Topics
Artificial Intelligence and Business Strategy
In collaboration with
BCG
In collaboration with
Stéphane Lannuzel has worked in the beauty industry for 15 years and now directs the Beauty Tech program at L’Oréal. His team uses artificial intelligence to improve customer experience in a variety of ways, including helping consumers try on cosmetics virtually and providing product recommendations. L’Oréal recently developed TrendSpotter, an AI-based social listening tool that tracks macro-influencer posts and other online content and informs the cosmetics, skin care, and hair products company of upcoming trends that can then inform new product development. Listen to this episode to learn how Stéphane sees AI, and technology more broadly, as a force of good and the enabler of more meaningful professional and customer experiences.
Read more about our show and follow along with the series at https://sloanreview.mit.edu/aipodcast.
Subscribe to Me, Myself, and AI on Apple Podcasts, Spotify, or Google Podcasts.
Give your feedback in this two-question survey.
Transcript
Sam Ransbotham: How is AI helping one beauty company spot key trends? Find out on today’s episode.
Stéphane Lannuzel: I’m Stéphane Lannuzel from L’Oréal, and you are listening to Me, Myself, and AI.
Sam Ransbotham: Welcome to Me, Myself, and AI, a podcast on artificial intelligence in business. Each episode, we introduce you to someone innovating with AI. I’m Sam Ransbotham, professor of analytics at Boston College. I’m also the AI and business strategy guest editor at MIT Sloan Management Review.
Shervin Khodabandeh: And I’m Shervin Khodabandeh, senior partner with BCG, and I colead BCG’s AI practice in North America. Together, MIT SMR and BCG have been researching and publishing on AI for six years, interviewing hundreds of practitioners and surveying thousands of companies on what it takes to build and to deploy and scale AI capabilities and really transform the way organizations operate.
Sam Ransbotham: Today, Shervin and I are talking with Stéphane Lannuzel, Beauty Tech program director at L’Oréal. Stéphane, thanks for joining us. Welcome.
Shervin Khodabandeh: Hi, Stéphane.
Stéphane Lannuzel: Hello. I’m really happy to be talking with you today.
Sam Ransbotham: Let’s get started. Stéphane, you’re at L’Oréal. Can you tell us about your current role? What does a Beauty Tech program director do?
Stéphane Lannuzel: I’m in charge of the beauty-tech transformation, which is a global transformation in all functions and in all geographies. And that adventure in beauty tech for me started in 2019 with the vision of our CEO — at that time, that was Jean-Paul Agon — who was really visionary in the fact that tech will disrupt the beauty industry. And he really listened and talked with all the CEOs of the big tech companies, asking them the question of what tech will do to beauty — how tech will impact beauty. And that’s how we started on that journey, saying that we want to be the champion, the leader of beauty tech, to be the No. 1, because at L’Oréal, we are the leader of the beauty industry, so we decided that we wanted to be the leader of beauty tech.
And I started with that mission, being the Beauty Tech program director, with only these two words: beauty and tech. And basically, the simple motto of Beauty Tech is to invent the beauty of the future while transforming into a company of the future. So what I’m doing every day is inventing the beauty of the future and transforming L’Oréal into a company of the future.
Sam Ransbotham: What did you learn? How will technology affect beauty? What’s going to be the big change?
Stéphane Lannuzel: There are two big impacts. There is the development of services for our consumers, but there is also, “How can we leverage technology to make the life of our employees easier and make them faster and more creative and more nimble?”
Let’s start first with consumers. L’Oréal has been around for more than 110 years, and we produce 7 billion physical cosmetic products every year, but we are more and more into services, and basically tech is playing a huge part in developing beauty services. We have been working a lot on helping consumers, through services and through technology, to be able to find the right product for them. [For] example, we have developed some solutions using AI and computer vision and augmented reality to be able to do virtual try-ons of makeup.
Another example is a skin diagnostic to make some recommendations in terms of what are your top concerns and what are the products that you should apply in your daily routine. So this is how technology is really transforming beauty, because we want to develop a beauty that is more and more inclusive — a beauty that is more and more personalized.
Sam Ransbotham: You’ve got a varied background in banking and consulting and luxury and consumer goods. Can you tell us a little bit more about what got you to your current role and, in particular, what got you interested in artificial intelligence and applying these technologies in your current role?
Stéphane Lannuzel: I’ve been in the beauty industry for 15 years now, so after consulting, I worked for many luxury or cosmetic goods companies. I decided to really be part of that industry, and I joined the cosmetic industry, first in Shiseido and then in L’Oréal. Technology was not that prominent when I graduated a long time ago, but what I’ve done throughout my career is really look at how we can make the organization evolve to be able to cope with new trends. And obviously, people play a major part in that — the way you add new skills in your organization, the way you structure the organization. And more and more, technology is also playing a key role.
I’ve always been very curious in looking at how technology was evolving and trying to see in my industry, in the beauty industry, what could be the impact: What can I leverage? I think that’s why I’m the head of Beauty Tech: because I’m really into being curious about technology, being a strong believer of transformation, and being a strong believer that organizations and people can adapt and can be even better if you give them the incentive and you upskill them in the use of technologies. I’m a very optimistic person, and I’ve always seen tech as a force of good for the people, good for the planet, and really very curious at embracing new technology.
Shervin Khodabandeh: You mentioned upskilling. Do people at L’Oréal need to know anything about artificial intelligence?
Stéphane Lannuzel: Yes, they need to know. And not only the data scientists or the few people that are really practitioners of artificial intelligence, but everybody. And here we’ve created the tech and data university for L’Oréal that is targeting [our] 88,000 employees. Obviously, we have different programs — some programs [that are] more acculturation, and some programs that are really hard core. And we do get requests from general management: “Tell me about artificial intelligence and what I need to know.”
What I am saying is that we don’t need everybody at L’Oréal to know how to code in Python or to select the right hyperparameters of models. But what they need to understand is what we can do with artificial intelligence, what we can’t do, what we can expect, what we can’t expect, in order to deal with these solutions that are making some recommendations; [and also] how we should use them, and what are the limitations. And I think every manager needs to develop some knowledge on that. And I’ll give you one example.
We are developing some solutions to help the people in the labs to do the formulation of all our products — more precisely, to help them to predict the performance of the formula when you change one or a few ingredients, so that they don’t have to formulate in the real world, make the test, and get the results. They can do that digitally using the algorithms. And the type of reaction that you get when you start working on that — there are people that are saying, “I’m not going to help you train or validate the models on a solution that will probably impact my job in the future.”
And there are people that are also saying, “This is not working. I found one case where it’s wrong. Even if it’s right in 99% of the cases, I’m not going to use it because I don’t trust the system.” And these obviously are two extreme cases, but that’s where the middle management and the general management have a strong role to play to help the democratization and to help people have the right interaction with these solutions that are part of the artificial intelligence that we develop.
Sam Ransbotham: In some of the research that Shervin and I are currently working on, this idea — and what you’re describing is how you would work with a coworker, not really how you’d work with a technology — I think a theme that’s starting to emerge is that, just like it’s true that I’ve made a mistake or two in my past (I know that’s hard for everyone to believe), but I’m glad that my colleagues didn’t immediately throw me out and say, “Oh, you’re useless. You’re pointless. Why would I ever work with you again?” And what you just said there was that same sort of perspective that we have. We have an expectation of a technology that we don’t necessarily have of people. It seems like people are shifting more to think about a team being composed of humans and of machines.
Stéphane Lannuzel: I fully agree. And I can tell you that in all the different solutions that we have developed with AI in them, I’ve always underestimated that aspect, but people really still see that as a technology and not as a help to achieve some task. And it takes a lot of convincing, a lot of explanation.
Shervin Khodabandeh: Do you have any examples of AI projects or products that are being well received at L’Oréal?
Stéphane Lannuzel: We are developing a solution to detect beauty trends. It’s called TrendSpotter. When you look at what is happening in the academic world, the research world, the macro-influencer world … we are reading the different posts that they make on social media, reading some papers, getting some ideas, and seeing some trends emerging on ingredients and on the whole thing. So those are the initial seeds of a new trend that is emerging. And then you are looking at all these trends that are then being amplified by, let’s say, the general population. So without revealing all the secrets, it’s listening in on these different groups across different geographies — in Asia and the U.S., in Europe — that you see some trends emerging.
Sam Ransbotham: Sign me up. I mean … can I get access to it? I certainly need all the help that I can get in that department. I like the idea there, though, because obviously that can aggregate a ton of information from lots of different sources and let you pick up on things early, because I’m guessing you face a time crunch, too, because to go from an idea for a product to a product isn’t an instantaneous thing. And so the more lead time you can get on when those products are coming, the greater you’re likely to have them on the shelves when someone comes in. How does that process work? How do all those pieces come together?
Stéphane Lannuzel: When we were working on that TrendSpotter solution, we were really not starting from the technology and the idea but starting from what you said, which is, what is the usage? What is the usage of knowing a trend? And basically, what we realized [is] there was one use — the one that you mentioned — which is, OK, how can we identify a trend that will then translate into a product that will be launched, as you rightly said, in 12 to 18 months?
So basically, the obvious need [is] where we need early on to be able to detect some early-stage trends. But there was another use that we discovered: You can also use a new trend to be able to activate part of your existing portfolio, meaning that you see a trend popping [up] — and we do have quite a wide range of products. So there are probably products that are corresponding to that trend, so then you will work on, OK, what can I do in terms of making the activation to these products to be able to answer the trend? So what you can see is, trends have different horizons, and depending on the horizon, then you can choose what you do. And that’s what you discover when you do proper user research to understand their needs then.
That was a new expertise for us that we have acquired to make sure that in all the solutions and services that we develop, UX [user experience] is really at the center of it. And there are some skills that we have developed and internalized. Basically, we were doing consumer research. We were doing some research on the design of the packaging, but we are doing exactly the same work. We have different specialists on the digital services that we developed. And it’s really key to develop services that make an impact for consumers.
Shervin Khodabandeh: That’s fantastic. Sam, do you want to move to the five questions?
Sam Ransbotham: We have a segment where we ask you a series of rapid-fire questions. So just say the first thing that comes to the top of your mind. What’s been your proudest moment with AI so far?
Stéphane Lannuzel: It’s always difficult to pick one. Very top of my mind, I think, is when we’ve launched a solution that is helping to do a quick analysis of reviews and ratings and really to see how people can now leverage what consumers are saying on our products, and really leveraging that information at scale throughout the world, throughout the category. So it’s really … for them, it was mind-blowing to get access to that information at that scale.
Sam Ransbotham: What worries you about artificial intelligence?
Stéphane Lannuzel: Always the same subject, which is about bias — bias that we don’t see that creeps in.
Sam Ransbotham: What’s your favorite activity that does not involve technology — that has no technology?
Stéphane Lannuzel: On the personal side or the professional side?
Sam Ransbotham: Personal side, yeah.
Stéphane Lannuzel: I would say running, because it is my favorite activity. But it doesn’t qualify as not involving technology, because I use a watch, and then I track my performance using technology.
Sam Ransbotham: I think that’s a common trend — that everyone finds that whatever they’re doing that involves no technology actually does involve technology.
Stéphane Lannuzel: It may, and yes.
Sam Ransbotham: What was the first career that you wanted as a child? What did you want to be when you grew up?
Stéphane Lannuzel: I graduated as a civil engineer, and I wanted to build bridges, so that’s what I started to do in the very beginning of my career. But I quickly moved away from it and worked, as you mentioned earlier, in the banking industry doing project finance for infrastructure projects.
Sam Ransbotham: What’s your greatest wish for AI in the future?
Stéphane Lannuzel: I think it’s really helping us to improve the world in which we live and to help us solve the climate issue that we face. I’m a strong believer that only technology will help us find solutions to face the difficult situation in which we are in.
Sam Ransbotham: Sounds good. Stéphane, thanks for a great discussion. We really enjoyed talking with you. Thanks.
Join us next time, when Shervin and I speak with Teddy Bekele, chief technology officer of Land O’Lakes.
Allison Ryder: Thanks for listening to Me, Myself, and AI. We believe, like you, that the conversation about AI implementation doesn’t start and stop with this podcast. That’s why we’ve created a group on LinkedIn specifically for listeners like you. It’s called AI for Leaders, and if you join us, you can chat with show creators and hosts, ask your own questions, share your insights, and gain access to valuable resources about AI implementation from MIT SMR and BCG. You can access it by visiting mitsmr.com/AIforLeaders. We’ll put that link in the show notes, and we hope to see you there.
