December 13, 2022
Accelerating Innovation & Living on the Cutting Edge with Marianne JohnsonEpisode 191 of The Innovation Engine podcast.
This podcast is part of the Product Mindset Leadership Series.
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From the time a vehicle rolls off the manufacturing floor to its next life, Cox Automotive is working to improve every step of the process. Their $8 billion product portfolio is transforming the way the world shops for, purchases, and sells any type of vehicle, and they provide a variety of digital products and technology-enabled services that connect the automotive ecosystem at a global scale.
Marianne Johnson sits at the center of it all. She’s the Executive Vice President and Chief Product Officer at Cox Automotive, where she oversees a team of roughly 5,000 people across 700 Scrum teams. She’s responsible for a vast product portfolio that includes a number of products that are household names, including Autotrader and Kelley Blue Book.
Listen to the Episode
On this episode of The Innovation Engine podcast, Scott Varho and Bernard Doone talk with Marianne about building a culture where rapid innovation and living on the cutting-edge of technology are the norm.
Running an Agile culture at massive scale
When considering Agile for your organization, it’s important to remember that it’s not a technology methodology, it’s a business methodology. Agile is all about rapid iteration, prioritization, and iterating your way forward. Doing so effectively requires the cooperation of the entire organization, which is no small feat.
When Marianne first arrived at Cox Automotive, she saw that one methodology for a company that large was not going to work. Instead, she created patterns across teams that were built to purpose. Some areas needed to work faster with less oversight, but in other areas that are very dependent on cross-team collaboration, there needed to be an overlay guiding them together. This resulted in the creation of a proprietary discipline and methodology called FLOW, which is all about leaning out the process and optimizing the entire software development cycle.
Reusing existing capabilities to create composable solutions
One area Marianne and her teams are laser focused on is creating reusable business capabilities to create composable solutions. This focus helps greatly accelerate Cox Automotive’s development process and is one of the keys that will have enabled them to launch 37 new products by the end of this year.
It has also been instrumental in streamlining the way a large number of their acquisitions and product lines operate and are iterated upon.
“If I need to build something new, I’m looking at our capabilities,” Marianne says. “Maybe out of the 10 things I need, I have 8 already that can be consumed internally or externally because I’ve packaged those capabilities in a way to be consumed.”
Using data to prioritize product launches
When making the difficult decision of what to focus on first, it’s important to have an outside-in lens. That means taking a digital-first, client-obsessed approach to product development, and ensuring that the overall corporate strategy, business strategy, and product strategy align with that.
Data can be used to determine where the market needs positive disruption, where future growth will come from, and where current capabilities serve that purpose. That data needs to be driven by the customer’s voice, solving the pain points of today and creating opportunities they didn’t know existed. Using data from customer interactions allows organizations to innovate toward future opportunities.
Tune in to the full conversation to hear about how Cox utilizes its $8 billion dollar product portfolio, more details on the exact methodology of running AGILE across such a large organization, and utilizing AI for future growth opportunities.
[01:13] What Marianne’s role at Cox as Chief Product Officer entails
[09:20] What makes up Cox’s $8 billion dollar product portfolio
[13:20] Running an Agile culture across 700 Scrum teams
[18:47] Insights from running the five patterns of Agile
[24:00] How composability informs what products to launch
[28:03] Leveraging data to drive value
[32:31] How Cox Automotive uses AI for growth
Learn more at coxautoinc.com
Follow Marianne Johnson on LinkedIn
About The Innovation Engine
Since 2014, 3Pillar has published The Innovation Engine, a podcast that sees a wide range of innovation experts come on to discuss topics that include technology, leadership, and company culture. You can download and subscribe to The Innovation Engine on iTunes, Stitcher Radio, Spotify, and SoundCloud to listen online, via Android or iOS, or on any device supporting a mobile browser. You can download The Innovation Engine’s dedicated iOS app from the Apple Podcasts App store, and you can subscribe to receive new episodes in your inbox each time one is published.
Scott Varho: [00:00:03] This is the Innovation Engine podcast from 3Pillar Global, your home for conversations with industry leaders on all things digital transformation and innovation. Welcome back to the Innovation Engine. I’m Scott Varho, 3Pillar’s chief evangelist and your co-host for today’s episode. Alongside Bernie Doone, industry lead for information services here at 3Pillar. Hey, Bernie.
Bernie Doone: [0:00:29] How are you, Scott?
Scott Varho: [0:00:30] I’m good. I’m good. Thank you. And I’m particularly excited to be speaking today with Marianne Johnson about building a cultural rapid innovation and living on the cutting edge of technology are the norm. Marianne is executive vice president and chief product officer at Cox Automotive, where she oversees the team of roughly 5000 people across 700 teams. That’s impressive. She’s responsible for an $8 billion product portfolio that includes a number of products that are household names, including Autotrader and Kelley Blue Book, just to name a couple. Marianne, we’re really excited to have you on and to learn from some of your experiences. Thank you so much for joining us.
Marianne Johnson: [0:01:10] I’m happy to be here. I’m looking forward to it.
Scott Varho: [0:01:13] Excellent. Let’s dive in and always good to kind of start with, you know, your role as a chief product officer. Like what does that mean? That can mean so many things in different contexts. And even from the intro, just the spread and sprawl of your portfolio is such that I’m curious to know more about your role and what does it entail at Cox Automotive?
Marianne Johnson: [0:01:34] That’s a great question, Scott, because a lot of times titles mean different things at different companies. And for us at Cox Automotive, chief product officer really encompasses all of our product strategy, product management, our software engineering, our data science, and our advanced technology. And we run that all in one organization. And we all talk about that I’m sure throughout this time together about how that comes together and really unlocks potential, especially at scale. So if you’re thinking about large enterprise companies, and even small companies, really trying to drive nimbleness and really differentiation in whatever area they are in the market, having this integrated model to me is really some magic in getting things done and done in a way that matters.
Scott Varho: [0:02:24] You know, and just to make sure that I understand that right, one thing that I’m really passionate about is that there’s no such thing as success in product and failure in engineering or vice versa. We are judged by what we ship. And so I’ve always found those divisions to be very unhealthy. If you want to create a great product, you’re going to need a cross-functional team. So do I understand, then, that that you have all of those functions responsible for?
Marianne Johnson: [0:02:49] Yeah. And let me give you just a little snapshot of how we have organized ourselves as well. I think it’s somewhat unique. I think I see more companies moving towards this model, especially companies that have scale. But what we have done really over the past four years, little over four years, I was given the responsibility for all of those functions, was given the opportunity to decide how we wanted to run, what did our how look like.
And when you have that opportunity, you know, you can go more traditional where you have all your functions within those disciplines separate. We stepped back and said, you know, what are the classic traps that you fall into from a product standpoint and engineering standpoint or data, things that needed to have enterprise capability and enterprise value. How do we get out of our own way as a large company?
And so we stepped back and said, let’s look at how we put parts and services together in portfolios that matter from an outside in view. So what product portfolios did we put together? Because if we put certain capabilities and products in the same team, could they go faster? Could they have more collaboration? Could they have more coordination? So we did that from an outside in view, not a P&L structure view. That’s really important.
A lot of times, you see companies that are just structured to line up with that leader of however their P&Ls were structured. And we wanted to unlock enterprise value so we didn’t let that be a guiding principle. While we have accountability into the P&Ls that we drive, we wanted to unlock value across our P&Ls. So that was the principle one that we’ve continued to evolve.
Number two, you know, in that structure, we have five product portfolios today with that guiding principle as to what goes in each portfolio. But that leader over that portfolio, they own product and engineering. It is a full stack, completely integrated agile portfolio team. Engineering cannot say product isn’t giving them the right what. Product cannot say engineering isn’t delivering because they own it. You build it, you run it, and you own it. And so there is coordination across those portfolios as well.
So we have an enterprise methodology of prioritization and how we do work when things cross portfolios. But also part of a magic sauce is we have four centers of excellence that are horizontals, that support those five product portfolios. And those COEs are, just to give you a snippet, we have a chief technology officer who runs our cloud business office, our engineering enablement team, engineering operations. We do site reliability engineering out of that. We have the data discipline engineering in that team as well. We have a whole ecosystem of how we level up in that discipline. And we have enterprise architecture there.
So, many of those teams are embedded in those portfolios. They’re part of those portfolios but they run horizontal so that we lift our capability and our maturity continually in that discipline. Same thing on product. We have a product COE where we’ll talk a little bit later in this conversation about the disciplines of product. But how we mature that product organization and how readiness and commercialization and go to market as an enterprise capability list all of those portfolios to execute and execute well.
We have an agile office. As you heard, we have a very large agile discipline. That is our primary methodology, but we have five patterns that we run. And those patterns are fit for purpose depending on what we’re doing. If it’s more of a lean startup model or if it’s something that has a lot more dependency and maturity and a run model, we fit the discipline for purpose.
And so we’ll come back to that as well because we do a lot of leaning. When you think about leaning, how do you just take waste out of the process from adiation all the way to launch.
Scott Varho: [0:06:55] Oh gosh, there’s so much here that resonates so strongly with me. And I’ve seen so many companies get that wrong and optimized for capability, but forget that we’re trying to leverage those capabilities to drive outcomes.
Marianne Johnson: [0:07:07] That right.
Scott Varho: [0:07:09] It feels like you’ve got you the right emphasis. You still want to support the other, but it’s – you always want to put –
Marianne Johnson: [0:07:14] Yes. Now, our last COE is data because data, we kind of view, not to use an automotive analogy, but we often do, it’s kind of our oil. Data is the oil that makes everything work together, and really drives differentiations. We have a whole discipline around data ingest, data governance, data acquisition, data cleansing. And then we have data product and we have data science. And so they support the enterprise and they feed in capabilities into the portfolios.
So it is really an interesting ecosystem of how we’re doing work. And we’re continuing every year to look at what are the next level of capabilities and disciplines that we need to challenge ourselves to be nimbler, be smarter, be faster, and leverage advanced disciplines and advanced technologies really to deliver more value to the business.
Scott Varho: [0:08:10] You mentioned agile and the 700 scrum teams. And I’m just really interested in how that agile culture came about. That is a tremendous scale for agile to be effective, 75 plus data scientists, 5000 team members, all working together on different products, different configurations. So I’m just curious from your standpoint, what does that look like and what are some of the factors in success and or where you’re still struggling?
Marianne Johnson: [0:08:41] You know, I will say I started in Doone of 18 and I was very blessed that just before I started that the leadership team at the time had made the decision to invest in an agile methodology. And I think some people get this so wrong. They think it’s a technology methodology. It is not. It is a business methodology. And it is, you know, rapid iteration and prioritization and iterating your way forward in a rapid way. And you have to have complete buy in of the organization to do it right.
So that had happened, but I did find when I got here I had to resell it because it was heavy at the time that I got here. It was one methodology for a very large company. And I quickly recognized that was not going to work. So we really dove into what were the patterns that we wanted to be able to run that were again fit for purpose.
So if you really had to go fast and you were doing something more in a startup, you know, PE type methodology of something de novo brand new, you didn’t need the same heavy overlay that some of the agile can provide. But then in some areas where you’re very dependent on different teams working together, you have to have the orchestration.
So we came up with the discipline and a pattern around that and we have a very structured process from delivery streams to release train engineers to scrum masters. And we adopted a methodology that we often call flow and it’s all about leaning out the process from how effective are we at discovery? How effective are we at our stories? And what we’re working on and why? What’s the business value? So every part of the software development life cycle and agile, how do we optimize that? And we have instrumented that in a meaningful way.
And so it anchored on human centered design with our innovation framework that we can talk about a little bit. It’s anchored on our how of our digital cloud ecosystem that we’ve created. So how your environments get spun up, how your capabilities can come together. And then we have an engineering ecosystem that we’ve created to at scale. We went – when I got here, bit 67 different acquisitions and we had 23 different major product lines at the time, and everybody was doing their own thing, everybody. It looked different. Everybody had their own tools, had their own methodologies, had their own, I would say, well, I had one of everything. Maybe I’ll just go that way, one of everything.
So we started to step back and said what is our ecosystem and how intentional we need to be, and how do we start standardizing on best in class, and still providing some flexibility around the work is different. And so how did we create the ecosystem? And we establish these types of standards and drove that discipline.
And it was not – I wouldn’t say that it was just all joy and balloons and smiles were going through that. It’s been a transformation. But as you’ve highlighted the successes and you created a community on it, everybody leaned in. And I would – if you talk to some of my direct reports now, if they had to look back over the past four years, they’re shocked at what we’ve been able to accomplish and got done. You know, two years ago, three years ago, they might have said that’s never going to happen, and it’s happened.
So that has been the coolest aspect of it. So really, thinking about the full life cycle, breaking down the disciplines that are within that, and then how do you optimize those? And then how do you measure? One of the things that we do is we want to measure what matters and then make it easy to measure. So that we’re trying to instrument through tooling as much as possible so that it is not a burden and a heavy orchestration of being able to get to where your opportunities are.
So we’ve been after that in a meaningful way. And we’ve gotten some really really good results. And I don’t know that we’ll ever be done but we are continuing to lean into it.
Scott Varho: [0:12:50] Yeah. No, it’s a really hard process. And I love your description of it, that sense of starting intentionally, but also building momentum. Because ultimately, I think people lose sight of, you know, any kind of transformation, whether it’s agile or digital or whatever label you want to put to it, ultimately, the success and value are hinges on momentum and humans buying into it and seeing value in what they do. And even while you’re, you know, where you’re trying to figure out what are the constraints versus what ar ethe opportunities. That can be a key piece of actually living agile and not just saying you’re agile or following a template.
So yeah, that’s a very insightful description of what that looks like, especially inside a large organization, which can be tough.
Bernie Doone: [0:13:37] Hey, Marianne. Are there any lessons learned or insights to share around landing on the five patterns of agile and the used cases?
Marianne Johnson: [0:13:47] Yeah. I would say that we really stepped back and said what are the outcomes we were trying to achieve? So yeah, one pattern might be all about being nimble and being isolated, so you can go as fast as you can. Another one might be how have you simplified the work. If you’ve simplified the work that you’re doing in a given portfolio, that allows you to not have as much orchestration. If you are building something that is very compiled, if you will, or composed across multiple capabilities, you might need more orchestrations.
So we then said what are our patterns based on what is in front of us and which ones make the most sense? And then we’ve continued to modify those. And you’ll have teams that start in a pattern and will evolve to another pattern. So they might start up in a very independent lean startup type pattern, but as they get more mature and as they have more capabilities they’re bringing in, they might move to a different pattern.
So I think it depends on the maturity of the product, how nascent what you’re doing is, and then how dependent you are on other capabilities. So teams will come in and out of patterns over time depending on the work that they have in front of them and you have to be nimble enough in your resource model to be able to adjust for that.
I’ll also say that, you know, the 5000, a little over 5000 really, but the 2000 roughly of that are offshore engineers that are with three strategic partners that we have. And we don’t run them in a way that they are standalone and we give them work and they do that work. They are completely integrated in our ecosystem and are those full teams in how they run. So we don’t treat it as here’s the employees and here’s how they run. Here’s our contract partners and here’s how they run is completely integrated.
So that also requires us to have, you know, the right level of communication and orchestration across time zones as well. And then making sure that your strategic partners are bought in on your methodologies and your approach.
Scott Varho: [0:15:58] Yeah. Well, and it’s really shocking to me or striking I should say like how richly you – I mean it’s not often that I talk to a chief product officer who understands the ins and outs of, you know, like composability. It’s not a word that I typically will hear from a chief product officer. So, you know, I’m very struck by how holistic your own understanding is of how the building gets, how the sausage gets made if you will, which is necessary for you to be able to even lay that out the way you just did. And I hope for other chief product officers, that that’s a goal to try to have that rich understanding because you’re always optimizing for some sort of trade off.
Marianne Johnson: [0:16:37] Yes. Scott and Bernie, I’ll tell you what we’re focused on right now that is probably one of the most exciting things. We wouldn’t be at the place that we are right now if we hadn’t have done all this other work ahead of this. Like I said, we were 67 different acquisitions of VIN of a car. There’s a capability called a VIN decoder. You know, I have like – I don’t even know how many have. I have probably 15 VIN decoders.
And so you have all these different capabilities that were built siloed in these different companies or different product stacks and they were running their own way. So now, when you start running as an enterprise, which one requires investment, which one should be the invested capability going forward? So we have taken the time over the past 18 months to catalog our capabilities from what we call a Level 1 capability, all the way down to a Level 4.
And when you decompose your assets that way, you then can have an investment strategy that aligns up to your growth strategy. And we’ve done that work. And because we’ve also made our journey to the cloud, we took everything that was fit for purpose to the cloud. I think we have one remaining workload that is not in the cloud that will go in ‘23, but pretty much everything that’s growth driven is in the cloud now.
So with the cloud work, the discipline work that we’ve talked about, the capability mapping, we are now – and you’ll hear, this is the mantra and everybody’s on it now, it’s packaged business capabilities to create composable solutions.
So if I need to build something new, I’m looking at our capabilities. Maybe out of the 10 things I need, I have 8 already that can be consumed internally or externally because I’ve packaged those capabilities in a way to be consumed. Now, I can compose a solution. And so we’re having to make sure that we have common design systems of look and feel, ease of use, workflows, things of that nature. But all of our shared capabilities that we did before, that put us in a position now that we can do this.
And so while we’ve gotten a lot done, I feel like we are just tipped over into like warp speed and we’re super excited about it.
Scott Varho: [0:18:44] That is phenomenal.
Bernie Doone: [0:18:46] Brilliant.
Scott Varho: [0:18:49] And it’s a true testament too. I mean I was going to ask you about how have you launched 37 new products by the end of this year, but I think that might be the answer. Is there more you would you would say about that because this idea of composability is, you know, it’s music to my ears. Microservices, you know, and having a services or an architecture, but more importantly a services-oriented mindset. And it should go beyond just the APIs but also the cloud services and infrastructures and the appropriate or inappropriate use of those, as the case may be.
But I mean, so all of these make sense to me. But I mean, yeah, is there more you would say about how, what went into figuring out what products to launch? And do you have any examples of that composability helping with launching all those products?
Marianne Johnson: [0:19:35] Yeah, I do. We, you know, one of the things we have to anchor in on this is really having an outside end lens on what you should be working on and putting – we talk about being digitally obsessed and client obsessed, digital first in everything that we’re doing.
So as we do our business, our overall corporate strategy, and then our business strategy, we are lining our product strategy up to that. So that we know our strategic focus areas of where the market needs positive disruption, where our growth will come from in the future, and then taking that blueprint if you will, and saying, where did the capabilities that we currently have served that purpose?
And so not every capability that we have is going to drive that future state, but so as we invest in key capabilities and create that composable solution is not everything I have it’s going to be focused. And so that has to be driven from our strategy that has that outside voice, customer voice, market voice. Some of it is solving customer pain points of today. Some of it is creating opportunities that our customers didn’t even know that they could realize. And also looking at how we drive and shape the future.
So all of those go into input points on how those capabilities will come together in the future. And we’ve been on a journey just to start showing up more solution-focused while we have best in class, deep, rich product capabilities as you buy every one of our products, but how do they work together? How do they change the outcomes for our customers in a way that because of the combination of our products and the data that you get across, that somebody else can’t replicate.
And we do see because of the breadth and depth of the services that we have, we see the data, we see the consumer, we see the business partner, we see the outcomes of the transactions or the interactions. And through that data, that allows us to then go back and innovate because then we’ll put our data against that problem or against that opportunity.
And so what are we seeing and how do we create a solution, solve a problem? Or how do we give the art of possible that somebody never thought that they could go do. So it’s really anchored. It’s connected. And I wouldn’t say we’re perfect at it, but we’re after it.
Scott Varho: [0:22:02] Well, I mean, what you’re describing is there’s so much more complexity and you talk about it so elegantly, you know. And I often define elegance as making the complex simple. But there’s no shortage of complexity underneath what you’re talking about for sure.
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Bernie Doone: [0:22:53] We know that data plays a big role in your agile culture, driving insights for your customers but also internal decision making. Would love to hear more about how you’re leveraging data and products like drive Q to help customers make better decisions. And then in prior conversations, we’ve had some interesting conversations around measurement, making it easy and driving right behaviors with measuring data. So we love the double clicking with both of those.
Marianne Johnson: [0:23:19] Yeah, two sides of the data. One is how do you leverage data to commercialize and drive value in any market that you’re serving. And I think data has a play, in that data also has a play inefficiency, how do you find efficiencies weather in your business or within how you run your organization, whatever function it may be.
On the commercialization side of it, drive Q is a data platform, something that we have matured over the past couple of years, as we had a lot of data. But again, much like I described before, many of that pieces of data were in silos. And so as we put together our cloud strategy and our data ecosystem or ethos of our data, we put a platform capability around it called drive Q.
That is all about creating, capturing and nurturing the data that we see. Noticing and looking and being very intentional about where that data plays across both at an individual data element level and in an aggregate level. So, you know, the vehicle itself and our world is a persona, because it’s understanding the life of the vehicle and what happens to that vehicle throughout the entire life cycle of that vehicle.
And that’s important to understand that. people think of personas as your customers, but personas can also be entities and assets that you need to be able to provide value back into, but we also do that from a consumer standpoint. You know, we see the consumer in their shopping through KBB and Auto Trader. We have over 1000 websites. We’re close to 70 percent of the market in the digital dealer website. So if you’re on a dealers website, you’re probably got a Cox hosted digital property.
And so we are able – and then we see whether you buy the vehicle, we see whether you bring it into service. So we understand the lifecycle of the vehicle, the life cycle of the consumer journey. We want to anticipate those needs of the consumer so that we find ways to delight them, to create personalization. What are they really looking for? What do they need? What can they afford? And how do you help them on that journey?
So those are just some examples of how we take the data and then we apply intelligence on top of that. I like to think about the car or I shouldn’t say car, I should say vehicle. But as the vehicle rolls off the manufacturing floor from that time to the next life, at any point in time that you want to know the value, the price, the condition, the best placement, the best next step for it. Should it go into an auction? Should it go on a dealer’s lot? Should it be sold person to person? Should it go into a fleet? What’s the best recommendation for that vehicle at that point in time?
And then what’s the service it may need? Does it need to be reconditioned? And do you need it moved? We can do all of that. So I think of it as a superhighway. That vehicle gets on and off that highway. And every time it does, there’s a point of interaction. We can tell you price, placement, value, condition, and then provide the services.
And so that is what we’re enabling across our data, whether it’s a consumer interaction or whether it’s a B to B interaction, or whether it’s a fleet vehicle that’s trying to move goods from point A to point B.
Scott Varho: [0:26:41] Wow, that’s fantastic. And, you know, I would be remiss of me not to share this but one of our top UX people was involved in an engagement with you all not too long ago at Manheim at one of the auctions. And I literally was in Romania last week. And I don’t know if you know George A, if you met him, but he was telling me the story. He’s like it was amazing. It was so – there’s so much stuff going on and got to ask all these questions. And he was just really thrilled to tell me that story. Yeah. So it would be wrong of me not to share.
Marianne Johnson: [0:27:16] I love that.
Scott Varho: [0:27:17] He literally was just recounting that story to me last week.
Bernie Doone: [0:27:19] Fun story. Let’s pivot a little bit. I want to talk about AI. So AI is often a buzzword for cost saving algorithms. And many, if not most, companies struggle to find a use case for AI.
You were using AI to drive product innovation and what I would call an evolution of the customer experience. So would love to hear some few examples of how you making that work possible. Any lessons learned and struggles on the way, but really, like how are you leveraging AI successfully with those 75 plus data scientists and you’re integrated teams?
Marianne Johnson: [0:27:53] Yeah. And I probably should’ve given you an updated number on that. About a year and a half ago, we bought a company that’s also just focused on nothing but computer vision and AI, so that number ended up doubling. And I’ll talk about a couple of the examples there.
But what we just finished talking about around data, you don’t have the ability to leverage these advanced capabilities of artificial intelligence with machine learning patterns or computer vision or natural language processing without data. Data is the secret sauce to that. And then you can apply these capabilities, techniques to the data.
So if you don’t have the data, you’re kind of out of luck. So first of all is the data. So a good, great example of that is because in the Manheim world that we just talked about, Scott was we move and see the majority of vehicles across the country in the U.S. for an example.
And so as we’re touching those vehicles, how do you image those vehicles and image those vehicles in a way that data can be used internally and externally? So we today have capabilities through artificial intelligence and computer vision where you’re either driving through what we call a gantry with cameras undercarriage and around the vehicle or in through, if it’s out in the wild and not at a physical auction, through a mobile device that you’re walking around the vehicle. You know, we call it a double bubble. You walk around twice and all of a sudden you have a 3D image of the vehicle. It’s a digital twin.
And because you see – because the volume of vehicles that we see, we then can allow our AI and computer vision models to pattern, is that a shadow or is that actually a dent? Is that scratch? How deep is that scratch? Is there road rash around the tires? If you have the ability to then highlight the damage and we call it intelligent damage detection.
And so within, you know, seconds, you’re able to then say and highlight visually, Scott, your car is in this condition. And how does that translate to its value? And then if a buyer or a seller is looking at vehicle, they have these advanced images to look at, but they also have that translated into a value in a store of the condition of that vehicle.
And then you can translate that all the way to a consumer. How does the consumer do an offlease self-inspect to the quality of a vehicle? Any point in time you need to do chain of custody of a vehicle and knowing the condition, we’ve now enabled through intelligent damage section because we have the vehicles to do the data on and then we applied computer vision with machine learning. You now have this advanced capability. That’s just one.
But we do it on other data like consumer data. So, you know, I know what Marianne is looking at. I know what she’s shopping. I know what kind of car she’s focused in on that particular time. And based on your pattern, Marianne’s pattern, we can predict the likelihood of Marianne purchasing and if she’s going to purchase in the next 60 days. So we look at patterns of behavior and trends and then do predictions.
We then do personalization based on what we think that you’re interested in. How do we help you find what you’re looking for in a way that saves you time? Makes it feel simple. We’re working to really kind of disrupt that. You know, the auto industry is an interesting place for digital. It’s really on the tipping point right now of going full digital and changing the way the consumer will shop and experiences.
So those advanced capabilities of artificial intelligence, when you think about the metaverse and virtual reality and how virtual reality will help consumers think through, we’re bringing those type experiences. We call it a vehicle experience page so that you got an experience that helps you move along and get what you want and make a decision.
So that happens in all of our interactions. We bring that AI into – you know, it happens in Autotrader. It’s happening in our CRM. It’s happening on a business to business standpoint of how to predict the best price for a vehicle, how long you should hold onto a vehicle if you’re selling it?
If you’re a dealer, where that vehicle should go? Should it be in Kansas City or should it be in Atlanta because that particular make, model, and color is more attractive in this market versus this market? So all of that data is going into predict and recommend actions and help guide an outcome we often play.
Scott Varho: [0:32:31] Yeah. No, this is – I mean it’s interesting. We just sold a vehicle. We had my wife’s old car which we were using for repair. It doesn’t matter, all the details about that story, but we were going to sell the car. And I had that moment of like is it worth me fixing the dents in the car and will that affect the sale price? And I didn’t know where to go and so the types of tools you’re describing solve a very real problem.
And now my wife is making noises about getting a new car for herself. And again, there’s plenty of scratches and things that – not happier there, but I have this unfaced once again with this question of what do I do about it and will it be worth – is it worth it?
Marianne Johnson: [0:33:14] Right?
Scott Varho: [0:33:14] Interesting. This is very – a lived solution to a problem.
Bernie Doone: [0:33:18] So I think that really summarizes as improving the buyer and seller experience, and we’re moving a lot of friction from the process with price intelligence and placement, right?
Marianne Johnson: [0:33:29] That’s spot on.
Scott Varho: [0:33:31] That’s great. Well, you know, this is awesome. And one of the things we like to torture – I mean offer our guests the opportunity to participate in, is a speed round of questions at the end. A little bit more fun oriented. So if you’ll indulge me, I’d love to kick that off for us here.
Marianne Johnson: [0:33:51] I would love to.
Scott Varho: [0:33:54] When you’re not thinking about cars or vehicles, as you corrected yourself earlier, you’re thinking about boats. Is that right?
Marianne Johnson: [0:34:02] That is true. That’s very true.
Scott Varho: [0:34:04] So what’s sitting in arena that you can’t wait to break out when spring comes around again?
Marianne Johnson: [0:34:10] So I’m not going to wait until spring. So I’d tell you that. So and I think there’s a song and probably we might be in a similar genre that says I was born under the sign of water. That’s me. I love the ocean. So we have a 40 foot sea ray. She’s 20 years old, but everything is pretty new on her. Her name is Bella Victoria. She survived Hurricane Ian because we have a home in Southwest Florida.
So on Thanksgiving, I hope to have that boat out and I do have my captain’s license. So I’m still learning, but that’s what I’m going to be doing.
Scott Varho: [0:34:43] All right. Fantastic.
Bernie Doone: [0:34:47] So you built an amazing team in Cox Automotive which means you’re really good at hiring. And I’ve heard there are five things or characteristics you look for in new hires? So can you share what those are?
Marianne Johnson: [0:34:59] Yeah. And I would say, Bernie, it’s new hires, but it’s also really in leaders that I’m also looking to promote. But I think you’re a leader whether or not you have a hierarchal position or not. So I think if you’re trying to influence the actions, the thinking, the behaviors of someone else, you are engaged in leadership.
So I look for a bias for action, that’s number one. Put yourself in motion. And even if the motion needs to be adjusted, be in motions. Bias for action. Number two, I’m looking for someone who can lead. And again it doesn’t have to be hierarchical where you have people reporting to you, to be able to set a direction and drive a path forward and lead.
But I also believe, number three, you have to be able to follow. I don’t care who you are. If you’re the CEO or a chairman of the board, you have shareholders, if you’re the CEO, you have a board, whoever position you’re in, you still have to be able to take direction and follow well in any position.
The fourth one is someone who can communicate in a way that casts a vision that people can buy into that vision and internalize it and say, here’s how I connect to it. So it’s all about the communication and connectivity.
The last is giving credit where credit is due because no one does anything alone. They don’t. And so you have to bring people with you. And it’s always a shared win. So everything that we’ve talked about today, you know, my goal is to empower people, hire people smarter than me, and get out of their way and remove barriers for them and then let them go.
So my team is amazing and they’ve done some amazing work. So you got to give credit where credit is due. So those are my five. There’s always a lot more to that, but when I anchor into it, if you nail those five.
Scott Varho: [0:36:44] That’s a pretty good five I got to say. I wish I worked with more leaders who had that criteria because –
Bernie Doone: [0:36:50] Wanted to shout out one of those things because we were just working with the client on establishing a product vision, but he said cast division, communicate it, and create connection to the vision. And that is like often the missing piece. So I love to hear that.
Marianne Johnson: [0:37:03] Yes.
Scott Varho: [0:37:04] Yep, that’s awesome. What’s the most impactful business or technology book you’ve read?
Marianne Johnson: [0:37:10] So I read a lot. So when I saw that question, I’m like okay, how do I narrow this down? I’m going to go back to two books that I always, always go back to. And I probably read them, I don’t know, maybe 15, 20 years ago so, but they are tried and true. So the first one is 21 Irrefutable Laws of Leadership by John Maxwell.
If you – and he’s updated that book, but those laws of understanding, again it’s not about hierarchal leadership, but if you understand those laws, you will be successful in life and in business. So that is an anchor.
Profit from the Core and Beyond the Core by Zook, I always go back to those because when you think about a business strategy of growth strategy, what’s the formula? And that formula that was laid out in those books, here I am 10 years, you know, out from reading that, 15 years out from reading that and I’m like it’s tried and true. So I would always anchor on those two if I refer somebody to do that.
Scott Varho: [0:38:07] Wow, those are uncommon recommendations. I like that. That’s great.
Bernie Doone: [0:38:11] It sounds like you should be writing a book sometime soon too.
Marianne Johnson: [0:38:14] I need to. I got to figure that one out.
Scott Varho: [0:38:16] If you need some help, I think we’d have a lot of fun.
Bernie Doone: [0:38:18] Yeah, I’ll sign up for it. Maybe the hardest question here, so it’s not revealing my age, but maybe I am. I’ve seen Back to the Future plenty of times. Where are we on the flying cars?
Marianne Johnson: [0:38:33] Okay. So they exist. We all know that they exist. They don’t exist in any kind of scale or real use. However, I would anchor a little bit more on autonomy. So you think about autonomous cars, so flying cars will happen. When? I think it’s out. I think it’s a ways out. I even thought autonomous, fully autonomous cars would be sooner than they are but I think we’re still probably a decade out.
But what you’re going to see, though, is more and more things of AI that you didn’t even, talking about AI, you didn’t even know what was happening. Your driver assistance, your sensors on your vehicle telling you how far vehicle is in front of you. The vehicle doing some functions for you. All of that is that advanced technology and are going to have levels of autonomy.
You’re going to see a level two and a level three happen and some focus on that in the next two, three, five years. And that’s that technology software defined vehicle. The vehicle is no longer just a transportation mode. It’s a software defined vehicle. It’s a technical platform. Entertainment, commerce, and transportation.
So I would – while we – I think flying is going to be cool and I certainly would like it in Atlanta, given some of my commutes, a helicopter flying car, I bought in. But I think autonomous is what we should be looking at and looking at the incrementality of how that’s going to evolve for us over the next five years.
Bernie Doone: [0:40:04] Very insightful, software defined vehicle. Love that.
Scott Varho: [0:40:07] Yeah. It’s a great concept. And it makes me also wonder about, you know, where are we with respect to cars talking to each other? You know, we –
Marianne Johnson: [0:40:14] Well, and they do. Machine to machine learning is a different amount of vehicle talking to and that your sensors are already doing that. It tells you if there’s a vehicle beside it. Those sensors are connecting often as well. So the next five, ten years on connected commerce, connected cities, connected home to your vehicle, connect, all of those different types of machines that can connect, the art of the possible is just out there. I think we should start with crazy and work backwards and see what happens.
Scott Varho: [0:40:43] That’s a line. That’s actually a great snap, start with crazy and work backwards. Always, always a good starting point for product vision. Well, Marianne, this has been an absolute joy and pleasure. I wish there were more chief product officers with your depth of understanding of how the sausage gets made. It definitely comes through in our chat here. So thank you so much for sharing your perspective.
Marianne Johnson: [0:41:06] I appreciate that. Thank you so much.
Bernie Doone: [0:41:08] Thanks, Marianne.
Scott Varho: [0:41:10] Thank you. This has been an episode of the Innovation Engine, a podcast from 3Pillar Global. 3Pillar is a digital product development and innovation partner that helps companies compete and win in the digital economy. To learn more about 3Pillar Global and how we can help you, visit our website at 3Pillarglobal.com.
Lastly, remember to give us a rating and leave a review on your podcast player of choice. If you have any feedback or guest suggestions, send them over to email@example.com. Thanks for listening and see you next time.