(placid music)
Sam: What does coffee
have to do with artificial intelligence?
Shervin: In this episode, Mattias Ulbrich will talk to us
about how Porsche is driving a cultural
innovation and digital transformation
with AI across all functions in the company.
Sam: Welcome to Me, Myself, and AI,
a podcast on artificial intelligence in business.
Each week, we introduce you to someone innovating with AI.
I'm Sam Ransbotham,
professor of information systems at Boston College,
and I'm also the guest editor
for the AI and Business Strategy Big Idea Program
at MIT Sloan Management Review.
Shervin: And I'm Shervin Khodabandeh,
senior partner with BCG,
and I co-lead BCG's AI practice in North America.
And together, BCG and MIT SMR have been researching AI
for four years,
interviewing hundreds of practitioners,
and surveying thousands of companies
on what it takes to build and deploy
and scale AI capabilities
and really transform the way organizations operate.
Hi, Mattias, welcome to the podcast.
We're really excited that you could join us today.
How are you?
Mattias: It's a pleasure for me to be with you.
Thank you for your time.
Sam: Can you tell us a little bit about yourself
and your role at Porsche?
Mattias: My name is Mattias, and I'm the CIO of Porsche,
and at the same time, the CEO of Porsche Digital,
a subsidiary of Porsche
where we really focus on the new stuff.
For example, for AI, for cloud technology,
for other like blockchain,
and where we are, let's say, more international
and that means we are in the United States,
like Atlanta and Silicon Valley,
but we as well in China, for example,
we are in Tel Aviv, and of course in Germany.
So, this is a company where we really look
for digital projects that we can really support
within the Porsche organization.
But at the same time,
we are looking at new ideas in the market
and looking for new business ideas
and business models within this organization.
Sam: You know that I'm actually from Atlanta?
Mattias: Oh, I didn't know that, no.
Sam: Yes. Mattias: But you know
that the Porsche headquarters's there, right?
That's the reason why we're there,
because we have a very close collaboration
with their headquarters in the United States and Atlanta,
where we're really looking to find the best solution
for the US market.
Sam: I like the phrase "new stuff."
Tell us a little bit about how you yourself
got interested in "new stuff."
You mentioned a fair number of new technologies
as "new stuff."
Mattias: Yeah, I'm personally very interested
in new technology.
Well, I studied electronics when I started my career.
I worked with Hewlett Packard.
That was a very innovative, at that time,
it was very innovative organization.
So, I really like to understand
what are the advantages of new technology,
and what can it bring to the business
to bring really technology and business together.
This is what drives me and where I'm interested
in finding the best solutions.
Sam: So, tell us how that background started.
Like how you got from Hewlett Packard
or from electronics to Porsche.
Mattias: I started my career
at Hewlett Packard a long time ago in the 90s.
Then I had the opportunity to join Audi at the time
in Neckarsulm, this is a plant
where the A8, for example, is built,
and there was a lot of new stuff between the car,
the IT, and the production side.
So, it was very interesting to see all the electronics
and the software in the car
and how you can handle that in the production process.
And so, I learned a lot about car business, IT business,
and production at that time.
And after that, I had the opportunity to move to SEAT.
That is, as well, part of the Volkswagen group, as Audi is.
And I had a great time in Barcelona,
where I was the CIO of SEAT at that time.
After that, I had six years in Wolfsburg,
the headquarters of the Volkswagen group.
I was responsible for the IT services worldwide,
and after that I became the CIO of Audi.
I took this position for six years,
and then I decided to get, let's say, a wrap-up
of the new technology.
So, I moved to MIT in St. Gallen here in Switzerland
to learn more about the term of, let's say, transformation,
digital transformation about new technology.
And after that, I came to my role here at Porsche
to drive the transformation of Porsche, and as well,
getting all this stuff as well
from this Porsche digital organization
into the Porsche organization.
Shervin: You mentioned your interest in AI,
you mentioned your interest in technology and innovation.
Why cars?
Mattias: Yeah, that's a good question.
Because I thought when I started with Hewlett Packard,
it was really interesting,
and I saw a lot of different branches
and companies starting from trucks and going to ships,
for example, as well for other things like chemical stuff.
And then, I had those projects with Audi,
and it was so interesting
to see what technology really did to the car.
So, it was a time at the end of the 90s
where there were so many different electronic devices
in the car,
and it was a huge challenge to manage that,
because in the beginning,
they didn't communicate well with each other.
And so, there was a huge technology challenge,
and this was really interesting for me
to understanding this challenge
and bringing together production knowledge,
IT knowledge, and the car technology together.
And so, that was the moment when I changed
to the automotive company.
Sam: What kinds of new stuff
are you interested in right now, particularly at Porsche?
Mattias: Yeah, the main focus is really AI, to be honest.
Of course we are looking how we can organize as well
with, let's say, agile working,
what can we do as well in our development centers
for the car business.
And of course, software in the car
is a very important thing as well,
because this is changing the world of driving.
But what we are focusing on as well
is to look how we can use AI, for example,
to improve our internal processes,
how can we use AI to get a better contact
and a better understanding of our customers.
That is very important for us as well.
And of course, yeah,
to look what can we do in our product
and really increase as well our product portfolio
to have digital products
that we can deliver for B2C markets.
Like we started, for example, with some ideas
in the direction of supporting sustainability as well,
like Porsche Impact,
where we developed a solution
on how a customer can compensate, for example,
his CO2 footprint that he drive with the car,
and how we can really increase our product portfolio
for our customers and make driving more attractive.
Sam: So, is there some particular example
of how AI has made a big difference
in a way that other technologies would not have
that you're particularly fired up about?
Mattias: Yeah, what we really found out, for example,
in production that we can really use AI to predict,
of course, a lot of things, for example,
in the auto management systems,
how we can predict for order to deliver markets
to have the right cars in the dealerships.
That is not easy, for example, in China.
So, sometimes it's really a challenge to understand
what kind of cars they would buy in three months.
So, it's very important to get feedback from the market
and understand what is the most important driver for that.
But as well, to understand what can we do
in the production process, for example.
Shervin: These are some very, very great examples
of use of AI.
You mentioned a whole bunch on the marketing side,
a whole bunch on the supply side and supply chain,
and also production.
Are there also some examples where roles or functions
that are typically more like engineer driven,
like design or some of the trade-offs
in terms of performance, et cetera, are aided by use of AI?
Because we see that in other industries,
which is sort of a new thing,
because are typically things
that engineers have a strong sort of discipline
and playbook for.
Is that something you can also comment on?
Mattias: It's very interesting
that you mentioned design, for example.
So, because I was in the design studio here
in Weissach two weeks ago,
and we had a long discussion on how they use AI
to really support their design ideas.
And they have a program that they're using for new cars,
for example, they can use different models
and really reshape the digital model
before they go into the first physical model.
And they are using AI to supporting the designer,
for example, but as well, we have, of course,
in other areas of engineering,
as well support tools that really use AI
to improve technical development.
Shervin: When you guys implement these AI tools
in these areas where a strong collaboration
between man and machine is needed,
do you find there is a fair amount
of sort of culture change needed or re-skilling
or change management needed
for the human to become friends with AI?
Mattias: I think the collaboration between the machine,
the IT machine or the AI machine, and the person
is very important.
And you need to understand how you can use that.
And it's totally different if you go to production,
for example, or to engineering,
because sometimes it's a supporting tool,
and it supports the worker,
for example, in the production line,
in the other area in engineering,
they're like friends, like colleagues
that work on the same issue.
And it's very important to understand
that AI is further developed by the business area.
So, it's not an IT task anymore.
It's really a collaboration between the AI expert,
but as well, the business expert and the machine,
and you have to manage that.
So, this is a huge difference to normal IT projects.
So, we have a totally different approach
to go together on such pilot projects.
We have, for example,
an acoustic anomaly assistant that works really
with an engineer to understand anomalies that we have,
for example, in the door and how he can really understand
what is the reason for the noise.
And this support, it's only possible
if you worked really together for months
to understand all the noises,
and then you can adapt it to a different part of the car.
But it takes a while and you learn,
you have a learning curve like this,
and it's only possible
if you have a very good collaboration.
Sam: When you implemented this system,
what were people's reactions?
Did they say, "Oh my gosh, this is taking my job"?
Did they say, "Oh my gosh,
this is a great way to do this"?
How do people react the day that you turn the system on?
Mattias: Like always, people react totally different.
As of course, we have a lot of very technical oriented guys
that see the opportunity and see really
how this can help them in doing their tasks better,
doing their work better.
Sam: You mentioned a little bit about the fears
that some people have about when you say AI in general,
and they think a machine will rule versus machine vision
to help understand the right label
or the acoustic anomaly system on the doors.
How did you come up with these sorts of,
like acoustic anomaly system, for example?
I wouldn't have thought of listening to a door.
I would've thought of looking at a door.
How do you get someone to think about listening to a door?
My doors haven't said anything, as far as I know,
but maybe I'm not listening.
Mattias: Listening to a door is already a task
that has been done in Porsche and at Volkswagen,
for example, and the whole industry for years.
But the idea to use AI to really improve
that noise that a door makes,
that came really from drinking coffee.
Now, it was in the lab that we have in Berlin and I,
as a specialist, wrote an application
that could listen to the coffee machine
and know what kind of coffee is done.
So, he knows this was a cappuccino,
this was an espresso, for example.
And then there was the idea, what can we do with that,
with this acoustic system?
And then we had some discussion with our R&D people,
and they said, "Well,
we are listening to our door all the day,
but we can't listen tonight, for example,
because we are not there.
And sometimes there is a noise,
and we're coming back in the morning."
So, together we started this project then,
and it was the beginning of a success story,
because right now we are doing this
in several places in R&D and it was a good example
how it can work.
Shervin: Yes, for sure,
and the step to really educate, I'm sure it really,
really helps too, because as you said,
lack of information could create a lot of anxiety.
And so, how widespread are these programs?
Is it tens of people or hundreds of people
or thousands of people?
Sam: Yeah, how many people in the organization need
to know about these technologies, everyone?
Mattias: I think, yeah.
I started to train really every IT person
in my organization,
so that we have a broader view on that
and a common view on that as well.
But of course, the AI program is,
let's say, it's 200 person that really work on that
in the Porsche organization
and that are connected of course to others,
but you need a very small, core team
that is driving this change
and bringing the best use cases in place.
And we tell about that.
And so, we have a good mixture of business people
that drive that,
and some people came as well to the IT organization
that was new. They moved from engineering
to the IT to drive this as a platform.
We have an AI platform,
and they had really fun to drive this program together
with the IT people.
And so, we have a good mixture of business and IT people
that are driving this program.
Shervin: That's great, thanks for clarifying that.
And then another question I had is you mentioned 200 people.
How many of these people are new people or re-skilled people
because of course, some of this training is to educate,
but some of it could also be to really build new skills?
Do you find that you have to bring talent
that may not exist a massive amount
of that talent from outside?
Or do you find that it's more
about re-skilling and training the existing workforce?
Mattias: It's different in the different business areas.
For example, in engineering
you have a lot of good, trained people
that understand technology
and that really understand as well
the possibilities of AI.
In finance, for example, you have totally different
approach, and you have to bring more external people
to really drive those ideas
because there's no technology knowledge
on the business side.
So, if I look at my organization,
we have maybe 40% new people
and 60% that were already in the organization,
but some are of course really focused in the past
as well to new technology.
So, they are very adaptive and they would like to learn.
So for us, it's a very good mixture
because you need really to understand the business process
to find the best solutions, that is very important as well.
Shervin: It's all about continuous
and ongoing learning at all levels, right?
For people, for the algorithms, for everybody.
Mattias: Yeah, that's right.
And creating a culture that is really open for that,
that is very important as well.
Sam: Mm-hmm, so what are you excited about?
You've mentioned new stuff,
the new stuff from the beginnings of Hewlett Packard days
to new stuff now, what's the next new stuff
that you're excited about?
Mattias: Yeah, the most thing I'm excited about
is to work together with great people, to be very honest.
I like technology of course, but to work with people,
it's the best thing that you can do
and really to learn together as well.
So, we are just in the beginning of AI,
so there's a long way to go
because we have done some really great project,
but we are still having a lot of things to do with AI.
And I believe really that AI is the biggest challenge
that we are facing right now still.
And all the other things are not such a game changer like AI
is right now in the technology field.
And I believe that AI and as well, other technologies,
but AI in this very special situation
can really drive the change
that we have right now in society,
all the challenges that we have in society,
for example, sustainability.
And I believe that digitalization can really help
in those very important fields.
And if you look, Porsche is doing a lot
to getting better cars on the road,
like the Taycan, for example, to have better cars
that really helps as well as the environment,
and doing a lot in terms of sustainability.
And I think those things are driving me
to really creating a better world
and looking what can technology really do for that.
And of course, supporting people
to really focus on the most important things in life,
but as well, helping the world
to getting a little bit better.
And I think this is a great motivation for me,
and this is very helpful for me.
Sam: Mattias, thank you for joining us today.
We appreciate all the time you spent
and the interesting conversation.
Mattias: It was great with you, thank you for your time.
Shervin: Thank you very much, yes.
(placid music)
Sam: That was great.
Mattias was really interesting.
Shervin: Mattias hit a lot of very key points
that we see in our work, we see in the survey this year,
we saw it last year.
He made the point around culture of innovation
and creation of new ideas.
He made the point around, it's not tech,
it's about business and technology coming together.
He also underscored the importance
of just by being who he is and the role he has,
the importance of this being a senior executive role.
And then, the other thing I really liked
is the point he made about different roles of AI.
We say that in our report that there
are at least five different modes,
and then he talked about it.
He talked about vision and automation of that.
Then he talked about design where AI gives some ideas
to the engineer or to the designer.
He talked about AI as generator of insights
for supply chain or for the marketer
or for the product designer.
I really feel like Porsche is getting it.
It's really, really impressive.
Sam: Yeah, Mattias had a nice combination
of excitement about technology
but also a methodological approach towards it,
which I thought was a nice combination.
He both exuded excitement about technology,
but at the same time,
a very realistic view about how to implement it.
Shervin: Yeah, the other thing I was quite impressed
is the extent of culture change that Porsche is undertaking
that he underscored with training,
with education, with re-skilling,
with getting a base level education
for everybody in his organization.
And it's hundreds of people, not a handful of people.
Sam: Right, and they have to
because of the number of applications that they're,
he listed off dozens of places that they're using it.
And they were just all across the organization.
Shervin: Yeah. Sam: When he was talking
about introducing it, he said,
"Oh yeah, we don't talk about bringing in AI as a big,
scary general thing that's abstract
and who knows what baggage it's bringing with it."
He said, "We're bringing in this application."
He was very specific and very narrow.
And then people can get their mind around what that means
versus bringing in a lot of baggage from every sci-fi movie
that anyone's ever seen.
Shervin: Yeah, the other thing I really liked
is the coffee example.
It was a great question you asked, why sound?
And I didn't think he's gonna go to coffee.
I thought there's a million other places he could go.
But that's a great example,
and I think we also heard
that from some of our other interviewees
that a success story or an anecdote
or an example somewhere else translates
into a completely new idea in a completely different field.
Sam: Yeah, that's a very human role
of still that creativity of recognizing
that this situation isn't exactly
where we saw that technology before,
but it's a great place we can use the technology now,
and that's still a very decidedly human creative part,
but it still requires expertise.
And he was very clear about that,
that you had to have that expertise as a baseline,
and it sounds like they're working very hard to make sure
that most people in the organization
have some expertise in there.
When I asked him about new technologies he's excited about,
he didn't bite it all in the rattling off the latest,
greatest new AI thing.
He's all about getting the people excited about it.
That that was not where I thought he would go there.
Shervin: Yes, that's right.
(placid music)
Sam: We really enjoyed speaking with Mattias today.
He really combined an enthusiasm for technology
with an enthusiasm for business,
and that was a fun combination.
Shervin: Join us next time when we talk
with Arti Zeighami, head of AI at H&M.
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