Episode 242 / Tina Tonielli / Haleon / US and North American Lead, Consumer and Business Insights and Analytics
Diving Into Data: How Insights Pros Can Supercharge Curiosity with AI
Tina Tonielli is the US and North American Lead, Consumer and Business Insights and Analytics at Haleon. With over 17 years of experience at Johnson & Johnson working on brands like Tylenol, she has also held insights functions at Pfizer and GSK. Her Shiny New Object looks at the dichotomy of AI: how people should use AI as a supercharger and not a crutch.
Balancing Automation and Manual Analysis
Tina emphasises the importance of balancing advanced analytics with descriptive analytics and performance management in data driven marketing: "If you don't understand the mechanics behind your business, you're toast." Her top tip is to regularly explore raw data sources to gain unexpected insights. "Those little quick laps in the data are where you'll see nuggets you weren't looking for." After all, serendipitous data discoveries are just like serendipitous conversations in everyday life - you never know when one could change your life.
AI as a Supercharger for Curiosity
Tina's Shiny New Object is using AI as a supercharger rather than a crutch. "People think of it the wrong way, as a ‘serve me’ culture versus a curious culture." Instead of supercharging the ability of AI to retrieve data, while making an effort to make more of the data received, most marketers are now content with just “asking AI to solve questions.”
Tina sees potential to enhance curiosity during business reviews and post-campaign analysis. By cultivating curiosity through generative AI, insights professionals can gain a deeper understanding of their business.
Preparing for an Uncertain Future
Marketers should not underestimate the importance of anticipating trends far in the future to avoid being caught off guard. As Tina says, "Some of this stuff is pretty predictable if you look at it." Going back to the focus on analysing data - if you look and ask questions, you will uncover patterns that can give you an advantage for the longer term. Just like Hasbro’s David Khoshpasand explained in an earlier podcast, marketers and business leaders need to stop looking at the near term only and identify trends with a longer timespan in mind.
Find out more about balancing the capabilities of machine learning and automation with human analysis and curiosity, as well as more tips from Tina on maximising insights and marketing performance, in the full episode.
Transcript
The following gives you a good idea of what was said, but it’s not 100% accurate.
Tina Tonielli 00:00
those times where you go swimming in the data in the database, those little quick laps, you're gonna see some of those nuggets in that data that you weren't looking for. And you'll never see those nuggets if all you're looking at is a completely like beautified chart.
Tom Ollerton 00:20
Hello, and welcome to the shiny new object podcast. My name is Tom Ollerton. I'm the founder of automated creative, we are a creative effectiveness ad tech platform. And every week or so I get to interview one of our industry's leaders. And this week is no different. I'm on a call with Tina Tonielli. Who is US and North American lead consumer business insights and analytics at Haleon. I'm in New York and Tina, you're in New York too but we're different ends of the state and it seems such a shame not to be doing this in person. But here we are on a call, so for anyone who doesn't know you and what you do. Could you give the audience a bit of a background?
Tina Tonielli 00:56
Yeah. So the journey of Tina Tonielli started with Johnson and Johnson as a marketer. So I always joke that I'm a marketer at heart. So I spent my first five years of my career doing brand management at Johnson and Johnson on their OTC products. And then I took a little leap over, a leap of faith, so to speak into the insights function, which was called Market Research at the time, not to date myself, but I was intrigued by the idea, and it stuck. So I stayed there for a long time. I've been there ever since actually. So I stayed at Johnson and Johnson, specifically in the OTC group for about 17 years, I worked so long on Tylenol that they called me triple T. And then I decided to try something wildly different and went over to Pharma. So I worked on neuroscience, which was primarily schizophrenia, and infectious disease, which was primarily HIV, so really, really different than OTC products for headaches. So I worked there for three years, and I learned a lot about data and doctors and advanced analytics and really got some good learning. And then I felt the swansong of the consumer calling me back. And I got a call from a recruiter who asked me to come and transform the insights function at Pfizer. And after four weeks of emotional processing, I decided to go and take them up on it, because it would mean going to work on Advil, Tina Tonielli of Tylenol going to work on Advil. So I went over and led the insights function, the insights and analytics function for Pfizer consumer. And then I've gone on a wild ride of Pfizer, GSK. And now Haleon, which is this aggregate of all of those businesses together now we're standalone, publicly traded company for consumer health care. So it's been a bit of an interesting journey, that's for sure.
Tom Ollerton 02:45
Right? What a journey. I have high expectations, Tina, so here we go. So in the last five years or so what has been the best investment of your own time, energy, or money in your career?
Tina Tonielli 02:58
Yeah, so it's probably not what one would think the best investment that I have made of my money and my time, and to me, time is more precious than money. Because we never seem to have enough of it, I definitely don't have three kids at home, and work full time. So I don't have a lot of time, the best investment of my time, honestly, Tom are those informal or sometimes formal chats with people. And a lot of times they're chats without a specific topic. They might be catching up with someone where I'm mentoring someone new in their career, or it might be catching up with someone who I haven't talked to for a while, or someone new to the organization came in and just wants to learn what my, what my particular function does. I learn so much. I make connections, I connect different projects, I learn about new people I know learn about projects, I'm able to share with them what I work on, it's really, you get that informal connection that really enables you to get so much more accomplished than those three hour meetings where everybody sits around a table and doesn't get anything done.
Tom Ollerton 04:09
Yeah, I agree. You never know when one thing that one person says will change the course of your life I find and you have to be open to those conversations, right? You can just have a be meeting someone casually or as you say at different stages of their career, but someone's perspective can get distilled in just one moment to make you think completely differently about things. So I absolutely shared that view so quick one, though, how do you give yourself permission to do that? You know, because you've got your three hour meetings, you've got your deadlines, you've got your commitments, often the benefit of these talks can be not immediately obvious. So if your boss is saying what you're doing now Oh, I'm gonna go and speak to so and so about. I don't really know, do you find that quite hard to justify or how do you explain those choices to the people you work with?
Tina Tonielli 04:52
Yeah, no, that's a great point. So I don't call them like random calls with no agenda. I usually just call them connections. And I find that if you call something a connection, nobody doubts it or questions it. And I just I've been very open and made myself very available to a lot of people. And I've, I've really openly and and like I said, I've been very public and open about the fact that I'm really my virtual doors always open, I like to say to people, so if somebody is curious about something, or they want to talk about something. Now, granted, obviously, it's not like I you know, accept anybody who comes in the door, but I generally will, will try to make time for people and half hour is not that bad. You can make a half hour work out of a week for for just about anybody. And I would say I probably do like one or two of them a week, a couple of them a week with people and just learn new things or teach new things to people.
Tom Ollerton 05:58
So we're gonna move now on to data driven marketing specifically. So what is your top tip for data driven marketers that you work with? Do you have a silver bullet bit of advice, something you've learned that you find yourself passing on to people quite often?
Tina Tonielli 06:12
Yeah, so my, my current, I would say, drum that I'm beating with people, I have a lot of drums that I beat with people on this one, this one that I'm meeting is, as we have moved up the advanced analytics curve, and gone up into predictive analytics, advanced analytics, AI, generative AI, as we've moved up that curve, we've lost sight of some of the more base analytics. And if you look at the base analytics, the descriptive analytics, the performance management, the understanding how your business is going, the mechanics of your business, the mechanics of people, that is the basics of how you run your business. And what I have noticed, that's terrifying, is there's a lot of people who can read a graph that like a algorithm, or, you know, a model spits out, but they don't understand the mechanics behind it. And if you don't underastand the mechanics when you're when your car breaks down, you're toast. And so I think what I've been talking to people about a lot is we really need to balance and make sure that we have both ends of those spectrum covered. And we don't atrophy the muscle, at the base and the bottom because it is the foundation. It's not as sexy or exciting as AI, I get it. But it is the foundation and you want a solid foundation.
Tom Ollerton 07:39
So how do you make sure that you do that? Right? So someone's listening to this going, and I love that line don't atrophy the muscle? If someone's going, Ah, that's happening to me, how do you make sure you don't do that or stop doing that?
Tina Tonielli 07:51
So I would say, Now, granted, I'm going to date myself a little bit on time here. But when I was a young man, you know, when I, when I started, we did a lot of digging in databases. So there's a lot of stuff that has been automated, which is great. I'm all for that. Not, you know, doing major manual, putting together PowerPoint slides and the like. But people are afraid to jump into the pool of data I find. So either you have folks who are like real comfortable in data, they might be like model makers, and you know, the data scientists and folks like that. And then there's the folks who are like terrified to jump in the pool of data. And when I think you know what I mean, when I say jump in the pool of data, it's like, literally, if your business has a database, or cross tabs or anything where you can get at more raw data, do it. Get in there, see what you see, look for the patterns and data, look for the insights about your business or your consumer, like get down and dirty in that raw data, versus sitting back and waiting for someone to send you a beautiful PowerPoint slide that has been completely like, fixed for you.
Tom Ollerton 09:09
Yeah, so what where's the line between automating the analysis of that data and at worst, eyeballing that, right? So sure, you could get you could really get into the weeds of it and trying to make your own conclusions, but then isn't a well written automation or analysis, what we really need? So help you understand what are the shortcomings of not writing the automated way through it and as you say, getting manual with it.
Tina Tonielli 09:33
Yeah. So I am an eternal optimist time. And I believe in the power of and which probably drives some people who work with me not so certainly my family members occasionally get driven nuts by that. And so to me, it's not a black or white decision. It's not well, you either get that beautifully insightful document, or you got to get down and dirty and build it all by yourself, it's actually both. So if you think about it, you should be getting that cultivated insights, and you should be getting some automated things, and you should be able to look at that. But at the same time, you should continue practicing, getting into that database, whether that's once a week, once a month, but like, Don't let a year go by, and you haven't dove into the database, one time to see what's going on with your business, or what's going on with your brand or your consumer. So if you have to schedule it once a week and say, Hey, I'm gonna go see what's going on with my business or by the way, a great time to do it is if something's not going well. So if you're sitting there like, we're not performing as well as I think we should be in X retailer, or that particular SKU is not doing as well as I want it to be doing. Those are perfect opportunities, Tom, to just put on those what are they called, the little, the floaties, jump in the pool, you know, and go swim in some data, because you have you have an actual objective to go do it. I'm not suggesting that we go back to the days when people built all of the decks themselves, no. But also, we can't go 100% over to the other side, where, you know, we're sitting there just ingesting graphs and charts and don't understand the data behind it. Because by the way, like I said, those little chats are those moments where you find things that you didn't realize you were looking for, or you didn't think you might learn those times where you go swimming in the data in the database, those little, little, you know, doing a couple quick laps, not not spending all day there, but a couple quick laps, you're gonna see some of those nuggets in that data that you weren't looking for. And you'll never see those nuggets, if all you're looking at is a completely like beautified chart. Hopefully that makes sense.
Tom Ollerton 11:57
It makes a lot of sense. And it rings very true with one of our things we say a lot at Automated Creative, that people confuse automated with optimal automated is something you know, you press a button and happens, right, you know, we can or literally automate the production of creative but actually, the optimal thing is when you have a human brain in there thinking tangentially because an automation is a set of rules, usually set by a human. But to your point, if there's something wrong or it's not doesn't cover everything completely, then you're going to miss something. And you do need, as you say, put the armbands on, as we sit in the UK and jump back in the pool, and we think you're not going to get the best creative, you're not going to get the best result if you purely automate everything, you need the creative side of it as well. And you're a different person every day, right? So you might come up with the same dataset or creative problem from a different angle just because time has passed. So yes, it's interesting to hear that from a insights perspective, as well. But now it's time for your shiny new object. So your shiny object is quite a long one. How people should use AI as a supercharger and not a crutch.
Tina Tonielli 12:57
Yes.
Tom Ollerton 12:58
So I mean, you could just leave it there to be honest.
Tina Tonielli 13:03
And scene. No.
Tom Ollerton 13:10
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Tina Tonielli 13:40
It's actually like a continuation of the conversation we were just having Tom, I think it's, it's a supercharge of the conversation we were just having because what I'm seeing happen now is folks are so in love with what the possibility of what AI can do, which by the way, I'm also in love, like it is amazing. But the danger to me that I'm seeing ahead of us is if you use AI, if you're misusing machine learning, and you're misusing some of that earlier, more advanced data and automation, like you were saying, Tom, and you put AI into the mix. It's almost like I was gonna use an inappropriate metaphor, please. Sounds like you're giving somebody who's who's addicted to the wrong thing, like an even more powerful drug, right? Like you're not you have to, you have to know the right way to use it in order to get the most out of it. Versus if you're using something as a crutch to begin with and you give them an even bigger crutch, then you're only making the issue you're you're making that muscle at the bottom even more like atrophied So I am terrified that people are going to just go further up that curve, because they're like, listening to the swan song of generative AI. And they are not realizing that that that muscle has literally just like, gone and withered. And one of the biggest things that I see from people, and it goes back to that like swimming analogy that we were talking about, people are kind of afraid to go into the water, but they and they've forgotten how to swim like people are not curious. At the level that they used to be. I notice then that there's almost like a fear associated with going into the water versus, in the past, people would be sitting there. And sometimes this would be like the hallway banter conversation or something, hey, what's going on with your business and Walmart this week, you know, oh, let me go look, and person would go look, and they would roll up their sleeves and see what was going on. And they come back and be like, Man, it's not just Walmart, it's also Walgreens. And I got an issue over here. Because they went in and looked at the data. And they were curious about it. While they were there, they looked at something else. And they were curious and interested. And now people sit back and just wait. So they're like, Okay, Google hand me my spoon, please. You know, it's like the serve me culture versus the curious culture. So I think what I'm trying to do in my role, and I want all of us to try to do this is how do you use AI as a superpower for curiosity? So that's what I was talking about Tom in the beginning of like, a superpower instead of a crutch. If you use AI, as a supercharger for your curiosity, which I personally think generative AI, I think could be an amazing superpower for curiosity. But people have to see it that way. So people have to get comfortable with being curious. And remember what it's like to feel curious and be curious. And actually kind of go play a little bit with generative AI. It's not doing a use case where everything is perfect. And we have all the answers, and it's automated. And now you can do it and you know, three less hours, it's like, no, I can actually go in there and brainstorm. And it helps me like, when I get stuck on something, it can help me think through things or it can help me, you know, think of the different pawns where I want to investigate. So I think people think of it the wrong way, a lot of times, and I then, and we have a danger of that muscle, really getting a lot weaker. And that muscle is the foundation of how we think about running our businesses. So it's kind of important.
Tom Ollerton 17:49
So Rhoda Sell, our CFO, has this lovely phrase, which is everyone is trying to use AI to do the same thing that we did before faster and cheaper. But we're trying to use it to do it better, right? And that's why that's why that's why I got on board with your supercharge. It's like, right, okay, yeah, sure, if everyone can use AI to do things faster and cheaper, it only cost 20 quid a month or something. So everyone's gonna do it. It's not an advantage. It's a disadvantage to not do it to get to the same place everyone was at. But like, that's what fascinates us in our our insights and creative business is to go right, well, what can we do now that we couldn't do before? So I'm going to push you a little bit here. So you talk to the very high metaphorical level, swimming analogies. Can you get specific right without giving away trade secrets? Is there an element of your business or or a practice that you see people falling most foul of? Is it post campaign analysis? Or is it sifting through the data you're getting back from the Walmarts, or the Walgreens like, just give me a specific example of whether you've seen it not done well. And you would like to see people supercharges as opposed to the use it as a crutch?
Tina Tonielli 18:59
Um, yeah, I think there's two areas of opportunity that I see. And we don't have it like unlocked in terms of the technology at this point. And so to me, I'm going to talk about this as a potential future application. But we have to get our curiosity at the right level in order for me to feel comfortable bringing it into that application, if that makes sense, Tom, so, but I will get real specific. So there's two areas I can think of off the top of my head. So one is on a monthly basis, and I'm sure every company has something like this on a monthly basis, you have a business review, right? And you you know, the managers of the business, talk to the executives about the business and they come in and they say here's how my business is doing. And they present that if you're, you know, on track, off track and why and why not right, everybody does that. And today that conversation goes something like, why? And you start asking questions or around why the business is doing what it's doing. And the executives who grew up swimming in that data are expecting the team to be able to answer questions at a much deeper level than that team is able to answer because they're not swimming in the data, if that makes sense. So my point that I'm making here is, I think if you reversed your thinking and said, instead of automating everything, so that the people who are coming in and talking about their business didn't come in with like, something that had been cultivated by someone else, versus they spent their time preparing for that meeting with a supercharged curiosity for their business, that they could go and understand really quickly what's going on with their business Tom, like at a more granular level, so like, swim with sorry, I love metaphors. So I apologize, don't but like, I don't know, put the flippers on, or like, it sounds as though you can go faster, right? So you can make that process of learning and swimming faster. Versus we kind of took them out of the pool, and we're handing stuff to them. So it's like, how can we get them in that pool and get them swimming faster? Which I think was your point about? You know, how do you get somebody to do something better, versus taking that job away from them? Like, I feel like we took jobs away from people and gave them to, you know, AI? Because we said that job was beneath people. But instead, Could we somehow give them an opportunity to do a job in a supercharged way so that it feels like it's so much easier, and they can get so much more out of it? Was that granular enough Tom? It's good, it's good. We're running out. We run out of time a bit, unfortunately. But I think it's a fascinating space. And what I like about your view is you're not being defensive, you're not saying well, you know what, you go back to the old way, you just say, Look, you know, to support the thing that you are doing with AI, actually, the classical education beneath it is that this is the thing that's gonna give it more validity. So the last question, I have been reading a book recommended by a podcast guest, I'm sorry, I can't remember who but it's called Fooled By Randomness. And the whole premise of the book is that humans are terrible at thinking probabilistically I can't even say the word. But what it comes down to is that we are totally oversubscribe our role in things, right. So if we're a trader, we might make a good trades, we do really well. But I will, I will start maybe in a great trader, or if you're an artist, or whatever it is, well, it worked because it was me, whereas in reality, there's just a ton of random events, big black swan events, like COVID, for example, or that you have some seismic shift in in the world. And actually, all of those things are far more of effect in the effort we make. So in an insights world, which a lot of you speak, don't realize you could go market research, and it says lots of news marketing itself to itself. Yes. When it comes to using AI or not, or getting into the data with you, with your own bands in the pool, how would you approach making sense of your own data when there's things that are completely outside of the data set? So for example, we saw this sales of this product go through the roof, but actually, what's not in your dataset? Is the competitor not running ads that day, or, you know, or they didn't get put on the shelf. So how do you model for that? Tom, that's like a million dollar question right there. So, I mean, I would say two things, I would say one, you know, you're always gonna get it wrong. Because you, you are Fooled By Randomness. Like you're always going to miss something, when what if you're predicting the future, you're always going to be wrong, it's just how wrong are you going to be? And so you want to try to be sort of within a realm of reasonableness when you predict the future. The other thing that I've started to do with our organization is trying to look far enough into the future, that you're not shocked by things when they happen. So like, we generally look what's happening right now, or we look at the next quarter, or we even call things a trend, but it's like stuff that's happening right now. Or we look at technology, we're gonna start looking at stuff like, what does society look like 10 years from now? What does the climate change look like 10 years from now, we never do that kind of thing, because we're all so busy. But if you start doing that kind of stuff, I bet if somebody would have done that 10 years ago, they would have probably said there's very possibly going to be a global pandemic. In fact, I think they did. Like I think there were people who said that, and there were companies that already had that in their scenario plans. So I think part of a time is you got to anticipate the stuff that nobody's thinking about but if you think about it, you actually would anticipate it
Tom Ollerton 24:39
I think Amazon do a regular thing every year. I mean, might be fiction, but that I heard I read that every year they go right what's going to destroy Amazon this year? Is it a pandemic or is it like a war or and then you need to have a plan in place for when thing happens. So you're actively working out when your business is gonna fall over. And then you make a plan for when that thing does you like, oh, who had the thing about Godzilla? Brilliant, okay.
Tina Tonielli 25:10
We got the Godzilla plan, like it's already locked, you know, like, it's the it's the gift of hindsight. In foresight, I think like, you always say, Oh, if we don't if we only thought about this, you know, 10 years ago, for you only had that gift of hindsight, it's, I, I'm excited by the idea of putting yourself into the future. Because guess what, some of this stuff is pretty frickin predictable, like, the climate. If you look at it go, Okay, well, here's what's happening. Yeah, it's probably not going to slow down. Like, there's stuff that's obvious, if you really look at it Tom. And so doing that and giving yourself that moment, it is a little depressing. But if you look at that future straight on in the face, and then say, okay, that's the future, what am I going to do now to get us ready for that future? It's really eye opening. And so then you're not caught up in that? Is it 5% or 10%? Or is it you know, what is the respiratory category going to be this year? It's not like that. It's more like, hey, we really should be thinking about this, you know?
Tom Ollerton 26:11
Yeah and it harks back to a conversation I had with Rebecca McCowan, who's a design director at Coke in Europe. And she was talking about from a design perspective, talk about slow design, like how do you design a brand to grow over a 10 year period? You know, it's not a matter of releasing a new format, and everyone's gonna rush in there and produce their like, 3d GIF, and the metaverse whatever it is, is like no, go on, these things aren't gonna change, like, how is this? How is this visual going to be iconic and last for a 10 year period? It sits quite nicely along your like, Well, you know, what is definitely going to happen. And oddly, in chats with people about their own career planning and stuff. I'm always like, well, look what's small now that's gonna be massive in 10 years time, like, go there. Right? Yeah. Because if you get on the train now, well, it's it's growing fast. But small, then you'll be on the, you know, the most exciting thing in 10 years time. So it's really good to have this conversation, you've provoked a lot of thoughts. And I'm going to, I'm going to start throwing swimming pool analogies around.
Tina Tonielli 27:09
Feel free, we call them arm bands, right? I'll start calling them arm bands instead of floaties. And then I'll sound very cultured
Tom Ollerton 27:17
Floaties has a very unpleasant English to it. But I will, I will discuss offline. So final one, if someone's getting in touch with you about floaties or anything else, where's the best place to do it? And what makes a message to you that you respond to?
Tina Tonielli 27:42
Yes. So I'd say the best way is my email at tinaxtonielli@haleon.com. And what tends to work for me is I'm a sucker for people looking for advice or perspective, because I like to make things better. So that tends to work versus it's almost like the pull instead of the push tends to work better for me. So if there's something that you're working on, that's going to make the world a better place, or help people, and you want some help in making it better. That usually is more of a siren song for me than like, Hey, we got this new, great thing that's going to like grow your business tenfold. Like I have a lot of those. It's more the other than that tends to get my attention.
Tom Ollerton 28:31
Brilliant. I think that's great advice for anyone writing messages to anyone. So thanks for that. Tina, that was a lot of fun. And unsurprisingly, so many lovely things to take away. And remember, I really appreciate your time. Excellent.
Tina Tonielli 28:42
Thanks so much for the opportunity Tom, take care.
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