25-minute listen

In our first episode of DigitalNOW, an original podcast by Logic20/20, Matt meets with special guest, Nick Kelly, who is the Director of Visual Analytics at Logic20/20. He will spend time look at the differences between data, data literacy, data-driven culture, and more and why we should care about each. In addition, he will take a look at how to get started within your organization, where to focus, and how to get leadership buy in. Finally, he will take a look at the top trends for 2021. Don’t get left behind!


Matt Trouville: You’re listening to DigitalNOW, an original business and technology podcast by Logic20/20. I’m your host, Matt Trouville. Each episode, I’ll be interviewing a new expert to learn more about industry trends, fascinating new tech, shifting customer expectations and the steps every business can take to stay ahead.

Today, we have a very special guest joining us on DigitalNOW, Nick Kelly, director of visual analytics at Logic20/20 and overall analytics guru. Nick used to work in the UI and UX field, but moved to analytics over 10 years ago. You’ve worked across the globe from Singapore and the Philippines to Ireland to now the US, and actually this is a pretty fun fact: You’ve had the opportunity to design dashboards for Formula One drivers! I definitely want to hear more about that. Nick, thanks for joining us today. I’m very happy to have you here. I’m very excited to talk about data driven culture, but first of all, how are you?

Nick Kelly: Thanks for having me, Matt, doing great, happy to be here. It’s been a fun journey and it’s taken a long time. Really excited to be here, talking to you, and looking forward to it.

MT: Awesome. I want to touch on this: 10 years ago, you were in visual analytics. I can’t imagine that there was much happening back then. Can you tell us a little bit about what it was like? We’ll get into the “now” a little bit later on.

NK: That’s a good point. Whenever I think I’ve been it a while, there’s always someone there who’s been in it for like 20 years, 30 years, you know? And they’ve seen it all before. So quite often when I’m coming up onto this stuff, and I think I found out something new, then it’s like “So-and-so has been doing that since the 1970s!” [Visual analytics] seems like it’s kinda new, but the whole reporting space has been around for ages.

What I would say is when I got into it, [visual analytics] was more focused on the technology. Using the technology to solve our problems, rather than what we’re going to be going into: the cultural side of it and the people side of it. To your point, there wasn’t much going on in the culture, but there was definitely lots going on with the technology/data side.

MT: Let’s start simply, if you don’t mind. I’m not the subject matter expert here and I need you to help me! There’s a lot of people that are probably listening to this that don’t know a whole lot about data, data literacy, data culture. Can you just give us a simple overview of what that is and why they should care about it?

NK: Yes! There were a few schools of thought out there. The term was really popularized in the last few years by Jordan Morrow and the idea is that we should be making our decisions based off data. We should be going to a meeting and using some form of data to support the decision making. [It’s also about] “Hey, how do we get our whole organization thinking about how they’re going to leverage data.”

The great thing is, there’s more focus on it. We can probably get into it a bit later as well, but also Donald Farmer talks about not using the term data literacy because you know, why don’t you tell someone, “Hey, you’re not data literate!”

It doesn’t sound great, you know? It can be offensive. The term is great to describe an organization and building up a culture around that. If you take data literacy and take it on a small scale and you blow it out to a whole organization, you can say, “Hey look, let’s have a data culture shift.”

That really is the [key.] Does everyone seek to use data where appropriate? (Not all is appropriate) But [do they seek to use data] where appropriate to support the organization and its goals? Very broadly speaking, that’s how I would call the data literacy piece and the data culture part of it.

MT: Well, data culture is what I want to talk about, actually, to start with. What challenges have you seen right now with building a data culture? There have to be some major issues that companies face when they’re trying to change it. What are [those issues]?

NK: Yeah! If we were to start with something as tactical as the tools that are out there, [such as] various technologies that people use for reporting and for dashboards.

Are people using them? Even at a base level of culture, as are you using the available tools that are there? A lot of folks aren’t, and then there’s the, “Okay, what data is available? Are people using that?” The first barrier to look at is really “Can people find it? Can people find and access the data they’re looking for?”

It’s not even a case of “People aren’t making decisions using data.” Probably many of them want to. But it’s just not available in the form that they want to have it there. That’s probably the first problem we have: the availability of tools and availability of data. Then there’s the people side of it; how people discover and access data.

Then on top of that is getting the willingness for people to do it. There’s many layers to it. Broadly speaking, I think, there’s a technology problem and there’s a people problem to that.

MT: So essentially: adoption, right? With people accepting it and saying, “This is what we’re using from now on.” My question on that is: “If that’s a huge part of the data-driven culture, does that come from top down or bottom up?”

NK: Ideally, it’s both. Ideally, we’re going to be having some executive-level initiative [with] budget. It’s going to potentially even have structural implications: how we serve people within the organization with data, the management-level buy-in as well as the folks that are making the decisions day-to-day. We’re arming everyone. Top-down, bottom-up.

MT: What if you don’t have leadership that has a data-driven mindset? What are the obstacles? What would you suggest for folks that want leadership to buy in?

NK: If you don’t have the buy in, we can go get those smaller wins at a less executive level and show the value. What happens when you do make more of these data-based decisions? What’s the implication? What’s the win? How do we surface that to the executives? Establish quick wins. Again, none of this is new. This has been around for a long time, especially in the field of change management. Some of those tactics that would be used to get people on board and get people to buy into, “Hey, look, there’s something to this data culture thing. There’s something to this data literacy thing.” We’ve got a few wins we can reference, let’s go scale it.

MT: On change management, right? You spoke about adoption and you spoke about leadership. If it’s coming from top down, you need good change management, right? What is the importance of it and what tactics can you recommend for adoption of analytical assets?

NK: Yeah, it’s funny: even behind me here, you have the kids running around all over the place, half the day. Right? Welcome to 2020.

One of the things the kids do is jujitsu. Their trainer will set goals for them. One thing we had was like, “Okay, we could have the kids just do that blindly and not really have the wider view of how they’re doing towards their goal.” Like what does it mean for them, right? All these things to help them track.

What we decided to do was put up a chart here on the whiteboard. We’d have them participate in that; they would start coloring it in and fill up a bar. The more they’re completing the goals and going to see this visual representation of, “Hey, you know what? I’m tracking my data and I can be motivated by that.”

At the top of the bar, we had a few things there. “If you hit your goal, you’re going to get a new Nerf gun,” right? “You can pick your Nerf gun. You’re going to have like a $30 budget to go buy a gun.” So that was one thing: showing how to motivate and get that change going with the kids.

[It also surfaced] the importance of tracking data. We had them fill out an Excel spreadsheet every time they did a few armbars. They type it in and that spreadsheet would then tell them, “Okay, you’ve got this many armbars left for the end of the month, but also here’s how many you would need to do every day to hit your goal.” To get them really focused on that. That helps them determine, “Hey, tomorrow I need to do this. Tomorrow I need to get up early in the morning and structure my day a little bit.” So even that minor amount of  data was helping have some change impact, just at home.

MT: I’d say that’s a lot clearer on how they’re doing than when I would come home with a test with an F that looked more like an A by the time I got home! I’d say it’s hard for the kid to argue with their results when it’s data driven, I’d say!

NK: It’s kind of unfair, I suppose.

MT: The other part of that is, how old are your kids?

NK: Four and Six. If you can get them to adopt PAL BI reports and things like that, I would challenge that you can get anyone to adopt it! But you’re right. It’s putting the right meaning behind it. They have to understand why they’re doing it and what the value is on the other end. It’s spot on and that’s change management 101: “What’s in it for me?”

In some regards, it’s a victory to get kids using data, but in others, they don’t have any energy behind it. Like in terms of negativity, right? They don’t have any resistance behind it. If I want to do something new, I really have to make fanfare about it. It has to be really super clear to you. It’s like, “Hey Matt, this is different. It’s not business as usual. We’re completely changing things up here. We’d love your input on how to do that. Let’s put our heads together and figure this thing out. We’re going to be part of the solution here.” That’s really all the good change management stuff, you know: being transparent, getting the buy-in, and working together.

Some of the things like that really blew my mind in analytics: the impact you can have, looking at change management methodologies that are out there—there’s lots to learn.

MT: I want to continue on that vein, but I have to ask you first: how many armbars did you cop from your kids during this experiment?

NK: I’d say they had about 8,000 on me. About halfway through it, I thought I should buy a jujitsu dummy. So we did, and that promptly had its arm almost ripped off after about 2000 armbars or so!

MT: Back on topic! You know, we were talking about change management and I want to get your perspective on how that has changed over the years, and within analytics in an enterprise setting,

NK: I think a good proxy for that matters, like seeing what’s going on LinkedIn and people’s reaction to change management analytics. You started off by saying, you know, what was analytics and where was it at 10 years ago?

If I had started talking about change management back then, no one would have given me any attention really. They wouldn’t give me the time of day! The focus was on data. It was on data quality [and] on the technology. It was like, “How do you architect your data warehouse?”

All important things, no question. Really important! It was when people moved past that and started to realize, “Hey, look, we’ve got this stuff set up, but people still aren’t really acting on data. So why is that? We’ve done what we think we should have done.” That piece where we are in the enterprise now. I think we’re starting to realize that we need to focus more on people.

MT: I have to jump all over that. When it comes to prioritizing people coming from a team sports background, there’s nothing more important. Everyone has to be on the same page going in the same direction. So I like that one a lot, mate.

I want to shift gears a little bit. I know the people the most important, but we have to talk about tools. You’ve said they’ve come a long way. They were initially the focus in this arena, but what are the key tools you think that every organization should have in order to best organize and visualize their analytics assets?

NK: I think even two or three years ago, you wouldn’t have caught me talking about tooling very much. I think it has come full circle with there are a few things that are indispensable. Probably because of a proliferation of tooling. If we look out there and we say, “Okay, take any company, enterprise level, a fairly large organization, and probably what’s happened over time is they’ve ended up having their departments adopting different BI tools and BI technologies. To throw out a few names, you know, their marketing might be using Tableau, the sales team maybe is using QlikSense and the IT organization is using Power BI to visualize their data.

The challenge there is: do we try and mandate a certain technology which may work, but it’s going to take fairly big structural change within the organization to make that work, or, do accept that there will always be technology silos within the enterprise and figure out, “Okay, we’re going to go with it. We’re not going to change that, but let’s put a layer on top. Let’s put a technology there on top of all of that.” If there’s one technology out there that I think has the biggest impact, especially in relation to change management and adoption, it’s analytics hubs—by far.

MT: I’ve been hearing the term analytics hub everywhere. It’s all over LinkedIn—and obviously this is why, right. It’s become a focus point now and people are very interested in it. It’s a powerful tool, right? It’s something that everyone should have, not everyone does have, but it’s only good if people actually use it, right? We’re back to this adoption situation. Do you have any tips and tricks for increasing adoption? Because like any tool that you implement, it has to be adopted, right? I think that’s an important thing for people listening to understand.

NK: Totally, totally. You just reminded me of it. It’s so easy to forget. It’s like, “Hey, technology is going to solve all our problems.” That’s kind of what got us into the situation. You’re spot on—I think any technology implementation has to come with a change management approach. I think it’s nearly a waste of time to do it without it.

It’s not any different for the analytics hubs. If we haven’t done all of those change management aspects of it, like just letting people know that it’s there, how did they find it? How do they access it? Have you set up the permissions correctly? Even getting to the level of “How have we defined the taxonomy?”

We’re totally familiar. It’s like second nature to us when we go onto something like, let’s say Netflix. We go to Netflix and say, “Look, I want to just see anything, any comedy. That’s the type, that’s a taxonomy, the comedy, there you go. Or action adventure. All of those things—we need those in the enterprise space for our analytics hub.

So how do I enable discovery and help people find things? There’ll be the things I’d be looking at, but we would need a fairly comprehensive change management program. We don’t want the hub just to be another piece of technology that’s thrown on the top. That that’s another place, another thing people have to worry about.

MT: And it sounds like simplicity of use, you know, is a big part of it, too? Right?

NK: Spot on, the desire is to expose data and, potentially, the complexity behind it. There’s no ill will behind that, but just to give all of that power to the end user, but the end user might be overwhelmed by it. So absolutely like simplicity is going to be really, really important in approaching this.

MT: So, we talked about data literacy at the start. What role does it play in creating a data-driven organization?

NK: It could be your start. It could be the Genesis for how we might build up a more data-driven organization. In the past, when we looked at this without the data literacy piece, it would always start with some level of assessment. Where are the people right now in terms of analytical maturity?

Now we can look at it in terms of: “Where is our organization in terms of data literacy?” That can be a really, really good place to start, because we might say, “Look, the CEO is not data literate.” We wouldn’t say it to the CEO’s face, and that’s going back to that thing: it can be offensive, right?

If we say, “Well, we don’t necessarily have the buy in from the CEO.” So, let’s look at that as a gap. That is a gap. It’s an opportunity to educate and then look in the rest of the other pockets of the organization to say, “Well, maybe it’s a good to start with the most data literate.”

We can get better wins there. There’s less convincing to be done there and then use them as a stepping stone to show, “Hey, look at the sales team! They’ve really, really embraced this data-driven culture piece here. They’ve got great dashboards that they’ve really built trust with their data and they’re making decisions with it. They’ve had this 50% increase in productivity.” Or “Their sales are up 20% because of it” or whatever criteria metrics we can get there to help sell another department, then the wider organization and beyond. That’s one way. There are many, but that is one way you could certainly approach building a data-driven culture now.

MT: Yeah, because that’s my next question actually: [what are] practical steps that companies can take so that their employees can start adopting data literacy? Do you have any tips around that?

NK: I mentioned the assessment, right? Start with the assessment. You have to start there anyway, but if it’s in a small group, it’s much easier to do it. You can tackle that. That’s something you can take on and then develop this thing called a change plan. What is our plan? [It’s about] understanding that people are really going to be key to making any of this stuff work. How are we going to communicate with folks to address the gaps that are there, any potential risks, etc. There are plenty of processes out there that you could follow. There is change management process out there. There’s user experience process. There are all these different processes that you can start to leverage and then look to do small baby steps, small iterations. We’re not going to boil the ocean.

You have to get these small little quick wins along the way, right? Don’t focus on grand change—that will come. If you focus on the small wins, then it’s much easier to get the buy-in. Also—focusing on the education piece. doing brown bags, different sessions where you can invite people, maybe even internal webinars, internal workshops, etc. where you can get people on board.

It is very hands-on and those require quite a bit of effort, but the reward is absolutely worth it.

MT: Yeah. What you’re alluding to is “people first,” right? Let’s stay on the working from home situation: obviously, tools, changes, all these things that are coming into workplaces…when you’re at home—it’s different to the office!

Are these tactics transferable to the home workplace? When you’re in the office and your manager or your leader is saying, “We’re going to do this and etc., etc.,”—it’s different over a video call, you know? So, are they transferable?

NK: Yeah, I know we’ve been doing workshops recently, remotely, and not out of a desire to do them remotely! It’s like, obviously you were forced to do it because of COVID, right?

I never would have seen myself doing remote workshops. I would have [said] any time we do workshop, it has to be in person. I have to see people’s reaction. I have to read the body language. We need people around a whiteboard, you know, and using sticky notes and all these things, right? Then COVID came along and it was like “Uh-uh—if you want to function, you’ve got to do it. You gotta use the remote.” There’s a remote world. And, and so that was certainly a big shift.

Some of the tools then that helped with that: […] I end up using virtual whiteboards a whole lot more, [which is] something I would have avoided in the past. Is it as good as doing a whiteboard in person? For me, it’s not, but it is way better than just a regular video call. Way, way better to have that interaction.

That that’s one piece that I’ve noticed as a difference, but also then, to go back to the analytic hub: having that element of being able to collaborate, being able to give ratings that makes the remote world more manageable, for sure. I would even say in aspects [like] productivity and in terms of being able to have the time to find the things you need to find, and a hub [enabling] that and [unlocking] that for people.

MT: Well, that was going to be my next question. It’s sounds like you just answered it! What’s the most important thing…for the rest of 2020 into 2021? To make sure they have a data driven culture? You’ve mentioned tools, training, change management, but it is it the analytics hub that’s probably the most important?

NK: I think if there was one thing we could tangibly put our finger on, it’s analytics hubs. It’s not in and of itself a solution, but it can be a vehicle for the solution.

Let’s say you got in your change management program, you can surface all of those materials on the training, on a hub. You can drive the data culture through a hub. The hub is going to be a big focus, certainly towards the end of the year.

But I think then going forward in 2021, certainly.

MT: Okay, well, mate, that’s time for us today. I’ve really appreciated this chat. It’s an important topic right now, and I appreciate your subject matter expertise and the way you were able to simplify it for me. Personally, I appreciate that.

NK: I hope people listening appreciate that, too! Thanks again, Matt. Thanks a lot. Really appreciated it and enjoyed the conversation.

MT: No worries, mate. Speak to you soon. Thank you.

NK: Thank you.

MT: You’ve been listening to Logic20/20’s podcast DigitalNOW. To learn more, visit our website at www.logic2020.com or follow us on social media. See you next time!

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