1 00:00:01,480 --> 00:00:04,200 Speaker 1: We are looking at five G because we do see 2 00:00:04,200 --> 00:00:10,639 Speaker 1: opportunities for improved safety, reducing traffic congestion, and delivering rich 3 00:00:10,760 --> 00:00:13,080 Speaker 1: media experiences in the vehicle, not just for the driver 4 00:00:13,200 --> 00:00:16,800 Speaker 1: but for the passengers. So those experiences should just flow 5 00:00:16,920 --> 00:00:19,240 Speaker 1: naturally and should be enabled, and five G is going 6 00:00:19,280 --> 00:00:21,040 Speaker 1: to be a great opportunity to do that in a 7 00:00:21,120 --> 00:00:25,960 Speaker 1: much more meaningqual way. Welcome to the Restless Ones, where 8 00:00:26,000 --> 00:00:28,720 Speaker 1: we speak with the leaders who push the envelope when 9 00:00:28,760 --> 00:00:32,880 Speaker 1: it comes to technological innovations and solutions, leaders who don't 10 00:00:33,040 --> 00:00:38,080 Speaker 1: follow standards they set them. I'm your host, Jonathan Strickland. 11 00:00:38,640 --> 00:00:41,559 Speaker 1: Our guest today is Zach Hicks of Toyota, North America. 12 00:00:41,920 --> 00:00:45,560 Speaker 1: He has worked in several capacities at Toyota, eventually occupying 13 00:00:45,600 --> 00:00:49,320 Speaker 1: the role of ce IO. As ce IO, he received 14 00:00:49,479 --> 00:00:53,880 Speaker 1: numerous awards and accolades, but he didn't stop there. Zack 15 00:00:53,920 --> 00:00:58,080 Speaker 1: found himself tackling challenges and taking opportunities that don't fall 16 00:00:58,160 --> 00:01:06,080 Speaker 1: neatly into the c I O bucket. Zach, thank you 17 00:01:06,319 --> 00:01:09,520 Speaker 1: so much for joining us on the Restless Ones. It's 18 00:01:09,520 --> 00:01:11,959 Speaker 1: a real pleasure to be able to sit down and 19 00:01:12,200 --> 00:01:15,319 Speaker 1: have a conversation with you. Thanks Jonathan, I appreciate the opportunity. 20 00:01:15,840 --> 00:01:18,800 Speaker 1: Before we jump into your background, one thing I would 21 00:01:18,880 --> 00:01:22,720 Speaker 1: love to do is just hear from you what you're 22 00:01:22,959 --> 00:01:27,440 Speaker 1: full official title is, because I think that just me 23 00:01:27,600 --> 00:01:31,919 Speaker 1: saying it might take up an entire episode. It sounds 24 00:01:31,920 --> 00:01:34,720 Speaker 1: like a lot. But they're all very closely related, you know. 25 00:01:34,760 --> 00:01:37,679 Speaker 1: So in in North America, I'm the Chief Digital Officer. 26 00:01:37,800 --> 00:01:42,560 Speaker 1: I'm responsible for digital transformation and mobility. In those functions, 27 00:01:42,600 --> 00:01:45,760 Speaker 1: I have traditional I T Corporate I T for sales 28 00:01:45,760 --> 00:01:48,480 Speaker 1: and manufacturing and all of the functions within Toyota and 29 00:01:48,520 --> 00:01:52,840 Speaker 1: North America. I'm also responsible for our Connected Technologies, which 30 00:01:52,920 --> 00:01:56,240 Speaker 1: is our in vehicle, the hardware and software and the 31 00:01:56,320 --> 00:01:59,560 Speaker 1: multimedia units in the vehicle. UM. I also have a 32 00:01:59,600 --> 00:02:01,880 Speaker 1: mobility the group, and that's kind of how we look 33 00:02:01,920 --> 00:02:05,320 Speaker 1: at mobility in the future, rideshare, car share and new 34 00:02:05,360 --> 00:02:07,840 Speaker 1: ways of operating. And then almost five years ago, we 35 00:02:07,920 --> 00:02:11,360 Speaker 1: launched a big data a I M L company called 36 00:02:11,360 --> 00:02:14,920 Speaker 1: toy To Connected and for that I'm the CEO. So 37 00:02:15,000 --> 00:02:17,760 Speaker 1: I spend a lot of time bouncing back and forth 38 00:02:17,840 --> 00:02:21,239 Speaker 1: between the two roles, but they're very interrelated, so it's 39 00:02:21,240 --> 00:02:24,239 Speaker 1: not like to managing two completely separate jobs. There's a 40 00:02:24,240 --> 00:02:26,680 Speaker 1: lot of overlap there, and I do have a role 41 00:02:26,760 --> 00:02:29,160 Speaker 1: within our parent company in Japan. As a Japanese title 42 00:02:29,200 --> 00:02:33,680 Speaker 1: of combo shoku just means management executive management over mobility. 43 00:02:33,919 --> 00:02:38,560 Speaker 1: I love your humility and modesty because from my perspective, 44 00:02:38,600 --> 00:02:41,840 Speaker 1: I look at it and I think about other challenges 45 00:02:41,840 --> 00:02:44,440 Speaker 1: that I'm sure we'll we'll dive into in this episode, 46 00:02:44,480 --> 00:02:49,040 Speaker 1: things that aren't barriers necessarily, but just considerations. The fact 47 00:02:49,080 --> 00:02:54,600 Speaker 1: that you have a large data company that operates perhaps 48 00:02:54,639 --> 00:02:57,000 Speaker 1: more like what we would think of as a Silicon 49 00:02:57,120 --> 00:03:00,760 Speaker 1: Valley startup in some ways, and also a role with 50 00:03:00,919 --> 00:03:05,400 Speaker 1: a company that has a more traditional approach to corporate culture, 51 00:03:05,919 --> 00:03:12,240 Speaker 1: and those sort of of potential disagreements of culture, to 52 00:03:12,320 --> 00:03:15,080 Speaker 1: me are really fascinating and how you navigate it. I 53 00:03:15,120 --> 00:03:18,239 Speaker 1: think you're You're right. I think anybody working in technology 54 00:03:18,320 --> 00:03:21,320 Speaker 1: has the natural kind of challenge of technology is changing 55 00:03:21,320 --> 00:03:24,040 Speaker 1: so rapidly. Business has a desire to change, but they 56 00:03:24,040 --> 00:03:27,120 Speaker 1: don't always move at the same pace. And working for 57 00:03:27,160 --> 00:03:32,280 Speaker 1: a company that is rooted in in consensus driven management, 58 00:03:32,520 --> 00:03:34,440 Speaker 1: but if we go at the pace of of getting 59 00:03:34,480 --> 00:03:37,560 Speaker 1: adverbordy to agree, there's natural tension in the system. And 60 00:03:37,680 --> 00:03:40,040 Speaker 1: that was really exactly right. Why we created a toy 61 00:03:40,080 --> 00:03:43,120 Speaker 1: To Connected as a separate company so we could go fast, 62 00:03:43,200 --> 00:03:45,840 Speaker 1: so we could be a digitally native company and not 63 00:03:46,000 --> 00:03:49,440 Speaker 1: have the approvals and the typical management structure that you 64 00:03:49,440 --> 00:03:53,080 Speaker 1: would in a multinational company. Well, let's learn a bit 65 00:03:53,120 --> 00:03:57,000 Speaker 1: more about you, Zach. I'm curious because I know that 66 00:03:57,080 --> 00:04:01,880 Speaker 1: your journey towards the digital and information side of things 67 00:04:02,000 --> 00:04:05,480 Speaker 1: wasn't necessarily a straight path. How did you first get 68 00:04:05,520 --> 00:04:10,080 Speaker 1: interested in technology? I was working at the unitineral lines 69 00:04:10,240 --> 00:04:13,600 Speaker 1: and I started off in reservations and uh, this was 70 00:04:14,000 --> 00:04:15,520 Speaker 1: a long time ago, but it was the first time 71 00:04:15,560 --> 00:04:17,640 Speaker 1: I had access to a computer, and it was to 72 00:04:17,720 --> 00:04:21,040 Speaker 1: me was fascinating that I could look up flights from 73 00:04:21,040 --> 00:04:23,760 Speaker 1: anywhere and find out what the cost was um and 74 00:04:23,839 --> 00:04:26,680 Speaker 1: find different ways to find different pricing. Back in the day, 75 00:04:26,720 --> 00:04:28,920 Speaker 1: if you worked in the corporation, you wanted to travel somewhere, 76 00:04:28,920 --> 00:04:32,320 Speaker 1: you found you complete a paper form to say I 77 00:04:32,320 --> 00:04:34,720 Speaker 1: have to go to Chicago for this business trip. Your 78 00:04:34,720 --> 00:04:37,040 Speaker 1: boss would sign it, the travel department would put the 79 00:04:37,040 --> 00:04:39,240 Speaker 1: price on it, and then by the time you got 80 00:04:39,240 --> 00:04:41,120 Speaker 1: that approved, the price would change and you start that 81 00:04:41,120 --> 00:04:43,560 Speaker 1: process all over again. It really wasn't the technology, but 82 00:04:43,600 --> 00:04:46,280 Speaker 1: it was what it enabled um And soon after that 83 00:04:46,440 --> 00:04:50,480 Speaker 1: was when the airlines were launching online booking tools, and 84 00:04:50,520 --> 00:04:54,320 Speaker 1: I was responsible for selling and supporting those with big 85 00:04:55,120 --> 00:04:58,000 Speaker 1: companies like Toyota, and and now was this putting the 86 00:04:58,040 --> 00:05:00,799 Speaker 1: information in the hands of everybody. It was a liberation 87 00:05:01,040 --> 00:05:04,960 Speaker 1: of travel information and that was exciting. And so that 88 00:05:05,040 --> 00:05:07,400 Speaker 1: was when I first came to Toyota, and how I 89 00:05:07,440 --> 00:05:10,719 Speaker 1: came to Toyota because I was supporting their travel department 90 00:05:10,720 --> 00:05:12,960 Speaker 1: and had a chance to interact with them, And you 91 00:05:13,040 --> 00:05:16,159 Speaker 1: said something there that really struck a chord with me. 92 00:05:16,279 --> 00:05:20,719 Speaker 1: The idea of loving what technology enables us to do 93 00:05:20,920 --> 00:05:24,679 Speaker 1: as opposed to loving a specific technology. If you love 94 00:05:25,320 --> 00:05:27,880 Speaker 1: the things that the technology allows us to do, then 95 00:05:27,960 --> 00:05:29,960 Speaker 1: that I think allows you to be a little more 96 00:05:30,080 --> 00:05:36,080 Speaker 1: flexible in adapting to new technologies that continue to fulfill 97 00:05:36,160 --> 00:05:38,760 Speaker 1: that mission. Is that does that sort of sound like 98 00:05:38,800 --> 00:05:41,680 Speaker 1: your philosophy? Yeah, that that's exactly right. In the early 99 00:05:41,760 --> 00:05:44,360 Speaker 1: days in I T, we used to have titles that 100 00:05:44,440 --> 00:05:49,080 Speaker 1: were products specific. So I'm a I'm an IBM CAPE engineer, 101 00:05:49,520 --> 00:05:51,440 Speaker 1: or today's world you may see it as an S 102 00:05:51,480 --> 00:05:55,359 Speaker 1: A P engineer or data specialist. But I really like 103 00:05:55,520 --> 00:05:59,160 Speaker 1: to become product agnostic in all of our roles because 104 00:05:59,240 --> 00:06:01,760 Speaker 1: technology change to so quickly and what maybe the right 105 00:06:01,800 --> 00:06:04,680 Speaker 1: tool today is probably not gonna be the right tool tomorrow. Well, 106 00:06:04,760 --> 00:06:08,720 Speaker 1: you joined Toyota in the mid ninety nineties. What was 107 00:06:08,760 --> 00:06:11,600 Speaker 1: your first role with the company. I started off in 108 00:06:11,800 --> 00:06:14,520 Speaker 1: the travel department and fast forward became the CEO of 109 00:06:14,520 --> 00:06:18,000 Speaker 1: a data company for Toyota. I was hired to automate 110 00:06:18,000 --> 00:06:21,279 Speaker 1: the travel processes um and to deal with exactly what 111 00:06:21,320 --> 00:06:24,680 Speaker 1: I just described earlier in that paper process and it 112 00:06:24,720 --> 00:06:26,680 Speaker 1: was a great experience. Also learned how to negotiate, you know, 113 00:06:26,680 --> 00:06:28,720 Speaker 1: I think in every role you'd get to learn so much. 114 00:06:28,960 --> 00:06:32,240 Speaker 1: And so I had learned how Toyota operates, I learned 115 00:06:32,520 --> 00:06:35,920 Speaker 1: the different organizational structure, and I had began to create 116 00:06:35,920 --> 00:06:39,000 Speaker 1: some relationships and at Twitter relationships I think at any 117 00:06:39,000 --> 00:06:42,160 Speaker 1: company really relationships or everything, it's how you navigate. And 118 00:06:42,160 --> 00:06:44,679 Speaker 1: and so that created an opportunity for me to step 119 00:06:44,680 --> 00:06:46,920 Speaker 1: in to a role because soon after that we had 120 00:06:47,000 --> 00:06:49,800 Speaker 1: launched our e business group and I was able to 121 00:06:49,839 --> 00:06:52,000 Speaker 1: be one of the founding members of our early days 122 00:06:52,000 --> 00:06:54,080 Speaker 1: of the dot com space, and that was when we thought, 123 00:06:54,160 --> 00:06:57,400 Speaker 1: you know, everybody that was in the new dot com space. 124 00:06:57,480 --> 00:07:01,279 Speaker 1: We were the digital natives and we were clicking order 125 00:07:01,320 --> 00:07:03,080 Speaker 1: and you guys are old school and brick and mortar, 126 00:07:03,120 --> 00:07:05,640 Speaker 1: and uh, you know, the world finally changed and caught 127 00:07:05,720 --> 00:07:07,440 Speaker 1: up to that, but we didn't go as fast as 128 00:07:07,480 --> 00:07:09,000 Speaker 1: we thought it was gonna happen at that time. But 129 00:07:09,040 --> 00:07:12,440 Speaker 1: it is fascinating because you you came on board at 130 00:07:12,720 --> 00:07:17,080 Speaker 1: really a transformational time, particularly for the automotive industry. A 131 00:07:17,160 --> 00:07:21,320 Speaker 1: lot of people my age think back to when cars 132 00:07:21,400 --> 00:07:26,960 Speaker 1: were almost a purely mechanical system with some other automated 133 00:07:27,080 --> 00:07:29,920 Speaker 1: features starting to work their way in, and today we 134 00:07:30,000 --> 00:07:33,960 Speaker 1: think of them as they are compute platforms themselves. We 135 00:07:34,080 --> 00:07:36,520 Speaker 1: have moved to a point where cars are some of 136 00:07:36,560 --> 00:07:40,800 Speaker 1: the most sophisticated technologies that we access on a daily basis. 137 00:07:41,200 --> 00:07:43,160 Speaker 1: I grew up watching Night Rider thinking that that was 138 00:07:43,200 --> 00:07:44,560 Speaker 1: gonna be the promise that I'd be able to hop 139 00:07:44,600 --> 00:07:46,360 Speaker 1: in my car, and it was gonna everything I wanted, 140 00:07:46,360 --> 00:07:48,560 Speaker 1: and it was gonna be this great experience. I was 141 00:07:48,720 --> 00:07:50,800 Speaker 1: in grade school and I remember an engineer from Ford 142 00:07:50,880 --> 00:07:52,760 Speaker 1: came in and talked to us and said, and I 143 00:07:52,840 --> 00:07:55,160 Speaker 1: was probably in in third or fourth grade, and they said, 144 00:07:55,160 --> 00:07:57,680 Speaker 1: by the time you are driving driving age, you're gonna 145 00:07:57,680 --> 00:08:00,200 Speaker 1: be in flying cars. And I believe that. And I 146 00:08:00,240 --> 00:08:01,960 Speaker 1: realized when I was about fourteen or fifteen, this is 147 00:08:02,000 --> 00:08:05,000 Speaker 1: not going to happen, but it's still the promise. Well, 148 00:08:05,040 --> 00:08:08,800 Speaker 1: I'm curious in your career at Toyota, are there any 149 00:08:09,160 --> 00:08:14,640 Speaker 1: projects that stand out defining moments that either shaped your 150 00:08:14,680 --> 00:08:19,720 Speaker 1: philosophy or reinforced something that you had made as part 151 00:08:19,760 --> 00:08:23,280 Speaker 1: of your philosophy. The first big learning that I had 152 00:08:23,480 --> 00:08:26,080 Speaker 1: was UM I had been in the E business group, 153 00:08:26,120 --> 00:08:28,640 Speaker 1: and then there was our big our biggest project within 154 00:08:28,640 --> 00:08:31,200 Speaker 1: Toyota on the technical side, which was automating all of 155 00:08:31,240 --> 00:08:35,840 Speaker 1: our dealer operations, so building a new retail system. The 156 00:08:35,880 --> 00:08:39,880 Speaker 1: project had was was failing. The c I O asked 157 00:08:39,880 --> 00:08:41,880 Speaker 1: me to take it over. I hadn't had a formal 158 00:08:42,000 --> 00:08:45,520 Speaker 1: role in corporate I T so it was it was. 159 00:08:45,760 --> 00:08:46,959 Speaker 1: It was a big leap. They put a lot of 160 00:08:46,960 --> 00:08:49,200 Speaker 1: trust in me. I probably wasn't qualified to take it 161 00:08:49,320 --> 00:08:54,240 Speaker 1: at that time, contractors working on a couple hundred Toyota employees. 162 00:08:54,280 --> 00:08:56,679 Speaker 1: It was. It was overwhelming and the only way I 163 00:08:56,679 --> 00:08:58,960 Speaker 1: could get my arms around it was I had just 164 00:08:59,000 --> 00:09:01,760 Speaker 1: finished my undergraduate degree cause I was going to school 165 00:09:01,760 --> 00:09:03,640 Speaker 1: at night, and so I approached it from a business 166 00:09:03,720 --> 00:09:06,040 Speaker 1: lens of trying to put controls around the costs, and 167 00:09:06,120 --> 00:09:08,520 Speaker 1: that helped to kind of bring it back. And I 168 00:09:08,520 --> 00:09:10,960 Speaker 1: also created a strong team that I could trust. So, 169 00:09:11,200 --> 00:09:12,480 Speaker 1: you know, a year and a half or almost two 170 00:09:12,520 --> 00:09:14,200 Speaker 1: years later, when I landed the project, I was very 171 00:09:14,200 --> 00:09:16,240 Speaker 1: proud of myself. The CIO calls me in her office 172 00:09:16,240 --> 00:09:18,319 Speaker 1: and I'm waiting for a pat on the back and 173 00:09:18,320 --> 00:09:19,880 Speaker 1: and she said, you know, you really turned it around. 174 00:09:19,880 --> 00:09:21,839 Speaker 1: You did a great job, but let's see if you 175 00:09:21,840 --> 00:09:23,720 Speaker 1: can do that again without leaving so many bodies on 176 00:09:23,720 --> 00:09:27,040 Speaker 1: the side of the road. And I was completely caught 177 00:09:27,040 --> 00:09:29,040 Speaker 1: off guard. I was very unaware. I was so focused 178 00:09:29,040 --> 00:09:31,439 Speaker 1: on getting the project back on track and doing whatever 179 00:09:31,480 --> 00:09:35,000 Speaker 1: it took to be successful that I probably wasn't the 180 00:09:35,080 --> 00:09:37,280 Speaker 1: nicest person to be around if you weren't performing. And 181 00:09:37,360 --> 00:09:39,960 Speaker 1: I had to learn how to be a better manager 182 00:09:40,160 --> 00:09:42,360 Speaker 1: and be a better person and get the same result. 183 00:09:42,880 --> 00:09:45,280 Speaker 1: And I'm grateful for that kind of slap that she 184 00:09:45,320 --> 00:09:48,520 Speaker 1: gave me, but I needed that awareness. I think the 185 00:09:48,559 --> 00:09:51,160 Speaker 1: other thing that was a pivotal turning point for me 186 00:09:51,360 --> 00:09:53,320 Speaker 1: was when I first became the c I O of 187 00:09:53,320 --> 00:09:55,840 Speaker 1: our sales and marketing company and about it. A few 188 00:09:55,840 --> 00:09:58,040 Speaker 1: months into the role was when Toy to face its 189 00:09:58,080 --> 00:10:02,200 Speaker 1: biggest crisis in our history. We went through our recall crisis, 190 00:10:02,200 --> 00:10:05,040 Speaker 1: where we had to recall almost every vehicle that that 191 00:10:05,160 --> 00:10:09,640 Speaker 1: we had produced, and all of our systems were becoming overloaded. 192 00:10:09,960 --> 00:10:12,040 Speaker 1: For example, our call center went from about six thousand 193 00:10:12,080 --> 00:10:13,680 Speaker 1: phone calls a day to over a hundred thousand phone 194 00:10:13,679 --> 00:10:15,280 Speaker 1: calls a day. We were getting d n S errors 195 00:10:15,280 --> 00:10:17,400 Speaker 1: because so many people were hitting our web pages, and 196 00:10:17,440 --> 00:10:20,880 Speaker 1: then all of our systems around driving our business began 197 00:10:20,920 --> 00:10:24,000 Speaker 1: to break. So we had a big mainframe system and 198 00:10:24,200 --> 00:10:27,439 Speaker 1: we had so many warranty claims that it was still processing. 199 00:10:27,440 --> 00:10:30,199 Speaker 1: It was taking thirty hours to process the warranty claims, 200 00:10:30,240 --> 00:10:32,040 Speaker 1: and so when the financial systems would come up in 201 00:10:32,080 --> 00:10:34,960 Speaker 1: the morning, all of our systems were becoming disconnected and 202 00:10:35,000 --> 00:10:37,760 Speaker 1: out of whack. And so during that time, not knowing 203 00:10:37,760 --> 00:10:39,440 Speaker 1: what to do and being a new c IL, we 204 00:10:39,520 --> 00:10:42,400 Speaker 1: had set up early morning meetings and meetings throughout the 205 00:10:42,480 --> 00:10:44,280 Speaker 1: day and before we don't go on home late at night. 206 00:10:44,559 --> 00:10:47,040 Speaker 1: And what we just said was whatever our employees need, 207 00:10:47,080 --> 00:10:49,680 Speaker 1: let's give them the money, the resources, but let's let's 208 00:10:49,720 --> 00:10:50,920 Speaker 1: do what they need to do to take care of 209 00:10:50,960 --> 00:10:53,680 Speaker 1: our customers. And something amazing came out of that was 210 00:10:54,040 --> 00:10:56,120 Speaker 1: the guy that was working in the main frame. He 211 00:10:56,120 --> 00:10:58,920 Speaker 1: took that batch job from over thirty hours to down 212 00:10:58,960 --> 00:11:01,760 Speaker 1: to three and a half hours. It was never three 213 00:11:01,760 --> 00:11:04,040 Speaker 1: and a half hours, even in good times. And I 214 00:11:04,160 --> 00:11:06,439 Speaker 1: just had that kind of clarity of moment to think, like, 215 00:11:06,520 --> 00:11:08,000 Speaker 1: why did it take for us to be in this 216 00:11:08,120 --> 00:11:10,600 Speaker 1: crisis for him to do what he knew to do. 217 00:11:10,679 --> 00:11:12,559 Speaker 1: He has been waiting for somebody to ask in this 218 00:11:13,120 --> 00:11:15,760 Speaker 1: instead of just doing it on his own. And so 219 00:11:16,120 --> 00:11:18,160 Speaker 1: I thought it was my job and our job as leaders, 220 00:11:18,200 --> 00:11:20,040 Speaker 1: as I thought, if I still have a job at 221 00:11:20,080 --> 00:11:22,200 Speaker 1: the end of this crisis, it's going to be my 222 00:11:22,280 --> 00:11:25,160 Speaker 1: life's work is to unleash the latent talent that exists 223 00:11:25,160 --> 00:11:28,040 Speaker 1: within our organization. And that changed the course of my 224 00:11:28,120 --> 00:11:31,880 Speaker 1: career because I then at the end of that period, 225 00:11:32,559 --> 00:11:35,360 Speaker 1: began doing things like hackathons and and at the time 226 00:11:35,360 --> 00:11:37,640 Speaker 1: it was like a science fair where we were really 227 00:11:37,679 --> 00:11:41,040 Speaker 1: pushing the innovation and we changed the trajectory of of 228 00:11:41,360 --> 00:11:44,679 Speaker 1: corporate I T because people within the I T department 229 00:11:44,720 --> 00:11:46,480 Speaker 1: really knew what to do. We shouldn't be looking to 230 00:11:46,600 --> 00:11:49,200 Speaker 1: contractors or other people to tell us the answer. It 231 00:11:49,280 --> 00:11:51,560 Speaker 1: was really a finding way to unleash that talent that 232 00:11:51,600 --> 00:11:55,160 Speaker 1: exists in the organization. Very true. I just want to 233 00:11:55,160 --> 00:11:57,680 Speaker 1: know if we can get sort of a sense of 234 00:11:57,720 --> 00:12:00,640 Speaker 1: the scope of your role. If someone were to ask you, 235 00:12:00,720 --> 00:12:03,160 Speaker 1: what's the size of your team, how do you answer 236 00:12:03,200 --> 00:12:06,520 Speaker 1: that question? Varies based on where we're at in the 237 00:12:06,559 --> 00:12:09,720 Speaker 1: product cycles on we're working on. Roughly I have about 238 00:12:09,720 --> 00:12:14,199 Speaker 1: a thousand plus direct employees, but we scale up to 239 00:12:14,320 --> 00:12:21,880 Speaker 1: over eight thousand generally with partners and outsourced relationships and 240 00:12:21,880 --> 00:12:26,000 Speaker 1: and UH. In the automotive space, there's lots of partners 241 00:12:26,080 --> 00:12:29,120 Speaker 1: in the in the ecosystem that we we work with. 242 00:12:29,360 --> 00:12:31,960 Speaker 1: For example, like any connected car, you may have a 243 00:12:32,000 --> 00:12:35,720 Speaker 1: telephone carrier as a partner. You've got other automotive grade 244 00:12:35,880 --> 00:12:38,920 Speaker 1: companies that are maybe building the hardware, we're helping with 245 00:12:38,960 --> 00:12:42,360 Speaker 1: the software. So these teams can get quite large during 246 00:12:42,440 --> 00:12:45,960 Speaker 1: the build period, but like most projects, there's a cycle 247 00:12:46,000 --> 00:12:47,920 Speaker 1: to them that you can kind of plan around on 248 00:12:48,240 --> 00:12:49,960 Speaker 1: what your resource needs look like. Do you have an 249 00:12:50,080 --> 00:12:53,400 Speaker 1: estimate about how many projects your teams are working on 250 00:12:53,440 --> 00:12:55,720 Speaker 1: at any given time. I'm imagining it's going to be 251 00:12:55,800 --> 00:12:59,360 Speaker 1: a very high number. Yeah, it's in it's in the hundreds. Fortunately, 252 00:12:59,600 --> 00:13:02,240 Speaker 1: we got eight team members, but as you can imagine, 253 00:13:02,280 --> 00:13:05,760 Speaker 1: we've got seventeen manufacturing facilities, We've got lots of sales 254 00:13:05,800 --> 00:13:09,040 Speaker 1: offices around the US UM and then plus on my 255 00:13:09,400 --> 00:13:13,880 Speaker 1: AI and our big data company. We're doing lots of products, 256 00:13:13,880 --> 00:13:15,920 Speaker 1: but those may be software related, so you can have 257 00:13:16,040 --> 00:13:19,760 Speaker 1: much smaller teams working on those two or next generation 258 00:13:19,800 --> 00:13:23,320 Speaker 1: of vehicle hardware and software, and those teams can get very, 259 00:13:23,400 --> 00:13:26,520 Speaker 1: very large. But there's an evolutionary period today, so we 260 00:13:26,600 --> 00:13:29,000 Speaker 1: are getting ready to launch our next generation of multimedia 261 00:13:29,040 --> 00:13:32,640 Speaker 1: screens this year and then already starting on the next 262 00:13:32,640 --> 00:13:34,960 Speaker 1: generation which will come out of a couple of years later. 263 00:13:40,320 --> 00:13:43,600 Speaker 1: If there's one thing most businesses can agree on these days, 264 00:13:43,880 --> 00:13:47,000 Speaker 1: it's that change has never come about so quickly. New 265 00:13:47,040 --> 00:13:50,079 Speaker 1: ways of working have become the norm. As a result, 266 00:13:50,360 --> 00:13:52,680 Speaker 1: the status quo no longer cuts it when it comes 267 00:13:52,720 --> 00:13:56,160 Speaker 1: to helping businesses adapt and innovate. That's why T Mobile 268 00:13:56,200 --> 00:14:00,640 Speaker 1: for Business uses unconventional thinking to help businesses work smarter 269 00:14:00,840 --> 00:14:04,920 Speaker 1: and grow faster. Only T Mobile offers America's largest and 270 00:14:05,040 --> 00:14:08,720 Speaker 1: fastest five G network. It's just one reason they're better 271 00:14:08,760 --> 00:14:11,640 Speaker 1: able to help businesses solve the real world challenges they 272 00:14:11,640 --> 00:14:16,320 Speaker 1: face as they evolve. 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Slash Unconventional Open Signal awarded T mobile 281 00:14:44,360 --> 00:14:46,760 Speaker 1: fastest five G network based on average speeds USA five 282 00:14:46,800 --> 00:14:50,360 Speaker 1: G User Experience Report, January. Capable device required coverage on 283 00:14:50,400 --> 00:14:52,800 Speaker 1: available in some areas. Some users may require certain planner 284 00:14:52,800 --> 00:14:59,360 Speaker 1: feature see T mobile dot com. Having a better insight 285 00:14:59,480 --> 00:15:02,960 Speaker 1: into who Zach is and his journey within Toyota, I 286 00:15:03,040 --> 00:15:07,040 Speaker 1: decided to drill down further into his particular approach to leadership. 287 00:15:08,040 --> 00:15:11,320 Speaker 1: What are some of the unique challenges that you encounter 288 00:15:11,680 --> 00:15:15,720 Speaker 1: at Toyota, Things that are very specific to your role. 289 00:15:16,240 --> 00:15:18,120 Speaker 1: I think a lot of them are probably similar to 290 00:15:18,200 --> 00:15:22,080 Speaker 1: what other people face in any type of transformational activity. 291 00:15:22,400 --> 00:15:25,560 Speaker 1: It's usually technology is not the hardest part. It's the 292 00:15:26,040 --> 00:15:30,760 Speaker 1: aligning the business and trying to triangulate as consumer behaviors 293 00:15:30,760 --> 00:15:32,960 Speaker 1: are changing in this direction and technology is moving in 294 00:15:33,000 --> 00:15:35,440 Speaker 1: this direction, how do we move in that same direction 295 00:15:35,760 --> 00:15:37,560 Speaker 1: and get ahead of where they are today? And what 296 00:15:37,600 --> 00:15:39,400 Speaker 1: may be a little bit more unique to working at 297 00:15:39,520 --> 00:15:44,560 Speaker 1: at Toyota UM is we are a large global company. 298 00:15:44,680 --> 00:15:47,240 Speaker 1: I probably spend at least one week of every month 299 00:15:47,240 --> 00:15:50,800 Speaker 1: in Japan, sometimes more, and so the travel can be 300 00:15:50,840 --> 00:15:54,360 Speaker 1: a lot, but those face to face interactions are really meaningful, 301 00:15:54,920 --> 00:15:59,120 Speaker 1: and these global teams are very important right preserving the 302 00:15:59,160 --> 00:16:03,840 Speaker 1: integrity of those relationships so that they have the meaning 303 00:16:04,040 --> 00:16:06,480 Speaker 1: that you want from them and not just feel like 304 00:16:06,520 --> 00:16:09,920 Speaker 1: it's a checklist off an email or something along those lines. 305 00:16:10,760 --> 00:16:15,800 Speaker 1: So communication is clearly an important skill for any leader 306 00:16:16,000 --> 00:16:19,400 Speaker 1: in any industry. It's something that when I speak to 307 00:16:19,440 --> 00:16:21,160 Speaker 1: a lot of c I O s that tends to 308 00:16:21,240 --> 00:16:25,320 Speaker 1: be one of the biggest skill sets that they really 309 00:16:25,360 --> 00:16:28,200 Speaker 1: point to that you have to be able to communicate 310 00:16:28,200 --> 00:16:32,600 Speaker 1: to very different business groups, perhaps two different customers, and 311 00:16:32,680 --> 00:16:37,240 Speaker 1: get buy in on uh ideas that and you have 312 00:16:37,320 --> 00:16:39,600 Speaker 1: to contextualize it and frame it in a way that 313 00:16:39,640 --> 00:16:42,400 Speaker 1: makes sense to that particular group. Would you say that 314 00:16:42,440 --> 00:16:45,480 Speaker 1: communication is is one of the top skills for someone 315 00:16:45,520 --> 00:16:49,400 Speaker 1: who's doing your role. Yeah, absolutely, I think you framed 316 00:16:49,400 --> 00:16:52,320 Speaker 1: it up right on. For me, I think it was 317 00:16:52,520 --> 00:16:54,920 Speaker 1: what allowed me to progress in my career, is be 318 00:16:54,960 --> 00:16:57,640 Speaker 1: able to have these relationships. When I first started off 319 00:16:57,640 --> 00:16:59,720 Speaker 1: in i T, there was this feeling that, well, the 320 00:16:59,760 --> 00:17:03,120 Speaker 1: dis knows what they want, they'll give you that prioritization. 321 00:17:03,640 --> 00:17:05,560 Speaker 1: And I felt like i T was waiting for this 322 00:17:05,680 --> 00:17:08,200 Speaker 1: leather bound strategy to be dropped off on their desk, 323 00:17:08,480 --> 00:17:10,600 Speaker 1: and it wasn't about that. It was about getting out 324 00:17:10,600 --> 00:17:13,760 Speaker 1: of your office, going with the business to the location 325 00:17:13,880 --> 00:17:15,720 Speaker 1: where the customer exists and hear the voice of the 326 00:17:15,760 --> 00:17:19,719 Speaker 1: customer and see the pain points of your business leaders. 327 00:17:20,000 --> 00:17:21,560 Speaker 1: And then you can bring forward and say, hey, there's 328 00:17:21,560 --> 00:17:24,640 Speaker 1: these emerging technologies that may be able to solve this problem. 329 00:17:24,720 --> 00:17:26,879 Speaker 1: Or if you're having a problem of moving these parts faster, 330 00:17:27,200 --> 00:17:29,040 Speaker 1: maybe we could put sensors on them, and here's some 331 00:17:29,040 --> 00:17:31,200 Speaker 1: some ways that we can do that. But to include 332 00:17:31,200 --> 00:17:33,320 Speaker 1: them in that process. To I D eate U, the 333 00:17:33,400 --> 00:17:35,640 Speaker 1: business does know where they want to go, they do 334 00:17:35,720 --> 00:17:38,919 Speaker 1: have a strategy, but they're not going to take the 335 00:17:38,920 --> 00:17:40,520 Speaker 1: time to write it all down and then sit down 336 00:17:40,560 --> 00:17:41,920 Speaker 1: with you and then tell you. You know, if they 337 00:17:42,000 --> 00:17:43,920 Speaker 1: do that problem, it's already too late. You should have 338 00:17:43,920 --> 00:17:47,240 Speaker 1: been solved before. And so I think in today's world, 339 00:17:47,320 --> 00:17:49,800 Speaker 1: to be able to engage with the business and speaking 340 00:17:49,840 --> 00:17:53,640 Speaker 1: in their terms and not overlay with a bunch of 341 00:17:53,760 --> 00:17:56,840 Speaker 1: technical jargon. It's about where we started this conversation, is 342 00:17:56,880 --> 00:17:59,320 Speaker 1: what it can enable, and envisioning that and then going 343 00:17:59,400 --> 00:18:02,040 Speaker 1: back and on your team to to begin that process. 344 00:18:02,119 --> 00:18:05,320 Speaker 1: But it is that communication and that intersection between I 345 00:18:05,400 --> 00:18:07,720 Speaker 1: T and business where the magic happens, and that's where 346 00:18:07,720 --> 00:18:11,359 Speaker 1: CIOs have to live. I certainly have heard from people 347 00:18:11,400 --> 00:18:15,600 Speaker 1: who work in various I T jobs that a pain 348 00:18:15,640 --> 00:18:20,400 Speaker 1: point typically ends up being, yeah, but why are we 349 00:18:20,560 --> 00:18:23,119 Speaker 1: doing this? Like I know what I'm supposed to do, 350 00:18:23,160 --> 00:18:25,240 Speaker 1: I don't know why I am doing it. But as 351 00:18:25,280 --> 00:18:28,920 Speaker 1: you point out, when you go back to that use 352 00:18:28,960 --> 00:18:31,520 Speaker 1: case where you're saying, let's look at what we're trying 353 00:18:31,520 --> 00:18:36,600 Speaker 1: to enable, when that becomes a parent and everyone understands that, 354 00:18:36,760 --> 00:18:38,879 Speaker 1: it clears away a lot of the problems that you 355 00:18:38,920 --> 00:18:43,080 Speaker 1: would typically see otherwise. What is it that really excites 356 00:18:43,119 --> 00:18:46,240 Speaker 1: you about your work? What are the things that get 357 00:18:46,280 --> 00:18:48,560 Speaker 1: you up out of bed when you're about to jump 358 00:18:48,600 --> 00:18:51,680 Speaker 1: on another flight over to Japan, or you're about to 359 00:18:51,720 --> 00:18:54,320 Speaker 1: head to Europe, or you're just going into one of 360 00:18:54,359 --> 00:18:59,919 Speaker 1: your offices. Were at Toyota when when we created toy 361 00:19:00,000 --> 00:19:02,639 Speaker 1: to Connect in we talked about what should our goals 362 00:19:02,720 --> 00:19:05,240 Speaker 1: be and it wasn't just about ingesting the data. Anybody 363 00:19:05,359 --> 00:19:06,919 Speaker 1: can do that, and we knew we wanted to use 364 00:19:06,920 --> 00:19:10,640 Speaker 1: the data for customers to make their lives better. And 365 00:19:11,880 --> 00:19:15,320 Speaker 1: we set a lofty goal of saying Toya Connected should 366 00:19:15,320 --> 00:19:19,120 Speaker 1: be making the world better. And it sounded a little 367 00:19:19,119 --> 00:19:23,080 Speaker 1: bit cheesy or maybe overreaching, but we've done these hackathons 368 00:19:23,080 --> 00:19:24,680 Speaker 1: and we've challenged our team members of how can we 369 00:19:24,760 --> 00:19:27,879 Speaker 1: use data to make customers lives better? And I'm blown away. 370 00:19:27,960 --> 00:19:30,239 Speaker 1: You know, I can give you some examples where, um, 371 00:19:30,760 --> 00:19:33,439 Speaker 1: we've come up with this concept and we're testing out 372 00:19:33,520 --> 00:19:36,440 Speaker 1: right now. Is in in an amber alert, we can 373 00:19:36,480 --> 00:19:38,879 Speaker 1: pop up a message on on the person's screening their 374 00:19:38,920 --> 00:19:40,760 Speaker 1: car and say can we use your outward facing camera 375 00:19:40,840 --> 00:19:42,919 Speaker 1: to look for this license plate? And if you opt in, 376 00:19:43,200 --> 00:19:45,080 Speaker 1: then you've got an army of cars that are looking 377 00:19:45,480 --> 00:19:48,639 Speaker 1: to help, you know, find a lost child. We can 378 00:19:48,720 --> 00:19:52,280 Speaker 1: use that same technology if there's let's say, a wildfire 379 00:19:52,320 --> 00:19:55,040 Speaker 1: like in California, as there was last year, and maybe 380 00:19:55,160 --> 00:19:57,440 Speaker 1: we know that you know that there's toyotas in that area, 381 00:19:57,440 --> 00:19:59,359 Speaker 1: that we can light up those cameras let the firefighters 382 00:19:59,359 --> 00:20:02,640 Speaker 1: know exactly where the fire is occurring. Too. We're doing 383 00:20:02,720 --> 00:20:06,280 Speaker 1: some testing right now with some nanotechnology to be able 384 00:20:06,280 --> 00:20:08,280 Speaker 1: to detect if there's a life form left in a vehicle. 385 00:20:08,400 --> 00:20:10,280 Speaker 1: So if a baby has been forgotten in the car, 386 00:20:10,720 --> 00:20:13,040 Speaker 1: even if they've fallen asleep, can we pick up their heartbeat. 387 00:20:13,480 --> 00:20:17,440 Speaker 1: So I really believe that technology or the data isn't 388 00:20:17,440 --> 00:20:20,320 Speaker 1: about selling more ads. It's about making the world a 389 00:20:20,320 --> 00:20:23,240 Speaker 1: better place, and my team is doing that. As someone 390 00:20:23,280 --> 00:20:26,679 Speaker 1: who covers technology for a living, I find that extremely refreshing, 391 00:20:26,760 --> 00:20:30,720 Speaker 1: the idea of using technology to enable things that have 392 00:20:31,560 --> 00:20:35,280 Speaker 1: a positive impact. It's a subtle way of presenting the 393 00:20:35,320 --> 00:20:40,280 Speaker 1: information where in one instance it is not intrusive and 394 00:20:40,359 --> 00:20:43,720 Speaker 1: it's helpful, and in the other instance it's obnoxious. I 395 00:20:43,720 --> 00:20:45,320 Speaker 1: also think to the other thing is it can be 396 00:20:45,359 --> 00:20:47,080 Speaker 1: if not used the right way, it can be creepy. 397 00:20:47,240 --> 00:20:49,560 Speaker 1: So I we talked a lot about not being creepy 398 00:20:49,640 --> 00:20:54,760 Speaker 1: but being delightful and inspiring our customers. And so example, 399 00:20:54,800 --> 00:20:57,120 Speaker 1: I I can use is um if a customer wants 400 00:20:57,119 --> 00:20:58,600 Speaker 1: to share with us their likes. And I know that 401 00:20:58,680 --> 00:21:02,040 Speaker 1: somebody customer likes say Taylor Swift, and they're heading down 402 00:21:02,080 --> 00:21:04,040 Speaker 1: the road that they've not traveled before, but now it's 403 00:21:04,040 --> 00:21:06,160 Speaker 1: in the general direction of where Taylor Switch is performing. 404 00:21:06,359 --> 00:21:08,399 Speaker 1: We can say, hey, it looks like you're heading to 405 00:21:08,400 --> 00:21:10,800 Speaker 1: the Tailor Swift concert. That could just be creepy, but 406 00:21:10,800 --> 00:21:12,800 Speaker 1: what could be delightful as where I can say, can 407 00:21:12,840 --> 00:21:15,199 Speaker 1: I route you around traffic and prepay your parking? That 408 00:21:15,320 --> 00:21:19,040 Speaker 1: becomes delightful and so. And if the customer has clear 409 00:21:19,720 --> 00:21:23,200 Speaker 1: control of his or her data and opting into these services, 410 00:21:23,640 --> 00:21:27,239 Speaker 1: then it's it's more meaningful. The automotive industry has been 411 00:21:27,280 --> 00:21:30,320 Speaker 1: a key component in the technological sector for more than 412 00:21:30,359 --> 00:21:33,480 Speaker 1: a century. You really get the full spectrum of tech, 413 00:21:33,880 --> 00:21:38,880 Speaker 1: from manufacturing processes to supply chain management, to data analysis 414 00:21:39,040 --> 00:21:43,480 Speaker 1: to implementing new technological features into consumer products. I wanted 415 00:21:43,520 --> 00:21:46,560 Speaker 1: to learn more about what Zach is interested in and 416 00:21:46,640 --> 00:21:49,840 Speaker 1: maybe even get a sneak peek into where the automotive 417 00:21:49,880 --> 00:21:54,200 Speaker 1: industry is headed next. So today or or connected vehicles 418 00:21:54,440 --> 00:21:56,800 Speaker 1: share data and and at a at a basic level, 419 00:21:56,880 --> 00:22:00,520 Speaker 1: if a customer is in an accident and nearbag is 420 00:22:00,520 --> 00:22:03,480 Speaker 1: deployed and they've opted in for these services, we can 421 00:22:03,760 --> 00:22:06,640 Speaker 1: notify a nine O one responder to know exactly where 422 00:22:06,640 --> 00:22:09,320 Speaker 1: the accident occurred. And even as we're getting begin to 423 00:22:09,320 --> 00:22:11,800 Speaker 1: get more data from the vehicles, we could let them know, well, 424 00:22:11,800 --> 00:22:14,680 Speaker 1: there was three seat belts buckled, or the accident occurred 425 00:22:14,680 --> 00:22:18,440 Speaker 1: at this velocity UM and maybe even as data gets 426 00:22:18,480 --> 00:22:21,080 Speaker 1: in our algorithms get better, we can begin to estimate 427 00:22:21,600 --> 00:22:24,600 Speaker 1: UM what other problems may have occurred UH and and 428 00:22:24,640 --> 00:22:28,320 Speaker 1: give that to the nine one responders. UM to some 429 00:22:28,440 --> 00:22:32,000 Speaker 1: of the services that you've you've talked about UM helping 430 00:22:32,040 --> 00:22:33,879 Speaker 1: people and say the next time of in this area 431 00:22:34,200 --> 00:22:36,800 Speaker 1: and I want to try this, UH this new bakery. 432 00:22:37,520 --> 00:22:39,200 Speaker 1: Have the car remind you that you're in that area 433 00:22:39,240 --> 00:22:42,240 Speaker 1: that you know, maybe pick up some some bake goods. UM. 434 00:22:42,320 --> 00:22:43,760 Speaker 1: One of the things we recently got a patent on 435 00:22:43,800 --> 00:22:46,800 Speaker 1: that will be releasing, which is more of a convenience service. 436 00:22:46,920 --> 00:22:49,280 Speaker 1: So we can look at UM as somebody's entering a 437 00:22:49,320 --> 00:22:51,760 Speaker 1: parking garage and we can tell by how fast you're 438 00:22:51,760 --> 00:22:53,680 Speaker 1: accelerating up the hill and what they all right, and 439 00:22:53,720 --> 00:22:56,239 Speaker 1: the turn rate looks like our algorithms can now with 440 00:22:56,359 --> 00:22:59,920 Speaker 1: maybe roughly around accuracy, can tell somebody looks like you're 441 00:23:00,119 --> 00:23:02,760 Speaker 1: the third level of a parking garage in the northeast corner, 442 00:23:02,920 --> 00:23:04,240 Speaker 1: so as you get out of your car, to pop 443 00:23:04,320 --> 00:23:05,880 Speaker 1: up on your screen to remind you where you parked 444 00:23:05,880 --> 00:23:09,080 Speaker 1: at in a parking garage. So from convenience services to 445 00:23:09,200 --> 00:23:12,879 Speaker 1: late life saving services, that's what connectivity means to me. 446 00:23:13,520 --> 00:23:16,520 Speaker 1: It's still I would suggest it's early days. All of 447 00:23:16,520 --> 00:23:18,639 Speaker 1: the data coming on the car is not meaningful. It's 448 00:23:18,680 --> 00:23:21,359 Speaker 1: too costly to manage and process all of that data. 449 00:23:21,480 --> 00:23:22,960 Speaker 1: So I think in the future you're going to see 450 00:23:23,000 --> 00:23:25,800 Speaker 1: more of this processing happening on the edge, happening in 451 00:23:25,840 --> 00:23:29,000 Speaker 1: the vehicle, and the customers will dictate those services that 452 00:23:29,040 --> 00:23:31,840 Speaker 1: they want and which ones they don't want. I imagine 453 00:23:32,040 --> 00:23:37,560 Speaker 1: we're looking at instances where machine learning and artificial intelligence 454 00:23:37,800 --> 00:23:40,320 Speaker 1: and some data automation are going to play a big 455 00:23:40,359 --> 00:23:43,520 Speaker 1: part in that. And in my view of the future, 456 00:23:43,600 --> 00:23:46,639 Speaker 1: it becomes a thing where every single person's experience with 457 00:23:46,720 --> 00:23:50,679 Speaker 1: their vehicle becomes more and more personalized, to a point 458 00:23:50,720 --> 00:23:53,240 Speaker 1: where if you were to step into someone else's car 459 00:23:53,280 --> 00:23:55,159 Speaker 1: and drive it for a little while, you might just 460 00:23:55,240 --> 00:23:57,639 Speaker 1: feel like, Wow, this is a really different experience because 461 00:23:57,680 --> 00:24:00,320 Speaker 1: it's no longer specifically catered to the way I drive 462 00:24:00,400 --> 00:24:03,080 Speaker 1: and the places I go. But to me, that's that's 463 00:24:03,080 --> 00:24:05,600 Speaker 1: really exciting. This release that we're going to have this 464 00:24:05,680 --> 00:24:07,760 Speaker 1: year on some of our new vehicles will solve that 465 00:24:07,840 --> 00:24:09,439 Speaker 1: for you. So the next time you get into a 466 00:24:09,440 --> 00:24:13,440 Speaker 1: Toyoto or Alexis vehicle, your persona will travel with you. 467 00:24:13,920 --> 00:24:17,040 Speaker 1: So if you your preset destinations on your head unit, 468 00:24:17,080 --> 00:24:19,720 Speaker 1: your temperature controls, maybe even your seat settings, and you 469 00:24:19,720 --> 00:24:21,240 Speaker 1: can even have the flow with you perhaps in the 470 00:24:21,240 --> 00:24:23,000 Speaker 1: future when you get into an uber or lift to 471 00:24:23,080 --> 00:24:24,760 Speaker 1: make sure that we've got the right temperature controls and 472 00:24:24,760 --> 00:24:27,320 Speaker 1: maybe even which music you want to hear. So, just 473 00:24:27,400 --> 00:24:29,600 Speaker 1: like your phone, which knows everything about you, if you 474 00:24:29,600 --> 00:24:31,119 Speaker 1: want to share that with your vehicle, we can make 475 00:24:31,160 --> 00:24:32,840 Speaker 1: sure that it goes from vehicle to vehicle with you 476 00:24:33,119 --> 00:24:35,680 Speaker 1: and then disappears from a privacy and security point of 477 00:24:35,720 --> 00:24:38,399 Speaker 1: view as you exit that vehicle. Zach, you're talking magic 478 00:24:38,440 --> 00:24:41,480 Speaker 1: to me now. But then Arthur C. Clark said, any 479 00:24:41,520 --> 00:24:46,480 Speaker 1: technology sufficiently sophisticated seems like magic. So you know, that's 480 00:24:46,480 --> 00:24:49,520 Speaker 1: connectivity that I think of as being very outward facing 481 00:24:49,920 --> 00:24:54,320 Speaker 1: for consumers. I imagine that behind the scene internally, that 482 00:24:54,359 --> 00:24:59,120 Speaker 1: connectivity plays an enormous role at Toyota, from the corporate 483 00:24:59,160 --> 00:25:02,920 Speaker 1: side to the manufacturing side. Absolutely, you know, on the 484 00:25:02,960 --> 00:25:06,560 Speaker 1: manufacturing side, I think that's kind of the next huge opportunity, 485 00:25:06,640 --> 00:25:10,040 Speaker 1: which which I think all manufacturing companies are experiencing and 486 00:25:10,520 --> 00:25:14,600 Speaker 1: experimenting on, and so from a manufacturing perspective, our products 487 00:25:14,600 --> 00:25:16,440 Speaker 1: and quality continue to get better and better and better 488 00:25:16,440 --> 00:25:19,640 Speaker 1: because we have real time information as anything is going wrong, 489 00:25:19,680 --> 00:25:21,280 Speaker 1: instead of waiting for it to come off the line 490 00:25:21,280 --> 00:25:23,439 Speaker 1: and the customer experiencing a problem and then having to 491 00:25:23,480 --> 00:25:25,959 Speaker 1: fix it. But we do have that feedback loop now 492 00:25:25,960 --> 00:25:28,600 Speaker 1: as our cars are getting serviced in the garage, all 493 00:25:28,600 --> 00:25:32,399 Speaker 1: of that data goes into our machine learning algorithms to 494 00:25:32,480 --> 00:25:34,359 Speaker 1: understand is it's the problems is torn and how can 495 00:25:34,400 --> 00:25:36,480 Speaker 1: we fix that on the line so it doesn't happen again. 496 00:25:36,880 --> 00:25:39,200 Speaker 1: Um Or let our suppliers know that they're We're starting 497 00:25:39,200 --> 00:25:42,680 Speaker 1: to see some failures in these areas um to how 498 00:25:42,680 --> 00:25:46,119 Speaker 1: we design cars knowing that certain features may not be 499 00:25:46,119 --> 00:25:48,199 Speaker 1: being used very much in the vehicle, So why I 500 00:25:48,240 --> 00:25:50,040 Speaker 1: spend the money if the customer doesn't care about it. 501 00:25:50,480 --> 00:25:53,680 Speaker 1: Everything that we do is connected in from a corporate 502 00:25:53,680 --> 00:25:57,600 Speaker 1: I T perspective, your I T infrastructure is just a 503 00:25:57,640 --> 00:26:00,560 Speaker 1: digital manifestation of how you do business. That's a good 504 00:26:00,680 --> 00:26:03,760 Speaker 1: lens and to look to how companies operating well and 505 00:26:04,119 --> 00:26:07,560 Speaker 1: with this connectivity. I mean, obviously, connectivity can't happen unless 506 00:26:07,640 --> 00:26:12,320 Speaker 1: you have the technologies that actually allow different pieces to 507 00:26:12,359 --> 00:26:16,440 Speaker 1: communicate with one another. And with the rollout of five 508 00:26:16,520 --> 00:26:21,360 Speaker 1: G technologies, we're seeing some new potential applications, whether we're 509 00:26:21,359 --> 00:26:23,600 Speaker 1: talking about high frequency five G where you can have 510 00:26:23,800 --> 00:26:27,840 Speaker 1: very high throughput, low latency just to to the other 511 00:26:27,920 --> 00:26:33,359 Speaker 1: flavors as well. What sort of ways are Toyota implementing 512 00:26:33,680 --> 00:26:37,960 Speaker 1: or relying upon five G technologies. So I can't give 513 00:26:38,000 --> 00:26:40,199 Speaker 1: you specifics and some of these future products, but I 514 00:26:40,200 --> 00:26:42,800 Speaker 1: can share with you that we are looking at five 515 00:26:42,840 --> 00:26:46,560 Speaker 1: G because we do see opportunities for improved safety, reducing 516 00:26:46,600 --> 00:26:51,320 Speaker 1: traffic congestion, and delivering rich media experiences in the vehicle, 517 00:26:51,359 --> 00:26:54,200 Speaker 1: not just for the driver but for the passengers. So 518 00:26:54,480 --> 00:26:57,439 Speaker 1: those experiences should just flow naturally and should be enabled. 519 00:26:57,440 --> 00:26:59,680 Speaker 1: And five G is going to be a great opportunity 520 00:26:59,720 --> 00:27:02,040 Speaker 1: to to do that in a much more meaningqual way. 521 00:27:02,119 --> 00:27:03,840 Speaker 1: But I also think that we're still going to always 522 00:27:03,880 --> 00:27:06,760 Speaker 1: need edge computing for really fast decisions. So as you're 523 00:27:06,800 --> 00:27:09,800 Speaker 1: looking at two more autonomy in our vehicles, you still 524 00:27:09,800 --> 00:27:11,040 Speaker 1: don't want to be relying to go up to the 525 00:27:11,040 --> 00:27:13,040 Speaker 1: cloud to make a decision. You want to be making 526 00:27:13,040 --> 00:27:16,239 Speaker 1: decisions real time on that vehicle. So to that end, 527 00:27:16,280 --> 00:27:20,080 Speaker 1: do you also see cars as playing an important role 528 00:27:20,240 --> 00:27:24,520 Speaker 1: in things like smart city infrastructure where there's perhaps the 529 00:27:24,520 --> 00:27:29,160 Speaker 1: the opportunity for vehicles on the road to interact with 530 00:27:29,520 --> 00:27:32,960 Speaker 1: city infrastructure and to do things like reduced traffic congestion 531 00:27:33,080 --> 00:27:36,280 Speaker 1: things like that. Yeah, huge opportunities, I think, and that's 532 00:27:36,280 --> 00:27:38,800 Speaker 1: one of the great promises of five g S to 533 00:27:38,960 --> 00:27:41,800 Speaker 1: allow cities to better manage that and help with the 534 00:27:41,800 --> 00:27:46,080 Speaker 1: interplay between the driver and the infrastructure to have better routput. 535 00:27:46,520 --> 00:27:49,120 Speaker 1: One thing people may have not not have not heard yet, 536 00:27:49,119 --> 00:27:53,879 Speaker 1: but we're launching a prototype city in Japan called Woven City, 537 00:27:54,320 --> 00:27:57,240 Speaker 1: pretty close to Mount Fuji, and the whole concept there 538 00:27:57,280 --> 00:28:00,679 Speaker 1: is that people will live there and researchers and research 539 00:28:00,720 --> 00:28:03,440 Speaker 1: groups will come in, and that's what we're trying out. 540 00:28:03,760 --> 00:28:05,679 Speaker 1: You may be surprised to learn that in the city 541 00:28:05,680 --> 00:28:08,639 Speaker 1: center that there won't be cars driving through our personally 542 00:28:08,640 --> 00:28:11,520 Speaker 1: owned vehicles, and that may be shocking for Toyo to do, 543 00:28:11,880 --> 00:28:13,960 Speaker 1: but we're trying to envision what that better future can 544 00:28:14,000 --> 00:28:18,000 Speaker 1: look like. And it's that interplay between walking, public transportation, 545 00:28:18,160 --> 00:28:21,199 Speaker 1: personally owned vehicles, shared vehicles. How will that work in 546 00:28:21,240 --> 00:28:24,440 Speaker 1: a much more smooth environment. Five gigle play a large 547 00:28:24,440 --> 00:28:26,320 Speaker 1: part of that, but we all have to work together, 548 00:28:26,800 --> 00:28:30,720 Speaker 1: private and public entities to to enable that future. And 549 00:28:30,760 --> 00:28:32,720 Speaker 1: related to that, I mean, I've I've heard that you 550 00:28:33,119 --> 00:28:37,800 Speaker 1: have described Toyota as really a mobility company, and uh, 551 00:28:37,840 --> 00:28:40,680 Speaker 1: that really caught my attention to because it speaks to 552 00:28:40,840 --> 00:28:45,080 Speaker 1: something much larger than even automotive company. Can you go 553 00:28:45,120 --> 00:28:47,200 Speaker 1: into a little more detail about what you mean when 554 00:28:47,240 --> 00:28:50,440 Speaker 1: you say it's a mobility company. Yeah, And internally, when 555 00:28:50,440 --> 00:28:53,080 Speaker 1: we we talked about being a mobility company, I like 556 00:28:53,160 --> 00:28:56,000 Speaker 1: to share that it could be helping somebody get across 557 00:28:56,040 --> 00:28:58,560 Speaker 1: country or getting across our living room if they have 558 00:28:58,680 --> 00:29:01,600 Speaker 1: limited mobility. It's not just a personally owned vehicle. And 559 00:29:01,640 --> 00:29:04,720 Speaker 1: so we've got lots of prototypes and testing around the 560 00:29:04,760 --> 00:29:08,239 Speaker 1: world where we're interacting with public transportation. So how does 561 00:29:08,240 --> 00:29:11,080 Speaker 1: somebody take their personal vehicle drive to maybe a train station, 562 00:29:11,480 --> 00:29:13,760 Speaker 1: and from that train station maybe to a bus, and 563 00:29:13,800 --> 00:29:15,200 Speaker 1: then even if they get off the bus, how do 564 00:29:15,240 --> 00:29:17,240 Speaker 1: we still get them to their destination where they want 565 00:29:17,280 --> 00:29:20,200 Speaker 1: to go to. That's the opportunity. So we we won't 566 00:29:20,200 --> 00:29:23,320 Speaker 1: define mobility, our customers will. And we get right back 567 00:29:23,320 --> 00:29:26,760 Speaker 1: to that philosophy of how do we leverage technology to 568 00:29:26,920 --> 00:29:30,440 Speaker 1: enable the outcome that we desire. Do you have any 569 00:29:30,480 --> 00:29:35,200 Speaker 1: particular favorite emerging technologies things that you're really excited about 570 00:29:35,280 --> 00:29:39,320 Speaker 1: or curious about. I think video is on board. We're 571 00:29:39,360 --> 00:29:43,560 Speaker 1: also looking at another use case where seniors that have dementia, 572 00:29:43,920 --> 00:29:45,920 Speaker 1: if they're not found within twenty four hours, there's high 573 00:29:46,000 --> 00:29:48,400 Speaker 1: risk to their life. But could we even use outward 574 00:29:48,400 --> 00:29:51,800 Speaker 1: facing technology to help find that person on a camera 575 00:29:52,120 --> 00:29:55,480 Speaker 1: but not risk other people's privacy or you know, we 576 00:29:55,480 --> 00:29:58,080 Speaker 1: we did a test where vehicles go through every intersection 577 00:29:58,280 --> 00:30:00,720 Speaker 1: in Tokyo every fifteen minutes, and so we help them 578 00:30:00,720 --> 00:30:02,640 Speaker 1: look for litter and and for things in the road 579 00:30:02,680 --> 00:30:04,880 Speaker 1: that could be an obstacle and then feed that information 580 00:30:05,360 --> 00:30:08,680 Speaker 1: that could be used in our vehicles today for looking 581 00:30:08,720 --> 00:30:11,280 Speaker 1: for ice or when we detect our any lock breaks 582 00:30:11,280 --> 00:30:14,320 Speaker 1: starting to you know, see some slipping on the roads happening. 583 00:30:14,440 --> 00:30:17,240 Speaker 1: Could we feed that information to local authorities so they 584 00:30:17,240 --> 00:30:18,640 Speaker 1: can come in and take care of the roads in 585 00:30:18,680 --> 00:30:21,320 Speaker 1: that area. I think we can make life better if 586 00:30:21,320 --> 00:30:23,360 Speaker 1: we use this technology in a way that still keeps 587 00:30:23,360 --> 00:30:26,840 Speaker 1: people's privacy safe, insecure, but allows us to have a 588 00:30:26,840 --> 00:30:31,040 Speaker 1: better life. Before I could let Zach go, I needed 589 00:30:31,080 --> 00:30:35,000 Speaker 1: to ask him one more thing. At the end of 590 00:30:35,000 --> 00:30:38,800 Speaker 1: the day, what opportunity are you most excited to pursue? 591 00:30:39,800 --> 00:30:47,120 Speaker 1: The opportunity to build faster services and products for our customers, 592 00:30:47,160 --> 00:30:49,480 Speaker 1: to make a better experience in a better world. That's 593 00:30:49,520 --> 00:30:52,760 Speaker 1: a great answer, and and I cannot stress enough to 594 00:30:52,840 --> 00:30:56,320 Speaker 1: my audience that that itself is a is an enormous challenge. 595 00:30:56,320 --> 00:30:59,840 Speaker 1: When you're looking at an industry like the car industry, 596 00:31:00,040 --> 00:31:05,960 Speaker 1: where you are marrying this very rapid iteration of technology 597 00:31:06,000 --> 00:31:11,000 Speaker 1: and potential implementations of it into platforms that have incredible 598 00:31:11,080 --> 00:31:14,440 Speaker 1: legacy behind them, and you have to honor both. That 599 00:31:14,560 --> 00:31:18,200 Speaker 1: is an an enormous challenge and one that I find 600 00:31:18,520 --> 00:31:22,560 Speaker 1: really fascinating. So Zach, thank you so much for joining 601 00:31:22,640 --> 00:31:25,479 Speaker 1: us today. Thank you for having me. I enjoyed it. 602 00:31:33,680 --> 00:31:36,400 Speaker 1: Thanks again to Zach Hicks for taking time to speak 603 00:31:36,400 --> 00:31:39,800 Speaker 1: with us on The Restless Ones. My big takeaways really 604 00:31:39,840 --> 00:31:43,280 Speaker 1: come back to something Zach said early on, focusing on 605 00:31:43,320 --> 00:31:47,760 Speaker 1: how technology enables us to do specific things without getting 606 00:31:47,800 --> 00:31:52,880 Speaker 1: bogged down into specific instances of tech. That's what's really important. 607 00:31:53,160 --> 00:31:56,920 Speaker 1: It's what frees up organizations to pursue a mission without 608 00:31:57,000 --> 00:32:00,680 Speaker 1: turning tech into an anchor that slows things down. And 609 00:32:00,840 --> 00:32:03,320 Speaker 1: involving the I. T side of a business in a 610 00:32:03,360 --> 00:32:08,080 Speaker 1: more integral and coherent approach really can have enormous benefits, 611 00:32:08,080 --> 00:32:11,840 Speaker 1: removing communication barriers and making it easier to achieve buy in. 612 00:32:12,640 --> 00:32:16,480 Speaker 1: And of course, the evolving technologies that facilitate this kind 613 00:32:16,520 --> 00:32:20,720 Speaker 1: of approach to business are absolutely critical. Without them, we'd 614 00:32:20,720 --> 00:32:24,880 Speaker 1: have great ideas but no way to execute them. Connectivity 615 00:32:24,920 --> 00:32:27,640 Speaker 1: is crucial for Toyota, but I think it's safe to 616 00:32:27,680 --> 00:32:32,480 Speaker 1: say it's importance is evident across all industries. With solutions 617 00:32:32,520 --> 00:32:35,760 Speaker 1: like five G opening up new ways to achieve connectivity, 618 00:32:35,760 --> 00:32:40,320 Speaker 1: we're headed toward a very exciting future. Make sure you 619 00:32:40,440 --> 00:32:42,920 Speaker 1: join us for the next episode of The Restless Ones 620 00:32:43,200 --> 00:32:45,600 Speaker 1: as we continue to speak with the leaders who are 621 00:32:45,640 --> 00:32:56,840 Speaker 1: bringing the future into the present. I'm Jonathan Strickland. These days, 622 00:32:57,080 --> 00:32:59,440 Speaker 1: new ways of working have become the norm, and the 623 00:32:59,480 --> 00:33:01,680 Speaker 1: status oh no longer cuts it when it comes to 624 00:33:01,720 --> 00:33:05,280 Speaker 1: helping businesses evolve and grow. 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