How Siemens Is Using AI to Transform Skills, Learning and the Future of Work
AI is moving faster than most organisations can redesign themselves, so how do you stop transformation becoming a series of disconnected technology fixes?
In the most recent HR Leaders Podcast episode, I had an insightful conversation with Judith Wiese, Chief People and Sustainability Officer (CPSO) of Siemens AG.
She explains how Siemens is rethinking its operating model, skills infrastructure and approach to AI as it becomes a more connected technology company. From simplifying the foundations underneath HR to embedding learning into everyday work, Judith shares how Siemens is preparing its people and organisation for a world where transformation never really stops.
5 things you’ll learn from this episode:
The three-part AI model Siemens uses to separate everyday adoption from the much harder challenge of redesigning business processes
Why one of the biggest barriers to scaling AI has nothing to do with the technology itself
The unglamorous HR foundations Siemens believes need to be in place before personalised learning and skills strategies can really work
How Siemens is using skills data to uncover far more internal career opportunities than traditional CV matching could reveal
Why Judith believes the ability to keep learning may become more valuable than much of the knowledge employees already have today
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We really want to make sure that we're invested in the people that we have, because
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with the pace of change, we need to make sure that people keep learning anyway.
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And it should be in people's best interest to do that as well.
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They have 40, 50-year careers. So I think also people need to get used to the daily
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gym that is the learning muscle, right?
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Of course, from a change management perspective, everybody still hopes that this
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transformation is done, or this big change initiative is finally over.
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And I think we just need to collectively embrace it never will be, and change will
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never be as slow as it is today.
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Hey, Judith. Welcome to the show. How are you doing?
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I'm really well. And you?
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Yeah, I'm good. How time flies since we last spoke.
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I can't believe it's been so many years. Let's start with how are you?
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How are things?
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Well, I am good because I'm about 10 days away from a summer break.
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And I've been known to take a summer break.
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I am very busy because we're in the midst of a transformation, and I think
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we are progressing. And given particularly the German macro
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climate, I think we're doing really well at Siemens. So knock on wood.
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Nice.
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Hopefully there's more than wood here. So yeah, that's how I am.
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Nice. That's very good. Yeah. So where are you off on holiday then?
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Well, for the first time, we decided to go absolutely nowhere because we've been
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spending so many weekends away. It's been such a busy schedule that I simply
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decided to stay put. Unless the weather really turns bad, then I might still decide
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to escape.
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Yeah. Some people don't realize that.
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I try to explain to my family and friends that my life is always traveling.
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And I said the same thing this year, so my luxury is not going anywhere.
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And they're like, "What do you mean?" The idea of getting on another plane and
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going to another thing, I'm like, "That's what I do all...
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That's my job." So I just want to be at home and wake up and be like, "What do I
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want to do today?" Because every part of my life's so scheduled, if that makes
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sense.
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So I love that for you. I'm excited for you.
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Yeah. And I also need to fill up my social
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tank, yeah? And so in the last few years, we've rented a big house and just invited
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everybody who had time and wanted to come along.
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Oh, nice.
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But this year, we've done a big party at home, and I think I'm just going to stay
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put.
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Yeah. I'm doing a similar thing, but I am traveling to Canada, but it's basically
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all of the family's traveling, to your point.
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Wow.
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So I think there's about 20 plus people coming along.
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Oh, wow.
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Yeah. So we're all going to meet in Toronto, and then it's going to be a nice
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couple of weeks of everyone-
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And monopolizing an entire airline.
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We're taking over. No, we literally are, actually, probably.
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Yeah, so it's going to be fun there.
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But so the transformation you mentioned, I'm excited to get into this.
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What's the why that's leading this transformation?
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And then we can jump into some of the cool stuff you're working on.
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Yeah. So maybe a few Siemens buzzwords.
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First of all, we're calling it the One Tech-
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Yes
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... Company program, and I'll say a little bit about that in a minute.
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And I think from a strategy perspective, we think that we combine the real and the
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digital world like nobody else does.
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And the two things go together in that, on the one hand, we are anything between
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a splendid hardware company and a pure play software company.
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We want to be leader in physical AI.
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And at the same time, there are things that we deliver into data centers, AI
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factories, that is still very hardware-y as well. Yeah?
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And we come from a history. We've been around for almost 179 years now,
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but we come from a history of having many different businesses.
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We were called the conglomerate for the longest time, and we have now really become
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a much more focused technology company, but one that still does many things in
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splendid silos. And I think in the day of AI and data now, where
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sharing of data is the name of the game, and where platforms are the name of the
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game, this has got to start with us.
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So how do we build data lakes that are for us, and make us use our own
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data better? How do we build technology platforms that we can actually
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take horizontally across our businesses?
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And how can we be much easier for our customers?
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Because at the moment, we come with too many people to one customer, instead of
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being really facing as Siemens, and then dealing with our own complexity in the
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background. So we want to make sure that we actually are much more customer
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focused, that we innovate faster, and that we therefore grow faster profitably.
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So those are the things that we want to work on, and that is quite a big shift
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internally, and it's going to make quite a big difference externally for our
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customers and, of course, for our business performance as well.
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Love that. So just a few things.
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What does that mean then for the role of P&O on this journey?
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Yeah. So one of the things that I, if you allow me that tangent, one of the things
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that was really important for me when I came was renaming HR to P&O, because I
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really think that words matter. And I think there's also a role that we can play
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that is critical, that doesn't necessarily find its natural home elsewhere.
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So the first thing is, I think people want to be people rather than human
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resources. So let's just talk to them up as people and treat them as people.
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The second thing is that the O for me is organizational development, how you build
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operating models, et cetera. And that for me is absolutely crucial.
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There's not that many functions that naturally take a systems lens onto an
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enterprise, and I think this is what exactly P&O can do.
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So one of the things that we've been very involved with, not alone obviously,
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together with strategy and other stakeholders internally, is really rethink the
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operating model for Siemens. Because Siemens very much likes its organizational
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structure and org cults. So there's also a degree of education of our leaders and
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our people to say, an operating model is so much more than structure.
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It's about how you redefine accountabilities in a matrix.
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It is about systems and processes.
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But it is very much about leadership and behavior and people and skills as well.
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So therefore, redesigning that for Siemens has been really very important.
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And when we started out to put a program together around the One Tech company, we
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were an inherent part with strategy in leading that as a transformation office.
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And of course, we have started to put work streams into place that we're now
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tipping on the 1st of October, the beginning of our next fiscal year, into really a
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new operating model for Siemens. And so therefore, we have been involved in really
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looking at this from a very systemic perspective through the OD lens.
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But then, of course, we are also very involved in terms of the leadership side and
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the people and skill side as well. And part of what we're doing,
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and I keep making these movements, yeah?
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We come from a very verticalized organization in terms of businesses.
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We're putting horizontal fabric in.
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Data, technology platforms, how we go to the customer.
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But also we're taking more functions horizontally as well.
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And so that also means that we as a P&O organization become much more horizontal
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than we have been in the past. So therefore, we're involved in many different ways,
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and we build our P&O strategy well ahead of this as well, and we're building it
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around three pillars. One is organizing for impact, the other one is leaders who
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transform, and the third one is skills for life.
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And we build that ahead of this One Tech Company program, but it
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is something that we have work packages on that will go until
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2030 and beyond to really work through that for the entire business
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and for our people as well.
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Love that. Where did you start? You mentioned the work streams, you mentioned the
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three pillars that you just said there. Where did you start on the journey?
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Does this mean you also had to rethink your existing HR operating model as well?
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Yeah, absolutely. So it was about thinking about the Siemens operating model, yeah,
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and where we really want to continue to go with each of the different businesses to
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market, and where horizontal fabric really makes sense.
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But then, as a result of that, of course, we've also looked at our own P&O
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operating model. What about our data? What about our tech stack? Yeah?
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Where are we developing things more than once?
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Are we really building capability across, or are we too fragmented to really be
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doing
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this well? And how are we getting disrupted and need to disrupt ourselves
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in terms of processes from an AI perspective?
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And so therefore, we've been very clear about where we take stronger governance to
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make sure that we really do develop things only once. Yeah?
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We've got a plethora of leadership programs.
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Besides some of our global flagship programs, there's still a plethora of
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leadership programs, as an example.
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Yeah.
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We've done some cleaning up on our tech stack to really make sure that we have our
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backbone in place, and that we can rethink AI processes.
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And we are also in the process of continuing now for the enterprise,
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to do things like job architecture, skill taxonomy, so that a lot of the things
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that we've already started to put in place actually work even better than they do
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now.
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Mm. Has that meant a lot of upskilling and reskilling of your own team? As well?
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Yeah. First and foremost, I think we're focused on the entire enterprise, but it
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does. Yeah. It does mean that we need to have a good look at how we do things now.
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And I would say the areas where we think there is most opportunity
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is in talent acquisition, is in learning platforms across the
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enterprise, and then of course also in operations.
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And I think the big thing, no surprise, is how do you in the future actually keep
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people and line managers, team leaders, out of our P&O systems?
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So that they have one interface, and then you have steering agents, but nobody has
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to remember logins and-
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Mm
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... how a married system works that you only use once or twice a year.
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Yeah.
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So I think those are the classic ones.
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And then I think we continue to upskill also our business partners in terms of what
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is their role, what is not their role.
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And so yes, absolutely. But we have, depending on how I count,
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250,000 people that we see operationally if I leave out the Siemens Healthineers.
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And we have anything from people who weld trains in mobility through to the 1,500
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AI experts that we have across the organization and everything in between.
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So we do need to make sure that we actually have something really relevant to offer
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for everybody-
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Yeah
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... in a world that is changing so much faster than it ever has before.
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Yeah. In terms of empowering your people to apply AI
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practically, what does that look like so far?
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I appreciate it's a journey and it's going to evolve.
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Yeah.
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What does that look like so far? What are some of the steps that you've taken?
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So we think of AI in three different buckets in Siemens.
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Everyday AI, process AI, and product AI or industrial AI, physical AI.
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Everyday AI is how can we actually do something for everybody, no?
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Doing things like base camps.
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Mm-hmm.
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Making sure that people get licenses in terms of the everyday products that they
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use or if you think software developers now, what do they need?
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Sales, what do they need? What special tools?
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So there is something around really making sure that people have the tools
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available, but that they also have a baseline education around
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AI. And whilst we don't measure that hard and fast because we haven't really found
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a way of measuring that hard and fast, we do ask people as part of our engagement
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survey how much access to learning they think they have and how much more
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productive they feel with AI. And
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we do this every half year. And particularly since the last survey, because the
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recent one has just come out, we see that many more people have spiked now in
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terms of telling us that, A, they have access to learning, and B,
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that they feel more productive. And we see a direct correlation with how their line
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managers answer those questions.
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Really interesting.
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So it sounds obvious, and the data absolutely shows it.
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Now that is everyday AI. And of course, we started with our own GPT version at
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Siemens to make sure that this is all safe, et cetera.
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And we've since expanded into the well-known products that are out there for
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everybody. And so I think that is all well taken care of.
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Let me jump to the other end, which is product AI.
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And this is really who in Siemens builds products and technology
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that is AI infused. And most of our 53,000 R&D
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are in a related to software one way or another.
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We have 30,000 software developers across Siemens.
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So this is really where some of our core product needs to evolve.
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And we have found different ways of dealing with that.
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We, for instance, have found a new way of organizing in terms of pods around
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how to bring use cases to a dedicated organization that really churns this very
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quickly-
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Yeah
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... in terms of turnaround. And we're also leveraging the speed of the US and China
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very much. And we do have some of that development in Europe as well, but we are
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relying on the big nations, the big AI nations, and their speed in that regard as
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well. I think the middle piece now, the process AI is where everybody has kind
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of struggled so far to truly scale.
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Yeah.
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The famous pile of purgatory, and we're just as guilty of that as well.
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And this is where the link to one technology company and the program comes in as
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well. We think that by horizontalizing functions, you get a much better grip
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on processes that certain functions own, capability that functions own,
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the types of tools that functions own.
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And like I said, for us in P&O, we know it's operations, talent acquisition,
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learning, where the biggest impact is likely going to happen.
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So all of us are now really, after a lot of bottom-up, are now really also
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taking the top-down view to say how do we need to redesign?
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Mm-hmm.
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And I think the biggest prize is when you go into the core business
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functions where not a single function owns the big value streams and how you really
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think those processes end to end. That's probably where the biggest prize is.
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Yeah. But as you said, it's the biggest challenge, right?
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Exactly.
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To be able to consolidate all that.
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Most of the CPOs I'm chatting to at the moment, they're going through huge tech
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consolidation, completely relooking at everything right from the ground upwards.
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And it's taking a long time to do that. It's going to take time.
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But adding AI on top of existing
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technologies stack or strategy or ways of working can get you in more trouble,
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right?
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Just adding AI on existing processes that you already have in place is we've
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already seen last year how that went wrong very badly for many organizations.
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Yeah. And I think we've also had learnings.
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There were certain young companies that were AI first that
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we worked with, but then later found out it just didn't work with our tech stack.
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We needed to clean up our tech stack.
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Yeah.
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So some of these things we have decommitted from.
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I think it's also true to say that next to the splendid startups that are out
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there, of course, the big providers have also moved dramatically, and their
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ability to scale instantaneously on a well-established systems backbone product
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is of course also very relevant now.
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So therefore we're working with the big companies
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in the P&O space, and we still keep an eye on the application layer that needs to
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be put on top. But increasingly I think it is really also the big ones catching
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up.
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Yeah. No. I think they were kind of forced to.
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For a long time-
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Exactly
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... they got comfortable.
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And they had no choice. And either for acquisition right now or literally
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innovate or die kind of moment for them along the way.
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I do want to touch on one more thing when you talk about upskilling and learning
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because it's an incredible time, right?
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For the longest time we focused on courses, not capability.
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We focused on clicks and consumption, right? Not on application.
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And we've always had this conversation around adaptive, customized learning to
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every individual. How do you see AI kind of shaping the way that we upskill our
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workforce?
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Yeah. So
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I think there's a number of key things that you need to put in place.
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First of all, we're back to things that are typically more painful to implement
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than not and are not overly sexy. Job architecture, skill taxonomy.
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Those kind of things that you need as a backbone.
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But Siemens, for instance, went to digital learning platforms, to my learning
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worlds already in 2019. And over COVID we have
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very much maximized on that as well.
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So we actually do have all the platform already in place where you can actually
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scale learning, where you can channel learning, where you can make suggestions on a
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more personalized curriculum. And I think we're this far away from AI basically
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starting to write
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personalized curriculum as well now or adapt it.
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So I think there's a whole shift that we will see in the learning world
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and how learning finds people and how people find learning that I think is really
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interesting. And I think also here, the advantage sits with big data.
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So we're also in the way that we work with systems and data products.
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We're trying to leverage the big set of data that we have internally simply because
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of our size, but even that now gets infused with data from the external.
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And then you get early,
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not warning signals, but early indications as to where certain capabilities evolve.
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Yeah.
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What are some of the things that you need to do?
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What are some of the adjacent careers that you can get into?
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And from a talent acquisition perspective, and I also mean internal mobility with
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that. Because our TA folk, they really do external as well as internal.
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Mm-hmm.
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They, of course, are able to now break down CVs into skills, and they can find new
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pairings of people and potential job openings that are probably
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up to tenfold versus what they were before.
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And we have been on this journey for a while now.
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We have about 75,000 of our 250,000 people on
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skills profiles, but we're now really building that one big backbone that will
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actually even help the further acceleration of all of this.
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And then we have, for the longest time, also worked with our
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analogs to a tech stack, our learning stack, and we've basically said there are
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certain things that we will define as strategically important.
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Leadership is part of that sustainability capabilities, but then, of course,
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everything that is digital and AI.
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Then there are certain things that the businesses define as business critical.
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So in our mobility business, for instance, project management is critically
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important. And then increasingly, we're talking about foundational skills
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as well, critical thinking-
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Yeah
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... learning how to learn-
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Mm-hmm
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... collaboration skills. Because we know that particularly in the age of AI, those
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will become ever more important. And with the shelf life of knowledge coming down,
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I think the best thing is to know how to learn things quickly, and not be afraid
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of getting your arms around new things.
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So, that's how we're trying to do this.
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We're investing in people's resiliency, and I would put learning strategies,
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adaptability, et cetera, all into that, and give them an idea of how to stay
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relevant from a functional technical perspective as well.
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I love that. There's so much to take in there, that you said.
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But yeah, learning at the speed of business. Right.
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And I love that you mentioned those power skills because I feel like, as you said,
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as AI evolves, and a lot of the technical skills, a lot of that stuff can be done
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with AI. It's those sort of power skills like critical thinking and others that are
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going to become more and more important as well.
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But being able to connect learning to the business is also going to be really
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important for speed. So, learning shouldn't be something you have to go to.
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It should show up in the work itself, right?
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Exactly. It should show up in the flow of work.
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Yeah.
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So I think that this whole idea of formal training versus training on the
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job, all of that should really blend.
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And you should find learning in the flow of work.
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And I think for us, it's also from a values and a business perspective, really
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important that we invest in the people that we have.
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Because it's very easy to say, particularly in geographies where maybe it's easier
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to go out and hire new and separate from old.
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We really want to make sure that we're invested in the people that we have.
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Because with the pace of change, we need to make sure that people keep learning
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anyway. And it should be in people's best interest to do that as well.
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They have 40, 50 year careers. So I think also people need to get used to the daily
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gym that is the learning muscle, right?
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Yeah.
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And of course, from a change management perspective, everybody still hopes that
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this transformation is done- ... or this big change initiative is finally over.
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And I think we just need to collectively embrace it never will be.
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Yeah.
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And change will never be as slow as it is today.
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How has this made you
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reassess
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how you look at entry-level jobs?
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Yeah. We've had that discussion as well, and quite honestly, I will not
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claim that we have all the answers around that, but we're observing that very
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carefully. And we think that how much you invest and how you invest into early
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career is also a choice. Yeah. And it's always been a
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part of our strategic pipeline
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in the past, and it will continue to be.
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A lot of what we do comes through the German kind of apprentice and dual
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study programs as well, which are very close to business.
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Mm-hmm.
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And so therefore that bridge or that blend between formal education and already
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working in the business, I think actually plays well for us or plays to our
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strength here. We have a big professional education organization as well, where we
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can actually compensate some of the things that maybe the education system leaves
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wanting at this very point in time.
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So we will continue to invest, and we will continue to monitor very carefully how
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roles evolve. But there is just as many proof points of how early
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career talent becomes productive faster with AI-
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Yes
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... than this notion of early career jobs are going to go away.
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And like I said, I think at the end of the day, organizations will need to make
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choices around that as well.
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Mm-hmm.
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Because if everybody's hoping that somebody else does it-
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Yeah
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... then
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that is a dead-end street very quickly. So, we will continue to do this.
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We will continue to make sure that we understand what is changing.
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And we will make sure that we do our very best to both influence the education
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system, but also partly compensate for what may not be happening there today.
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Mm-hmm.
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And then we need to see what happens five years down the line anyway.
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Because everybody who, I don't know, does software development these days will pick
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it up AI first, and AI native in the next few years as well.
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I look at my children and how they learn.
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They use AI heavily to augment them, but I haven't seen them lose their critical
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thinking yet. So I think this is where we need to pay attention, both from an
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education system perspective, as parents-
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Yeah
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... and from an employment perspective, or as from an employer perspective.
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And so this is how we look at this today.
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Yeah, I love that. When you think about
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innovation in your organization with such a large, complex organization.
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We touched on some of it in terms of the way you think about learning, which
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obviously is massively going to influence that.
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But what's your approach in terms of fostering innovation and making sure that you
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can keep that culture of curiosity going? Within the organization.
406
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Yeah. The million-dollar question, right?
407
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How you keep your organization on their toes and engaged.
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I think a number of things. So one is, it is in our DNA, otherwise we wouldn't be
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here 179 years in, right? So I think we have done something right, and
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there is something in the culture and in the DNA of Siemens that really is
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well-established. And we keep nurturing that.
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What has changed, I think, over the years is Siemens is big enough to basically
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innovate on just about anything themselves. But the question is should we?
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So I think the question of how do you actually work with the famous ecosystems,
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where do you actually find partners, anything from fundamental research,
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applied research, what we do ourselves, startup scene, et cetera, and then
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venture funding is where I think innovation happens best and happens the most.
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We invest 8% of our global revenue every year into innovation.
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Wow.
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So that has been
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north of six billion euros every year now in the last few years.
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And of course, we also discriminate between businesses that cycle
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a bit slower versus businesses that cycle faster-
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Sure
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...
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in terms of how this works. And I think because we are now everything from smart
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hardware to software, we've also learned from software, right?
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If you pure play hardware, what you want to do or what the temptation is that you
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want to put out the perfect product. Yeah?
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And you want to put out the next bells and whistles, et cetera, et cetera.
431
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If you're software, you know how to iterate with customers, right?
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You've got your use case, you iterate fast.
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At some stage, you release, and then you still upgrade your product.
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And so I think we've also learned from that.
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And we've embraced the different horizons.
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Now what are the different horizons in innovation?
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And maybe last thing that I would also want to say, because it's so important for
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me, is we have had some really interesting stats on our
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patents and our innovation from a diversity perspective.
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So we know that we actually get better innovation out of a team versus an
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individual.
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Mm-hmm.
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We know that we get 12 points better innovation out of a nationally diverse
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team, and we know that we get a 19-point better innovation out of a gender diverse
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team. So, that really works for us.
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And we will continue to embrace that very much.
447
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I love that last part. I'm glad you added that, right?
448
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One of the things I love about our team is the diversity of thought, perspective,
449
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experiences that everyone brings to the table, and everyone has a different lens.
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Everyone has a different collection of experiences that they bring to the table as
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well, and some of our best innovation has come from that.
452
00:29:48.078 --> 00:29:50.328
People are always like, "Chris, that's a really good idea." I'm like, "That's my
453
00:29:50.389 --> 00:29:50.598
team."
454
00:29:52.548 --> 00:29:56.163
And during our toughest times where we're going through significant moments of
455
00:29:56.208 --> 00:30:00.048
transformation where things are really difficult, is when actually those moments
456
00:30:00.078 --> 00:30:03.183
and those conversations with the team bring the best ideas to life.
457
00:30:03.483 --> 00:30:06.919
And I think it's from an innovation perspective, but it's increasingly in times
458
00:30:06.978 --> 00:30:11.389
like these where change is so fast-paced. A lot of things are unprecedented.
459
00:30:11.448 --> 00:30:11.808
Yeah.
460
00:30:12.169 --> 00:30:14.493
The same old, same old formulas are not going to work.
461
00:30:14.958 --> 00:30:18.093
It is so important that you get different perspectives around the table and that
462
00:30:18.139 --> 00:30:23.868
you are able to embrace all of them, and come out better for it.
463
00:30:23.899 --> 00:30:29.853
So I think this is really important, and it may not be as important depending on
464
00:30:29.868 --> 00:30:34.428
the environment. Yeah? I think anything that is more predictable and solid-
465
00:30:34.908 --> 00:30:35.118
Yeah
466
00:30:35.132 --> 00:30:39.468
... maybe there's nothing wrong with homogeneity.
467
00:30:39.708 --> 00:30:44.598
But I think if you want innovation, and if you want to navigate times like these, I
468
00:30:44.628 --> 00:30:45.798
think it's actually critical.
469
00:30:45.889 --> 00:30:49.279
Yeah. I was thinking of that recently from a personal lens.
470
00:30:49.339 --> 00:30:55.308
I was chatting to Dave Ulrich, and I was asking him, "How do you continue to
471
00:30:55.368 --> 00:30:56.538
disrupt yourself?"
472
00:30:57.048 --> 00:30:57.198
Mm.
473
00:30:58.488 --> 00:31:03.558
Because a martial artist would say, "What got you here won't get you there."
474
00:31:04.248 --> 00:31:04.878
Right?
475
00:31:04.908 --> 00:31:05.389
Yeah.
476
00:31:05.568 --> 00:31:09.018
So I know it's a tough question. I'll put you on the spot, but maybe what are some
477
00:31:09.078 --> 00:31:13.443
of the thoughts or commitments that you've made in the past that you no longer
478
00:31:13.458 --> 00:31:15.889
believe in, that maybe have evolved in your career?
479
00:31:16.908 --> 00:31:18.318
Commitments that I've made?
480
00:31:18.948 --> 00:31:24.649
I mean, like assumptions maybe, or perspectives that earlier in your career that
481
00:31:24.708 --> 00:31:28.008
you had that maybe now you look back and actually it's evolved.
482
00:31:28.818 --> 00:31:31.878
For Dave and I, we were talking about obviously his HR business partner model,
483
00:31:32.029 --> 00:31:32.222
right?
484
00:31:32.298 --> 00:31:33.558
Mm-hmm. Yeah.
485
00:31:33.678 --> 00:31:35.779
He was very straight away, "That's very out of date, Chris.
486
00:31:35.808 --> 00:31:38.373
That wouldn't work in the current way we're working right now.
487
00:31:38.389 --> 00:31:42.768
We just had to shift." And I was just talking through, that was quite a tough
488
00:31:43.788 --> 00:31:44.208
shift-
489
00:31:44.688 --> 00:31:44.718
Yeah
490
00:31:44.733 --> 00:31:46.218
... those beliefs, right?
491
00:31:47.688 --> 00:31:51.978
So maybe one of the things that I will be forever grateful for is that I actually
492
00:31:52.068 --> 00:31:57.649
started my career, or I had most of my career upbringing in Mars. Yeah?
493
00:31:58.158 --> 00:32:03.889
With a very strong P&L function, and a
494
00:32:04.038 --> 00:32:09.798
very strong belief in leadership skills being transversal and
495
00:32:09.828 --> 00:32:12.618
functional, technical, being a good add-on.
496
00:32:12.649 --> 00:32:17.538
And John and Forrest always said, "We make chocolate bars, not rocket science."
497
00:32:17.568 --> 00:32:20.913
Siemens does make a bit of rocket science and chocolate bars, quite frankly, and
498
00:32:21.139 --> 00:32:24.169
therefore I think organizational context is really important.
499
00:32:24.198 --> 00:32:27.333
But the German paradigm is
500
00:32:29.058 --> 00:32:32.343
very much content driven. Yeah? It is
501
00:32:33.708 --> 00:32:37.353
an engineering mindset, and that is good and that is very strong.
502
00:32:37.878 --> 00:32:43.774
I think what I learned is systemic thinking, facilitation
503
00:32:43.818 --> 00:32:49.323
of meetings and processes. How you basically mobilize and
504
00:32:49.399 --> 00:32:52.248
channel. Yeah? I think
505
00:32:53.868 --> 00:32:59.642
today I feel that I am so much more of a rounded leader because
506
00:33:00.198 --> 00:33:05.448
I came through my German roots, but I also learned something that was very
507
00:33:05.478 --> 00:33:11.014
different. And I think if I had learned the ropes of P&L on the Continent, it
508
00:33:11.029 --> 00:33:16.667
would've been much more around codetermination, which I've also learned,
509
00:33:16.757 --> 00:33:21.919
obviously. But I've learned many more things over and above that.
510
00:33:22.608 --> 00:33:28.503
And I think today I have a more holistic view on levers now that you can
511
00:33:28.518 --> 00:33:32.358
pull. So, I don't know whether that answers your question.
512
00:33:32.538 --> 00:33:33.348
Yeah.
513
00:33:33.378 --> 00:33:36.768
But that was really eye-opening for me. Yeah.
514
00:33:36.783 --> 00:33:38.808
Yeah. No, that makes a lot of sense.
515
00:33:38.853 --> 00:33:44.808
And I think we collect that experience throughout our journey, right,
516
00:33:44.899 --> 00:33:49.968
as leaders. And I think when I started to where I am now is kind of crazy,
517
00:33:51.258 --> 00:33:56.643
in terms of the way I lead, the way I have conversations with my team, and I never
518
00:33:56.688 --> 00:34:02.163
thought we would have conversations around leading with empathy and
519
00:34:02.268 --> 00:34:08.103
wellbeing. And the way I was taught to lead in my 20s, you didn't talk about things
520
00:34:08.149 --> 00:34:12.574
like that, right? Now, it's part of everyday conversations with my team, right?
521
00:34:12.589 --> 00:34:15.544
I'm very open to say, "Hey, guys, I need a day off. I'm not feeling great." Right?
522
00:34:15.618 --> 00:34:16.069
Mm-hmm.
523
00:34:16.128 --> 00:34:21.828
And the team being very open. So for me, that was a hard thing to be vulnerable.
524
00:34:22.608 --> 00:34:22.819
Mm.
525
00:34:23.419 --> 00:34:23.538
Like-
526
00:34:23.928 --> 00:34:26.899
And I think what I have also learned is,
527
00:34:28.638 --> 00:34:31.428
what is the notion of control? Yeah?
528
00:34:31.608 --> 00:34:34.488
What can you really control in an organization?
529
00:34:35.508 --> 00:34:35.524
Yeah.
530
00:34:35.524 --> 00:34:37.938
What can you really control in your life, yeah?
531
00:34:38.194 --> 00:34:38.194
Yeah.
532
00:34:38.748 --> 00:34:40.488
Quite honestly, the answer is not very much.
533
00:34:42.378 --> 00:34:42.393
No.
534
00:34:42.828 --> 00:34:48.258
But nevertheless, organizations also, and leaders,
535
00:34:50.538 --> 00:34:54.589
come back to that notion of control and needing to be in control.
536
00:34:54.603 --> 00:34:55.503
And I think if you
537
00:34:57.199 --> 00:35:02.404
shift that a little bit and look at that a bit differently, I think you can build a
538
00:35:02.478 --> 00:35:04.548
very different organization as a result.
539
00:35:04.578 --> 00:35:08.868
And of course, there are certain governance things that you need to be in control
540
00:35:08.883 --> 00:35:08.883
of.
541
00:35:08.883 --> 00:35:08.883
Sure.
542
00:35:08.928 --> 00:35:14.763
Yeah, sure. But I always like to think about organizations more
543
00:35:14.808 --> 00:35:17.358
like energy systems. And if you do that,
544
00:35:18.828 --> 00:35:22.713
and if you know what you really need to be in control of, and for the rest of it,
545
00:35:22.788 --> 00:35:27.574
you think about how do you actually guide the energy of an organization, I think
546
00:35:27.618 --> 00:35:29.208
you'll get different results.
547
00:35:29.298 --> 00:35:34.068
Yeah. I normally find that if you're super focused on trying to maintain that sense
548
00:35:34.098 --> 00:35:36.048
of control, it's normally the thing that's holding you back
549
00:35:37.266 --> 00:35:37.656
Right?
550
00:35:37.686 --> 00:35:37.927
Exactly.
551
00:35:37.986 --> 00:35:41.346
Because by doing that, you're almost excluding
552
00:35:43.356 --> 00:35:47.136
the other opportunities of what could be as well.
553
00:35:47.196 --> 00:35:53.016
And it's difficult for people to let go because change is scary for people.
554
00:35:53.181 --> 00:35:58.297
And I think once you just understand that we're always going to be in a-- like you
555
00:35:58.326 --> 00:36:01.986
said earlier, there's always another transformation. There's always another change.
556
00:36:02.496 --> 00:36:07.836
So change resilience is huge. It's so important now, and I kind of realized.
557
00:36:07.896 --> 00:36:11.556
And also recognizing when you are and when you're not in different sprints, if that
558
00:36:11.616 --> 00:36:12.067
makes sense.
559
00:36:12.111 --> 00:36:12.111
Yeah.
560
00:36:12.216 --> 00:36:14.677
I try to talk to the team about that, even my wife, actually.
561
00:36:15.156 --> 00:36:20.317
I'll communicate, "Hey, next X many months, I just want to let you know that this
562
00:36:20.526 --> 00:36:23.797
is-- I'm recognizing I'm in these sprints and in these moments."
563
00:36:24.081 --> 00:36:24.156
Mm-hmm.
564
00:36:24.231 --> 00:36:26.976
And before, I didn't know I was in those moments, and I would burn out.
565
00:36:27.186 --> 00:36:30.366
I would get sick, or just the team feels exhausted.
566
00:36:30.486 --> 00:36:32.736
So just being a bit more aware-
567
00:36:33.726 --> 00:36:33.741
Yeah
568
00:36:33.741 --> 00:36:38.047
... of it, as well as, I used to have my foot down to the floor all the time and
569
00:36:38.106 --> 00:36:40.236
did not realize that that's not sustainable.
570
00:36:40.386 --> 00:36:41.706
No, it's not.
571
00:36:41.826 --> 00:36:44.692
Yeah. To be able to do that as well. So yeah.
572
00:36:45.486 --> 00:36:47.766
Someone asked me this the other day, and I wanted to ask you it.
573
00:36:47.781 --> 00:36:51.726
It was an interesting one. I heard it on a podcast as well.
574
00:36:52.086 --> 00:36:57.306
What would you say is one thing about your team or your organization that no one
575
00:36:57.336 --> 00:37:01.626
knows, but they really should? That you don't talk about enough.
576
00:37:01.686 --> 00:37:06.756
So I think for me, it is that spectrum of Siemens, yeah?
577
00:37:06.817 --> 00:37:12.726
That we really are leaders in physical AI, that we are a software
578
00:37:12.756 --> 00:37:17.061
company as much as we are a hardware company, and that it is that sheer combination
579
00:37:17.106 --> 00:37:22.131
of the two that makes us stronger. And if you listen to people in Silicon Valley,
580
00:37:22.536 --> 00:37:26.526
they all talk about physical AI as the next inflection point.
581
00:37:26.616 --> 00:37:26.976
Yes.
582
00:37:27.576 --> 00:37:30.036
And really how
583
00:37:31.356 --> 00:37:37.236
AI therefore manifests itself in the real world now, how AI really,
584
00:37:37.356 --> 00:37:41.766
and the laws of physics go together to create impact in the real world.
585
00:37:42.186 --> 00:37:47.106
And I think we are increasingly being recognized as that company,
586
00:37:48.096 --> 00:37:51.817
but we want to shout much louder about that going forward.
587
00:37:52.116 --> 00:37:55.206
Yeah. No, I love that you mentioned that because even quite a few of my friends
588
00:37:55.236 --> 00:37:59.586
have mentioned to me recently, "What is physical AI?" And I was like, "Oh, here we
589
00:37:59.646 --> 00:37:59.976
go."
590
00:38:01.536 --> 00:38:05.736
But I'm with you. I'm super excited for the future, and physical AI is top of my--
591
00:38:06.306 --> 00:38:10.716
is something I've been looking at a lot, actually investing in a lot as well.
592
00:38:10.836 --> 00:38:12.666
So I'm glad you mentioned that.
593
00:38:14.256 --> 00:38:15.396
Last question.
594
00:38:16.746 --> 00:38:18.427
I hope you're not dissing Siemens as well.
595
00:38:18.547 --> 00:38:19.611
You don't have to answer that, but-
596
00:38:19.641 --> 00:38:23.615
Yeah. I was like, what can I say on a podcast?
597
00:38:25.206 --> 00:38:25.567
Yeah.
598
00:38:25.611 --> 00:38:30.336
Yeah. As you look ahead, both personally and professionally, what are you most
599
00:38:30.396 --> 00:38:32.317
excited about? What gives you energy?
600
00:38:33.696 --> 00:38:37.776
Yeah, so I get energy from the people around me.
601
00:38:37.866 --> 00:38:42.246
And I see how we have been faring through...
602
00:38:42.306 --> 00:38:44.376
I mean, like I said, I've been here for six years now.
603
00:38:44.856 --> 00:38:49.716
None of the times were ever normal. I joined in COVID.
604
00:38:50.797 --> 00:38:55.416
We had Ukraine, Russia. We had supply chain crises.
605
00:38:55.506 --> 00:39:00.396
We had the rise of AI. You name it. Geopolitical tension.
606
00:39:01.056 --> 00:39:06.336
So nothing has been normal. But the sheer resilience of the organization and the
607
00:39:06.396 --> 00:39:12.336
fact that people pull together and still do great things is really what makes me
608
00:39:12.366 --> 00:39:17.166
positive. And I think that there is very little that people can't do if they put
609
00:39:17.196 --> 00:39:21.621
their mind to it. So we talk about growth mindset a lot, and I'm always
610
00:39:22.927 --> 00:39:27.606
conscious that it might sound like a big corporate word, but I really believe that.
611
00:39:27.666 --> 00:39:33.561
I think there's no limits, or virtually no limits, if you believe that things can
612
00:39:33.606 --> 00:39:39.141
be done. And if we learn how to play together better as Siemens in the spirit of
613
00:39:39.186 --> 00:39:43.567
One, I think that there is very little that can stop us in terms of really being
614
00:39:43.656 --> 00:39:49.416
successful and delivering value to our customers as well, and to have people who
615
00:39:49.446 --> 00:39:54.516
thrive in the organization. Because I think all of that is important, or that mix
616
00:39:54.606 --> 00:39:58.506
is important. So that is what I really get excited by.
617
00:39:58.626 --> 00:40:03.861
And of course, I also have days where the sheer complexity of everything is just
618
00:40:03.906 --> 00:40:09.547
exhausting. But no, those are the things that I'm really hopeful about.
619
00:40:09.696 --> 00:40:13.386
I'm a big believer in humanity, and that's what I bank on.
620
00:40:13.716 --> 00:40:16.716
Amazing. Well, listen, thank you so much for coming on the show.
621
00:40:17.677 --> 00:40:20.646
I appreciate you showing the journey so far. It is a journey, right?
622
00:40:20.840 --> 00:40:20.840
It is a journey.
623
00:40:20.871 --> 00:40:25.506
And it will continue to evolve. But congratulations to you and the team so far.
624
00:40:25.806 --> 00:40:30.996
And I want some sort of One tech company merch.
625
00:40:31.356 --> 00:40:35.346
I want to see you and the team. I want to see some LinkedIn posts
626
00:40:36.666 --> 00:40:36.680
with the-
627
00:40:36.696 --> 00:40:38.736
We'll get you the T-shirt that says One.
628
00:40:39.156 --> 00:40:39.636
Do you have it?
629
00:40:39.846 --> 00:40:39.861
Yeah.
630
00:40:41.406 --> 00:40:42.606
Oh, of course you do. Yeah.
631
00:40:43.866 --> 00:40:44.706
I'll send you the T-shirt.
632
00:40:45.216 --> 00:40:50.436
Amazing. Well, listen, enjoy the holidays and time with the family, and I look
633
00:40:50.466 --> 00:40:53.526
forward to catching up again soon. Let's not leave it another six years.
634
00:40:54.771 --> 00:40:54.771
Exactly.
635
00:40:54.817 --> 00:40:57.966
Until next week. But thank you for coming on the show. I appreciate you.
636
00:40:58.686 --> 00:41:02.646
Yeah. Thanks, Chris. And you enjoy your time as well with the family in Canada.
637
00:41:02.856 --> 00:41:03.156
Thanks.
Judith Wiese, Chief People and Sustainability Officer (CPSO) of Siemens