A Conversation with Juniper & Mike Krack, Aston Martin Aramco Cognizant F1 Team Principal

0:04 So everybody, welcome.

0:05 My name is Bruce Bennie on the area of vice president of Juniper Networks.

0:08 And we have a Juniper and the Aston Martin Aramco Cognizant Formula One team.

0:13 I want to welcome you to tonight's event.

0:15 So Juniper believes that success is built on teamwork and strong partnerships

0:20 Winning in Formula

0:20 One is all about bringing together the best efforts of all of the partners.

0:24 And we're incredibly proud to be a major partner of the mountain Formula

0:27 One team.

0:33 You know,

0:33 what's it like leading a high performance team

0:36 at an organization that has technical technology at its core?

0:41 Yeah, and thank you very much for having me, for giving me the possibility.

0:45 Yes. This you have obviously

0:49 performance driven individuals that they all have the same goal.

0:53 I mean, race teams these days,

0:55 we have always these discussions about safety,

0:58 operational excellence, excellence, not making mistakes at the racetrack.

1:02 And the race teams these days, they take these boxes.

1:05 So it's all about car performance.

1:08 Who makes the fastest car?

1:10 And to have this performance culture in there is one thing.

1:14 And then to keep going with, even if you have maybe if

1:20 if you are not not leading or if you have not won the last race

1:24 to keep the motivation up because the people are very motivated.

1:28 But we must not forget they are human beings and people. So

1:32 sometimes it's really important to to communicate,

1:35 to communicate why why we are in the situation where we are.

1:40 And you realize very quickly that

1:43 and this all of these individuals are very data

1:47 driven, very, very technology driven,

1:50 but they are human beings.

1:53 This we must not forget.

1:54 So I think that is 11 important part of my role to to not forget that part.

1:59 So on one hand, to promote all kind of technological innovation,

2:04 but not to forget that they are teams with human beings,

2:08 with all their problems that every one of us is having.

2:11 So, yeah, that's that's part of the role.

2:14 How artificial intelligence and machine learning plays a huge part in the Formula

2:20 One sport, because I imagine it is in just about everything that you do.

2:24 Yeah. I mean,

2:26 it started on a smaller scale, let's say.

2:28 And I started as a data engineer, by the way.

2:32 Yeah.

2:32 So data driven, you know, we

2:35 we had a situation where it comes from, a situation where you get

2:40 more and more and more and more and more information or more data.

2:43 And at one point you need to find ways of structuring

2:46 or getting hold of this data, what you need without manual process.

2:51 So I think this is where basically it's starting more and more

2:55 where you try to go for routines for programing.

2:59 And it has evolved more and more into data mining or algorithms

3:04 that help you get the information out that you want to have or combine information

3:08 that the human brain might not even be able to combine. So

3:13 there is there is some some examples we have

3:15 and some are relatively simple like

3:19 we have.

3:21 We try to save weight on the car.

3:23 So we do not want to create to to take census yet.

3:25 So some some census data, they have like a substantial weight

3:30 like half kilo a kilo,

3:33 which we do not want to carry over a distance.

3:36 So we thought about how can we is there a possibility to rebuild

3:40 the signal of the sensor with the with the machine learning algorithm?

3:46 Feeding data in?

3:47 And then this the algorithm can predict where

3:51 can predict the signal from taking other signals

3:54 that that you have to leave in the car. So

3:57 that is one example where for example, where

4:00 on on Sunday the sensor will not be in the car,

4:03 but we will have the data that comes from the algorithm.

4:06 Oh, yeah, that's pretty good.

4:07 So that's that's 11 isolated use case.

4:11 I would say we have many, many routines

4:14 running to to very often

4:18 you have the example of video data combined with structured data, with

4:22 data coming from the wind tunnel

4:24 and it is about how do we combine it and get information all that we want.

4:29 And then also let let you do the job.

4:32 Yeah. Somehow, yeah.

4:33 Or at least the jobs that are too time consuming for the human brain to

4:37 to conduct or where one brain is not, not, not good enough.

4:42 How much difference does the driver make to a race car?

4:45 And while we were getting acquainted out there, I sort of said, well,

4:49 how would you weight the car

4:52 versus the driver versus the pit crew

4:57 versus the team principle on race.

5:00 It's all about the team

5:04 no, it's not all about the team principle.

5:08 Yeah.

5:08 In Formula One, because everybody does his own car,

5:12 so you cannot buy a car from someone else

5:15 or there's not ten different not not ten the same.

5:19 So car performance is dominant there.

5:22 So to put the percentage is now quite difficult. But

5:26 I think Sebastian is the best example. Yep.

5:29 He won four world championships in, in the pool

5:33 and he struggled last year with our car because the car was not performing enough.

5:37 So you have and I think if we give him a car that can win, he will.

5:42 Yeah, he will win.

5:43 So I think the large percentage is the car

5:47 and then it's certainly the drivers next to say

5:52 percentage is difficult, but for sure more than 50% of the car 50% of the cars.

5:57 Yeah. Yeah.

5:59 And then you have seen you go to last year in the championship with Max Estaban

6:02 and his teammate Luis Hammonds and the teammates,

6:06 you see what the difference the driver can make.

6:07 Yes. Yeah.

6:08 If, if, if, if the car is at its peak and the drivers can add to it.

6:13 Yeah. Yeah.

6:14 And then obviously the crew, the pit stop the strategy guys.

6:17 We should not forget and they make the rest.

6:20 Yeah. So if we see

6:23 60, 30, ten, then at that 60. 310.

6:26 Are we then.

6:27 Get close enough,

6:28 you know,

6:28 think about and think, well how am I going to get the best out of Sebastian?

6:32 Yeah.

6:32 I mean the most important first of all is to have the trust between the two

6:36 and not only between the two of us,

6:37 but also between the team and the driver and the driver team.

6:40 And he's a great guy

6:43 and he's obviously getting got older.

6:46 Yeah, me too.

6:48 And the conversations are a little bit different than they used to be

6:52 because we all have families now and then and stuff like that.

6:55 And we had also we were less in touch in the period

6:58 in between when we did not work together when he won these world titles. And

7:03 so, yeah, the conversations are

7:08 more multifold.

7:09 You have you we speak about family we speak about private life as we speak

7:13 also.

7:14 And here is one of the important bits of Sebastian with his experience

7:18 and and what he has learned over all these years.

7:22 He's not only a driver for us, but he's someone that needs to help

7:26 us develop the team because

7:30 we are on the path.

7:31 Yeah, we have a plan

7:33 for the next years, and it is important that we have key people like him

7:37 who can be a motivating factor

7:40 and also help us steer the ship in the right direction

7:42 because he sees also from another perspective, from the driver perspective.

7:46 So from that point of view,

7:49 the series discussions go along with what development direction have we taken.

7:54 And I think it's very, very important for a person

7:58 like Sebastian who is now close to 35 years old,

8:02 very intelligent person

8:05 to understand where we are moving and hear what he has to say about it.

8:09 Because he has to believe in this direction as well.

8:11 Otherwise, we are not we are not in another line.

8:14 So a lot of conversations go in that direction.

8:17 You know, where are we heading to

8:20 and how do we organize ourselves?

8:22 These discussions that you don't have with every driver,

8:25 how you organize, how we structured your organization, you know,

8:29 but I rate I rate his opinion very high, and that's why

8:32 we have these conversations.

8:33 So how do you get high performers to keep going when they hit the wall

8:38 and we spoke about this bit earlier, I like Schumacher crashing

8:41 pretty, pretty heavily.

8:44 How do you get them back up?

8:45 How do you bring them back up for the next race?

8:48 Yeah, I mean, race drivers, they have

8:50 they have a lot of internal motivation already.

8:52 You don't have to really motivate them to race. But

8:56 I think it's

8:56 very important that and we had it with Kofi also now with with Sebastian,

9:00 he they come back and they had to have the hit or

9:05 even if it is a bad performance or whatever,

9:06 I think it's very important that you speak to them

9:10 and also show the appreciation or how important it is.

9:14 I mean, I spoke spoke to Sebastian today and I gave him the example

9:17 that we are all super happy that he's back.

9:21 And I think he needs that as well. Yes.

9:24 To to to get a bit more out

9:25 because I said it initially the trust between the team and the driver,

9:28 if the driver feels trusted, I think there's maybe a little two

9:31 to three tenths extra that he has that maybe he doesn't have.

9:36 If he doesn't trust so again, it comes down to the human relationship

9:40 between between the driver and the team or the people that deal with the.

9:45 Drivers

9:47 how do you see

9:48 budget caps affecting your ability to innovate

9:51 and how do you balance that with operational challenges?

9:55 Yeah, but is CAP is new since the beginning of 2021.

10:00 So we have to basically

10:05 what what I said before when we want to develop the car. No,

10:08 before when you have unlimited resource, you could say, OK,

10:12 I go five parallel path and I try to

10:16 see what is the best.

10:17 Yeah.

10:17 And I leave completely open my development field and I see which returns the best.

10:24 With the budget cap, you have to go much more into value for money and identify

10:29 to give you an example is downforce

10:32 giving me more lap time or weight reduction?

10:34 Give more power because I will not be able anymore to do everything so

10:41 now obviously

10:42 the budget cap has a value this year and it has it will reduce

10:46 the do what you must, what you must spend will reduce more and more over the years.

10:50 So I think it's very important that you have a very good overview

10:53 of your cost structure.

10:55 Where do I spend, what does it cost me to reduce rate

10:58 and what is the basically the lap time per

11:00 dollar spent that I will get from it and to establish

11:05 these sensitivities is very, very time consuming and but very important.

11:09 So before you had for example,

11:13 technicians in the room,

11:15 technicians and engineers only and drivers.

11:18 Now the finance guys come as well.

11:19 Of course,

11:21 you have to say we certainly have this.

11:23 I'm not allowed now, but this is this is the way we we have to tackle it

11:27 because the cost engineering is very, very important so that you

11:31 you have a very good overview of what gives you

11:33 the most return for the money you spent. OK?

11:37 And yet to be able to still innovate is is just the next step.

11:42 Yeah.

11:42 When you when you

11:44 when you get to a direction where you think it's promising

11:47 and it gives you a lot of lap time or a lot of performance,

11:51 then you have you just have to say I focus on that

11:55 and I say no to the others because to say no is a difficult part, isn't it?

11:59 To say yes?

12:00 Yes, we spend and we do everything we have.

12:02 The idea we have we try to put into reality is easier.

12:05 If you have.

12:06 If you got the money, yes, you could give you Mercedes.

12:08 Yes, it's OK.

12:09 Well, you've certainly indeed yourself to me.

12:11 I'm sure you've enjoyed yourself, too.

12:12 Everybody in the room

12:14 will you'll have 50 or more supporters of Aston Martin this weekend.

12:19 We wish you well and

12:21 sincere.

12:22 Thank you for spending some time with us. Thank you very much.

12:24 We'll do our best. Thank you. I don't think.