Make Your Message Clear, with Stephanie Evergreen

Dave Stachowiak (0:00)

Data, we've all got access to tons of it these days, but perhaps almost too much. How do we actually make sense of it and then communicate clearly with it? In this episode, how a leader can best use data to make their message land. This is Coaching for Leaders, Episode 800

Stephanie Evergreen (0:20)

Produced by Innovate Learning. Maximizing human potential.

Dave Stachowiak (0:29)

Greetings to you from Orange County, California. This is Coaching for Leaders, and I'm your host, Dave Stachowiak.

Leaders are born, they're made. And this weekly show helps leaders thrive at key inflection points. I know one of the things that we all have on our mind is our messaging. The messaging that we have in our conversations, in meetings, in influencing stakeholders, and how do we make our messages clear as possible. Today, I'm so glad to welcome an expert who is so effective at helping people and organizations to do this well, and also effective at helping us think about the big picture and some of the nuances behind making our ideas clear. I'm so pleased to introduce Stephanie Evergreen. She is a data visualization and design expert, and has trained future data nerds worldwide through keynotes and workshops for Fortune 500 clients like MasterCard and Facebook, and Mission Aligned clients like the UN Boys and Girls Club, AARP, and the Alaska Native Tribal Health Consortium. She has three books and a popular blog on data visualization at stephanieevergreen.com.

Stephanie, such a pleasure to have you on the show.

Stephanie Evergreen (1:40)

Thanks, Dave. I've really been looking forward to this conversation.

Dave Stachowiak (1:43)

Me too. One of the reasons I've been looking forward to it is because I've been thinking so much about your work and how we all have this, I shouldn't say all, but a lot of us certainly have this desire to make our messaging really clear, especially when it comes to data and information. I was struck by something that you wrote in a blog post. It says, I've listened to everyone from data analysts to CEOs lament that they're up to their eyeballs in data, but it isn't effectively used to inform decisions and actions that increase performance.

I thought about that and was thinking, wow, how I hear that a lot too from leaders and stakeholders. I'm wondering, what do you see most often when you see people running into that and struggling that with it would just overload?

Stephanie Evergreen (2:39)

This is a good question and a common problem. I think that the reason we got here is different for the different employee group that we are talking about. In my experience, my background is in data. I used to be the analyst kind of person, and we are trained so deeply to understand data and the context and how to read charts that we can see a chart and immediately read into it and pull out the story that it's trying to tell.

But our audiences do not have that kind of background. Our audiences aren't knee deep in the data every minute of the day, so they need a little more help. They need us to explain the story that we think should be evident to everyone else so that they can understand it. So we see that we have decision-makers. Sometimes those decision-makers are the public, sometimes it's the analyst's boss or the boss's boss, and we're talking to the decision-makers that are in the C-suite. But those people need the data to be translated a little bit, so that the things that the analyst thinks are evident are actually articulated.

Dave Stachowiak (3:47)

One of our fellows, Jess Britt, is a big fan of your work and introduced us originally.

She was talking with me about some of your work, and she made the point to me that a lot of us got trained in school, in graduate programs, in formal trainings, where the mantra in the academic world is you put all your data out there, you share it with everyone, then you put it out and you let people pick it apart and review it and come to whatever conclusion they're going to come to. And I think it's just really interesting how it's so different in the workplace. Nobody has the time and bandwidth to really do that. And so it's this really interesting disconnect for where a lot of us were trained and then what actually works in the context of an organization that's trying to do work.

Stephanie Evergreen (4:41)

I completely agree with you. And I think when you come from an academic background in data, you're actually told you can't make a point and that you'd be biasing your audience. If you were to tell a story that is in the data set. So it is actually the exact opposite of what we want to see when we're in the workplace and people with deep data backgrounds have a hard time making that kind of adjustment. I was just talking to a reader who told me that she's actually seen this used in court cases where people bring up research and academic literature that doesn't ever draw a conclusion and always says we will always need more research to ever be able to say something definitive about this and they've used it to say see even academics don't think that such and such a thing is true. So this like academic habit of hedging is harming us when we're out here in the real world.