Expert insight – Adam O’Shaughnessy, SBD Automotive

Through independent research, evaluation and strategic consulting support, SBD Automotive helps vehicle manufacturers and their partners create autonomous, more secure and better connected cars. Adam O’Shaughnessy is a Senior Specialist – Connected Car. 

Lorna: Can you tell me a little bit about your background and how you’ve come to be working with data and statistics and so on?

Adam: My degree was in mechanical engineering. There’s obviously a fair amount of data analysis there. After I left university, I joined SBD Automotive – a market research and technical consulting firm that operates in the automotive sector. The head office is in Milton Keynes. Then we have offices in Germany, Shanghai, Bangalore, India, in Japan and Detroit in the US: anywhere that that there’s an automotive hub of some sort. The company is very data-centric. Everything we do is related to proving the point with data of some sort.

We work with clients across the board in the automotive industry. Our main clients are vehicle manufacturers, but we also work with anyone else in the automotive value chain as such. It could be mobile network operator such as Orange, Vodafone. It could be your traditional Tier-1 suppliers such as Bosch, Denso. Those types of companies. We’re increasingly finding that we work with consumer electronics companies as well because they’re starting to get into the automotive space.

We work across three areas, really. We have security, we have an autonomous car division and then we have the connected car department, which is the department I’m in. That covers things like the car’s entertainment systems and navigation systems, the user experience in the car, and the backend IT infrastructure.

Lorna: Are you using data that the client companies bring to you, or you’re generating your own data? How does that generally work?

Adam: A bit of both. The majority data we’ve generated ourselves, but we do also have clients give us data. We do our own consumer surveys and we’re also using data generated from other research projects. We just done one on biometrics, for example, which has got a huge amount of data. You’re talking gigabytes of data. Then, we have our own internal datasets based on the market conditions. What the OEMs are selling cars for, how much they’re selling services for, which models are selling and to whom, et cetera, et cetera.

Lorna: What would you say are the main challenges that are facing the automotive industry these days?

Adam: Well, the big one, obviously, for last 5 or 10 years is big data. The idea that you have all these connected cars, if you extract data from them, that can be location data, it could be data about the driver in the car, it could be data about the vehicle, such as are there any fault codes, et cetera. You’ve got huge amounts of data. What can you do with it? How do you monetize this? I think that’s definitely one of the big questions at the moment as well. How do you monetize this data?

The flip side of that is, how do you manage issues to do with data privacy? That’s one of the very big things, alongside questions of who owns the data and what they can do with it. Is it the person in the car who owns the data, or is it the manufacturer, or is it the content provider, or is it Google who owns it? That’s definitely one of the big challenges we’re dealing with at the moment.

Lorna: On the monetizing front, who do you see doing that well at the moment?

Adam: The guys that are doing it well are the ones who have been doing it for a few years, and the ones which are really using in more creative ways. You can monetize data directly by selling it of course. However, what companies such as BMW, GM, and Volvo are doing is using the data from the car to help with warranty-type analysis, to help predict when particular faults are likely to happen, enabling them to fix the car before the fault happens or to do a software update to fix that particular issue. If you can reduce the number of warranty claims in a year, even by only a small amount, the financial rewards can be very significant.

Lorna: Are there any other areas of data-related development in the industry?

Adam: Another big challenge is normalization of the data – getting data from diverse sources into a consistent format for analysis. Different cars can be set up in different ways by different teams in different parts of the country or different parts of the world. That then poses a challenge if you want to give this data to third-party so they can analyze it for you. If it’s not in the same format, you spend a huge amount of your time trying to make the data from each car look the same.

Lorna: How have you seen the experience of working in the analytics industry change over the course of your career?

Adam: GDPR has obviously changed things. We have to do a bit more on the data handling side of things and clients are now much more cautious about what they can do with the data. We have instances where you’d be in a manufacturer and one of the engineers won’t release a certain type of data from the car, because there’s a fear that it could negatively impact them in the future.

Lorna: You talked earlier about this issue of who owns the data. Is there any kind of consensus on how to think about that across the industry?

Adam: Definitely not, no. It’s a battle at the moment between different parties who want to own that data. It’s a bit of a three-way battle between the OEM, that’s the vehicle manufacturer, the content provider, or the consumer electronics industry and consumers. There definitely isn’t a clear trend at the moment. Everybody wants to own it.

Lorna: How much of an issue is data security?

Adam: Security is a massive thing. We have a team that works solely on cyber security. They focus on what data can you extract from a car and how easy is it to extract. You’d be surprised how easy it is. Traditionally the automotive way of doing security was that if people don’t know about it, it’s secure, instead of actually making it secure. Now, there’s definitely a big shift from the very old school way of automotive security, thinking, “Look, let’s hide it, then there won’t be an issue” to actually putting the correct security measures in place.

Lorna: Do you see any additional opportunities for using data and analytics within the automotive industry to better deliver products and services?

Adam: Yes, definitely. The big one is mobility. At the moment, the automotive industry is shifting from people owning cars to people owning fewer cars. With that in mind, there’s a view that if you understand people’s driving habits, where they want to go, when they want to be picked up et cetera then you could have fleets of vehicles available to people, so they don’t actually then have to own a vehicle. If you own a vehicle at the moment, it sits on your car park at the office 99% of the day doing nothing.

However, there are many issues with that yet to be solved. For example, most people go to work at the same time. That’s where the data comes in. Perhaps you could use data to better understand when people could be leaving, how could you make traffic better, et cetera. There are so many different ways when you look at the future of mobility, moving away from everyone owning a car.

Lorna: Could you give any examples of projects that you’ve particularly enjoyed or products that you found particularly frustrating?

Adam: One of the most frustrating ones ended up actually being why we reached out to you guys. We were doing a survey once and that particular client was using SPSS whilst we were still using Excel and they were running rings around us. Stuff we had to take a day to do, they could do it in about two minutes. That was definitely one of the most frustrating things, highlighting how important it is to have the right tool carry out that particular task. Things that can take hours and hours in Excel are just a minute job in SPSS.

The most rewarding project are those where we can give real insight to clients. For example, to be able to say, “These particular people in this study, they think this particular thing and we characterize them in groups A, B, C and D.” That means if you’re going to sell to these particular people, these are things which matter. The reason that’s important is because if you think about the different types of cars from the very A or B type of car such as a VW Polo to a, say, like a E1 or E2 type of car such as a 5-series or 7-series, they’re very different types of cars targeted at very different types of people. If you can analyze the data in the correct way to understand what those type of people really want, then that’s a game changer for us and for our clients.

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