoke with Yuk about the art of crafting compelling data stories.
How did you become interested in harnessing data for storytelling?
It comes, in part, from my Caribbean background, where storytelling is part of our everyday life. In relation to data, my desire to learn more about the science of storytelling came through my own communication issues as a young data scientist. I was very good at creating algorithms but very bad at getting people to trust my results. So, I started to dig deeper to find out why I couldn’t convince my audience that what I did was correct, and I landed on storytelling as a way to influence my stakeholders.
What really inspires me is seeing people have that “ah-ha” moment. I get a dopamine and adrenaline rush when people say, “I didn’t see that before,” or “I get it now.” And more importantly, I love when it triggers decisions or actions.
How can actuaries move away from presenting a mountain of data and get to the “so what”?
I tend to find that people spend too much time on the “so what.” Once we see people care, we should move on to facilitating decision-making. I teach people how to read nonverbal cues. For instance, when someone nods for more than five seconds—that’s one cue. It’s been scientifically proven that nodding is a sign of agreement and usually means their brainwaves are congruent with yours. The second sign of congruency is when people stop asking questions and are looking to you for what’s next. It means you have clarified what they need to hear, and they’re waiting for the next thing. This is where your emotional intelligence should kick in, which is a big part of storytelling—understanding when your audience has had enough data and analysis and it’s time to act.
How does data visualization fit in with storytelling?
The power of data visualization—also scientifically proven—is that visuals stimulate our brains in different ways. According to the science of storytelling, during the first step, people envision themselves in the story we’re telling. In the second step, they begin to develop their own ideas, and in the third step, there is a release of dopamine in the brain that helps them to remember the story and take action. During the fourth and fifth steps, the brain creates memories. So, the visual component of the story is important. Everyone who works in data knows that when you put visuals in front of your stakeholders, you get a completely different reaction than what you get from a regular report.
How can actuaries employ storytelling with reports they need to update on a regular basis?
There are two areas of opportunity here: the recap and highlighting the changes. First, there is a high chance people won’t remember what happened in the last update, so properly framing the recap is always important and a great opportunity to set the narrative.
Second, there is an opportunity to highlight what has changed since the last update. Think of yourself as a movie producer, except with data—a data producer. Let’s take superhero movies, for example. They always follow the same sequence. We have a hero, usually shy and kind of geeky, and they spot a love interest who is way out of their league. In the middle of the movie, the love interest is captured by a villain. At the end, the once shy and timid hero defeats the villain and saves the love interest. Hollywood uses this well-known billion-dollar movie storyline over and over because it works. Think about that: You can tell a story repeatedly, and all you have to do is change small elements to keep people engaged. It’s no different with data stories.
In what ways can a person communicate the meaning behind the avalanche of data available today? What are some limitations or obstacles?
Data overload is real, but there is also a lack of the insight needed to make good decisions. Seek not to communicate everything but instead highlight the data points that have the greatest impact. This is much harder than it sounds, but with discipline and a clear framework, it is achievable. Storyboarding is important because it turns you into a data optician, helping the business see its story clearly.
In terms of limitations or obstacles, the biggest one is usually data access. We have tons of data, but the “right data” is usually the challenge. Another common obstacle is culture. In some organizations, no matter how much data you have or the quality of it, some people will just not accept the results (going back to my first data science job, which I mentioned in my answer to the first question). In these cases, you need to know when to cut bait, say ignorance is bliss and, honestly, just move on.
Many actuaries also experience the opposite challenge, which is a lack of data. How does this affect data storytelling?
When it comes to the amount and accuracy of data, many companies use the principle of “good enough,” also known as GE. If you wait for perfection, you may never move forward. Instead, you can take a look at the data you have and assign a GE score. For example, when judging the accuracy of the data, is it an 8 out of 10? Or is it a 7 out of 10? At the end of the day, you have to proceed with your best estimation. If it’s GE, move forward. But make sure you have a sense of what is “good enough” before you start.
Another approach: Instead of striving for data perfection, combine data with experience and make decisions that are data-informed. Top companies, especially unicorns, are using this data-informed concept. They’re no longer purely data-driven, and it’s not just because of data gaps. They realized they have people with lots of experience, and they should allow these intelligent people to do their jobs. This is a concept for actuaries to consider: “I have graduated from being simply data-driven, and now I’m data-informed.” Look it up!
Hear more from Mico Yuk at ImpACT
Register today for the 2022 SOA ImpACT Conference Oct. 23–26 in Orlando. Join us for the Oct. 24 opening general session to see Mico Yuk’s keynote presentation. The 2022 ImpACT Conference is a premier gathering of industry employers, actuarial professionals and thought leaders—the largest of its kind. Reconnect with colleagues, advance your career, build your network and learn how to refine your data storytelling skills. If you can’t join in person, you can register for the virtual conference, which includes Yuk’s presentation.
What are some of the biggest challenges in telling an impactful story through data?
After training more than 10,000 data professionals, the No. 1 challenge I see is a listening problem. Yes, a listening problem! Data professionals are so inquisitive; when they’re working with users, they just talk and talk and talk. The second challenge is knowing the right questions to ask. Whether you’re asking questions about the data itself or asking people questions, knowing what to ask is fundamental. The third challenge is putting too much data on the screen because you don’t understand the structure of a compelling data story, which I will show during my keynote at the 2022 SOA ImpACT Conference. This has the opposite effect of what you want—triggering analysis paralysis, not decision-making. All three problems lead into each other: not listening leads to asking the wrong questions, which leads to presenting too much data.
What are the key steps to becoming a savvy data storyteller?
I have a different take than most in the industry. Often, people will say you need great visuals to tell a good story. But I believe storytelling involves three steps:
- What you ask
- What you write
- What you draw
My framework is different because I don’t start with what I want to show, getting right to visuals. I’ve seen amazing visuals that have gone nowhere because the verbal and nonverbal communication was lacking, and the story fell flat.
Step 1 of true data storytelling begins with what you’re asking—or what you think the data is telling you if it’s just you and your data set trying to derive hypotheses. Step 2 focuses on taking your hypothesis and answers and putting them on a storyboard. Step 3 is visualizing the final storyboard. Clearly, I’ve simplified this and there is a lot involved, but that is the process. The art of doing this in a way that is simple, memorable and visual is the art of data storytelling.
Statements of fact and opinions expressed herein are those of the individual authors and are not necessarily those of the Society of Actuaries or the respective authors’ employers.
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