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 -- that 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 solution
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 recommendation 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 a practitioner 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 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.
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 https://mitsmr.com/AIforLeaders.
We'll put that link in the show notes,
and we hope to see you there.