1 00:00:02,520 --> 00:00:08,440 Speaker 1: Bloomberg Audio Studios, podcasts, radio news. Well, Cisco announced today 2 00:00:08,440 --> 00:00:11,920 Speaker 1: that it completed its twenty eight billion dollar acquisition of Splunk, 3 00:00:12,200 --> 00:00:14,800 Speaker 1: and its biggest deal ever. Now, these two software companies, 4 00:00:14,840 --> 00:00:18,400 Speaker 1: they're joining forces to power, protect, and advance the AI 5 00:00:18,480 --> 00:00:21,160 Speaker 1: revolution for their customers. And please to say that joining 6 00:00:21,160 --> 00:00:23,920 Speaker 1: me now we have Cisco CEO Chuck Robbins as well 7 00:00:23,920 --> 00:00:27,560 Speaker 1: as former Splunk CEO Gary steel Ian studio with me. 8 00:00:27,600 --> 00:00:28,400 Speaker 1: Great to see you both. 9 00:00:28,440 --> 00:00:29,640 Speaker 2: It's good to be here, here to be here. 10 00:00:29,720 --> 00:00:32,760 Speaker 1: So number one, congratulations. Number two, let's talk about the 11 00:00:32,800 --> 00:00:36,600 Speaker 1: timeline here because this deal, it was only announced in September, 12 00:00:36,640 --> 00:00:40,000 Speaker 1: and you think about the appetite for these deals coming 13 00:00:40,040 --> 00:00:43,080 Speaker 1: through and then getting blocked. How were you able to 14 00:00:43,360 --> 00:00:44,880 Speaker 1: secure approval so quickly? 15 00:00:45,040 --> 00:00:50,959 Speaker 2: It was primarily Gary's charm. I think, look hats off 16 00:00:50,960 --> 00:00:53,000 Speaker 2: to our legal teams, who I think did an amazing 17 00:00:53,080 --> 00:00:57,040 Speaker 2: job just providing clarity. I think it's also reflective of 18 00:00:57,120 --> 00:00:59,080 Speaker 2: the fact that we didn't have a lot of overlap 19 00:00:59,120 --> 00:01:03,160 Speaker 2: in the in the portfolios. I think two other things are. 20 00:01:03,240 --> 00:01:06,240 Speaker 2: Number One, I think there's a general understanding we actually helped. 21 00:01:06,360 --> 00:01:08,360 Speaker 2: We tried to help the regulars understand that from a 22 00:01:08,360 --> 00:01:10,560 Speaker 2: cyber perspective, which is super important. This is going to 23 00:01:10,560 --> 00:01:13,319 Speaker 2: be good for customers, and I think it also speaks 24 00:01:13,360 --> 00:01:16,800 Speaker 2: to the reputation that both companies have and with governments 25 00:01:16,840 --> 00:01:18,600 Speaker 2: around the world. Anything you'd add to. 26 00:01:18,640 --> 00:01:20,560 Speaker 3: That, No, I think that sums it up well. 27 00:01:20,600 --> 00:01:24,600 Speaker 1: Gary, since you were the charming one is according to Chuck, 28 00:01:24,920 --> 00:01:26,960 Speaker 1: I mean, do you think that the signals that maybe 29 00:01:27,000 --> 00:01:29,679 Speaker 1: scrutiny is lessening a little bit or was this really 30 00:01:29,720 --> 00:01:32,200 Speaker 1: about specific factors related to this deal. 31 00:01:32,880 --> 00:01:35,280 Speaker 3: I think it really was related to the specific factors 32 00:01:35,280 --> 00:01:38,320 Speaker 3: on this deal. I think, as Jeck described, there really 33 00:01:38,480 --> 00:01:41,600 Speaker 3: was no product overlap, and collectively we can do a 34 00:01:41,600 --> 00:01:44,680 Speaker 3: lot for customers from a cyber perspective, and so I 35 00:01:44,720 --> 00:01:46,800 Speaker 3: think there is a good agreement on that. 36 00:01:47,400 --> 00:01:49,120 Speaker 1: And I want to talk a little bit about your 37 00:01:49,120 --> 00:01:52,640 Speaker 1: timeline specifically, because you were named the Splunk CEO in 38 00:01:52,680 --> 00:01:55,800 Speaker 1: March twenty twenty two, you took over in April twenty 39 00:01:55,840 --> 00:01:58,840 Speaker 1: twenty two. How long into the job did you and 40 00:01:58,920 --> 00:02:00,400 Speaker 1: Chuck start talking of it? 41 00:02:00,960 --> 00:02:04,640 Speaker 3: So, Chuck and I first met at Davos in a 42 00:02:04,720 --> 00:02:07,600 Speaker 3: year ago, and that was our first time that we 43 00:02:07,600 --> 00:02:10,200 Speaker 3: had had the opportunity to meet. And I had prior 44 00:02:10,639 --> 00:02:15,600 Speaker 3: to that worked with the CFO Cisco, Scott Heron, and 45 00:02:15,639 --> 00:02:17,320 Speaker 3: so we had a prior relationship. He was on my 46 00:02:17,400 --> 00:02:20,880 Speaker 3: board at an earlier company. So there were some good things. 47 00:02:20,919 --> 00:02:24,040 Speaker 3: But it took a while, but the conversations went well. 48 00:02:24,120 --> 00:02:26,040 Speaker 3: We took it slow. We were very thoughtful about the 49 00:02:26,080 --> 00:02:28,960 Speaker 3: process and from my perspective on make sure I was 50 00:02:28,960 --> 00:02:30,239 Speaker 3: doing the right thing for our shareholders. 51 00:02:30,440 --> 00:02:32,840 Speaker 1: And we're going to get into integration and of course 52 00:02:32,880 --> 00:02:34,560 Speaker 1: product fit here. But I want to talk a little 53 00:02:34,600 --> 00:02:37,560 Speaker 1: bit more about Splunk because it had long been rumored 54 00:02:37,600 --> 00:02:40,080 Speaker 1: as a takeover target. You had the likes of Starboard, 55 00:02:40,440 --> 00:02:43,480 Speaker 1: Helman and Friedman taking stakes in the company. Did you 56 00:02:43,760 --> 00:02:46,400 Speaker 1: entertain any other bids in addition to, of course what 57 00:02:46,400 --> 00:02:47,240 Speaker 1: you got from Cisco. 58 00:02:48,000 --> 00:02:49,760 Speaker 3: So if you go back and look at our proxy 59 00:02:49,800 --> 00:02:52,720 Speaker 3: that we filed, Cisco was really the only party that 60 00:02:52,760 --> 00:02:55,639 Speaker 3: we were talking to at the time. But I would 61 00:02:55,639 --> 00:02:59,239 Speaker 3: say we had incredible support from our board members that 62 00:02:59,280 --> 00:03:01,880 Speaker 3: were private equity firms. About simmer Lake and Helman and 63 00:03:01,919 --> 00:03:06,320 Speaker 3: Freemen and Starbud was always a very subpartive relationship. 64 00:03:06,720 --> 00:03:09,280 Speaker 1: And let's talk a little bit more about this marriage. 65 00:03:09,320 --> 00:03:12,240 Speaker 1: Of course, Garrett, or rather Chuck, where do you see 66 00:03:12,320 --> 00:03:14,880 Speaker 1: splank really fitting in with the product and also the 67 00:03:14,919 --> 00:03:16,040 Speaker 1: financial strategy. 68 00:03:16,600 --> 00:03:18,280 Speaker 2: Yeah, I think there's two big areas that we have. 69 00:03:18,320 --> 00:03:23,800 Speaker 2: There's an emerging area called observability, which is effectively trying 70 00:03:23,840 --> 00:03:29,200 Speaker 2: to help our customers understand application performance, what's going on 71 00:03:29,240 --> 00:03:33,000 Speaker 2: in their technology infrastructure, particularly in this world where you 72 00:03:33,080 --> 00:03:37,960 Speaker 2: have hybrid cloud, multi cloud, private cloud SaaS and so 73 00:03:38,600 --> 00:03:40,680 Speaker 2: that's one big area. And then the other big area 74 00:03:40,680 --> 00:03:45,400 Speaker 2: of cybersecurity. If you think about the utilization of AI 75 00:03:45,920 --> 00:03:49,080 Speaker 2: by the bad actors, we're going to have to do 76 00:03:49,120 --> 00:03:52,400 Speaker 2: a better job of doing real time analytics and real 77 00:03:52,440 --> 00:03:55,520 Speaker 2: time detection and response. And in my view, we have 78 00:03:55,600 --> 00:03:58,000 Speaker 2: to be able to take three or four different things 79 00:03:58,000 --> 00:04:00,400 Speaker 2: that we're seeing happening at the same time, and those 80 00:04:00,440 --> 00:04:03,240 Speaker 2: three or four independently might not indicate a problem, but 81 00:04:03,320 --> 00:04:07,280 Speaker 2: together there's a problem. And their data platform. With our 82 00:04:07,320 --> 00:04:10,360 Speaker 2: detection response capabilities and all of our endpoints and all 83 00:04:10,360 --> 00:04:12,480 Speaker 2: of the sources of threat intelligence, so we have in 84 00:04:12,800 --> 00:04:15,800 Speaker 2: our massive amount of intel that we see on a 85 00:04:15,880 --> 00:04:19,159 Speaker 2: daily basis, we think brings our customers the ability to 86 00:04:19,160 --> 00:04:20,479 Speaker 2: actually do that in real time. 87 00:04:20,960 --> 00:04:22,680 Speaker 1: And of course when you talk to the cell side, 88 00:04:22,680 --> 00:04:24,919 Speaker 1: there's also this narrative out there that you're trying to 89 00:04:24,960 --> 00:04:28,280 Speaker 1: remake Cisco as a provider of networking services and really 90 00:04:28,279 --> 00:04:31,919 Speaker 1: trying to lessen your reliance on one time sales of equipment. 91 00:04:32,000 --> 00:04:34,240 Speaker 1: How do you see this deal as really pushing that 92 00:04:34,279 --> 00:04:35,000 Speaker 1: effort forward. 93 00:04:35,279 --> 00:04:40,120 Speaker 2: Well, that's an accurate narrative. So we have been moving 94 00:04:40,120 --> 00:04:43,080 Speaker 2: into more software. So I think the three metrics I 95 00:04:43,080 --> 00:04:45,800 Speaker 2: would share is at last quarter we hit a milestone 96 00:04:45,800 --> 00:04:47,200 Speaker 2: that we had set to try to get to fifty 97 00:04:47,240 --> 00:04:49,440 Speaker 2: percent of our revenue coming from recurring revenue, and we 98 00:04:49,480 --> 00:04:51,880 Speaker 2: did that last quarter, which is a big move from 99 00:04:51,880 --> 00:04:55,000 Speaker 2: eight years ago. The other thing is combined Gary and 100 00:04:55,000 --> 00:04:57,839 Speaker 2: the team bring four point two billion of ar ruin 101 00:04:57,880 --> 00:04:58,440 Speaker 2: in mid. 102 00:04:58,279 --> 00:05:00,400 Speaker 3: Teams, fifteen percent out of the CLIB at the end 103 00:05:00,400 --> 00:05:01,000 Speaker 3: of the year. 104 00:05:00,880 --> 00:05:05,520 Speaker 2: And combined we have arr now of almost twenty nine billion, 105 00:05:06,960 --> 00:05:10,600 Speaker 2: and we're over twenty billion from just software sales in 106 00:05:10,680 --> 00:05:14,000 Speaker 2: the company now, which is when we add Splunk software 107 00:05:14,040 --> 00:05:15,400 Speaker 2: sales to it. So I think we've made a lot 108 00:05:15,440 --> 00:05:17,680 Speaker 2: of progress and we're going to continue marching down that path. 109 00:05:17,800 --> 00:05:20,599 Speaker 1: Well as this integration goes forward. Of course, both of 110 00:05:20,640 --> 00:05:23,839 Speaker 1: your companies have announced layoffs in the recent months. As 111 00:05:23,880 --> 00:05:26,640 Speaker 1: you integrate these two, would you expect to be there 112 00:05:26,680 --> 00:05:28,960 Speaker 1: to be further headcount reductions. 113 00:05:29,360 --> 00:05:31,120 Speaker 2: I'll come at first, and then Gary can add on it. 114 00:05:31,480 --> 00:05:34,520 Speaker 2: This steal was not predicated on cost synergies at all. 115 00:05:35,120 --> 00:05:37,400 Speaker 2: It was built on revenue synergy. So it was built 116 00:05:37,440 --> 00:05:39,640 Speaker 2: on the integration that we talked about and the new 117 00:05:39,680 --> 00:05:42,960 Speaker 2: capabilities that we can bring to our customers. So that 118 00:05:43,000 --> 00:05:45,320 Speaker 2: was never part of our plan as we were putting 119 00:05:45,360 --> 00:05:46,440 Speaker 2: the integration plan together. 120 00:05:47,600 --> 00:05:50,080 Speaker 1: And of course you had mentioned, Chuck that when it 121 00:05:50,120 --> 00:05:53,719 Speaker 1: comes to AI, there's a concern and uptick and that 122 00:05:53,839 --> 00:05:56,520 Speaker 1: being harnessed by bad actors. And Gary, I'm curious what 123 00:05:56,560 --> 00:05:59,240 Speaker 1: you're seeing in your data when it comes to these 124 00:05:59,279 --> 00:06:01,160 Speaker 1: aiyer security attacks. 125 00:06:01,279 --> 00:06:05,640 Speaker 3: You've just seen more sophisticated attacks, whether they're specifically targeted attacks, 126 00:06:05,640 --> 00:06:10,840 Speaker 3: phishing attacks. We're just seeing more sophistication and a new 127 00:06:10,880 --> 00:06:14,880 Speaker 3: set of tools that bad actors can drive more and 128 00:06:14,960 --> 00:06:18,000 Speaker 3: more sophisticated attacks. And we feel very good about coming 129 00:06:18,000 --> 00:06:20,680 Speaker 3: together and the work that we can do collectively driving 130 00:06:20,720 --> 00:06:23,320 Speaker 3: great outcomes through the use of AI to ensure that 131 00:06:23,440 --> 00:06:25,120 Speaker 3: our enterprise customers are well protected. 132 00:06:25,560 --> 00:06:29,000 Speaker 2: If I could add real quickly, we have an organization 133 00:06:29,040 --> 00:06:31,719 Speaker 2: called Tellos that sees about twenty billion threats a day, 134 00:06:32,640 --> 00:06:34,640 Speaker 2: and so one of the things that we believe we 135 00:06:34,680 --> 00:06:38,160 Speaker 2: can do is take that all of that intelligence and 136 00:06:38,320 --> 00:06:41,560 Speaker 2: inject it into the data platform that they provide customers 137 00:06:41,600 --> 00:06:43,680 Speaker 2: and give them a whole new level of real time 138 00:06:43,760 --> 00:06:46,520 Speaker 2: visibility that they've never had before. So it's pretty exciting, 139 00:06:46,839 --> 00:06:47,080 Speaker 2: and of. 140 00:06:47,040 --> 00:06:49,680 Speaker 1: Course, in the press release this morning, this line caught 141 00:06:49,720 --> 00:06:52,320 Speaker 1: my eye that over the next several months, customers can 142 00:06:52,360 --> 00:06:55,880 Speaker 1: expect a number of new product innovations across the portfolio 143 00:06:56,160 --> 00:06:58,920 Speaker 1: with the integration of splun Could you give us some 144 00:06:58,960 --> 00:07:00,720 Speaker 1: color on what those product look like. 145 00:07:01,080 --> 00:07:03,760 Speaker 3: You know, we're early in our process, but we've identified 146 00:07:03,800 --> 00:07:06,799 Speaker 3: some great opportunities where we can bring the technologies together 147 00:07:07,279 --> 00:07:10,200 Speaker 3: to drive amazing outcomes for customers. So we will be 148 00:07:10,200 --> 00:07:12,640 Speaker 3: announcing a set of things over the coming months, So 149 00:07:12,720 --> 00:07:14,080 Speaker 3: stay tuned, Stay tuned. 150 00:07:15,000 --> 00:07:17,040 Speaker 1: I hope to talk to you guys about that when 151 00:07:17,040 --> 00:07:19,720 Speaker 1: they are announced. But let's talk a little bit about 152 00:07:19,720 --> 00:07:22,440 Speaker 1: the price tag and just how large this acquisition is 153 00:07:22,520 --> 00:07:27,200 Speaker 1: twenty eight billion dollars out of Cisco's largest acquisition ever. 154 00:07:27,280 --> 00:07:30,040 Speaker 1: And when it comes to acquisitions of these scales, they 155 00:07:30,080 --> 00:07:32,720 Speaker 1: tend to have a pretty low success rate. If you 156 00:07:32,720 --> 00:07:35,559 Speaker 1: look at some of the data how to minimize that risk. 157 00:07:36,280 --> 00:07:40,000 Speaker 2: Yeah, I think a couple things. Gary has been deeply 158 00:07:40,040 --> 00:07:43,120 Speaker 2: involved in the whole integration planning. I think that if 159 00:07:43,160 --> 00:07:44,880 Speaker 2: you go back and look even in your proxy, we 160 00:07:45,000 --> 00:07:47,000 Speaker 2: talked about the fact that we had an early conversation 161 00:07:47,120 --> 00:07:50,920 Speaker 2: in January February of twenty two before Gary came on board, 162 00:07:51,200 --> 00:07:54,000 Speaker 2: and then the progress that he's made with this company 163 00:07:55,120 --> 00:07:57,440 Speaker 2: and the detail planning that we did. We had our 164 00:07:57,640 --> 00:08:01,800 Speaker 2: entire engineering leadership team involved in making the decision, and 165 00:08:01,880 --> 00:08:04,880 Speaker 2: every single person felt like this was the right thing 166 00:08:04,920 --> 00:08:07,440 Speaker 2: to do. And then when you look at the financials, 167 00:08:08,320 --> 00:08:11,320 Speaker 2: I just think they were underappreciated because of what he 168 00:08:11,360 --> 00:08:14,360 Speaker 2: was doing at the time. And when you're picking up 169 00:08:14,400 --> 00:08:18,160 Speaker 2: four point four and some change billion in revenue, growing 170 00:08:18,200 --> 00:08:21,680 Speaker 2: mid teams and at seven x revenue multiple and they're 171 00:08:21,920 --> 00:08:25,080 Speaker 2: we're going to be cash flow accreative in year one, 172 00:08:26,200 --> 00:08:27,760 Speaker 2: it's I think it's a pretty good deal. 173 00:08:28,080 --> 00:08:30,360 Speaker 3: Yeah, And I feel really good about the opportunity to 174 00:08:30,360 --> 00:08:33,199 Speaker 3: come together. The cultures are really similar, the teams really 175 00:08:33,280 --> 00:08:36,559 Speaker 3: enjoy working well together, and we found so much low 176 00:08:36,600 --> 00:08:38,400 Speaker 3: hanging for it where we can go deliver great value 177 00:08:38,400 --> 00:08:41,560 Speaker 3: to customers coming together and usually it's about momentum that 178 00:08:41,640 --> 00:08:44,920 Speaker 3: makes deals work, and I feel incredibly good about how 179 00:08:44,960 --> 00:08:46,120 Speaker 3: we've come together thus far. 180 00:08:46,679 --> 00:08:50,160 Speaker 2: And there's a lot of ex Cisco people had Splunk, 181 00:08:50,320 --> 00:08:53,360 Speaker 2: so they know the culture and we're going to work 182 00:08:53,400 --> 00:08:55,280 Speaker 2: really hard to make sure that it's a place that 183 00:08:55,280 --> 00:08:57,880 Speaker 2: they want to stay, and we're working to retain that talent. 184 00:08:58,200 --> 00:09:00,520 Speaker 1: Well, gentlemen, that sounds like a great place, saliv I 185 00:09:00,600 --> 00:09:03,480 Speaker 1: really enjoyed this conversation. Thank you so much, of course. 186 00:09:03,640 --> 00:09:07,760 Speaker 1: Tacisco CEO Chuck Robbins and former Spunk CEO Gary Steel