Driving the Future
Season 3 Episode 4
Title: Using real-time data to shape the future of connected cars
Transcript
Speakers: Narrator, Tassilo Wirth, & Christian Hummel.
[Music Playing]
Narrator: Welcome to Driving the Future by Capgemini, the podcast where we discuss the automotive industry, the direction it's heading, and how not just to keep up with the rapidly changing business, but to shape it.
According to a statistic from eMarketer, automotive accounted for 23% of all retail sales in the U.S. in 2023. This highlights just how important customer experience is. But how can you go that step further and offer a premium service for the luxury market?
The BMW Group and their Connected Car analytics offers enough insight to provide database decisions, targeted measures, and speed of adaptation. We'll be exploring this in-depth today.
Joining us for this episode is Tassilo Wirth, who is Head of Data & Analytics and Business Intelligence for the Connected Car at the BMW Group.
Tassilo: I was working at BMW for, I don't know, 15 years now, and before, I started my career in a consulting firm within BMW, I was working in different fields, different divisions.
So, I had the opportunity to set up the diversity and inclusion strategy in the past, which was a very interesting and a very good job. And I had a lot of fun, and we reached a lot in that time. And afterwards, I had the possibility to let transformation change the process for digitalisation in sales.
So, we introduced the omnichannel sales system, and now, I'm in data analytics and AI.
Narrator: Joining Tassilo is Christian Hummel. Christian leads the global automotive sector for Capgemini Invent. Capgemini Invent is the managing consultant arm of the Capgemini Group, one of the largest European-based service providers.
Christian: I've been working in automotive for the better part of 20 years on all different continents, so I've seen a lot and worked with a broad variety of manufacturers, suppliers all around the world.
I've seen trends emerge, but particularly, the German manufacturers and BMW has been a company that stuck with me for almost the entire time. I also was very happy to come back.
Narrator: Let's join the conversation where Tassilo tells Christian when BMW first joined the Connected Car market, and why analytics are just so important for BMW Group.
Tassilo: BMW introduced ConnectedDrive over 20 years ago, and with that starting point, digital features are part of the cars. And with that, data analytics started to be very important, in order to improve the customer satisfaction or to improve your products ongoing, but also to make sure that the quality is good, and that you can update your features based on security findings or things like that.
So, I think it's a long history with data analytics and connected cars, and that leads to a big fleet of connected cars out there in the market. So, we have already more than 20 million connected cars driving around on the planet, and we are already becoming more and more a digital company.
Christian: I do think that BMW does it very well and is a very innovative company. There's a shift towards in-car communication. So, it's much more than previously that the customers want a broad range of entertainment functions and so on and so forth, which is also driven by China.
It's fundamental to understand what customers want in order to provide them with products that they really enjoy.
Tassilo: We call it eyes on the road, hands on the wheel, and this leads to a very advanced UI/UX approach because we have more and more functionality in the car, and you need to make sure that this is accessible to customers while driving.
We are forced, or that's our approach, to make it easy for the customers to approach all those functionalities, and in order to learn on how we can improve it, data analytics is the basis for that, and that leads the way a little bit in the industry.
Data analytics was done very centrally, so there was a central team. If you have questions on how a certain functionality is used, you can ask or approach that team and you ask them, and nowadays, it's more decentralised. So, everyone needs to be a data analyst.
So, if you have a product owner for a certain feature, this product owner has the responsibility to make sure that they know about how their feature is used, about their customer feedback, and they are in charge to improve their feature ongoing.
So, it's more decentralised, and in the past, it was more centralised, and this is a big transformation, which was ongoing the last years, and it's still ongoing.
Christian: I've been in this job for quite some time and 15 years ago, we did broad customer studies to understand what customers wanted.
So, you need to understand the fundamental shift this means. You have an immediate feedback that goes back to the design of the car to see how customers are using those features, what kind of features to provide. So, this is really immediate feedback. So, I think it's a step change.
Tassilo: Of course, we focus on usage analytics, so how features are used, but also customer feedback. As you said in the past, there was market research, you did a big research study, but now, you already start to collect feedback directly from customers in the car.
You are used to it from CE devices, so if you use WhatsApp or Teams or something like that, you are asked afterwards for a five-star rating. And we already implemented things like that into the car.
If you use the navigation or the speech assistant, you are directly asked for feedback and you get more and more direct information and you can turn it into product improvements.
Narrator: Real time data collection is very important to shaping the product which BMW offers to the market. Here, Tassilo explains their data privatization policy.
Tassilo: One point is important; data analytics is always based on the data privacy regulations. So, you can only use data and analyse data when the customer gives his opt-in.
So, this is one important point, especially when it comes to premium products, because data privacy is a premium topic, and that's why it is very important to BMW that all data analytics is based on data privacy.
Christian: We did a study, it's already a couple of years ago, and we asked customers who they trusted with their data, and they trusted car companies. Well, in particular also, again, BMW much more than the big tech companies of this world.
Now, obviously, that doesn't hinder them from using the services, but that is certainly part of, or a result of the level of process management that you guys put in place there, and adherence to those guidelines.
Narrator: Turning a traditional automotive manufacturer into a digital native requires a lot of organisation and processes to be in place. Tassilo goes on to speak about how BMW changed their focus from the bottom up.
Tassilo: If you are a traditional industry company and you would like to become more and more a digital native, I have a picture in mind. So, how did you start, because if you think about how it's raining, and then after a little while, you see some puddles of water on the street, and after a little while, you will see a lake of water.
So, what I would like to say is you start with those guys into the company who are motivated to start, they just work in a database, and they just begin to do it. So, it's a change process and bottom up you start with those guys, and they are getting more and more, and then you have a lake in the end.
So, you start bottom up with people who have the skills, who are willing to start, and then you produce best practises, and then also, you start to get top down commitment from the board because they see, okay, you can get product improvements out of that, you can get cost savings, you can handle quality issues faster.
So, this is I think the starting point of a classical transformation. So, you do it bottom up and top down, and that's how we did it in that case as well.
Christian: I've observed this from the outside, and I think it was really interesting to see in the beginning, your team was one of the first, let's say, digital teams in the automotive industry in general. And it was really interesting to see exactly how you describe from a department into something that's basically influencing the entire company, right?
Tassilo: Yeah, that was a big challenge to have cross-functional teams and let's say a coalition of the willing.
So, you just integrate people who have the same mindset, and then it's becoming a movement. I think currently, we collect more than 50 million drives per week. So, it's a really big amount of data. And in order to make sure that you can use the data to derive insights and to derive decisions, you need a proper IT infrastructure.
So, with scalable tools, state of the art, and that's the one thing technology-wise, but you also need the processes and the roles and responsibilities behind. And the good thing is at BMW, from my perspective, we have a robust IT strategy where we can rely on, that's the first thing.
But another thing is the process to make sure that the data you collect, you need first to make sure that you know what kind of data you would like to collect. Then you get the data, and then you need to make sure that you have a testing process that the data points you collect there, the quality is good of the data.
And then you can start to set up a, we call it semantic data asset, so that you can start to analyse it and derive insights. So, you need to have that process in place to make sure that you correct the right data in the right quality, and then to derive insights and decisions.
Christian: It's also amazing to see the evolution from a traditional car company, as you said, from a product-driven company to a digital company.
I remember the first time I had a meeting, we were talking about the setup of a connected company and the founder or the general manager at the time, he told me, “Bring me the guy in your company that has done the biggest software project that you know.”
And I've searched the entire company, I brought somebody and then they were talking for about the better part of two hours. They were obviously understanding each other. In the end, he said, “I need exactly what you've been doing times a hundred.”
So, you know the amount when you talk about features, when you talk about autonomous driving or highly automated driving, so the complexities you're dealing with. So, then you understand how big the transformation has been.
Narrator: The transformation has been huge. And as mentioned something which the rest of the automotive industry has been watching closely. The conversation moved back to analytics, but this time, the focus shifted to insights and being scalable. Here's Tassilo.
Tassilo: The developer integrates data analytics in their day-to-day work because then it's less effort for everyone and you can scale it, and we call it time to insight.
So, the time from you would like to have an insight, and until you have the insight, in the past it was almost two years and now, it's, I don't know, two hours. So, you can reduce the time to insight a lot, and this is based on that integration into the standard processes. But it took a long time to get there, and it was hard work.
Christian: Everybody talks about analytics and about AI and all the fancy things you can do with it, but if you don't have the proper infrastructure for really driving database decisions or database processes, you're going to fail. And I think that that groundwork is really essential.
Tassilo: One thing is to have scalable tools in place, and in that case, you talk about digitalisation, it is going across all verticals in a company. So, it's touching after sales production, so it's everywhere. And if you would like to combine data points out of different verticals, it helps if the whole company is using the same IT infrastructure and the same tools.
So, you can share data assets and then you can derive better insights out of it. And I think this is a major topic that your infrastructure is shared across the different departments and across the different verticals because then it's more scalable and you are faster.
This is always a challenge because if you have different departments, they have different problems, different strategies, and they somehow say they need different tools, but then you have, I don't know, many hundreds of tools, but you cannot combine it. They do not talk to each other, and then you need to bring it together again. And that's the challenge you're facing here.
Christian: The data you are collecting and analysing maybe in combination with direct customer feedback like verbatims or something like that will even become more important in the future.
You were mentioning earlier the timeframe, and you need to envision what this means. So, you get an immediate feedback, you can play out a new feature or something like that. So, a response immediately.
So, this is real personalisation, this is real communication with customers. So, you have the tools then to drive satisfaction and to really tailor the services that you provide to customer requirements. So, that's the step change I was talking about earlier.
Tassilo: Somehow, it depends a little bit on which phase you are in. So, if you are in a very early phase where you think about possible future products, then you need different insights than if you have a product already in place and you think about how you can improve it.
So, you have different phases of the product development process, and you have different insights you're using for that, and customer feedback is always relevant. So, first of all, you need to find out what are the customer expectations? Are customers willing to pay for certain services, or is that expected as a basis?
So, customer feedback is relevant in an early phase. And also, then if you have the product in place, you need to think about, okay, did we implement it in quality? Is it working out? What could we improve? Is it not used? Or maybe it's not relevant anymore. Can we just delete it for the future next version of our car?
So, in a different phase of the product development, you use different insights, but customer feedback is always relevant.
Christian: That's fantastic. And in our experience, I mean this is now 50/50 driving the purchasing decision just as much as car features and quality and so on and so forth.
And it increasingly becomes important; this is something that came to my mind with all the regional developments. So, in other words, customer requirements differ between regions. So, you can adapt to specific requirements.
Tassilo: Now, we have technology-wise, the possibility to update our product in a very fast cycle.
So, you have the possibility to just change something on your product, and then you rely on feedback from the customer to know what to adapt. And that's a big change to the past because in the past, we had one update per year, I don't know. But if you think about the CE industry, you update your smartphone or your apps on your smartphone, maybe weekly or daily.
So, there's also some steps to go to be able to update your car features daily, but then you need more and more data and customer feedback in order to improve it. There are big differences between the different regions, and now, we have the possibility. The car is the same, but maybe the digital features are different from country to country.
One easy example is China and U.S. and Europe. So, in China, of course, everyone is using WeChat, for example, or QQ Music. And in the U.S. and in Europe, everyone is using WhatsApp and Spotify. So, you bring different third-party apps into the car and adapt to the local markets or to the customer requirements.
Narrator: Adjusting the in-car technology due to the region the customer is in, is an interesting and very hot topic within the automotive industry. With all this talk of apps, at this point, the chat moved quickly to talk about the future of the car market and how BMW is putting an emphasis on entertainment.
Tassilo: In the future, you will see more and more electric cars on the road, and electric cars are charging, and this takes maybe 30 minutes. So, what are customers doing at that time? So, you now introduce more and more features where customers can spend those 30 minutes time for us.
So, social media, video streaming. So, those use cases are more and more relevant in future because the electric car market is expanding, but at the same time, you also have autonomous driving.
So, first, autonomous features and to improve that, and you offer those features to customers, but also in that time, when their car is autonomous driving, what are customers doing in that time?
So, you introduce new features, and you need to find out which one is relevant, which app you integrate, and so on.
Christian: The amount of functions I think will be exploding in the future. Gaming has been introduced and a lot of other entertainment functions, but just as Tassilo was saying, because there is time to spend in a car, it's basically limitless what you can offer and bring into the car.
Tassilo: Yeah, and we don't have the money to offer everything. So, we need to focus and to prioritise, and therefore customer insights are extremely relevant. To know, okay, which app is most relevant? Which app do we integrate?
And then if you have it integrated, you need to decide on is it still used? Why is it not used, how can we improve it? Do we reduce it and put another app into the car?
Christian: That's a great point by the way, because as the options are limitless as you say, you need to make sure it's meaningful.
Narrator: As ever with Driving the Future, the topic of encouraging talent into the industry is an important one. Tassilo explains what skills are needed to be successful within the BMW Group and their new analytics focus.
Tassilo: Well, first, you need passionate people. Passionate people who share the same vision and who have the same purpose. They should believe in the purpose of a data-driven company, and that is the most important point.
And then coming to a special skillset, somehow, we are looking for people who like to code. And it's not necessarily important that they have experience with a certain tool because tools are coming and going. And if you maybe looking today for an expert of AWS, then in future, maybe you change the technology and you use only AI maybe.
So, you need the passionate people, and they learn the technology from today, and they are open and they are curious to learn also the future skills.
Christian: He makes it sound so easy, but I've seen the team, and I think this is really a huge achievement because you have people that understand the business, let me put it this way, and understand the requirements at the same time, very technical profiles.
As you say, people that know how to code and they all merge together in one team with that purpose that you've been describing. So, I think this is really an achievement and this is a key to success because I've seen, on the other hand, a lot of companies fail at this. They bring in excellent people, but they just don't find the right way of working together because everybody has a different way of working.
So, I think this is really a real management task to do, to form a team and be successful and effective at that.
Tassilo: It is a challenge to build a team out of those individuals because those data engineers and data analysts and data scientists and so on, on the first view, they are somehow special, but they are all different. But they share the same passion about coding and data-based working, and they want to have a community where they can exchange, where they can get the best practises.
So, yeah, people who are like-minded, and if you focus on a diverse team but sharing the same vision and purpose, then you have that inclusive culture.
Christian: That is also why I'm not too worried about the German automotive industry in general and BMW in particular. Even though at the moment, there's a lot of talk around other outdated products. What about things we see in China? But the strength and the talent and the tradition and the DNA that those companies have is such a big advantage, and the adaptability.
So, I am a hundred percent certain with new product ranges, they're going to come out on top.
Tassilo: We are getting more and more diverse. And this makes absolutely sense because our customers are diverse first. This is the first thing.
The second thing is we are hiring only the best people, and we don't care about gender or age or your intercultural background. So, the skillset and the mindset and the sharing vision and purpose which matters.
So, coming from that perspective, it will get more and more diverse. And that's a challenge for the management, that you are able to integrate those people and have an inclusive culture that makes it possible that all those people are bringing their skills to decisions to good results.
Christian: Well, maybe what also helps is that you just have a great product, people enjoy working on an exciting product and new stuff.
Tassilo: Yeah. And interesting-wise, one topic which is very important is good coffee. So, it's not only about a good product, of course, it’s a big benefit or a good brand, but if you have a nice or a good environment in the office, and one thing is good coffee.
So, we saw that after the pandemic situation, people came back into the office and one thing was they don't come back if you don't have good coffee.
Narrator: I think most of us can agree that good coffee is very important. For me, it's important to have black, no cream, no sugar.
Looking to the future, both Tassilo and Christian, explain why now is a good time to join the automotive industry.
Tassilo: It's a challenge to transform this traditional company into a tech company. And this is much more complicated than just working in a digital company. And that's that challenge.
You can be part of that transformation, and you can also lead that transformation at BMW, because our objective is always to be number one in that transformation. An interesting thing is that you don't have examples, so you need to lead the way. And that's the interesting thing.
You can learn from digital companies a lot, but you cannot just copy it and apply it in a traditional company, it'll not work. So, you can learn best practices, but you need to adapt in order to make it happen or to make it running in a traditional company.
And that's the interesting challenge, and then in the end, you see great products on the road, and that's nothing better than that.
Christian: I started working quite some time ago, and at that time, it was really interesting because I talked to my peers at university, what we wanted to do. And at the time, product companies, we saw it as boring, and then I went to work in the automotive industry. And I've got to say, it's probably the industry that had the most change in the last 20 years.
And literally, everything you see going on in the outside world, whether it's energy changes, technology changes, digitalization, has found its way into those product, and you still have a great product.
So, I can just reiterate what Tassilo was saying, it's never boring and it's always a challenge, and the amount of new talent that I've seen coming into the industry from all kinds of sectors is amazing. And to have this flexibility, requires a very high level of management capability to be able to absorb that and make it your own.
[Music Playing]
Narrator: It's certainly a good time to join the automotive industry. And they're right, across the whole of automotive, we're seeing lots of talent join from other sectors and with it, bringing their knowledge, experience, and fresh perspectives, which are accelerating new product offerings, features, and ideas for customers to ultimately benefit from.
Thanks to both Tassilo and Christian for giving their insights and observations on how a traditional automotive company has been reshaped for the future. And thank you for listening to this episode of Driving the Future by Capgemini. See you next time.
Season 3 Episode 4
Title: Using real-time data to shape the future of connected cars
Transcript
Speakers: Narrator, Tassilo Wirth, & Christian Hummel.
[Music Playing]
Narrator: Welcome to Driving the Future by Capgemini, the podcast where we discuss the automotive industry, the direction it's heading, and how not just to keep up with the rapidly changing business, but to shape it.
According to a statistic from eMarketer, automotive accounted for 23% of all retail sales in the U.S. in 2023. This highlights just how important customer experience is. But how can you go that step further and offer a premium service for the luxury market?
The BMW Group and their Connected Car analytics offers enough insight to provide database decisions, targeted measures, and speed of adaptation. We'll be exploring this in-depth today.
Joining us for this episode is Tassilo Wirth, who is Head of Data & Analytics and Business Intelligence for the Connected Car at the BMW Group.
Tassilo: I was working at BMW for, I don't know, 15 years now, and before, I started my career in a consulting firm within BMW, I was working in different fields, different divisions.
So, I had the opportunity to set up the diversity and inclusion strategy in the past, which was a very interesting and a very good job. And I had a lot of fun, and we reached a lot in that time. And afterwards, I had the possibility to let transformation change the process for digitalisation in sales.
So, we introduced the omnichannel sales system, and now, I'm in data analytics and AI.
Narrator: Joining Tassilo is Christian Hummel. Christian leads the global automotive sector for Capgemini Invent. Capgemini Invent is the managing consultant arm of the Capgemini Group, one of the largest European-based service providers.
Christian: I've been working in automotive for the better part of 20 years on all different continents, so I've seen a lot and worked with a broad variety of manufacturers, suppliers all around the world.
I've seen trends emerge, but particularly, the German manufacturers and BMW has been a company that stuck with me for almost the entire time. I also was very happy to come back.
Narrator: Let's join the conversation where Tassilo tells Christian when BMW first joined the Connected Car market, and why analytics are just so important for BMW Group.
Tassilo: BMW introduced ConnectedDrive over 20 years ago, and with that starting point, digital features are part of the cars. And with that, data analytics started to be very important, in order to improve the customer satisfaction or to improve your products ongoing, but also to make sure that the quality is good, and that you can update your features based on security findings or things like that.
So, I think it's a long history with data analytics and connected cars, and that leads to a big fleet of connected cars out there in the market. So, we have already more than 20 million connected cars driving around on the planet, and we are already becoming more and more a digital company.
Christian: I do think that BMW does it very well and is a very innovative company. There's a shift towards in-car communication. So, it's much more than previously that the customers want a broad range of entertainment functions and so on and so forth, which is also driven by China.
It's fundamental to understand what customers want in order to provide them with products that they really enjoy.
Tassilo: We call it eyes on the road, hands on the wheel, and this leads to a very advanced UI/UX approach because we have more and more functionality in the car, and you need to make sure that this is accessible to customers while driving.
We are forced, or that's our approach, to make it easy for the customers to approach all those functionalities, and in order to learn on how we can improve it, data analytics is the basis for that, and that leads the way a little bit in the industry.
Data analytics was done very centrally, so there was a central team. If you have questions on how a certain functionality is used, you can ask or approach that team and you ask them, and nowadays, it's more decentralised. So, everyone needs to be a data analyst.
So, if you have a product owner for a certain feature, this product owner has the responsibility to make sure that they know about how their feature is used, about their customer feedback, and they are in charge to improve their feature ongoing.
So, it's more decentralised, and in the past, it was more centralised, and this is a big transformation, which was ongoing the last years, and it's still ongoing.
Christian: I've been in this job for quite some time and 15 years ago, we did broad customer studies to understand what customers wanted.
So, you need to understand the fundamental shift this means. You have an immediate feedback that goes back to the design of the car to see how customers are using those features, what kind of features to provide. So, this is really immediate feedback. So, I think it's a step change.
Tassilo: Of course, we focus on usage analytics, so how features are used, but also customer feedback. As you said in the past, there was market research, you did a big research study, but now, you already start to collect feedback directly from customers in the car.
You are used to it from CE devices, so if you use WhatsApp or Teams or something like that, you are asked afterwards for a five-star rating. And we already implemented things like that into the car.
If you use the navigation or the speech assistant, you are directly asked for feedback and you get more and more direct information and you can turn it into product improvements.
Narrator: Real time data collection is very important to shaping the product which BMW offers to the market. Here, Tassilo explains their data privatization policy.
Tassilo: One point is important; data analytics is always based on the data privacy regulations. So, you can only use data and analyse data when the customer gives his opt-in.
So, this is one important point, especially when it comes to premium products, because data privacy is a premium topic, and that's why it is very important to BMW that all data analytics is based on data privacy.
Christian: We did a study, it's already a couple of years ago, and we asked customers who they trusted with their data, and they trusted car companies. Well, in particular also, again, BMW much more than the big tech companies of this world.
Now, obviously, that doesn't hinder them from using the services, but that is certainly part of, or a result of the level of process management that you guys put in place there, and adherence to those guidelines.
Narrator: Turning a traditional automotive manufacturer into a digital native requires a lot of organisation and processes to be in place. Tassilo goes on to speak about how BMW changed their focus from the bottom up.
Tassilo: If you are a traditional industry company and you would like to become more and more a digital native, I have a picture in mind. So, how did you start, because if you think about how it's raining, and then after a little while, you see some puddles of water on the street, and after a little while, you will see a lake of water.
So, what I would like to say is you start with those guys into the company who are motivated to start, they just work in a database, and they just begin to do it. So, it's a change process and bottom up you start with those guys, and they are getting more and more, and then you have a lake in the end.
So, you start bottom up with people who have the skills, who are willing to start, and then you produce best practises, and then also, you start to get top down commitment from the board because they see, okay, you can get product improvements out of that, you can get cost savings, you can handle quality issues faster.
So, this is I think the starting point of a classical transformation. So, you do it bottom up and top down, and that's how we did it in that case as well.
Christian: I've observed this from the outside, and I think it was really interesting to see in the beginning, your team was one of the first, let's say, digital teams in the automotive industry in general. And it was really interesting to see exactly how you describe from a department into something that's basically influencing the entire company, right?
Tassilo: Yeah, that was a big challenge to have cross-functional teams and let's say a coalition of the willing.
So, you just integrate people who have the same mindset, and then it's becoming a movement. I think currently, we collect more than 50 million drives per week. So, it's a really big amount of data. And in order to make sure that you can use the data to derive insights and to derive decisions, you need a proper IT infrastructure.
So, with scalable tools, state of the art, and that's the one thing technology-wise, but you also need the processes and the roles and responsibilities behind. And the good thing is at BMW, from my perspective, we have a robust IT strategy where we can rely on, that's the first thing.
But another thing is the process to make sure that the data you collect, you need first to make sure that you know what kind of data you would like to collect. Then you get the data, and then you need to make sure that you have a testing process that the data points you collect there, the quality is good of the data.
And then you can start to set up a, we call it semantic data asset, so that you can start to analyse it and derive insights. So, you need to have that process in place to make sure that you correct the right data in the right quality, and then to derive insights and decisions.
Christian: It's also amazing to see the evolution from a traditional car company, as you said, from a product-driven company to a digital company.
I remember the first time I had a meeting, we were talking about the setup of a connected company and the founder or the general manager at the time, he told me, “Bring me the guy in your company that has done the biggest software project that you know.”
And I've searched the entire company, I brought somebody and then they were talking for about the better part of two hours. They were obviously understanding each other. In the end, he said, “I need exactly what you've been doing times a hundred.”
So, you know the amount when you talk about features, when you talk about autonomous driving or highly automated driving, so the complexities you're dealing with. So, then you understand how big the transformation has been.
Narrator: The transformation has been huge. And as mentioned something which the rest of the automotive industry has been watching closely. The conversation moved back to analytics, but this time, the focus shifted to insights and being scalable. Here's Tassilo.
Tassilo: The developer integrates data analytics in their day-to-day work because then it's less effort for everyone and you can scale it, and we call it time to insight.
So, the time from you would like to have an insight, and until you have the insight, in the past it was almost two years and now, it's, I don't know, two hours. So, you can reduce the time to insight a lot, and this is based on that integration into the standard processes. But it took a long time to get there, and it was hard work.
Christian: Everybody talks about analytics and about AI and all the fancy things you can do with it, but if you don't have the proper infrastructure for really driving database decisions or database processes, you're going to fail. And I think that that groundwork is really essential.
Tassilo: One thing is to have scalable tools in place, and in that case, you talk about digitalisation, it is going across all verticals in a company. So, it's touching after sales production, so it's everywhere. And if you would like to combine data points out of different verticals, it helps if the whole company is using the same IT infrastructure and the same tools.
So, you can share data assets and then you can derive better insights out of it. And I think this is a major topic that your infrastructure is shared across the different departments and across the different verticals because then it's more scalable and you are faster.
This is always a challenge because if you have different departments, they have different problems, different strategies, and they somehow say they need different tools, but then you have, I don't know, many hundreds of tools, but you cannot combine it. They do not talk to each other, and then you need to bring it together again. And that's the challenge you're facing here.
Christian: The data you are collecting and analysing maybe in combination with direct customer feedback like verbatims or something like that will even become more important in the future.
You were mentioning earlier the timeframe, and you need to envision what this means. So, you get an immediate feedback, you can play out a new feature or something like that. So, a response immediately.
So, this is real personalisation, this is real communication with customers. So, you have the tools then to drive satisfaction and to really tailor the services that you provide to customer requirements. So, that's the step change I was talking about earlier.
Tassilo: Somehow, it depends a little bit on which phase you are in. So, if you are in a very early phase where you think about possible future products, then you need different insights than if you have a product already in place and you think about how you can improve it.
So, you have different phases of the product development process, and you have different insights you're using for that, and customer feedback is always relevant. So, first of all, you need to find out what are the customer expectations? Are customers willing to pay for certain services, or is that expected as a basis?
So, customer feedback is relevant in an early phase. And also, then if you have the product in place, you need to think about, okay, did we implement it in quality? Is it working out? What could we improve? Is it not used? Or maybe it's not relevant anymore. Can we just delete it for the future next version of our car?
So, in a different phase of the product development, you use different insights, but customer feedback is always relevant.
Christian: That's fantastic. And in our experience, I mean this is now 50/50 driving the purchasing decision just as much as car features and quality and so on and so forth.
And it increasingly becomes important; this is something that came to my mind with all the regional developments. So, in other words, customer requirements differ between regions. So, you can adapt to specific requirements.
Tassilo: Now, we have technology-wise, the possibility to update our product in a very fast cycle.
So, you have the possibility to just change something on your product, and then you rely on feedback from the customer to know what to adapt. And that's a big change to the past because in the past, we had one update per year, I don't know. But if you think about the CE industry, you update your smartphone or your apps on your smartphone, maybe weekly or daily.
So, there's also some steps to go to be able to update your car features daily, but then you need more and more data and customer feedback in order to improve it. There are big differences between the different regions, and now, we have the possibility. The car is the same, but maybe the digital features are different from country to country.
One easy example is China and U.S. and Europe. So, in China, of course, everyone is using WeChat, for example, or QQ Music. And in the U.S. and in Europe, everyone is using WhatsApp and Spotify. So, you bring different third-party apps into the car and adapt to the local markets or to the customer requirements.
Narrator: Adjusting the in-car technology due to the region the customer is in, is an interesting and very hot topic within the automotive industry. With all this talk of apps, at this point, the chat moved quickly to talk about the future of the car market and how BMW is putting an emphasis on entertainment.
Tassilo: In the future, you will see more and more electric cars on the road, and electric cars are charging, and this takes maybe 30 minutes. So, what are customers doing at that time? So, you now introduce more and more features where customers can spend those 30 minutes time for us.
So, social media, video streaming. So, those use cases are more and more relevant in future because the electric car market is expanding, but at the same time, you also have autonomous driving.
So, first, autonomous features and to improve that, and you offer those features to customers, but also in that time, when their car is autonomous driving, what are customers doing in that time?
So, you introduce new features, and you need to find out which one is relevant, which app you integrate, and so on.
Christian: The amount of functions I think will be exploding in the future. Gaming has been introduced and a lot of other entertainment functions, but just as Tassilo was saying, because there is time to spend in a car, it's basically limitless what you can offer and bring into the car.
Tassilo: Yeah, and we don't have the money to offer everything. So, we need to focus and to prioritise, and therefore customer insights are extremely relevant. To know, okay, which app is most relevant? Which app do we integrate?
And then if you have it integrated, you need to decide on is it still used? Why is it not used, how can we improve it? Do we reduce it and put another app into the car?
Christian: That's a great point by the way, because as the options are limitless as you say, you need to make sure it's meaningful.
Narrator: As ever with Driving the Future, the topic of encouraging talent into the industry is an important one. Tassilo explains what skills are needed to be successful within the BMW Group and their new analytics focus.
Tassilo: Well, first, you need passionate people. Passionate people who share the same vision and who have the same purpose. They should believe in the purpose of a data-driven company, and that is the most important point.
And then coming to a special skillset, somehow, we are looking for people who like to code. And it's not necessarily important that they have experience with a certain tool because tools are coming and going. And if you maybe looking today for an expert of AWS, then in future, maybe you change the technology and you use only AI maybe.
So, you need the passionate people, and they learn the technology from today, and they are open and they are curious to learn also the future skills.
Christian: He makes it sound so easy, but I've seen the team, and I think this is really a huge achievement because you have people that understand the business, let me put it this way, and understand the requirements at the same time, very technical profiles.
As you say, people that know how to code and they all merge together in one team with that purpose that you've been describing. So, I think this is really an achievement and this is a key to success because I've seen, on the other hand, a lot of companies fail at this. They bring in excellent people, but they just don't find the right way of working together because everybody has a different way of working.
So, I think this is really a real management task to do, to form a team and be successful and effective at that.
Tassilo: It is a challenge to build a team out of those individuals because those data engineers and data analysts and data scientists and so on, on the first view, they are somehow special, but they are all different. But they share the same passion about coding and data-based working, and they want to have a community where they can exchange, where they can get the best practises.
So, yeah, people who are like-minded, and if you focus on a diverse team but sharing the same vision and purpose, then you have that inclusive culture.
Christian: That is also why I'm not too worried about the German automotive industry in general and BMW in particular. Even though at the moment, there's a lot of talk around other outdated products. What about things we see in China? But the strength and the talent and the tradition and the DNA that those companies have is such a big advantage, and the adaptability.
So, I am a hundred percent certain with new product ranges, they're going to come out on top.
Tassilo: We are getting more and more diverse. And this makes absolutely sense because our customers are diverse first. This is the first thing.
The second thing is we are hiring only the best people, and we don't care about gender or age or your intercultural background. So, the skillset and the mindset and the sharing vision and purpose which matters.
So, coming from that perspective, it will get more and more diverse. And that's a challenge for the management, that you are able to integrate those people and have an inclusive culture that makes it possible that all those people are bringing their skills to decisions to good results.
Christian: Well, maybe what also helps is that you just have a great product, people enjoy working on an exciting product and new stuff.
Tassilo: Yeah. And interesting-wise, one topic which is very important is good coffee. So, it's not only about a good product, of course, it’s a big benefit or a good brand, but if you have a nice or a good environment in the office, and one thing is good coffee.
So, we saw that after the pandemic situation, people came back into the office and one thing was they don't come back if you don't have good coffee.
Narrator: I think most of us can agree that good coffee is very important. For me, it's important to have black, no cream, no sugar.
Looking to the future, both Tassilo and Christian, explain why now is a good time to join the automotive industry.
Tassilo: It's a challenge to transform this traditional company into a tech company. And this is much more complicated than just working in a digital company. And that's that challenge.
You can be part of that transformation, and you can also lead that transformation at BMW, because our objective is always to be number one in that transformation. An interesting thing is that you don't have examples, so you need to lead the way. And that's the interesting thing.
You can learn from digital companies a lot, but you cannot just copy it and apply it in a traditional company, it'll not work. So, you can learn best practices, but you need to adapt in order to make it happen or to make it running in a traditional company.
And that's the interesting challenge, and then in the end, you see great products on the road, and that's nothing better than that.
Christian: I started working quite some time ago, and at that time, it was really interesting because I talked to my peers at university, what we wanted to do. And at the time, product companies, we saw it as boring, and then I went to work in the automotive industry. And I've got to say, it's probably the industry that had the most change in the last 20 years.
And literally, everything you see going on in the outside world, whether it's energy changes, technology changes, digitalization, has found its way into those product, and you still have a great product.
So, I can just reiterate what Tassilo was saying, it's never boring and it's always a challenge, and the amount of new talent that I've seen coming into the industry from all kinds of sectors is amazing. And to have this flexibility, requires a very high level of management capability to be able to absorb that and make it your own.
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Narrator: It's certainly a good time to join the automotive industry. And they're right, across the whole of automotive, we're seeing lots of talent join from other sectors and with it, bringing their knowledge, experience, and fresh perspectives, which are accelerating new product offerings, features, and ideas for customers to ultimately benefit from.
Thanks to both Tassilo and Christian for giving their insights and observations on how a traditional automotive company has been reshaped for the future. And thank you for listening to this episode of Driving the Future by Capgemini. See you next time.
