Make Data Talk - with Dr Selena Fisk

Hi, I'm Dr. Selina Fiske, and welcome to this episode of Make Data Talk. In this podcast, I help you turn your spreadsheets into stories in a way that's practical, accessible, and hopefully a whole lot more useful than your grade nine maths textbook. This week, I'm going to really kind of cover a topic that's coming up a lot in my world at the moment, actually. I guess we can have the data, we can have the processes, we can have the systems in place. But for me, this one thing is coming up as almost the key determinant as to whether or not an organization is actually going to use data well and individuals are going to use it well and teams are going to use it well. So yeah, let's just jump into it. So there are plenty of moments in our working life where, you know, the data is available, the dashboard's been built, the report's been circulated, the meeting agenda, you know, might include time to discuss the findings and yet very real or very little real learning actually happens. You might have people doing busy work, like they might be looking at the numbers, they might comment on the movement, they might notice whether something's gone up or down. You could have people in that conversation who offer possible explanations. Sometimes that happens quite quickly without deep thinking and I guess discernment. And a group can kind of sometimes move towards action before they've really explored the meaning of the data and considered lots of different options. So on the surface, or if you were kind of watching this happen, the conversation might appear quite data-informed because it's present and they're kind of talking about it, but this is not the same. Being just data-informed and having it is not the same as rigorous thinking and engagement with the numbers. Curiosity is often spoken about as though it's kind of a personality trait. So it's something that we either have naturally or we don't. We imagine somebody who's curious as somebody who deliberates, they ask questions, they ask really good questions, they might read widely, explore different possibilities, and they resist kind of the first answer. And all of those things are kind of true, of course. There are definitely people who are more curious naturally than others. But in our workplaces, and when it comes to using data, curiosity is not just an individual kind of disposition that people either have or they don't. It's actually also a cultural condition that our leaders have a really significant role in, I guess, cultivating and determining whether or not it's allowed. We have a lot of influence over whether that curiosity is able to and encouraged to grow or whether it's squashed. When leaders engage with data, they're rarely just interpreting information. They're also standing up in front of people or sitting down in front of people, and they're actually implicitly modeling how we use data in this work and what data is for in this organization. So what we're doing in that kind of, or what leaders are doing in that example is they're directly and indirectly teaching people whether data is something that they should defend against, whether it's something we should just comply with, whether it's something we use as proof or whether it's something that we genuinely learn from. So the questions that our leaders ask, the speed and how quickly they move to judgment, the tolerance and flexibility that they show for uncertainty and the way they respond, especially to like really inconvenient or disappointing data, those things all become really clear signals to the people in the room about what's accepted here and I guess how we perceive and use data in this workplace. Over time, those signals shape what people believe is safe, valued and expected and it absolutely influences how they then engage with data in the future. So if a leader's looking at some disappointing results, for example, and straight away say, you know, who's responsible for this? Or who can tell me what's happened here? The people in the room are going to learn something really clear. On the other hand, if the leader says things like, what do you think could be contributing to this? And what do we need to know more about? Or what are some other data sources that we could use to tell us more about this phenomenon. The people in the room and in that conversation are learning something totally different. Both approaches have really different connotations for the workplace and for employees, and as a result, really different consequences. The first, and I guess that really negative frame, can create a sense of urgency for staff, but it can also really narrow conversations before we can come up with really useful outcomes. In these conversations, people become quite fearful. They can become quite careful. They might explain what's happening, but ultimately they're going to want to protect themselves because there's almost an attachment to accountability. They might be sharing interpretations out loud, but they're going to be choosing the words really deliberately and they're going to be suggesting things that are less risky for them. But on the other hand, when a leader goes in with real curiosity and an openness to the conversation, there's a different kind of space that's opened up. Accountability is not removed completely, but it puts that kind of accountability and ownership of the data in relationship with understanding of what's going on, consulting multiple data sources, and ultimately the context that these numbers and these metrics are coming out of. So what it's doing for employees is that it is suggesting that the leader's not just interested you know in the result but in the conditions the assumptions the behaviors and all of the decisions that sit around that that helped produce that outcome so that distinction is really important and it really matters because data rarely speaks in a really black and white way in the you know in the simplicity i guess that we sometimes wish it would a metric might show decline over time or increase over time, but not explain why or the cause of that thing. A dashboard might show real variation between maybe a quarter or different metrics or different teams, but it's never going to fully unpack or explain the context. A target could have been met, like we could actually achieve a KPI, but actually that KPI is masking something that's really important that has been weakened or I guess negatively impacted along the way. So it's, I guess, a reminder for all of us that data is giving us signals, but those signals have to be interpreted by us. And curiosity in my world and in my perspective is the discipline that keeps that interpretation really honest. Otherwise, we can make some of those assumptions and jump to conclusions too quickly. Without that curiosity, what I see is that data becomes really performative. And I've worked in an organization like this before. You might have worked in one too where you know data's gathered because air quotes it should be collected it's reported because people expect a particular report at a set time we discuss it because it's on the agenda and we've said we'll talk about it but the deeper work of wondering being curious testing assumptions looking for context cues allowing the evidence to kind of complicate what we thought we new. All of that's completely avoided. So I guess on one level, there might be data activity and there's busy work happening, but absolutely not data maturity in the use. So curious leaders do something really different. They don't treat that first interpretation and thought as if it's the final one and if it's the be all and end all. They resist the temptation to make the data tidier than it maybe really is. They step away from that black and white perspective and reality. They're willing to ask kind of what else could be true, what might be missing from here, what might or who might see this pattern differently, like who else do we need to bring into the conversation and what is the data maybe not telling us. They understand that curiosity isn't actually delaying the process. It's also not delaying a decision, but it's a really key part of how better decisions are made. So obviously, this doesn't mean that every data conversation needs to become endless or theoretical. We still need to make decisions and we still need to act. But when curiosity is non-existent, we often decide on actions that arrive way too quickly and we haven't done really deep thinking about it. And therefore, the solution or the action or the next step is going to be an incomplete action. It might be something that we can pick up and run with quite quickly, but it may not be the best thing that we could have chosen. So in those kinds of, I guess, ways of working, what we're doing is we're responding to the visible symptoms rather than maybe leaving the deeper patterns untouched. So again, as leaders, this is why what we've got to do is model this curiosity through our work and why it's so, so important to the overall data culture in the organization. Obviously, like the reality is, is that our employees pay attention to what our leaders do, especially when the data is uncomfortable. So if there's an icky, uncomfortable conversation to be had about data, employees are going to be looking to their leaders to see, you know, are they becoming defensive? Are they looking for reassurance? Are they opening up the conversation? Are they really welcoming evidence that, you know, maybe confirms the existing strategy or are they actually okay to sit in that gray area and in the complexity long enough for, I guess, more truthful conversation to emerge. Employees are watching and what they're doing, maybe not explicitly, but they're thinking like, are we, you know, while we say we're data informed, does that mean bring me the numbers and you better hit your KPIs or does it actually mean we want to have open, honest conversations about understanding our reality more clearly, even when that reality is really inconvenient. So that kind of modeling is really powerful. Curiosity is socially contagious and so is defensiveness. And again, I've worked in both of those contexts and I'm sure you have experience of one, if not both. If leaders aren't willing to ask genuine questions, then people are really unlikely to feel free to ask genuine questions also. If leaders treat uncertainty as weakness, people will learn to hide their uncertainty. If leaders reward, you know, really polished clarity over thoughtful interpretation, that's what they're going to get, even when the situation calls for something much more considered, careful and discerning. So it's not about just as leaders encouraging people to ask more questions. It's actually about us building environments where those, where a range of questions are encouraged and asking questions is safe, it's useful, and actually it's expected by the leader. It does mean allowing a bit more time for discussion, interpretation, and not just reporting, but it means that we make better decisions and are more likely to choose actions that are aligned with actually where we need to go rather than kind of that quick fix or that quick solution. It also means protecting people if they surface inconvenient truths. So if we want I guess, an openness around curiosity and different perspectives to be heard. We've got to support people who raise those inconvenient truths. So, yes, they might ask hard questions and that slows the meeting down, but we actually need to encourage that. Otherwise, you know, if we don't, then people are going to stop bringing those things up. They're going to stop volunteering that information and that perspective if they're seen to be shut down and it's moved on pretty quickly. So if we want people to use data well, we need them to be able to wonder out loud or aloud. We want them to be able to do things like notice the patterns without immediately defending why that's happening. We want them to be able to test assumptions without kind of feeling disloyal to their team, their leaders, the exec or the organization. We want to encourage them to say things like, you know, this is really interesting, but I don't think we fully understand it yet or we need to do a bit more testing or we need some more data and we also want them to be able to ask questions like who's missing from this data what other data could we collect that would tell us a bit more what could this data be hiding or what might we expect to see if our interpretations are wrong so these are the types of rigorous questions that stop us and prevent us from kind of confusing movement with progress or avoid jumping to there's two decisions and actions that haven't been deeply considered. So I kind of mentioned this before, but curiosity is not separate from accountability. We're not saying that we're not holding people accountable. I guess the flip of that is that I believe that curiosity actually strengthens accountability because a curious leader is not avoiding responsibility by asking better questions. They're also taking responsibility themselves for understanding the situation properly before acting on it. They recognize that decisions made from thin interpretations might be fast, but they're not always wise. So the real test then for me and what I guess I get to see from my perspective is it's not whether or not leaders say on the surface that they value curiosity. I mean, most leaders would. For me, the more important test is what's actually happening in those conversations. What's their behavior when they're in front of other people, signaling to the people that they work with. And especially in those tricky conversations where it matters, is curiosity encouraged and made possible for other people in their team? Thanks so much for joining us on this week's episode of Make Data Talk. As always, you know, Algo loves a cheeky like, a review. And if you want to sign up to a newsletter on my website, it's at selenafisk.com. Thanks for listening.