1 00:00:02,400 --> 00:00:06,760 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. 2 00:00:06,960 --> 00:00:09,799 Speaker 2: One of their software watching is Motorola Solutions. It is 3 00:00:09,840 --> 00:00:12,680 Speaker 2: one of the best performing tech stocks in the SMP 4 00:00:13,000 --> 00:00:15,920 Speaker 2: this year. Shares are up roughly fifty five percent, driven 5 00:00:15,960 --> 00:00:19,520 Speaker 2: in part by a shift from hardware to software and services. Now, 6 00:00:19,560 --> 00:00:23,680 Speaker 2: remember Motorola Solutions makes things like bodycams, public safety walkie talkies, 7 00:00:23,720 --> 00:00:25,360 Speaker 2: that kind of stuff. Here in studio with more on 8 00:00:25,400 --> 00:00:28,640 Speaker 2: this is Greg Brown, chairman and CEO of Motorola Solutions. 9 00:00:28,680 --> 00:00:30,440 Speaker 1: Greg, it's great to see you, Thanks for having me. 10 00:00:30,760 --> 00:00:33,880 Speaker 2: So how is this transition going? Like it's really about 11 00:00:33,880 --> 00:00:38,800 Speaker 2: services and software at a hardware better margin. How do 12 00:00:38,800 --> 00:00:40,800 Speaker 2: you see that happening over the next year. 13 00:00:41,080 --> 00:00:43,519 Speaker 3: Well, so take a step back. We just printed a 14 00:00:43,520 --> 00:00:47,559 Speaker 3: great Q three. We had record orders across all three technologies. 15 00:00:48,080 --> 00:00:50,400 Speaker 3: Forget about hardware and software for a minute and think 16 00:00:50,400 --> 00:00:55,160 Speaker 3: of it about public safety and enterprise security. So we 17 00:00:55,200 --> 00:00:59,680 Speaker 3: are the leading provider of public safety emergency communications networks NYPD, 18 00:01:00,080 --> 00:01:04,280 Speaker 3: DNY Chicago and the like. There are about thirteen thousand 19 00:01:05,000 --> 00:01:08,360 Speaker 3: of these emergency or enterprise mission critical. 20 00:01:08,040 --> 00:01:09,120 Speaker 1: Networks around the world. 21 00:01:09,680 --> 00:01:13,679 Speaker 3: As that footprint ALEX expands, that's a good thing because 22 00:01:13,720 --> 00:01:17,039 Speaker 3: what we do then is we monetize different levels of 23 00:01:17,160 --> 00:01:20,800 Speaker 3: services on those networks, and we have device refresh. 24 00:01:20,920 --> 00:01:23,839 Speaker 1: You call them walkie talkies, We call them radios. 25 00:01:23,880 --> 00:01:26,760 Speaker 2: But the talk sound cooler by the way. 26 00:01:26,600 --> 00:01:28,440 Speaker 1: They do well, people get it? Do they go radio? 27 00:01:28,440 --> 00:01:31,240 Speaker 1: I don't understand. Well, didne Loaderolla invent the walkie talkie? 28 00:01:31,240 --> 00:01:34,160 Speaker 3: Indeed actually it was originally called the handy talkie? But yes, 29 00:01:34,440 --> 00:01:35,840 Speaker 3: but when now we call them radios? 30 00:01:35,840 --> 00:01:37,959 Speaker 1: But irrespective today fair enough they. 31 00:01:37,880 --> 00:01:41,160 Speaker 3: Last about eight years plus or minus, so we do 32 00:01:41,280 --> 00:01:42,200 Speaker 3: device refresh. 33 00:01:42,319 --> 00:01:43,640 Speaker 1: We now have LT. 34 00:01:44,959 --> 00:01:49,520 Speaker 3: Four G five G dual banded on these LMR walkie talkies, 35 00:01:49,960 --> 00:01:52,840 Speaker 3: so we have broad a reach software over their reprogramming. 36 00:01:53,920 --> 00:01:57,800 Speaker 3: Margins are up, cash flows up, total backlog. We anticipate 37 00:01:57,840 --> 00:01:59,760 Speaker 3: being up and look at the end of the day 38 00:01:59,800 --> 00:02:03,000 Speaker 3: we broke up Motorola. We are about safety and security. 39 00:02:04,000 --> 00:02:06,240 Speaker 3: Those needs are as high as ever and our end 40 00:02:06,320 --> 00:02:07,520 Speaker 3: user markets are vibrant. 41 00:02:07,560 --> 00:02:08,000 Speaker 1: So it's good. 42 00:02:08,040 --> 00:02:10,640 Speaker 2: Okay, it's a pitch, good pitch. Where does M and 43 00:02:10,680 --> 00:02:13,239 Speaker 2: A play in that? Are we looking at tuck in deals? 44 00:02:13,280 --> 00:02:14,920 Speaker 2: Are you going to have some transformative stuff to really 45 00:02:14,919 --> 00:02:15,959 Speaker 2: build up some of those. 46 00:02:15,760 --> 00:02:17,920 Speaker 3: I think it's played historically in both We've done about 47 00:02:17,960 --> 00:02:21,080 Speaker 3: forty deals in the last decade, two of them of 48 00:02:21,160 --> 00:02:24,000 Speaker 3: a billion dollars or more a little bit more consequential. 49 00:02:24,360 --> 00:02:27,280 Speaker 3: The rest I guess you would characterize as tuckins. We 50 00:02:27,360 --> 00:02:29,919 Speaker 3: sit now with a market cap of eighty billion, We're 51 00:02:29,960 --> 00:02:33,720 Speaker 3: generating two point three billion in operating cash flow. We've 52 00:02:33,760 --> 00:02:36,920 Speaker 3: got the best net debt to ebit US, so we 53 00:02:36,960 --> 00:02:40,080 Speaker 3: have dripowder. We don't have any short term financing. So 54 00:02:40,160 --> 00:02:42,079 Speaker 3: I think M and A does play a key role 55 00:02:42,160 --> 00:02:45,720 Speaker 3: going forward. I think it will likely be Tuckins. It 56 00:02:45,720 --> 00:02:49,079 Speaker 3: could be something more material, depends on what opportunities come 57 00:02:49,080 --> 00:02:52,239 Speaker 3: forward and at what price, and whether there's an actual 58 00:02:52,320 --> 00:02:52,760 Speaker 3: deal or not. 59 00:02:53,040 --> 00:02:56,120 Speaker 1: But I do view M and A as important going forward. 60 00:02:56,080 --> 00:02:59,840 Speaker 4: And you've done pretty well with that over your tenure, CEO. 61 00:03:00,040 --> 00:03:03,400 Speaker 4: I think fifteen hundred percent shareholder returns nothing to sneeze. 62 00:03:03,040 --> 00:03:04,800 Speaker 1: At since one one of eleven exactly. 63 00:03:05,080 --> 00:03:09,480 Speaker 4: So what what is next for Motorola Solutions? As I 64 00:03:09,520 --> 00:03:12,000 Speaker 4: think about your business, I have to think about AI 65 00:03:12,200 --> 00:03:15,600 Speaker 4: as well. Obviously it's almost synonymous now with cloud. 66 00:03:16,520 --> 00:03:18,799 Speaker 1: How do you put AI to work at Motorola Solution. 67 00:03:18,919 --> 00:03:19,720 Speaker 1: We're doing it now. 68 00:03:20,040 --> 00:03:24,480 Speaker 3: We've got ninety percent of our video edge devices cameras 69 00:03:24,480 --> 00:03:28,480 Speaker 3: that are powered by AI. We do video security and 70 00:03:28,639 --> 00:03:33,760 Speaker 3: access control. We have a big business of one software 71 00:03:33,840 --> 00:03:36,840 Speaker 3: nine one one command center. There's about six thousand of 72 00:03:36,840 --> 00:03:40,640 Speaker 3: those around the country. In sixty percent of the cases 73 00:03:41,040 --> 00:03:45,120 Speaker 3: they have our software. We use AI for perimeter detection, 74 00:03:45,320 --> 00:03:51,000 Speaker 3: anomaly detection, license plate recognition. If you reduce a nine 75 00:03:51,040 --> 00:03:54,000 Speaker 3: to one one call by sixty seconds, you save ten 76 00:03:54,040 --> 00:03:58,080 Speaker 3: thousand lives. We're using AI right now in nine one 77 00:03:58,160 --> 00:04:03,120 Speaker 3: one called translation, one one called transcription, and something we 78 00:04:03,160 --> 00:04:06,800 Speaker 3: call call assist where AI populates. 79 00:04:06,320 --> 00:04:07,360 Speaker 1: The dispatcher's screen. 80 00:04:08,040 --> 00:04:13,120 Speaker 3: Dispatcher can then mobilize the first responder police officer quicker, 81 00:04:13,440 --> 00:04:15,240 Speaker 3: so we'll be on the scene even faster. 82 00:04:15,760 --> 00:04:19,599 Speaker 1: And we're just beginning to use it internally. 83 00:04:19,440 --> 00:04:24,839 Speaker 3: Around a copilot for engineering and software development, documentation, sales 84 00:04:24,839 --> 00:04:28,400 Speaker 3: and services. So I think we've been prudent and measured 85 00:04:28,520 --> 00:04:32,120 Speaker 3: a little conservative in the deployment of AI. But we 86 00:04:32,200 --> 00:04:34,200 Speaker 3: have a great story of anything I, and we need 87 00:04:34,240 --> 00:04:34,960 Speaker 3: to tell it better. 88 00:04:35,440 --> 00:04:37,200 Speaker 4: But I think you've been doing a pretty good job 89 00:04:37,200 --> 00:04:39,760 Speaker 4: telling him. I'm I'm looking at the screen here at 90 00:04:39,800 --> 00:04:42,839 Speaker 4: the comp chart on the Bloomberg, and you've tripled the 91 00:04:42,839 --> 00:04:45,400 Speaker 4: performance of the s and p throughout your tenure. 92 00:04:45,480 --> 00:04:46,760 Speaker 1: So your communications are. 93 00:04:46,680 --> 00:04:48,400 Speaker 2: Spot on, but you used to come back more often. 94 00:04:48,440 --> 00:04:53,880 Speaker 4: What do you make though of the potential tariffs coming 95 00:04:54,040 --> 00:04:57,320 Speaker 4: in the next Trump administration? Is that going to be 96 00:04:57,360 --> 00:04:59,440 Speaker 4: a difficult thing for Motorala solutions? 97 00:04:59,440 --> 00:05:00,919 Speaker 1: I don't think. And here's why. 98 00:05:01,440 --> 00:05:05,320 Speaker 3: So Trump implemented tariffs on China starting in his first administration. 99 00:05:05,760 --> 00:05:09,200 Speaker 3: What did Biden do? He continued them? So I know 100 00:05:09,279 --> 00:05:12,240 Speaker 3: the administration has talked about widespread tariffs. I see Howard 101 00:05:12,279 --> 00:05:14,359 Speaker 3: Lutnik just got the Commerce secretary. 102 00:05:14,360 --> 00:05:15,360 Speaker 1: By the way, I like Howard. 103 00:05:15,800 --> 00:05:17,800 Speaker 3: I think he's a smart guy. He's created a lot 104 00:05:17,839 --> 00:05:20,880 Speaker 3: of value at Canner Fitzgerald. I think he will be 105 00:05:20,920 --> 00:05:26,800 Speaker 3: progressive and aggressive, So we'll see. I think the administration 106 00:05:26,880 --> 00:05:31,000 Speaker 3: has talked about tariffs in terms of full and fair trade. 107 00:05:31,680 --> 00:05:33,120 Speaker 1: Free trade, but fair trade. 108 00:05:33,640 --> 00:05:37,159 Speaker 3: Maybe tariffs are used for reciprocal fairness. 109 00:05:37,600 --> 00:05:41,480 Speaker 1: I'm good with that if they're deployed. So the other 110 00:05:41,640 --> 00:05:42,839 Speaker 1: problem if you're a US. 111 00:05:42,760 --> 00:05:47,359 Speaker 3: Company, maybe if tariffs are heavy, what about your input costs? 112 00:05:47,440 --> 00:05:50,320 Speaker 3: And can you pass them on with pricing. We have 113 00:05:50,440 --> 00:05:54,560 Speaker 3: gotten out of China effectively. We sued Chinese two Chinese companies. 114 00:05:54,560 --> 00:05:58,279 Speaker 3: We're the only American company to do that. Huawei initially 115 00:05:58,320 --> 00:06:01,080 Speaker 3: we settled. We're in our seventh year of litigation with 116 00:06:01,200 --> 00:06:06,880 Speaker 3: Hyterra that stole trade secrets, source code, patent infringement, and 117 00:06:07,000 --> 00:06:09,120 Speaker 3: therefore we've re architected supply chain. 118 00:06:09,480 --> 00:06:10,960 Speaker 1: We've done more dual sourcing. 119 00:06:11,400 --> 00:06:14,880 Speaker 3: So, irrespective of what the tariff landscape is, I believe 120 00:06:15,000 --> 00:06:18,800 Speaker 3: MSI can navigate it. But I think the administration coming 121 00:06:18,800 --> 00:06:22,840 Speaker 3: in has a lot of creative, disruptive and aggressive thoughts 122 00:06:23,000 --> 00:06:24,080 Speaker 3: and we'll see how it plays out. 123 00:06:24,080 --> 00:06:24,479 Speaker 1: Flip it. 124 00:06:24,760 --> 00:06:27,159 Speaker 2: Does a Trump administration mean more business and more end 125 00:06:27,240 --> 00:06:28,000 Speaker 2: user demand for you? 126 00:06:28,240 --> 00:06:31,400 Speaker 3: I think the Trump administration is favorable in that he's 127 00:06:31,440 --> 00:06:36,120 Speaker 3: been very strident and supportive of police. He believes big 128 00:06:36,160 --> 00:06:39,119 Speaker 3: city crime ought to be reduced. He believes we should 129 00:06:39,120 --> 00:06:41,760 Speaker 3: secure the border and build the wall. The wall's not 130 00:06:41,839 --> 00:06:45,760 Speaker 3: just physical, it's digital, it's more border control agents. 131 00:06:46,240 --> 00:06:47,039 Speaker 1: That's favorable. 132 00:06:47,279 --> 00:06:50,120 Speaker 3: We've got predictability in the corporate tax rate. Maybe we 133 00:06:50,160 --> 00:06:52,640 Speaker 3: get codification and certainty in the R and D tax rate. 134 00:06:53,080 --> 00:06:54,960 Speaker 3: And I believe the M and A environment and a 135 00:06:55,000 --> 00:06:59,320 Speaker 3: Trump administration should be more favorable than the current administration. 136 00:06:59,480 --> 00:07:01,200 Speaker 1: So I think there's a lot to. 137 00:07:01,279 --> 00:07:04,160 Speaker 3: Like about this administration through the lens of running a 138 00:07:04,279 --> 00:07:05,200 Speaker 3: US multinational. 139 00:07:05,800 --> 00:07:07,640 Speaker 1: Greg. Great to have you here in the studio. Thanks 140 00:07:07,640 --> 00:07:10,960 Speaker 1: for having me. Next time you come by join me at. 141 00:07:10,920 --> 00:07:14,560 Speaker 2: Nine am early or that's early, come at three. 142 00:07:16,080 --> 00:07:18,880 Speaker 4: Greg Brown is the CEO and chairman of Motorola Solutions