Unlocking Value and Supporting the Software-Defined Vehicle with Data and Connectivity

Point B welcomes special guest, John Correia, Managing Director at Connected Strategy Advisors, on a deep dive into automotive connectivity. How have OEMs leveraged connectivity and data in the past? How can they utilize connectivity to change and improve the customer experience? And what’s next in the realm of predictive analytics and the software-defined vehicle? All is revealed in this episode of Point B.

1:11 Early days of connected vehicle technology

4:08 Awakening to the importance of data

6:15 The internal value of data

8:28 Predictive analytics 

9:45 Transition to the software-defined vehicle

12:18 Challenges OEMs are facing 

12:45 The 5 C’s of connectivity

Announcer:

Welcome back to another episode of Point B. A Sibros podcast where we interview industry experts about the latest innovations and trends in automotive technology and the connected vehicle industry. Tune in to learn about topics ranging from the next generation of electric vehicles to advances in connectivity and micro-mobility.

Steve Schwinke:

Welcome to our Point B podcast, where we discuss the future of mobility and transportation products and services. My name is Steve Schwinke, Vice President of Customer Engagement at Sibros, and today, I have John Correia, Managing Director at Connected Strategy Advisors. Let me first start by introducing John. He's currently Managing Director at Connected Strategy Advisors, where they help clients accelerate their connected product lifecycle. John also held executive positions at both General Motors OnStar and Ford, where he led the development of software-defined platforms and services. John is also a technical fellow in infotainment technology and system integration. John, welcome to Point B.

John Correia:

Thanks, Steve. It's great to be here.

Steve Schwinke:

So, John, what were the early days of connected vehicle technology like, and what were some of the challenges?

John Correia:

Well, Steve, it's hard to believe that for both of us, it was almost 30 years ago that we got involved in this crazy space, and about 27 years ago both Ford and GM tried their hand at connecting vehicles. What we started with was pretty primitive. We started actually with 1G, as they call it, analog radios, no data channel. We had a screaming modem that was somewhere between 14 bits per second, I think, and we had to roll our own modem in that data channel, and we had to switch back and forth between data mode and voice mode. One of our key performance criteria was how quickly we could get the data conversation over with so we could go back to the human conversation. At the time, the industry was mainly focused on the safety and security of the consumer, or the driver of the vehicle.

At that time, I actually started coining a phrase that followed a Maslow hierarchy of needs, where safety and security justified wanting this feature and a willingness to pay for the feature. Then, over time, information, communication, and convenience features begin to sustain the customer and once they feel the initial safety and security and peace of mind, then entertainment ultimately satisfies the customer. And I would say that we're still in the world where we're following that hierarchy, and we're probably still somewhere in the middle of that rung. I don't think we've gotten to the “entertainment ultimately satisfies” I think when we get to the world of semi-autonomous where you've got more time in the vehicle, I think that will really see that take off.

In the early days of OnStar, it was largely peace of mind that drove the heart of the value proposition, providing help for people after a crash or another emergency situation. Overall, the first foray into this space was very successful. OnStar paid off their investment and then some, and we started to develop some other peace of mind services beyond just the automatic crash notification. And that's where we started to get into remote diagnostics. We also got into navigation of sorts, and if you can believe the crude navigation we had the advisor actually recited to you the turn-by-turn directions for the route, and conceivably, you'd have to write that down. So that wasn't the best customer experience, but that evolved over time with onboard navigation and so on.

Steve Schwinke:

There was also this awakening, I would say, that this data could be useful by General Motors in understanding how their products were performing. Can you talk a little bit more about that?

John Correia:

Yeah. I think we started realizing that the data that we were collecting for these remote diagnostic incidents could be a lot more valuable than just those times when you're heading out on a trip, or you push the OnStar button to find out what's going on. We unromantically call that whole genre of area internal benefits. How can we use the connectivity in the car to, not necessarily focus on the end customer's needs and problems to be solved, but how can we use that technology to help the OEM with its needs and its problems to be solved?

And one of those big problems is the warranty. We've got $1 to $2 billion of warranty liability being accrued each year by an OEM, by the big ones anyway. We actually proved that by using this data and getting it into the hands of the subject matter experts that knew how to interpret the data with the right tools, that they could actually find problems sooner than the traditional methods, which would be waiting for the claims to show up at the dealership and waiting for enough of them to pile up that it got on somebody's Pareto chart.

I still think, in general, we probably haven't harnessed the complete capabilities that exist there, and I don't think we're leveraging that data as an industry as much as it could be. But in the early days, the mid-2000s, we did demonstrate and prove that we could save hundreds of millions of dollars off of that annual warranty liability. So it was pretty amazing stuff.

Steve Schwinke:

So you said that the industry as a whole is not taking advantage of this internal value. Is that pretty much the case? I mean, are there more things that they should be doing to really understand product performance and how things are working?

John Correia:

Yeah. If you look more broadly at what are some of the internal benefits, I mean, we talked about how vehicles are performing in the wild with the goal of improving that product and making it better and also finding issues before our customers do or before a lot of our customers do. And keep in mind, the sooner you find the problem, the less customers are impacted and the less vehicles you build with the problem. So it's got a two-pronged approach there. But you also can use that data and that connectivity to understand and monitor how customers are interacting with their vehicles; what features did they use or not use? Where did they have some issues with the use of certain features? Did they start using a feature and abandon it because they got stuck or couldn't figure out how to do it, or didn't like it? And eventually, you can also get into how those vehicles are being driven or how those consumers are behaving in the vehicle.

Another big area was using the data about the vehicle, its users and the context that they're in, the environment that they're in, and in a way to develop insights or information that is valuable to the OEM or others in the ecosystem. So this could probe data of different types, it could be in this particular situation, in this particular vehicle, with this particular driver, they're engaging in this type of behavior. All those types of things are very valuable. And then obviously a much broader concept is: how do I use this connectivity to change the customer experience of purchasing, owning, operating, and selling vehicles? So the whole life cycle can be dramatically changed by connectivity.

Steve Schwinke:

I want to move this conversation to what's next in terms of, today we are troubleshooting problems that exist, but now we're also talking about predicting failure. And so predicting a problem and addressing it before it occurs, especially with the trucking industry, where uptime and keeping these assets on the road is the most important thing. How do you see that evolving here in the future?

John Correia:

So I think the vision we created early on, and when we created it, a lot of people, their eyes got big, or it blew their minds. Today, it's not so dramatic, but we basically said we're entering a future where the vehicle can be self-diagnosing, self-reporting, and ultimately self-healing. So I think we're in a place where the car can, with the help of some cloud-based agents, actually go through all these steps, figuring out that it's got a problem, reporting that problem to the cloud, asking for some help, and if we don't already have a software fix for that on the shelf that we can deploy, then let's go develop one and get it rolled out.

Steve Schwinke:

We've seen the advancements of the wireless network, we've seen the transition to the cloud, and now we're seeing the transition of the vehicle to what most are calling the software-defined vehicle. How do you define the software-defined vehicle?

John Correia:

It's basically trying to take more and more functions and instead of making them hardware dependent or hardware reliant, you're trying to put enough hardware in the vehicle, platformize that hardware as much as you can, abstract it as much as you can, expose all of its functionality and capabilities to a software layer above it or a couple of software layers above it, and then basically try to future-proof the functionality of that device by allowing software to unlock more and more value over time. So that's what a software-defined vehicle is to me. And I think some of the concerns I have, about where I see OEMs off racing to, they tend to get attracted by these shiny toys as opposed to going back to the fundamentals and understanding what are the customer problems they're trying to solve. For instance, there are a lot of AI and machine learning tools, and there's a lot of hype around that right now, especially with all this ChatGPT stuff that's recently come on board.

I think it's easy to think I could just throw a few data scientists and have them look at this haystack of diagnostic data and find the needles. Well, they might find a few needles, but they're not going to find all of them. And you need to make sure that analytics, and data science person is somebody that really understands the physics of the subsystem and has the domain knowledge of that particular commodity or that particular subsystem. When we started this, we started with those people, the subject matter experts that could look at a dataset and really say, "Oh, that's an interesting pattern. That's an interesting signature. That's an anomaly. We need to look at that more." A lot of times the data just exposes consumer behavior that's unique as opposed to device behavior that's unique.

Steve Schwinke:

Are there some other challenges that you see that OEMs might not anticipate?

John Correia:

A lot of OEMs are rushing to just push a bunch of data to the cloud. It's not only costly to send the data over the air, but it's costly to process it, store it, and then you've got privacy issues and other things that you've got to manage once you've accessed all that data. So just got to be mindful of how you use intelligence in the car to collect that data.

Steve Schwinke:

Okay. I'd be remiss if I didn't ask for at least one of my Correia-isms that you're known for. Can you tell me about the five Cs?

John Correia:

So early on in the days of me being responsible for connectivity at OnStar, I was trying to communicate to the wireless world, which was new to automotive, they were worried about their cell phones and stuff, and it's like, "Well, here's what's important to us automotive guys." And it was the five Cs of connectivity. The cost was number one because OEMs are always concerned about cost. So how much does it cost me to move the data? Also, how much does it cost me to buy the device?

What's the coverage? We were a safety and security system, so we needed to have as broad a coverage as possible. What's the capacity? So if I'm tailgating at the U of M Stadium, as we've been known to do, Steve, can I get my call out? Can I get my data out? Can I get my communication going? And then two that are somewhat unique to automotive is consistency. Can I deliver one modem to the world that works everywhere, and is it based on a standard or do I have to have a different modem for Europe and a different modem for the US? And then lastly, compatibility, which gets into backward compatibility more than anything, which is: this has been a long hard road for these OEMs to go through all these technology transitions, and basically many of their modems have turned into devices that are no longer operating because the technology and the infrastructure goes away.

Steve Schwinke:

Well, John, I think I could keep going on and on all day with you. This has been very enlightening. It's really good to get caught up and talk about what the industry was like during the early days, what we see happening as we transition to the software to find vehicles, and how OEMs can continue to enhance value through embedded connectivity. So thank you for sharing your thoughts. I'm really glad that you were able to join us on Point B today, and look forward to having you back here in the near future.

John Correia:

Thanks for having me, Steve. It was great to see you as well. And enjoy your spring.

Announcer:

Thank you for tuning into Point B. Join us next time for more Autotech innovations and trends. Point B is brought to you by Sibros.