#49 What if you have an epic data story but you're worried people in the meeting won't get it?

Hey, I'm Dr Selena Fisk and welcome to this episode of Make Data Talk. In this podcast, I help you turn your spreadsheets into stories in a way that is practical, accessible and hopefully a whole lot more useful than your Grade 9 maths textbook. I was presenting in Adelaide a couple of weeks ago and my mate Paul, yep, you're getting a shout out Paul, said to me, "I've got the data storytelling arc. He's done a lot of work with me over the last couple of years." He said, "I need some guidance. What if I'm trying to present that data story to a team or in a meeting and the people that I'm working with have really mixed ability?" And I thought, "That's an awesome question." And it's a great reason to record a podcast and to write a newsletter. So I'm going to answer that question today. So what if you've got an epic data story, but you're worried that people in the meeting may not get it or that some people won't and maybe some people will? I guess what we know and what we read online is there's a lot of information available and I've produced a lot of resources around how do we actually construct a data story? How do we do that? Meaningfully, how do we do it impactfully? How do we ensure that we're collecting the right visual, the right data and the right narratives that really kind of shape that data story to land with the audience? And that's really hard. It's really tricky and it's an important skill that we all need to learn. Because that's only going to work if your audience are receptive to the message that you're telling them. And obviously, when I do my data storytelling training, I'm constantly talking about, think about your audience. What do they need to hear from you? What context do they need included? What explanations do they need included? All of that's really important. But the reality is is that we're going to have people sitting in front of us who work with that data all the time and understand it really quickly. We're going to have people who are maybe reluctant to use the data or haven't seen that type of information before. And they're maybe struggling or people who are struggling with it. And we've got to be able to cater for all of that difference in that meeting time and make sure that the message lands really well for all of them or as many of them as possible. That's probably more realistic. So look, I'm not going to offer you a step-by-step process because I feel like the step-by-step process for me is in my data storytelling process and training which I've talked about before. But what I am going to give you is some step, I guess not step-by-step, sorry, I'm going to give you some broader principles to think about. You know, a couple of principles to think about, well, how do we actually approach this and what do we need to be mindful of rather than a step-by-step like do this, then do this? So I'm going to give you 10. So let's go. Principle number one. We have a lead with purpose, not proof. So I guess really start that meeting with the decision that you're trying to make. So don't lead with the data, lead with the reason why you're going to be sharing data with them. And it's, yes, Simon's Neck talks about the power of why and there's the golden circle and all of that. And it kind of, that's what we're doing. But we want to be connecting to the why to the purpose. We want to be getting their input during the meeting. The whole point is not just this, you know, brain dump of different charts. We actually want to have a reason for this conversation. So you might say things like, you know, by the end of this meeting, we want to be deciding this or we're going to use the data today to make a decision between or a choice between this and this. Or we've all been talking about this being an issue lately. I'm going to show you some of the data we've got about that and we want to be making a decision about what to do. So don't just throw the data at them to begin with, connect it really clearly to the purpose. You could even get people to kind of weigh in on things that they've seen or that they've noticed before you even start showing them the data. Principle number two, we want to make clarity a respected contribution. So when we have people who don't really understand, you know, as well as they might, they're not always going to be super confident and confident enough to actually name that. So what's more likely to happen is they're more likely to go quiet, they go a bit underground and they'll sit there quietly, kind of not understanding what's going on. So during the meeting, I want you to think about how can you really actively elevate clarity questions as valuable, you know, you want to be encouraging them to ask questions. We don't want to be making this embarrassing. We've got to be normalising the asking of questions and seeking clarity. And so, you know, say things like, look if something's not clear, please ask, our decisions are actually going to be better, the better you understand this data. You know, if you're asking plain language questions, it's a sign that we're doing this properly. You know, it's the whole, there's no silly questions here, but, you know, don't say that as a cliche, genuinely mean it. But we've actually got to respect people seeking out clarity because we've got to get that point that they're able to engage with decision making really meaningfully, rather than them getting caught up with the numbers. And that's obviously what we want to get past. So we've got to explicitly say that. Principle number three is we want to be separating the understanding from interpretation. So we've got to, I guess, separate the data from the interpretation and the conversation about what it means and then away from, like, separating it again from what are our possible actions and then what are we going to do? What I've seen a lot of teams do in meetings like this is they jump to the explanation or the excuses and they can jump to the interpretation. But you've got to guide participants through really deliberate sections of the conversation. So let's first look just as objectively as we can at what we're seeing is happening. Then let's talk about what we think it means. Then let's talk about what options we have for acting and then let's make some decisions on it. And so really siloed deliberate sections of the conversation will mean that people kind of hopefully stay in their lane, but the reality is they probably won't, but it allows you to bring them back to the lane they should be at that time. What it also allows you to do is to get them out of that lane and progress the conversation because we also know that teams can get really caught up in the interpretation and not get to the action piece. And as the person leading the data story or leading them through this, we've absolutely got to be the one that's getting them to that stage of, you know, the so what. Otherwise the whole data sharing has been probably a bit of a waste of time. Principle number four is obviously we use plain language and this is something that I talk about a lot in my, you know, in my training. But essentially if you can't explain it simply, you either don't understand the data well enough yourself or you don't actually have a really important message that you know you have to share. So using plain language isn't dubbing it down. It's actually a signal that you understand this really well and that you're trying to make it accessible to everybody in the room. I'm involved in a business school and the founder of that Matt Cher, Cheen courage is us to think about our intellectual property and the ideas that we kind of share with the world. And he says, how could you explain it to a seven year old? How could you explain that thinking to a seven year old? Now that's not being disrespectful to any of the adults we're working with. But you know, it's ensuring that we've actually have to clarify our understanding to the point that we can make it accessible to that level. And it's similar to the quote you might have heard, you know, I would have written you were short or let up, but I didn't have time condensing our understanding and being super concise and clear with our language is actually going to support the process. It's going to support people regardless of their ability to engage and tap into that conversation. Principle number five, and there's a lot here, but principle number five is to reduce the cognitive load of the participants. And you can do this in a number of different ways. You know, through the data storytelling process, we know that we reduce cognitive load by reducing the number of visuals that we choose to show by designing our presentation for the brains that we have in our meeting. It could be that we select, you know, only one or two different charts and we talk about those. Maybe it's one or two ideas. It's a master message. You know, if you've got people walking into that meeting and they're easily distracted, maybe they're pressed for time, maybe they're walking in at the end of a day after really a really intense day where they're exhausted, you're going to need to make some significant changes to how you do what you do. So we know that if that, the people in that meeting are working too hard just to interpret the chart and the meaning of the chart, they're not going to be able to then engage with the higher or thinking of the interpretation, considering options and making decisions. So we want to help them get there as easily as possible and use their brains for the great stuff like, you know, the what are we actually doing with it? Principle number six is to narrate the chart. So don't just put the chart up and let people, I guess, work out what you hope they establish from it. Talk about it. So when you're designing your charts, you could do things like, you know, putting the title, changing the title, maybe to the trend or insight you want them to see, you can get them to, you can highlight the relevant bar or line in like a color and make everything else gray scale. There's lots of different kind of visualization techniques that you can do that make the trend or insight easier to see. And then you're going to narrate it. So you want to say, look, here's what you're looking at. Here's what I'm seeing that I think is the most important. Here's what I'm thinking is it means for us. But then let's have a conversation about what you see and what your interpretation is. So don't just let them start from zero, narrate it. Obviously, when people have better skill and capacity, you can let them kind of start. But if they're maybe struggling and you have a lot of people who are lower skilled, lead the conversation for them. You're supporting them by doing that. And again, you're coming from this place of, look, this is just the stuff that I see. This is what I, deemed to be most important. I could be wrong. It's just my opinion. What do you think? Principle number seven is that we really want to normalise any uncertainty and limitations of the data. So people will often jump to reasons why the data is not valid or why it doesn't tell us the whole story. And we're not trying to, we're not trying to say that. So we've got to normalise that. And in the moment, we might say things like, look, here's some of the assumptions we're making about the data. Here's some of the factors that could be impacting this data or distorting it. Look, this is suggesting this, but it doesn't actually answer this. And so, I guess fill in the blanks for how you kind of do that. But it's just naming the fact that no data set's going to be perfect. It's never going to tell us the entire story. And so, therefore, we have to, I guess, think about it critically and have that conversation. And I'm flying through these, but I've got three to go. So let's just keep rolling. Principle number eight is we want to protect the airtime in the meeting so that confidence doesn't equal influence in the meeting. So we know that the people who are the most confident and the most skilled in data are probably going to be the most vocal of the loudest because they're the most fluent, right? It's not their fault. I know I've taken that kind of space in meetings with the best intentions, but it's because I'm confident doing it. And sometimes that person is in a position of responsibility or power sometimes they're not. But I guess this point's really got me thinking about Pat Lentio. And he talks about the dehippo, the highest paid person's opinion is often the person that we hear from the most. And look, that's, you know, it's not a character floor. It's just how groups behave. And it's how leaders behave. But as the person rolling with the data story and running it, you've really got to be thinking about how do you incorporate all the voices? If they're if they're important enough to be in that meeting, giving up that time to be with you, then you want to hear from them. So it could be that you give them a little silent read of the data before you start any discussion. You might get them to talk with their partner first to talk about what they think they've seen. If you have people who are dominating the conversation, say, right, I want to hear from some of the people that we haven't heard from yet. We want to make we need to make people feel included. We've got to amplify those voices of those quiet people who maybe aren't as engaged, because otherwise to be honest, they shouldn't be in the meeting if they're not contributing. So, yeah, it's your role to really activate them and really tap into that resource. Principle number nine is we know and we've talked about this before. We've got to offer options, not a single right answer. We know data is rarely a verdict. It's usually not something that says this data says this X so therefore we have to do this Y. It's a prompt. So sharing data in a meeting is a really great opportunity for you to look for actions next steps, consider different perspectives. Ask things or say things like, I'm seeing this and this is what I'm thinking, but in your role, what do you reckon is the most urgent and important for us to do? What's the action that you think we should take given your experience in your role? What haven't we considered? What are some of the benefits and risks of this possibility? Invite participation and again, ask and hear from those people, maybe you haven't heard from, so that you're building almost a bank of possible actions and ideas and options. You're not just jumping to the one. The final one, principle number 10 is make the decision really explicit and testable. So we want to be leaving with really kind of clear understanding of what we decided, who owns those next steps, what you're going to kind of measure and look at after the decision because you want to know whether or not you've been successful. And so the data or the insight isn't the end of this conversation, it's the next step. How are we coming back together to re-evaluate this? How are we coming back maybe with more data or future data to work out whether or not we actually did what we had hoped? So it's a bit of a longer episode today and I know that I've gone through a whole list of 10 different principles, but just as a reminder, I guess all this information is available on my sub-stuck newsletter and also in my LinkedIn newsletter. So if you need the text of this podcast episode, it's available there. I'd encourage you to go and have a look. But I hope that these principles have kind of helped you think about when you have a mixed-ability team, how do you have that conversation so it's more likely to land? And massive shout out to Paul from Adelaide, who asked me this great question in a session a couple of weeks ago. The kind of prompted this newsletter and this podcast for this week. So thanks so much Paul and for everybody else, stay safe and look after yourself.