How Can Insights Partner Better with Data and Analytics with Michelle Gansle

[00:00:00] Michelle Gansle: Remember when there just used to be insights and then all of a sudden this concept of big data showed up and it started popping up as different teams within, often within technology departments. Yeah, like I remember when that first happened, there was this like awakening of like, wait, we’re not the only people who own and control data and insight.

[00:00:18] Michelle Gansle: And it turned into this like weird competition. 

[00:00:23] MRII Announcer: Welcome to MRII’s Insights and Innovators podcast, where we talk to top market research professionals to get their inside stories about innovative and enduring best practices. Now here’s your host for today’s episode. 

[00:00:37] Nick Graham: Hi. Welcome to today’s episode. Why Insights needs to Partner better with data and Analytics.

[00:00:42] Nick Graham: I’m your host Nick Graham, and today I’m delighted to be joined by Michelle Gansle. Michelle is a seasoned data analytics and insights leader with deep experience building capabilities at some of the world’s most iconic consumer companies. Most recently, she served as the chief data and analytics officer at McDonald’s, where she brought together [00:01:00] insights, analytics, and data science to drive better decision making across a highly complex global organization.

[00:01:06] Nick Graham: And prior to that, she held senior global leadership roles spanning insights, foresight, and innovation at Mars Wrigley. Michelle now works as a data analytics and AI strategy consultant, partnering, partnering with organizations to turn the promise of data and AI into tangible business outcomes with a career spanning insights, analytics, and transformation.

[00:01:26] Nick Graham: Uh, she brings a uniquely grounded perspective on why insights needs to play better in the data and analytics sandbox, and what it really takes to make an impact in this environment. Michelle, welcome to the podcast and thanks so much for joining us. 

[00:01:40] Michelle Gansle: Thank you. Nick is one of my favorite people in the industry.

[00:01:43] Michelle Gansle: I’m super excited to do this with you today. 

[00:01:46] Nick Graham: Absolutely. No, I’m excited. I think it’s a great topic and it’s, uh, any excuse to spend time together, even if it’s virtually is, is awesome. 

[00:01:53] Michelle Gansle: Let’s nerd out on data. 

[00:01:56] Nick Graham: Let’s nerd out on data and why we as insights people need [00:02:00] to play better in the data analytics, uh, sandbox, which I think is, uh, is gonna be a big topic for today.

[00:02:06] Nick Graham: So let’s dig into, I guess, some of the questions that we were gonna cover today. I think starting out, there’s a lot of angst, I guess is probably the right word right now in the, about the role of insights. I think there’s this feeling in a lot of, uh, the industry that insight is sort of losing ground to data analytics, to it, particularly as organizations become much more data centric and, and data technology led.

[00:02:32] Nick Graham: But I’d love to hear your perspective. Obviously you’ve sat on both sides, you’ve sat on the inside side, you’ve sat on the data analytics side. Is that really an issue? Is it a concern? Like how do you think Insight should be thinking about that relationship, um, between themselves and data and analytics?

[00:02:48] Michelle Gansle: I’m going to answer it, but I’m gonna take a meandering, um, path there and just like reflect back to, I wanna say like 10 or 15 years ago. Remember when there just used to be insights? Yeah. And then all of a sudden this [00:03:00] concept of big data showed up and it started popping up as different teams within, often within technology departments.

[00:03:06] Nick Graham: Yeah. 

[00:03:07] Michelle Gansle: Like, I remember when that first happened, there was this like awakening of like, wait, we’re not the only people who own and control data and insight. And it turned into this like weird competition. Yeah. Of like who had what data and who could generate what insight. And there was always this tension because it insights people back in that day, 15 years ago, didn’t really have access to this big data and weren’t utilizing it to generate insights.

[00:03:33] Michelle Gansle: But the data science people 15 years ago didn’t understand the business and weren’t really generating insights. They were just generating interesting facts. Yeah. But ’cause they were sitting in different functions, they never talked to each other. And I always thought that was weird. And it, it was the beginning of this like insights, fear of like, oh, are we still relevant?

[00:03:54] Michelle Gansle: Yeah. And I think over the last 15 years what I’ve seen is there have been different iterations and big [00:04:00] companies of where. Each of those teams sit, but they almost rarely never sit together. And when I was at McDonald’s, I had the rare privilege of being across both, and even being on top of consumer insights, business insights, and data science, they still didn’t naturally work together unless I forced it.

[00:04:19] Michelle Gansle: Yeah. And I found that so interesting. 

[00:04:22] Nick Graham: Why do you think that is? ’cause as you say, I feel like it’s. It, it’s not a one-sided thing. I think the two, they should be so complimentary, and yet I feel like often the teams struggle to understand each other and the value that they can bring. And, and actually what frustrates me is the, the sum is so much greater than the parts, right?

[00:04:42] Nick Graham: Like if they can work together, the power that, that those collective teams they have is incredible. 

[00:04:48] Michelle Gansle: I agree. That’s what is always so confusing me, and I think I chalk it up too. We’re just all busy, right? It’s the same reason why insights people resist learning, like research tech tools [00:05:00] or, or, or learn res resist ai.

[00:05:03] Michelle Gansle: I don’t think it’s a lack of interest or curiosity. I think it’s like, um, I’m busy. I don’t really know where to get started. I don’t want to look dumb. I don’t know what questions to ask. We did back in 2020. I was on the SMR board and we had an online conference, and one of our sessions was this data scientist being like a day in the life of a data scientist.

[00:05:25] Michelle Gansle: It was one of the most attended sessions. 

[00:05:28] Nick Graham: Yeah. 

[00:05:29] Michelle Gansle: So that told me there’s not a lack of curiosity, so I’m hoping people are listening to this because they wanna hear like, what can we do differently? 

[00:05:36] Nick Graham: Exactly. 

[00:05:37] Michelle Gansle: Um, so I don’t think it’s that. I think it’s. Data science people are introverted, so they’re not naturally gonna reach across.

[00:05:44] Michelle Gansle: Yeah. Insights. People are curious. So my question back to you and back to everyone is like, what is stopping insights? People from better understanding? What more could they do if they connected all of the data dots with the work, the insights and curiosity [00:06:00] and business acumen that they have? 

[00:06:03] Nick Graham: So should we.

[00:06:05] Nick Graham: Because as you say, I think right now, even today, I mean, as you said, this isn’t a new scenario, right? This has been happening 50, 10, 15 years. But I still feel, um, in my experience, in my plus two roles, you know, talking to peers in the industry on the, on the corporate side, um, it still feels like there is too often this sense of competition between the teams.

[00:06:29] Nick Graham: Or or perceived competition that they are fighting over the same ground as opposed to actually, again, that they can, again, they can make the pie bigger if they actually play together. But I, I feel from the insights team, there’s an element still insights teams. There’s still this element of defensiveness and fear because there’s money, money and investment, right?

[00:06:51] Nick Graham: Money and investment is going into data analytics and ai, and I think there’s this feeling of being. Of this sort of like, well, all of that is, [00:07:00] it’s heading inexorably in one direction, but what I’m hearing you say is actually it doesn’t have to be like that. Right? It, that isn’t necessarily that the direction of travel, that there’s an opportunity to partner to, to, to make this a different story than the one that it feels like it is for people.

[00:07:19] Michelle Gansle: Yeah, I think, well, you know, like your enemy’s enemy is your friend. I think that, yeah, the sense of urgency right now and the commonality is that AI has the opportunity to elevate both of those roles or to, yeah, or to replace, right. So like for me, the, the call to actually, like after 15 years, why are we still talking about this is like, if not now.

[00:07:42] Michelle Gansle: The never, right? Like 

[00:07:43] Nick Graham: yeah. 

[00:07:44] Michelle Gansle: The combination of bringing AI plus data science plus insights together has never been more powerful. And so my take is what you said, it’s, yes, it’s a little bit of control and budget, but at the end of the day, everybody just wants to create value. Mm-hmm. [00:08:00] And creating value means, right.

[00:08:02] Michelle Gansle: A better job satisfaction, better career development, and the money goes in your direction. So rather than seen as a zero sum game, like one plus one equals three, you might have different budget sources, but if you come together to try to solve the business problem and take shared, uh, you know, take shared claim for it.

[00:08:22] Michelle Gansle: If everyone gets acknowledged for the work that they did, then maybe there wouldn’t be this sense of competition. Because I found that was true. Like with our data science folks, they feel like they’re doing all this work, but they, they’re never in the room where it happens. Totally. And they don’t get the credit and Totally.

[00:08:38] Michelle Gansle: So just simply bringing them into the room when the conversations are being had, giving them co-edit, like a lot of that, there’s a lot you can do to build bridges just by 

[00:08:48] Nick Graham: Yeah. 

[00:08:48] Michelle Gansle: Bringing a little bit of human understanding into the problem. 

[00:08:51] Nick Graham: No, I agree. And I think as, again, as insights teams. Have, we have inherent, we should have [00:09:00] inherent empathy and curiosity.

[00:09:01] Nick Graham: That’s a big part of our DNA. And I think you’re right. We, you know, we often direct that towards the people outside of our organizations, but actually directing that to the people. And yes, we may feel under threat, we may feel undervalued, but exactly to your point, you know, I’ve spoken to lots of data scientists who feel exactly the same, right?

[00:09:17] Nick Graham: Because Yes. That they’re not in the room. They don’t have all the context, they don’t really know where their data and recommendations go at the end of it. Mm-hmm. So having some empathy and thinking about how do you, how do you engage them and make them feel, uh, more satisfied, more rewarded, like they can make a bigger impact as well.

[00:09:34] Nick Graham: Feels like a big opportunity where you’ve seen, where have you seen, sorry, should frame it differently. When you’ve seen insights and data and analytics team work well, however they’re organized, whoever they report to you, I mean, I guess, you know, in McDonald’s, as you said, they reported both to you. When you’ve seen them work well together, what, what is it they’re doing?

[00:09:57] Nick Graham: Like, can you give me some examples of what is it that they’re [00:10:00] doing to work differently so that I guess we can all learn what specifically we should, we should be doing differently moving forward? 

[00:10:08] Michelle Gansle: Yeah. I think for me it’s all about, um, where you bring them together to solve the problem too often. I mean, we as insights, people hate that when we’re brought in too late.

[00:10:21] Michelle Gansle: Like no one wants to be an order taker, right? 

[00:10:23] Nick Graham: Yeah. 

[00:10:23] Michelle Gansle: So there’s a business problem to be solved. You bring the bi person, the data science person, the consumer insights person together in a room mm-hmm. And force them to discuss together. How would you answer this business problem? And the interesting thing is all three of them would give like a, their answer would be a siloed portional answer.

[00:10:44] Nick Graham: Yeah, 

[00:10:44] Michelle Gansle: right. But forcing ’em to think about like, how would you holistically answer the problem gets to obviously a better outcome. And we so rarely do that. Normally a leader will pose the question to all three teams and all three teams will independently try. 

[00:10:59] Nick Graham: [00:11:00] Exactly. That’s right. I never seen that before.

[00:11:03] Nick Graham: Definitely not. 

[00:11:03] Michelle Gansle: Yeah, definitely doesn’t happen. Yeah. But that’s the beauty is like the insights person brings business acumen and curiosity and storytelling. 

[00:11:09] Nick Graham: Yeah, 

[00:11:10] Michelle Gansle: the, I mean, the consumer insights person, the business insights person often brings like performance and business data. 

[00:11:17] Nick Graham: Yeah. 

[00:11:17] Michelle Gansle: And the data science person brings advanced reasoning, logic, LLMs, that can get to different answers than either of the other two could get to.

[00:11:27] Michelle Gansle: So collectively, you get more of a 360 perspective that gets you to net a better business outcome. 

[00:11:34] Nick Graham: Yeah, no, that makes sense. And it’s so, it’s, so it’s, it’s about bringing those people in from the beginning together and almost crafting that brief and I guess then crafting a brief and crafting the, the journey together, right?

[00:11:46] Nick Graham: So like what, what is each team gonna do and how do you sync it together through the journey? Because to me, I think there’s. There’s huge value in, in the start point. But there’s also in that iterative, like some of the best experiences I’ve had working [00:12:00] with, um, data scientists, is that sort of iterative back and forth that here’s where we think the opportunity or the problem or the space might be.

[00:12:07] Nick Graham: There’s a first cut of data or there’s a first model actually tells us something different. So we, so it’s that sort of iterative process. If you can do that as a collaborative team, I think that gets you. It feels clunky and it feels time consuming, but actually can help you get so much further, so much faster.

[00:12:24] Nick Graham: Right? If you are actually doing that in a more, um, joined up way. 

[00:12:29] Michelle Gansle: Yeah, we did, um, sometime last year we had this team offsite and the thing that the holistically the team loved the most is we did this like career fair where we had each sub-team have a little, remember like old school science fairs where you had like the poster that went three ways?

[00:12:47] Michelle Gansle: Yeah, 

[00:12:48] Nick Graham: yeah. 

[00:12:48] Michelle Gansle: Everyone had the little poster with like, what’s a day in the life of, what skill sets do you need? And everyone, all the sub-teams went around and learned about every other sub team. It was like the number one session of all the [00:13:00] sessions that we had on a two day offsite. So it just shows again, like taking a little bit of time.

[00:13:06] Michelle Gansle: So curiosity, but the beautiful that is, it helped the teams realize like a business insights Pearson could learn to become a data scientist or data science person could learn to become a consumer insights person. Yeah, totally. 

[00:13:18] Nick Graham: Right 

[00:13:18] Michelle Gansle: then. Then it opens up your career, you know, aperture. 

[00:13:22] Nick Graham: No, and as you said then they’re not, they’re, they have a lot more crossover than they have difference when you think about it relative to lots of other parts of the organization.

[00:13:30] Nick Graham: We actually, the Venn diagram would show we all care about data. There’s lots of things that we have in common. We might have different ways and different mm-hmm. Expertise and skills, but there’s actually a lot of potential crossover. 

[00:13:41] Michelle Gansle: Yeah. 

[00:13:42] Nick Graham: And you made me think about, um, something you said earlier about where we’ve come from, right?

[00:13:49] Nick Graham: The, in the, in the old days. AKA when we started our careers. Um, in the old days it was insights, right? Or insights and analytics. 

[00:13:59] Michelle Gansle: Was it? 

[00:13:59] Nick Graham: And [00:14:00] do you think, and, and that’s changed over time, as you said, the insights is no longer the arbiter of all data or the owner of all data or all analytics within an organization Is, do you think there’s a bit of a reframe we need to have about what our role is, what our contribution is?

[00:14:18] Nick Graham: I still sort of feel like sometimes we’re fighting the. The battle to control and own. Mm-hmm. All, all data and information in an organization, but in reality, I just, I don’t think that’s even possible anymore. And, and I’m not sure that’s my point of view. I’m not sure that’s where we can add the most value is trying to do all of that.

[00:14:37] Nick Graham: But what, what do you think, what do you think about that and what do you think we should think about our role being moving forward if we, not that just the data stewards, I guess, and data owners. 

[00:14:47] Michelle Gansle: I wonder if you agree with this, but I feel like in the last, let’s say five years, it’s actually insights people have moved from We control and all, all data to like we are the voice of the customer.

[00:14:58] Michelle Gansle: Customer and shopper. [00:15:00] Yeah. Like we own that, but I don’t even think we own that anymore. I think that what we, what insights people uniquely bring is critical problem solving, curiosity and deep human understanding. Mm-hmm. No, I don’t think any other function has that level of like depth and understanding and ability to connect dots.

[00:15:20] Michelle Gansle: So I think our role has turned from like data owners to orchestra conductors. Like where we are best is. Dots, storytelling, packaging it up and driving, you know, influence and decision making. 

[00:15:37] Nick Graham: Yeah, I think that’s a really interesting shift and, and I think might help a lot of insights, people listening to think about.

[00:15:45] Nick Graham: It’s not about losing things, it’s actually about just about reshaping our role and our focus, right. Within an organization to be, I, I love that metaphor. I mean, you know, you hear it sometimes about the conductor, but it’s that sort of orchestra conductor, which is. [00:16:00] But you and act actively playing a role to pull together the pieces because the orchestra doesn’t sound harmonious, just magically.

[00:16:06] Nick Graham: It takes work to make it all, all sync and all sing, literally. Right? Yeah. Um, when you think about the, uh, the, the guess, the what makes insights distinctive, you talked about some of the kind of unique strengths that insights brings. Um, empathy, the ability to connect the dots, the ability to sort of see, see.

[00:16:29] Nick Graham: At a deep human level across all of the different touchpoint, how do you think we can leverage those strengths more deliberately? Right in so in this new landscape where again, we don’t control data, but we need to play much better with, uh, our data and analytics partners, how do we bring more of those strengths to the table, do you think?

[00:16:50] Michelle Gansle: Well, I think all of those strengths that we just discussed are the same strengths of. What, um, are unique sort of competitive [00:17:00] advantages in the world of ai? Mm-hmm. ’cause that’s today, like ai, uh, what AI can’t do is today well is critical thinking and human deep, human understanding. And so for me it’s like that, that is our new competitive advantage is being able to bring humanness.

[00:17:18] Michelle Gansle: Storytelling, human understanding to the business problem to drive better business outcomes. And now we have all these amazing tools at our disposal to be able to do that better. So for me, like our huge opportunity is treat AI and data science as friends, not foes, to elevate our our impact. 

[00:17:43] Nick Graham: I think that’s spot on.

[00:17:44] Nick Graham: And as you say, thank you for bringing AI into the conversation. I can’t believe it’s been however many minutes and we haven’t really dug into ai. I know. 

[00:17:52] Michelle Gansle: Getting it not in the first one minute. 

[00:17:54] Nick Graham: I know exactly. Barely mentioned it for the first, uh, first 10 minutes talking about ai. To your point, [00:18:00] I think it’s not a foe, it’s a friend and there are lots of things it, it can do really well and can’t do really well.

[00:18:07] Nick Graham: Do you think insights is adapting? Well enough to the promise and potential of ai. And I guess, do you have any examples of where you, from your experience of where ai, where insights and AI can play really complimentary roles, I guess, of where the two, again, the human and the artificial intelligence can actually play really well, um, to actually deliver a better outcome?

[00:18:35] Michelle Gansle: I think. I mean, I’d be curious to hear your point of view, but I think like all things, it’s a, a bell curve, right? Yeah. That there are, there are places and spaces where insights teams and insights suppliers are, uh, very advanced. And then there’s, you know, places where just like in all companies, there’s laggards.

[00:18:53] Michelle Gansle: Yeah. So I can’t say that there’s, uh, a one size fits all, uh, shameless plug for people [00:19:00] who aren’t already following her. So, Christie Zuki, who’s, uh, an insights. Leader. She has a substack called AI for insights leaders. Oh, that’s great. And she posts these amazing, that’s super practical. Videos shows like, for example, she did one recently where she created like an insights evaluation tool like in two minutes on Claude and shows you how you do it.

[00:19:21] Michelle Gansle: Wow, that’s amazing. So I think there’s like people like her who are trailblazing in the industry. And showing how we can use AI to make our jobs faster, better. Um, you know, and then there’s probably insights folks out there who are still defaulting to outsourcing all of their research to big agencies.

[00:19:41] Nick Graham: Mm-hmm. 

[00:19:42] Michelle Gansle: So, I mean, I am trying to think of like, uh, good examples. Um, you know, I think. Those folks who are out there exploring what’s possible with AI or using AI as a strategic thought partner to drive, yeah, [00:20:00] like connect the dots where they maybe weren’t thinking about already or more quickly pulling in context.

[00:20:06] Michelle Gansle: I think it’s like easy, easy wins for insights leaders. 

[00:20:10] Nick Graham: Yeah, totally. No, and I may 

[00:20:12] Michelle Gansle: think, what about you? Like what have you seen? 

[00:20:14] Nick Graham: Well, I think I’ve seen a bit of, I’ve seen a bit of, um, everyone’s somewhere on the spectrum, if you like, about their reaction to it. Um, I feel like there’s some still re resistance or defensiveness about ai, which is like, well, it can’t possibly do all the things that are, that are.

[00:20:31] Nick Graham: Human insights per well, of course not. I don’t think anyone’s pretending that it can replace it, but I think, again, it’s natural technology comes along. People hear the noise about productivity and efficiency and, and sort of go to, let me defend why it can’t do qualitative research or it can’t do, um, deep strategic thinking.

[00:20:51] Nick Graham: But again, doesn’t mean it can’t be a partner, it’s not a binary in my opinion, but it’s not. It’s not perfect and it, I, yeah, it’ll get better, but I [00:21:00] don’t think it’s ever gonna be perfect at solving all of the, the myriad of, of questions that we have. I think the be, and then on the other hand, I’ve seen some teams, and in particularly IT and tech leaders go, well, we can do everything.

[00:21:13] Nick Graham: We can do everything. We don’t need any research. 

[00:21:16] Michelle Gansle: Yeah, 

[00:21:16] Nick Graham: we don’t need any new data anymore. Like it can solve all of our problems. I think the best teams are those who are. Very pragmatically saying, here are the problems that I need to solve for. Here are the ways in which AI might be able to solve. Maybe it’s an efficiency solution.

[00:21:31] Nick Graham: Maybe it’s actually about helping them see things we can’t see today. Maybe it’s a, you know, as you said, like a thought partner, somebody I can stress test ideas with, but I think it’s about actively jumping in and thinking about how it could solve your current problems, not just about. Trying to imagine all the ways it’s gonna replace whole departments or whole ways of doing things today.

[00:21:54] Michelle Gansle: Yeah. So, ’cause you know, people like practical tips. Um. Can I [00:22:00] share one of my most favorite like AI hacks? 

[00:22:02] Nick Graham: I would 

[00:22:02] Michelle Gansle: love that. So actually learned this. So there’s a guy named Jeff Woods. He wrote a book called the AI Driven Leader. It’s amazing, everyone should read it. He has a simple framework of how you use it as a thought partner instead of outsourcing it.

[00:22:15] Nick Graham: Yeah. 

[00:22:15] Michelle Gansle: But he created his own AI board of directors and he uses it to stress test. Big board presentations and it made me think like, how does that apply in our own lives? So now I do that, like when I’m about to work with a client or create a proposal, I create a persona of that person, or I create a persona of like, what would a world class consultant say to this?

[00:22:39] Michelle Gansle: And I stress test my work in that. And I had this idea, what if we had that like in insights? Yeah. Board person that you simulated the CEO or the CMO, so that you got to better output presentations. ’cause often my opinion, we insights people always have really good recommendations, but where we fail is in our [00:23:00] ability to story tell that, or deliver that in a way that lands for the different stakeholders.

[00:23:06] Michelle Gansle: So what if you had like your AI CMO, where you ran presentations through it before you presented it to get a better output? 

[00:23:13] Nick Graham: Yeah, I think that’s a great idea. And I think to your point, um, it would help with honing you. So we talked about, you know, you talked about the muscle that insights can bring in terms of storytelling, connecting the dots, thinking about the so what, because again, the data science team or the AI doesn’t always have the context to know how does this land into action mm-hmm.

[00:23:33] Nick Graham: Into activation. But I think even as insights people, we sometimes we get to the. But we struggled to take it that little bit further, which is what it needs in order for a salesperson, marketer, or whoever to then know what to go and do with it. I think it’s a brilliant idea to help you stress test and take it to that next level, at the very least to prepare you for the type of questions you can get.

[00:23:56] Nick Graham: Exactly. 

[00:23:57] Michelle Gansle: Do you have any AI hacks that you [00:24:00] use in your day to day? 

[00:24:02] Nick Graham: I, I use it particularly for storytelling. So if I have a. Like the fragments of a story. I’ll use it as a partner to help me sharpen it up. But it, it’s funny because again, it, you, you learn through that experience what’s good and what’s not.

[00:24:18] Nick Graham: So I, you know mm-hmm. There was giving it something, um, and it came back. It wasn’t quite right. But I, what I’ve learned is, again, I use it as a jumping off point, right? So I’m like, oh yeah, I like this sort of structure, but I’ll go back and tweak with it and maybe, you know, say I’m thinking more this direction.

[00:24:35] Nick Graham: And so I use it to help me sharpen up that and actually just to challenge my thinking. So for example, the other day. I was writing a perspective on, um, the, the future of direction of a particular, uh, uh, industry. And I put it in and said, tell me where are all my blind spots? Like, mm, I think it’s clear. I think it’s sharp.

[00:24:56] Nick Graham: But tell me, if I was an industry expert, where would you poke all of [00:25:00] the holes. Yeah. Great. And again, that’s great. You take it as a, as great input. And again, I think for insights, people telling stories, I think that’s so important to help push that a little bit further. 

[00:25:10] Michelle Gansle: Love that. 

[00:25:11] Nick Graham: Which leads us, I think to, obviously with the shift in AI data, data science, I think it places very different demands on the insights leads of the, of the future.

[00:25:23] Nick Graham: Not just in terms of the skills that they have, but also how they lead, where they focus, where they use their time and energy. So looking ahead, what would be, what do you think will distinguish those insights leaders who really thrive in this new. Even more data centric, AI driven environment. 

[00:25:44] Michelle Gansle: I mean, I think we’ve like led up to, uh, what the answer is, but.

[00:25:50] Michelle Gansle: More and more the soft skills are gonna be the thing that matters. Mm-hmm. Being curious about and following the trends of where it’s going is gonna be so critical [00:26:00] because it’s gonna change so much over the next few years. I was thinking about as you were talking, remember when mobile research first became a thing on the phone?

[00:26:09] Michelle Gansle: Yeah. Like most people were like super poo-pooing it. Like this is a terrible experience. This is never gonna replace surveys, and now you can’t even imagine doing. Surveys on anything else but a mobile phone. So it’s like that, right? Like, but if you poo-pooed it until it was too late, then you would’ve missed the beat on that.

[00:26:27] Michelle Gansle: So I think following the trends, being curious, being critical and skeptical, right? Not just accepting everything that comes along the way will be important, but more and more our ability to connect. Business problems to value creation and clearly demonstrating strategic thinking and bringing that human understanding is gonna be our towering strength.

[00:26:53] Nick Graham: And then what would, as you think about how, you know, we started, we started this conversation talking [00:27:00] a lot about how insights plays with data analytics, technology teams. In that future, how do you think insights leaders will need to show up differently and how they. Partner with and integrate those adjacent, um, functions in order to be successful.

[00:27:17] Nick Graham: Because to your point, we can’t, can’t put our, you know, can’t be ostriches and pretend those other teams don’t exist. Um, but there is, you know, has been this competition tension between the teams. So, looking forward, how do you think really successful insights leaders will play differently with those, with those teams?

[00:27:34] Michelle Gansle: My hypothesis. So, you know, AI is just an LLM and LLM. Responsibilities often sit in data science. 

[00:27:42] Nick Graham: Yeah. 

[00:27:42] Michelle Gansle: So it’s not always the case, but data science either sits in the same team as the AI team is the AI team, or sits adjacent to 

[00:27:50] Nick Graham: mm-hmm. 

[00:27:50] Michelle Gansle: My hypothesis if in my call to action is if insights people don’t learn to be best buddies with those two teams or that team, they’re gonna get [00:28:00] sidelined.

[00:28:01] Michelle Gansle: So like there’s like a real, real need for insights people to get close to that team and work together or else people are gonna just treat the insights teams as like an internal supplier. 

[00:28:11] Nick Graham: Right, right. No, no, you’re right. Exactly. And I think bringing that expertise on the data and, and the business, as you said, the business problems that we’re trying to solve for and what we need AI to help us with, I think is where we can bring.

[00:28:27] Nick Graham: Real value to that, to that conversation as well. Are there, um, from your, again, going back to your experience at McDonald’s, you talked a lot about the briefing moment, right? There are bringing everyone together at that sort of first point, getting the best out of everybody. Are there any other sort of practical tips you would give in terms of how to foster that collaboration and connection between the team, between the teams?

[00:28:52] Michelle Gansle: I think doing something like a day in the life of, you know, just go make, go have coffee chats with them to understand what do you do, what kind of [00:29:00] data do you have could go a long way. The other thing is, you know, I’m a huge proponent of going to conferences, insights. People go to insights conferences and data.

[00:29:09] Michelle Gansle: People go to data conferences. 

[00:29:11] Nick Graham: It’s, yeah. 

[00:29:11] Michelle Gansle: What about like commingling? Yeah, exactly. I know the Insights Association is trying to bring more data and analytics. Sessions to the insights. But I think if insights people went and they did a little bit of cross uh, conference sharing, that would be really helpful.

[00:29:27] Michelle Gansle: Yeah, 

[00:29:28] Nick Graham: that’s great. So I think a lot about seeing the world through the eyes of the other team and um, as you say, so learning a bit more, having curiosity. Right. You talked about having curiosity for the data, the approaches of the other team, because I think it’s only in that you’ll see, it’s that whole sort of.

[00:29:46] Nick Graham: The empathy wall, right? If you can just climb over the wall and have empathy for the people on the other side of the wall, you can, you realize we are, again, we’re all human check, or at least most of us are human. Obviously robots are [00:30:00] coming always. Most of us are human always. But, and again, I think within the context of most organizations, we share a lot in common really in terms of what Of the way we think.

[00:30:11] Nick Graham: The fact that we’re all data driven, just different types of data. And so I think if we can have that in common and actually we’ll realize we can actually be really complimentary and even more impactful if we work together. Easier said than done. I know, because organizational structure gets in the way.

[00:30:28] Nick Graham: Organizational priorities get in the way. As you said. I think a lot of people. Just trying to do a good job and just focus on what’s in front of them. Somebody ask ’em to do something, they just go ahead and do it. But I think if we can prompt people to always think, oh yes, but I think it would be even better if I just go and talk to the data science person.

[00:30:46] Nick Graham: I just go and talk to the insights person before I start work. Yeah. I know when I was at Monley, that was one thing we’d always try, and the sort of the. Five second pause is just to say, before I start doing something, let me just think about who else could I bring into [00:31:00] this, or should I consult on this before I start running?

[00:31:03] Michelle Gansle: Yeah. I’ll give like one more like practical, real example of bringing teams together. So at McDonald’s we were trying to step change how we did forecasting. And in order for that to be successful, what had to come together was the business insights folks, finance, data science, technology, um, and market people in the markets.

[00:31:25] Michelle Gansle: But they all came together and what they delivered in terms of step changing, how McDonald’s as forecasting couldn’t have been done if all of them hadn’t come together and to, to see. Team collaborating in that way and doing something that is like the most impactful business value creation that of any initiative in the company.

[00:31:45] Michelle Gansle: And they all, you know, got shared credit for it. It was like really cool to see, not without its drama along the way, but um, but an example of bringing multiple teams together to solve a business problem gets you to a better outcome than on your own. [00:32:00] 

[00:32:01] Nick Graham: Which, as you said is, is messy and complicated and political and you know, it, it can feel so much easier just to go off and do it in your own silo because it’ll feel a hell of a lot easier and hell of a lot quicker.

[00:32:16] Nick Graham: But actually, as you said, the business, the impact and the business value that you can create and the, the reward and the satisfaction actually getting to a better answer far outweighs the. There’s, you know, there is a bit of pain. There’s always pain in teams having to work together. It’s humanity.

[00:32:32] Nick Graham: Welcome. Yeah. Um, I wanna finish off by talking about, you know, a lot of times in the podcast we try and bring it back to, uh, people are the, sorry, I’ll start again. Um, I wanna try and bring it back the conversation now to some advice for the next generation of insights leaders. You know, a lot of the.

[00:32:53] Nick Graham: Folks listening to the podcast will be early, mid stage career, many of whom are looking around the [00:33:00] changes that we’ve been talking about, right? Data science, big data, ai. There’s a lot of uncertainty right now. So as you think about the next generation of insights, talent that, that you are seeing, you, do you, are you seeing that they’re coming in with the skills that they need to succeed and, and what do you, what would you encourage them to be focused on to help them continue to raise their game?

[00:33:23] Michelle Gansle: The great thing about younger people is they, you know, were born in a digital life and so I think unlike more seasoned insights people, they adopt tools and technology faster. Mm-hmm. I think the opposite thing for younger people is, especially those who’ve started their career during COVID. Now that we live in a hybrid work world, we have less water cooler moments.

[00:33:46] Nick Graham: Yeah. 

[00:33:46] Michelle Gansle: And so you, that’s a good point. You lose the opportunity just to learn through osmosis and through informal interactions from other people. You know, my number one thing would be younger people need to work harder [00:34:00] at creating, um, non-obvious connections. So creating virtual coffee chats, going to conferences.

[00:34:09] Michelle Gansle: Showing up to work and walking around the hall rather than just sitting at their table, you know, and working. Um, because you can’t, the intangible benefit of learning from others and building informal networks beyond those you have to work with is like the difference between being successful and not being successful.

[00:34:29] Michelle Gansle: And I don’t think people intentionally, um, plan that into their day and their work today. 

[00:34:37] Nick Graham: I think that’s true. I think you’re right. The, the hybrid hybridization or the remote hybrid, hybrid remote working makes it even more challenging, right? Because, uh. It feels harder to kind of create those spontaneous connections.

[00:34:50] Nick Graham: But to your point then, why there’s huge value in that, and then how do you carve out those moments to get to know people, to spot the connections [00:35:00] between your, your team and other teams? It’s, uh, it’s hard work, but I think you’re right. I think it’s, I think it’s a key space to focus on. Well, I think that’s a great way to close it.

[00:35:08] Nick Graham: Thank you, Michelle, and thank you for bringing such a thought provoking, refreshing, honest perspective, this conversation. I’ve really enjoyed it and I know a lot of the topics, uh, that we’ve covered today will be, uh, really top of mind for our audience. So really appreciate your perspective, your pragmatic tips as well.

[00:35:24] Nick Graham: I know they’ll be really helpful. And if anybody listening has some of their own tips, their own suggestions, how to use, how they’re using ai. Thoughts on how other people can, can use ai, how they’ve built relationships with their data and analytics teams. We’d love to hear them as well. So please, uh, add them to the conversation.

[00:35:40] Nick Graham: Add them to the chat. Thanks everyone for listening to the latest episode of the Insights and Innovators podcast. Until next time, I’m Nick Graham. 

[00:35:48] MRII Announcer: Thanks for joining the Insights and Innovators podcast for Market Research Institute International. Click subscribe to never miss an episode and visit us@rii.org for more market research [00:36:00] insights.