1 00:00:00,000 --> 00:00:03,360 Welcome to another episode of the Cloud Native in 15 Minutes podcast. 2 00:00:04,040 --> 00:00:08,320 The goal of this podcast is simple, to explain some complex but increasingly important and 3 00:00:08,320 --> 00:00:12,620 even strategic technologies in about the time it takes for a coffee break or a short commute 4 00:00:12,620 --> 00:00:16,440 or whatever it is you do in 15, 20, or in this case, maybe closer to 30 minutes. 5 00:00:17,160 --> 00:00:20,740 So because this episode runs a little longer than the 15 minutes in the title, I'm going 6 00:00:20,740 --> 00:00:21,160 to be brief. 7 00:00:21,780 --> 00:00:27,020 I'm Derek Harris from Pivotal, and the topic today is how to engage with enterprise startups. 8 00:00:27,340 --> 00:00:31,300 So if you're a large organization thinking, hey, I would like to buy software from the 9 00:00:31,300 --> 00:00:35,100 startup, or I'm thinking about buying software from the startup versus my legacy vendor, or 10 00:00:35,100 --> 00:00:39,560 maybe buying this cloud service from a startup, my guests today are going to give you some 11 00:00:39,560 --> 00:00:41,080 advice on how to go about doing that. 12 00:00:41,280 --> 00:00:47,300 And they are Jonathan Lair and Jessica Lin, the co-founders and general partners of an enterprise 13 00:00:47,300 --> 00:00:50,300 startup-based venture capital firm called Workbench. 14 00:00:51,000 --> 00:00:57,240 Also, if you are listening to this podcast on Apple and could be so inclined to leave a 15 00:00:57,240 --> 00:00:58,860 review, that would be very helpful. 16 00:00:59,440 --> 00:01:00,140 We enjoy them. 17 00:01:00,260 --> 00:01:05,380 Without further ado, please listen to John and Jessica from Workbench talking about engaging 18 00:01:05,380 --> 00:01:06,400 with enterprise startups. 19 00:01:07,440 --> 00:01:13,680 Okay, so John and Jessica, can you guys quick give listeners a brief description of what 20 00:01:13,680 --> 00:01:17,280 Workbench does and then, you know, like your quick 30-second personal history so people 21 00:01:17,280 --> 00:01:18,760 have a sense of where you're coming from? 22 00:01:19,380 --> 00:01:19,920 For sure. 23 00:01:20,080 --> 00:01:22,020 Happy to kick off, and thanks for having us. 24 00:01:22,380 --> 00:01:24,740 So Workbench is an enterprise VC fund. 25 00:01:25,140 --> 00:01:28,560 Our team is fully based in New York City, but we do invest across the country. 26 00:01:29,060 --> 00:01:33,760 And our mission is to rethink enterprise investment by leveraging our past lives in corporate IT 27 00:01:33,760 --> 00:01:37,880 and the 52 of the Force 500 that are fully headquartered here in New York City. 28 00:01:38,480 --> 00:01:40,800 So just by way of quick background, this is John speaking. 29 00:01:41,000 --> 00:01:45,000 And I used to work in IT at Morgan Stanley in a pretty cool team. 30 00:01:45,140 --> 00:01:47,340 It was called the Office of the CIO. 31 00:01:47,880 --> 00:01:53,000 And what we were tasked with doing was really helping figure out how to best use our $4 billion 32 00:01:53,000 --> 00:01:55,900 IT budget and engage the startup community. 33 00:01:56,120 --> 00:02:02,260 And that could be through identifying new revenue opportunities, cost efficiencies, or just net 34 00:02:02,260 --> 00:02:05,500 new capabilities that working with the startup community could bring us. 35 00:02:05,500 --> 00:02:11,000 So on a daily basis, we would meet hundreds of startups a year, all the big name VCs, all 36 00:02:11,000 --> 00:02:17,140 with that goal of figuring out who has technology that isn't just with bank tech, but also aligns 37 00:02:17,140 --> 00:02:18,280 to a pain point internally. 38 00:02:18,880 --> 00:02:20,180 And this is Jessica here. 39 00:02:20,580 --> 00:02:28,000 So prior to co-founding Workbench with John, was at Cisco Systems, working on an internal team 40 00:02:28,000 --> 00:02:29,620 on agile software transformation. 41 00:02:29,820 --> 00:02:36,480 So got to work with some of the high performing teams at Cisco and document those best practices 42 00:02:36,480 --> 00:02:39,340 on agile software transformation. 43 00:02:40,240 --> 00:02:46,280 And prior to that, worked with student startups at Harvard University and led a design fellowship 44 00:02:46,280 --> 00:02:49,580 program for students in Cape Town, South Africa. 45 00:02:50,300 --> 00:02:56,140 And so, so much of what we talk about at Workbench is really being at the intersection of what 46 00:02:56,140 --> 00:02:57,760 we call suits and hoodies. 47 00:02:58,200 --> 00:03:01,220 And that's really core to the DNA of our VC fund. 48 00:03:01,700 --> 00:03:02,080 All right, cool. 49 00:03:02,220 --> 00:03:03,720 So, yeah, so let's get into it. 50 00:03:03,880 --> 00:03:08,180 I think, I think as someone who's spent time working inside startups, the one thing I've noticed 51 00:03:08,180 --> 00:03:12,420 is like, does that enterprise customers are kind of the holy grail, you know, the bigger, the, 52 00:03:12,740 --> 00:03:16,600 the bigger the customer, the, the more validation, the more, you know, the more marketing 53 00:03:16,600 --> 00:03:18,780 you can do around it, all these different things. 54 00:03:18,780 --> 00:03:23,860 But if we, if we, if we turn the tables and we say, you know, like, so, so that's, but 55 00:03:23,860 --> 00:03:28,380 and there's, I think a lot of advice on how startups think about engaging with enterprises. 56 00:03:28,680 --> 00:03:32,100 But what I want to talk about here, and I would love to get your opinions on this, you know, 57 00:03:32,540 --> 00:03:36,160 like just from the, at a high level, I mean, if you're, if I'm an enterprise thinking of 58 00:03:36,160 --> 00:03:41,260 buying technology from a startup or engaging with the startup, how do I, you know, how do 59 00:03:41,260 --> 00:03:42,940 I begin thinking about that, right? 60 00:03:42,940 --> 00:03:47,240 What should be on my radar in terms of ways to get that process started? 61 00:03:47,340 --> 00:03:48,100 For sure. 62 00:03:48,280 --> 00:03:53,100 So when we think about the corporate community that we actually wrote a post a few months ago 63 00:03:53,100 --> 00:03:56,280 called Dear Enterprise Startups, Not All Customer Intros Are Equal. 64 00:03:56,840 --> 00:04:02,120 And what we try to do is actually break down the sophistication levels between someone like 65 00:04:02,120 --> 00:04:05,740 a Wall Street bank, who tends to be really at the high end of the spectrum. 66 00:04:06,080 --> 00:04:10,860 And then as you go down, there's regional banks and insurance companies go down further. 67 00:04:11,000 --> 00:04:15,540 You've got healthcare, pharma, and the media space, which do have pretty sophisticated processes 68 00:04:15,540 --> 00:04:16,980 of working with the startup community. 69 00:04:17,340 --> 00:04:23,000 And then if we go down even further on the list, things like telco, retail, manufacturing, 70 00:04:23,000 --> 00:04:29,120 those tend to have the least sophistication and a very difficult time actually engaging with 71 00:04:29,120 --> 00:04:30,160 the startup communities. 72 00:04:30,600 --> 00:04:35,220 So let's maybe start with some of the best practices that you have seen from companies 73 00:04:35,220 --> 00:04:37,740 that actually do are good at engaging with startups. 74 00:04:38,100 --> 00:04:43,480 So if I think back even to my personal experience at Morgan Stanley, as I mentioned, we had a 75 00:04:43,480 --> 00:04:46,080 team dedicated to this search and scout function. 76 00:04:46,640 --> 00:04:51,840 But in fairness, a lot of the Fortune 500 can't afford such a team and they aren't going 77 00:04:51,840 --> 00:04:52,980 to engage as frequently. 78 00:04:53,320 --> 00:04:58,880 So as a best practice, just even having a view of like, hey, what are some of our initiatives 79 00:04:58,880 --> 00:05:05,180 for the year and what are places where the existing large vendor landscape can actually meet those 80 00:05:05,180 --> 00:05:05,540 needs? 81 00:05:05,940 --> 00:05:10,040 And what is perhaps one or two key initiatives that we're going to look to do? 82 00:05:10,440 --> 00:05:14,300 So that could be something over the past couple of years of like, hey, we want to bring in 83 00:05:14,300 --> 00:05:15,760 a chatbot for customer success. 84 00:05:15,880 --> 00:05:20,580 Or we want to try, we have treasure troves of data and we want to try to do some sort of machine 85 00:05:20,580 --> 00:05:22,080 learning for better personalization. 86 00:05:22,340 --> 00:05:27,820 Or even something like, hey, we're getting tons of cyber attacks recently and we need to boost 87 00:05:27,820 --> 00:05:30,620 our internal kind of safety posture. 88 00:05:31,620 --> 00:05:36,460 And even just getting a sense of like, hey, the whole company is going to align around these 89 00:05:36,460 --> 00:05:40,220 goals and as a starting point actually makes a difference. 90 00:05:40,220 --> 00:05:45,260 Because where we've seen a lot of issues historically is different pockets of folks chasing after 91 00:05:45,260 --> 00:05:51,960 different companies that either inbound to them or they outreach to, but without a process and a 92 00:05:51,960 --> 00:05:58,180 desire and really a need to do so, at the best case, it leads to a quick no. 93 00:05:58,260 --> 00:06:02,460 But at the worst case, it could lead to a lot of wasted cycles, both for individuals at an 94 00:06:02,460 --> 00:06:04,340 organization as well as the startup itself. 95 00:06:04,660 --> 00:06:07,300 Are there things that these companies should think about too? 96 00:06:07,300 --> 00:06:13,140 I think the big fear sometimes is around product maturity or resources around support or 97 00:06:13,140 --> 00:06:13,480 commitment. 98 00:06:13,720 --> 00:06:19,760 I mean, like what is the expectation do you think that smart enterprises have as they go 99 00:06:19,760 --> 00:06:21,380 in and think about buying something from a startup? 100 00:06:22,060 --> 00:06:22,160 Yeah. 101 00:06:22,300 --> 00:06:26,380 So not to make this a total Morgan Stanley talk, but one of the ways that we viewed things 102 00:06:26,380 --> 00:06:32,440 internally was across really a couple of quadrants or four quadrants rather with these axes of 103 00:06:32,440 --> 00:06:36,000 number one is the risk of the startup itself. 104 00:06:36,200 --> 00:06:38,940 And number two is the risk of the service internally. 105 00:06:39,480 --> 00:06:43,940 So at the end of the day, most very early stage companies, series A and B, would be in that 106 00:06:43,940 --> 00:06:44,900 high risk category. 107 00:06:44,900 --> 00:06:51,760 But the key is, can you map that to a service or a use case internally where the hypothetical 108 00:06:51,760 --> 00:06:54,140 question of if they disappear Monday, what happens? 109 00:06:54,380 --> 00:06:55,280 You're actually okay. 110 00:06:55,780 --> 00:07:00,140 Because you'd be surprised how many times, even in, let's use an example of like the database 111 00:07:00,140 --> 00:07:00,760 world. 112 00:07:01,140 --> 00:07:05,660 Back in the day when we were looking at columnar databases and in-memory databases when they 113 00:07:05,660 --> 00:07:10,540 were kind of a new thing, we had a whole team that was set up cross-functionally with 114 00:07:10,540 --> 00:07:14,160 different expertise to meet with some of the leading startups at the time. 115 00:07:14,900 --> 00:07:16,980 And this was a big undertaking. 116 00:07:17,140 --> 00:07:22,100 So what we figured out was what are use cases, whether it was like a fixed income team or another 117 00:07:22,100 --> 00:07:26,700 small pocket of the firm where, look, we're not going to replace out IBM DB2 databases. 118 00:07:26,700 --> 00:07:28,600 We're not going to get rid of Oracle databases. 119 00:07:28,980 --> 00:07:30,960 They're not going away and no one's going to touch them. 120 00:07:31,200 --> 00:07:35,560 But for these net new capabilities, could we actually generate revenue if we brought in 121 00:07:35,560 --> 00:07:41,520 a new analytic database that could compress the data, enable cost savings, and frankly, 122 00:07:41,600 --> 00:07:42,960 just give us faster calculations? 123 00:07:43,760 --> 00:07:49,500 So part of it is really just as a starting point, figuring out where can you actually explore 124 00:07:49,500 --> 00:07:51,440 in a safe, so to speak, way? 125 00:07:51,800 --> 00:07:54,080 I mean, I think it makes a lot of sense, in fact, because you're right. 126 00:07:54,080 --> 00:07:59,860 I remember someone years ago who had a SaaS startup in the analytic space, and I remember 127 00:07:59,860 --> 00:08:04,600 the discussion being, hey, we're getting these big customers, but they want a code escrow 128 00:08:04,600 --> 00:08:06,640 or something, which was a thing. 129 00:08:06,740 --> 00:08:08,260 And they were like, well, this is a SaaS product. 130 00:08:08,480 --> 00:08:11,340 Like there's no, everything is tied so tightly together. 131 00:08:11,460 --> 00:08:14,340 It was a wholly new concept to them, right? 132 00:08:14,460 --> 00:08:15,800 And you know, you got to think like... 133 00:08:15,800 --> 00:08:20,900 The joke with that also is, because we used to sometimes have people ask that internal at 134 00:08:20,900 --> 00:08:22,700 Morgan, and it's like, hey, put it in Iron Mountain. 135 00:08:22,700 --> 00:08:27,000 And the joke is no one internally at Morgan could have ever actually supported that code 136 00:08:27,000 --> 00:08:27,300 base. 137 00:08:27,820 --> 00:08:32,840 And number two, that startup, a lot of times they didn't even go out of business, which 138 00:08:32,840 --> 00:08:33,640 was kind of the trigger. 139 00:08:33,820 --> 00:08:35,540 A lot of times you would have these zombie companies. 140 00:08:35,980 --> 00:08:39,640 So we kind of did away with that whole kind of notion of a code escrow for the most part. 141 00:08:40,120 --> 00:08:43,520 I guess the question back to you, John, do you think that's a litmus test, right? 142 00:08:43,580 --> 00:08:48,560 If a large enterprise is asking for a code escrow, do you think that's a litmus for how 143 00:08:48,560 --> 00:08:49,700 sophisticated they are? 144 00:08:49,700 --> 00:08:55,740 And is that a warning sign for some emerging startups like, hey, maybe this large customer 145 00:08:55,740 --> 00:08:57,840 is not great to work with? 146 00:08:58,800 --> 00:09:03,780 Yeah, that's a key point, I think, which is it has to start from the top, as we said, 147 00:09:03,820 --> 00:09:04,360 with these initiatives. 148 00:09:04,360 --> 00:09:09,940 But then there needs to be buying across legal, procurement, security, because the worst thing 149 00:09:09,940 --> 00:09:11,640 that we've seen is companies that are dying. 150 00:09:11,900 --> 00:09:16,220 And let's play off that chatbot example again, that say, hey, we have a use case, we want 151 00:09:16,220 --> 00:09:19,300 to share some data that's actually not sensitive, maybe it's support tickets. 152 00:09:20,100 --> 00:09:24,200 And then they get stuck where they'll start engaging the startup community, they've gathered 153 00:09:24,200 --> 00:09:29,180 their requirements, and they'll meet with these companies and throw a 50-page kind of POC 154 00:09:29,180 --> 00:09:30,040 agreement in front of them. 155 00:09:30,260 --> 00:09:35,360 Or they'll put crazy, onerous security architecture reviews, or things, as Jess is saying, like 156 00:09:35,360 --> 00:09:36,080 this code escrow. 157 00:09:36,080 --> 00:09:41,540 So one of the things that companies could do best is actually learn from some of these 158 00:09:41,540 --> 00:09:46,160 earlier adopters and more sophisticated buyers around, what does procurement look like? 159 00:09:46,300 --> 00:09:51,940 Can we meet internally with our legal teams and come up with a way abridged version of an 160 00:09:51,940 --> 00:09:56,600 early test and then ultimately support contract for this particular use case? 161 00:09:56,860 --> 00:10:01,180 And if you're buying from IBM, of course, that procurement cycle is made for them, right? 162 00:10:01,240 --> 00:10:04,480 But if you're an emerging startup, that's not going to be the best fit. 163 00:10:04,480 --> 00:10:08,560 And that's where, quite frankly, we spend all of our time at Workbench, is coaching our startups 164 00:10:08,560 --> 00:10:13,200 to say, hey, what is actually non-negotiable in a procurement, but what are other things 165 00:10:13,200 --> 00:10:17,660 that, quite frankly, you need to give in on, whether it's an MSA or warranty of the product 166 00:10:17,660 --> 00:10:19,180 or indemnification, right? 167 00:10:19,200 --> 00:10:20,160 There's a lot of education. 168 00:10:20,340 --> 00:10:25,540 I think an opportunity for both the suit and the hoodie to meet in the middle in order 169 00:10:25,540 --> 00:10:29,360 to be able to accelerate the procurement process. 170 00:10:29,360 --> 00:10:31,320 You mentioned this chatbot option, right? 171 00:10:31,360 --> 00:10:36,920 And the chatbot seems like a, you know, generally speaking, a low risk sort of place to engage. 172 00:10:37,000 --> 00:10:40,520 Are there certain areas or layers where it makes more sense, whether that's applications 173 00:10:40,520 --> 00:10:46,000 via infrastructure or tooling, you know, developer tooling versus databases, like in terms of 174 00:10:46,000 --> 00:10:50,460 this is probably a good startup place to look at a startup versus, you know, this is a place 175 00:10:50,460 --> 00:10:52,480 where we want to, we need to be dealing with a... 176 00:10:52,480 --> 00:10:57,800 Yeah, so a lot of times that does start at the application layer, just because if you think 177 00:10:57,800 --> 00:11:03,380 about the quadrant concept that we discussed, a lot of times, if you're going to match the 178 00:11:03,380 --> 00:11:07,180 high risk of the startup, anything touching infra, not anything, but most things touching 179 00:11:07,180 --> 00:11:08,640 infra are going to be hires themselves. 180 00:11:08,640 --> 00:11:11,380 So it kind of needs a more mature company. 181 00:11:12,040 --> 00:11:17,720 But what's been in, thinking back to the early days of SaaS, that is where Salesforce and 182 00:11:17,720 --> 00:11:23,980 even Workday came into play because the joke was, you can throw our own data on the cloud, 183 00:11:24,040 --> 00:11:27,460 you could throw an employee data on the cloud, but we never wanted to put our own customer 184 00:11:27,460 --> 00:11:28,200 data on the cloud. 185 00:11:28,800 --> 00:11:35,640 So that's where something like Workday, even when I was leaving Morgan in 2012, 2013, we 186 00:11:35,640 --> 00:11:37,300 were dealing with a huge limitation of that. 187 00:11:37,900 --> 00:11:42,600 What I would say is the whole cloud native ecosystem has made it easier in some areas, 188 00:11:42,920 --> 00:11:48,240 paired with the rise of an open source in the Forge 500, to do some of this more bottoms 189 00:11:48,240 --> 00:11:51,520 up, so to speak, adoption, both from the startup side. 190 00:11:51,520 --> 00:11:56,920 And if you think about it as an end user in the Forge 500 company, but I would say that 191 00:11:56,920 --> 00:12:02,040 the hype level of Peep developers being able to just spin up whatever they want in the cloud 192 00:12:02,040 --> 00:12:06,480 native space is a little bit overhyped from reality when you think about what it actually 193 00:12:06,480 --> 00:12:11,040 takes and the amount of systems that most tools would have to integrate with, that you're 194 00:12:11,040 --> 00:12:15,160 going to get some security person looking over your shoulder or touching you and saying, 195 00:12:15,340 --> 00:12:19,220 or tapping you on the shoulder and saying, hey, I see what you're doing and you're not 196 00:12:19,220 --> 00:12:19,920 allowed to do this. 197 00:12:20,400 --> 00:12:25,880 Is that a matter of, do you think that's a matter of the open source nature of the stuff 198 00:12:25,880 --> 00:12:30,380 and that it is theoretically, you know, it's there, it's available, you can, you have the 199 00:12:30,380 --> 00:12:33,060 access to do it if you want, if you want to start spinning stuff up? 200 00:12:33,160 --> 00:12:36,720 Or is it a nature of, you know, just some of the complexity generally? 201 00:12:36,720 --> 00:12:39,940 I mean, if everything in the cloud native space was closed source, it would still be 202 00:12:39,940 --> 00:12:41,800 a very complex ecosystem, right? 203 00:12:41,920 --> 00:12:45,400 And, and you open up a lot of avenues, I think for, for vulnerabilities. 204 00:12:46,160 --> 00:12:46,240 Yeah. 205 00:12:46,360 --> 00:12:51,720 Part, a part of it is the number of internal stakeholders that have to touch a given product 206 00:12:51,720 --> 00:12:58,320 between security teams, infrastructure teams, even sometimes like touching identity if it 207 00:12:58,320 --> 00:13:02,880 has to integrate with Active Directory or create some on-ramp into the cloud and versions of 208 00:13:02,880 --> 00:13:03,160 that. 209 00:13:03,660 --> 00:13:07,160 So that is where historically it has been tough. 210 00:13:07,500 --> 00:13:10,840 I mean, I even think to the early days of MongoDB and a lot of products that people know 211 00:13:10,840 --> 00:13:16,000 as open source winners, when we would evaluate them while I was still at the bank, it really 212 00:13:16,000 --> 00:13:20,880 did have an enterprise sales counterpart where people were really coming in, pitching that 213 00:13:20,880 --> 00:13:21,820 mid-level executive. 214 00:13:22,220 --> 00:13:27,060 So it is important to note, it's not about the CIO, he or she making these decisions, but 215 00:13:27,060 --> 00:13:33,100 it's about those people a couple rungs below at that ED level or even MD that have that pain 216 00:13:33,100 --> 00:13:33,340 point. 217 00:13:33,420 --> 00:13:34,400 They're looking to solve them. 218 00:13:34,900 --> 00:13:39,760 And to tie it back into your point, which is how do the enterprises themselves navigate 219 00:13:39,760 --> 00:13:44,640 this, I think that it all comes down to what is our mission for the year, what is the goal 220 00:13:44,640 --> 00:13:49,820 and then how can we arm our teams to, part of it is even just have the bandwidth and the 221 00:13:49,820 --> 00:13:54,780 prioritization because it sounds very simple to say, hey, let's look at a new business intelligence 222 00:13:54,780 --> 00:13:56,100 vendor or we need a new database. 223 00:13:56,380 --> 00:13:59,840 But you have all these people grinding at a big company and they're nine to five. 224 00:14:00,140 --> 00:14:05,740 And to be candid, the less sexy industry, the less they're getting paid, the less they may 225 00:14:05,740 --> 00:14:09,900 be enjoying their job, the more old school their peer group may be in terms of the tech 226 00:14:09,900 --> 00:14:11,680 that's adopted and their viewpoint on it. 227 00:14:11,800 --> 00:14:17,460 So you're really asking someone to do something differently and usually on top of their day 228 00:14:17,460 --> 00:14:17,840 job. 229 00:14:18,220 --> 00:14:20,280 And it comes down to what's the motivation. 230 00:14:20,740 --> 00:14:25,600 And if someone knows that the CEO and the CIO say that this is our goal and by doing this 231 00:14:25,600 --> 00:14:29,820 project, it ties into a bigger vision, they'll be more than willing for the hungry person 232 00:14:29,820 --> 00:14:32,180 that wants to get promoted, put in that extra effort. 233 00:14:32,560 --> 00:14:35,040 But if not, it's going to be kind of a bad road for everybody. 234 00:14:35,560 --> 00:14:39,960 Is there anything to, you know, the one thing we've seen, I think, that's really spun up 235 00:14:39,960 --> 00:14:44,620 the past couple of years, this idea of cloud providers versus startups, especially in the 236 00:14:44,620 --> 00:14:45,620 open source space, right? 237 00:14:46,040 --> 00:14:51,000 And, you know, it's this notion of, you know, well, should I buy from the startup, which 238 00:14:51,000 --> 00:14:56,220 might have created this project or has the creators on its team and theoretically is going 239 00:14:56,220 --> 00:15:00,800 to open up more opportunities and, you know, give us more, you know, there's more competition 240 00:15:00,800 --> 00:15:01,980 in the market, et cetera, et cetera. 241 00:15:01,980 --> 00:15:06,880 Or do I buy from like Amazon Web Services, which I know is going to be there in 10 years 242 00:15:06,880 --> 00:15:11,960 and, and I already spend, you know, X number of millions of dollars a year on, I mean, have 243 00:15:11,960 --> 00:15:13,620 you seen that discussion? 244 00:15:13,700 --> 00:15:18,140 How do you think about that notion in terms of just what should the marketplace for enterprise 245 00:15:18,140 --> 00:15:19,580 software look like? 246 00:15:19,580 --> 00:15:23,000 And do you benefit from buying from a startup in the sense that you're, you're expanding 247 00:15:23,000 --> 00:15:24,080 that marketplace theoretically? 248 00:15:25,040 --> 00:15:26,160 Yeah, that's a great question. 249 00:15:26,360 --> 00:15:29,840 Something we talk about probably every day with Fortune 500s. 250 00:15:29,880 --> 00:15:34,900 In fact, our September New York enterprise tech meetup had a whole panel all around cloud 251 00:15:34,900 --> 00:15:35,340 adoption. 252 00:15:36,100 --> 00:15:40,700 And when it comes down to it, you know, for the most part in the Fortune 500, we are hearing 253 00:15:40,700 --> 00:15:47,400 that the cloud is still safer from some of these larger vendors like Microsoft and AWS, 254 00:15:47,400 --> 00:15:52,500 because they can put in these large enterprise agreements in place for the service that they 255 00:15:52,500 --> 00:15:58,580 need at the, for the most part of the startups are still a little bit too risky for them. 256 00:15:59,580 --> 00:16:02,420 Well, how we define startup, I think shifts, right? 257 00:16:02,440 --> 00:16:06,060 I mean, I've been, you know, you sometimes are at a, like, like a 15 person company and 258 00:16:06,060 --> 00:16:10,200 that's definitely a startup, but sometimes you're at a company that's, you know, maybe five 259 00:16:10,200 --> 00:16:15,500 years old and, but it has hundreds of people and has raised whatever, a hundred million 260 00:16:15,500 --> 00:16:15,860 dollars. 261 00:16:15,920 --> 00:16:16,720 It's a huge valuation. 262 00:16:16,840 --> 00:16:17,560 Is that still a startup? 263 00:16:18,000 --> 00:16:20,560 I'm not sure where that level is. 264 00:16:21,820 --> 00:16:22,840 Scale up startup. 265 00:16:23,640 --> 00:16:27,620 Well, from the enterprise perspective, I think the question becomes, what is their revenue? 266 00:16:27,740 --> 00:16:31,400 What sort of customers in their peer group are using it? 267 00:16:31,640 --> 00:16:34,120 Because there's companies that have raised hundreds of millions of dollars. 268 00:16:34,120 --> 00:16:38,820 Let's look at Docker, for instance, but not to beat a dead horse, but like the enterprise 269 00:16:38,820 --> 00:16:41,440 adoption there was pretty limited at the end of the day. 270 00:16:42,120 --> 00:16:46,060 And that's why when they were looking at what's the actual use case internally, what are we 271 00:16:46,060 --> 00:16:48,740 going to get benefit from it? 272 00:16:49,180 --> 00:16:54,080 The, the large enterprise ultimately, I guess, and the world moved to Kubernetes, it just wasn't 273 00:16:54,080 --> 00:16:54,640 aligned there. 274 00:16:55,080 --> 00:17:01,620 Docker is a unique, I think it's supremely unique and maybe like, is like the epitome of, of, 275 00:17:01,620 --> 00:17:04,840 of, of some of the risks of the current state of enterprise IT. 276 00:17:04,840 --> 00:17:08,660 But, but, but even to share then a few other examples, I mean, 277 00:17:08,820 --> 00:17:13,640 part of my old job was to help with the financial viability assessments of the companies. 278 00:17:13,640 --> 00:17:18,040 And it was actually a lot of fun because what that entailed was getting on the phone with 279 00:17:18,040 --> 00:17:22,460 CEOs and CFOs of all of the startups that we do, did business with, which is actually a 280 00:17:22,460 --> 00:17:23,280 huge number. 281 00:17:23,900 --> 00:17:27,840 And reviewing their P&L, but also beyond just the pure numbers. 282 00:17:27,840 --> 00:17:32,060 Because again, most of them were early understanding things like who are your top 10 customers? 283 00:17:32,660 --> 00:17:35,040 What is the concentration risk associated with that revenue? 284 00:17:35,500 --> 00:17:38,060 Help us understand the background of your management team. 285 00:17:38,460 --> 00:17:41,240 Help us understand your net burn and then also your VCs. 286 00:17:41,780 --> 00:17:44,260 And does it look like they would fund you in the future? 287 00:17:44,420 --> 00:17:45,760 How much cash do you have left in the bank? 288 00:17:45,920 --> 00:17:52,500 And of course, a lot of startups are naturally reticent to share this information, but we 289 00:17:52,500 --> 00:17:55,640 actually did have a Chinese wall where it wasn't going to the purchase of the house for the 290 00:17:55,640 --> 00:17:55,940 users. 291 00:17:56,200 --> 00:18:00,500 So they ultimately would share in an effort to try to win that Morgan Stanley contract. 292 00:18:00,680 --> 00:18:05,200 But the things that you would see in terms of some of these high flying companies and candidly 293 00:18:05,200 --> 00:18:10,960 how small the revenue was, a lot of these companies that you see hyped in the news are pretty early. 294 00:18:11,060 --> 00:18:16,500 So the trick becomes who actually will get the benefit from that use case that they're pitching 295 00:18:16,500 --> 00:18:22,720 so much so that they wouldn't use the AWS offering of it or the Microsoft managed service offering. 296 00:18:23,460 --> 00:18:28,060 And when a startup can actually solve a problem that they can bypass some of these big vendors, 297 00:18:28,180 --> 00:18:29,720 you know that you can be onto something huge. 298 00:18:30,760 --> 00:18:35,660 Have you seen notable success stories within your, let's say within your portfolio, maybe of 299 00:18:35,660 --> 00:18:43,760 companies, I guess I should say of enterprise customers who've engaged with, you know, a startup in a 300 00:18:43,760 --> 00:18:50,060 particular space and seen like really notable results and that, you know, like it was a really a net win 301 00:18:50,060 --> 00:18:50,700 for both sides. 302 00:18:51,280 --> 00:18:51,440 Yeah. 303 00:18:51,540 --> 00:18:52,320 So there's a ton. 304 00:18:53,100 --> 00:18:58,400 We have a company, SoCure, it's in the financial services space for identity verification. 305 00:18:58,400 --> 00:19:05,020 And they use online social data and some algorithms they developed to basically help with at new account 306 00:19:05,020 --> 00:19:11,180 opening, make sure that someone is actually a real account and it helps increase acceptance rates 307 00:19:11,180 --> 00:19:12,260 and decrease fraud. 308 00:19:12,600 --> 00:19:17,120 So you're touching money and bottom line from both sides of that equation. 309 00:19:17,840 --> 00:19:21,900 And we actually put them in touch with Bank of America back when they were just series A funded. 310 00:19:22,740 --> 00:19:27,420 And B of A had a ton of different use cases they were exploring internally, but decided to just start 311 00:19:27,420 --> 00:19:29,320 with one several years ago. 312 00:19:29,540 --> 00:19:33,020 The beauty is, is that, and we can say this publicly, they spoke at a conference that we 313 00:19:33,020 --> 00:19:39,100 co-hosted with B of A back in May, and they're on multiple use cases now where SoCure is offering, 314 00:19:39,100 --> 00:19:43,860 it's a simple API integration that fits into their existing workflow, has been helping them 315 00:19:43,860 --> 00:19:47,900 dramatically change the acceptance rate and actually reduce fraud. 316 00:19:48,380 --> 00:19:51,160 And again, that's been just money that comes to the bank's bottom line. 317 00:19:51,620 --> 00:19:56,320 It sounds like the start small is the, is probably one of the key things, right? 318 00:19:56,360 --> 00:20:00,360 I mean, obviously like, like, don't think, yeah, I'm looking at the startup and this is going to, 319 00:20:00,520 --> 00:20:02,760 like you said, replace our Oracle databases tomorrow. 320 00:20:03,140 --> 00:20:03,460 Right. 321 00:20:03,500 --> 00:20:07,060 But it's not, it sounds like the answer is what's this one thing we really think is strategically 322 00:20:07,060 --> 00:20:07,540 valuable. 323 00:20:07,540 --> 00:20:11,060 And we probably, you know, there's probably, there may not be a legacy vendor that that's 324 00:20:11,060 --> 00:20:11,760 even doing that. 325 00:20:12,160 --> 00:20:12,520 Right. 326 00:20:12,540 --> 00:20:15,640 Is that, is that kind of the, the ideal starting point? 327 00:20:16,060 --> 00:20:16,180 Yeah. 328 00:20:16,180 --> 00:20:18,700 So it's funny because we've seen actually both work successfully. 329 00:20:18,700 --> 00:20:21,200 One, which is, Hey, there's a legacy vendor. 330 00:20:21,940 --> 00:20:23,120 Maybe we've been with them for years. 331 00:20:23,120 --> 00:20:25,000 They're up for renewal and they're not meeting our needs. 332 00:20:25,000 --> 00:20:29,760 And we're ready to understand what the startup landscape looks like, because maybe there's 333 00:20:29,760 --> 00:20:35,000 been a 10 X improvement in, in efficiency and lower cost, et cetera. 334 00:20:35,000 --> 00:20:38,340 And sometimes there are those net new use cases that just never existed. 335 00:20:38,340 --> 00:20:43,620 Like back when containers first came out and all the orchestration stuff related to it. 336 00:20:44,200 --> 00:20:49,380 But you, you, it really is company specific because someone like a Morgan or a Goldman or 337 00:20:49,380 --> 00:20:55,080 a B of A could make a big bet because they know how to properly evaluate again, the internal 338 00:20:55,080 --> 00:20:58,860 mechanisms for, for control, as well as that, the startup. 339 00:20:59,260 --> 00:21:01,560 We have seen that even happen in pharma too. 340 00:21:01,720 --> 00:21:06,840 So we have a company algorithmia that focuses on model deployment and with one pharma that 341 00:21:06,840 --> 00:21:11,440 we can't share the name publicly, they made a huge bet on empowering basically all their 342 00:21:11,440 --> 00:21:14,560 data scientists on this single platform for model deployment. 343 00:21:14,560 --> 00:21:19,000 And then they've built up an internal sort of a model marketplace internally for people 344 00:21:19,000 --> 00:21:19,760 to collaborate on. 345 00:21:20,140 --> 00:21:25,040 That was a pretty new, it was a brand new offering and a pretty big bet, but because they, 346 00:21:25,040 --> 00:21:29,560 it was a pain point that they felt they collectively got behind it and built a relationship with 347 00:21:29,560 --> 00:21:32,740 the company so that they were willing to, to kind of give it a shot. 348 00:21:33,280 --> 00:21:35,360 We commented on this implicitly, but I want to do it expressly. 349 00:21:35,800 --> 00:21:40,060 If I may, so, cause this is one thing I've noticed too, like, yes, there are huge companies 350 00:21:40,060 --> 00:21:42,300 and they have, they're sophisticated in many ways. 351 00:21:42,320 --> 00:21:47,760 And then there are these midsize enterprises that, that might be, you know, many years or several 352 00:21:47,760 --> 00:21:50,120 years behind, you know, where we see the cutting edge. 353 00:21:50,120 --> 00:21:58,040 Um, well, if I'm that kind of company, what's the, you know, what's the path to, to, to engaging 354 00:21:58,040 --> 00:21:58,560 with the startup? 355 00:21:58,560 --> 00:22:01,260 If I'm, you know, I have to digitally transform, I have to do all these things, right? 356 00:22:01,260 --> 00:22:01,920 Every buzzword. 357 00:22:02,340 --> 00:22:04,220 And then what's the, what's the move? 358 00:22:04,740 --> 00:22:05,140 Yeah. 359 00:22:05,420 --> 00:22:07,400 And so there's a whole spectrum, right? 360 00:22:07,420 --> 00:22:11,460 And, uh, we've advised our companies and John blogged about this. 361 00:22:11,460 --> 00:22:15,640 How do you find the ones that are, uh, much more sophisticated, much more early adopting. 362 00:22:15,640 --> 00:22:20,540 And the reality is that there's also, uh, you know, people behind that curve. 363 00:22:20,540 --> 00:22:25,420 And the question is with those folks, what tends to happen is they have these internal 364 00:22:25,420 --> 00:22:32,100 innovation teams and the challenge is if they're not tied to actual business challenges or be 365 00:22:32,100 --> 00:22:36,140 used, it can suck a lot of time out of startups. 366 00:22:36,140 --> 00:22:43,560 Um, and they end up, uh, in these cycles with them doing demos, showing them their product. 367 00:22:44,040 --> 00:22:50,080 Um, and the end of the day doesn't end to actually anything meaningful, whether it's a POC or 368 00:22:50,080 --> 00:22:50,480 pilot. 369 00:22:50,860 --> 00:22:54,140 Um, and for startups, you know, every day is burn. 370 00:22:54,140 --> 00:22:59,220 And so that can be really, really painful and actually harmful to the startups. 371 00:22:59,220 --> 00:23:04,540 And so for, uh, these large companies who are trying to, you know, make their KPIs, whether 372 00:23:04,540 --> 00:23:08,820 it's how many new startups they've met with, they don't realize that it can be really, really 373 00:23:08,820 --> 00:23:09,740 hurtful to start up. 374 00:23:09,820 --> 00:23:14,960 So we actually advise most companies to stay away from quote unquote innovation teams and 375 00:23:14,960 --> 00:23:17,360 as soon as possible, get into the line of business. 376 00:23:18,140 --> 00:23:19,680 And to just play off that. 377 00:23:19,820 --> 00:23:23,200 So one of the things that we do recommend when you're saying, Hey, what should you do? 378 00:23:23,200 --> 00:23:25,780 So don't necessarily jump to an innovation team. 379 00:23:25,880 --> 00:23:29,680 The thing that we recommend actually is talk to your peer group. 380 00:23:30,300 --> 00:23:31,960 And there's some structured ways to do this. 381 00:23:32,140 --> 00:23:36,880 And candidly, we offer a corporate round table series for areas like machine learning, cloud 382 00:23:36,880 --> 00:23:42,140 native infrastructure, future work in cybersecurity is we bring all our corporate exec friends 383 00:23:42,140 --> 00:23:45,900 and it's, we, we joke, it's like group therapy because they can talk in the machine learning 384 00:23:45,900 --> 00:23:51,300 one about everything from hiring data science talent in today's environment to again, like 385 00:23:51,300 --> 00:23:54,240 deploying models and new, new modes for ETL and whatnot. 386 00:23:54,700 --> 00:23:59,040 And in that process, they're in a safe, so to speak, because it's only corporate peers 387 00:23:59,040 --> 00:24:04,000 and us as the XIT person in the room, but there's no vendors, there's no consultants. 388 00:24:04,000 --> 00:24:09,440 And we think that there's a need for more safe spaces like that because there's in every area 389 00:24:09,440 --> 00:24:14,660 of a, of a corporate kind of IT stack, they're going to be a laggard in some, maybe there'll 390 00:24:14,660 --> 00:24:15,860 be a leader in another one. 391 00:24:16,260 --> 00:24:20,960 And for them to be able to actually learn from their peers, keep that conversation ongoing 392 00:24:20,960 --> 00:24:21,960 on some cadence. 393 00:24:21,960 --> 00:24:27,520 I mean, we do these quarterly, it helps them actually tie in the pain points, not just tech, 394 00:24:27,520 --> 00:24:32,700 but also the people, the process related things to make sure that they're bit by bit actually 395 00:24:32,700 --> 00:24:35,900 driving change in the organization, hopefully tied to that big picture goal. 396 00:24:35,900 --> 00:24:41,360 The last thing I'll just add, we heard about this from a financial institution is that even 397 00:24:41,360 --> 00:24:47,360 within large companies, there are pockets where people and business units will be able to engage 398 00:24:47,360 --> 00:24:48,360 and others won't, right? 399 00:24:48,360 --> 00:24:53,920 And so this one financial institution has shared with us how they had a matrix, right, of people 400 00:24:53,920 --> 00:24:59,100 who have the ability to buy from a startup, but won't, and vice versa, right? 401 00:24:59,100 --> 00:25:03,000 People who want to help buy from a startup, but don't have the internal power and capital 402 00:25:03,000 --> 00:25:04,460 to actually push that through. 403 00:25:04,460 --> 00:25:09,800 And so to be able to see that type of a matrix was a real eye opener and just goes to show 404 00:25:09,800 --> 00:25:15,260 that even within large enterprises and corporates, they recognize there are people who can actually 405 00:25:15,260 --> 00:25:17,460 help startups move things forward or who unfortunately can't. 406 00:25:17,460 --> 00:25:24,020 And then finally, I just, you know, I'm curious, are there spaces where you, if you were, where 407 00:25:24,020 --> 00:25:30,120 you think it makes next to no sense to actually meaningfully look at a startup company? 408 00:25:30,120 --> 00:25:34,280 Like, I mean, if I were being frank today, if I were a large enterprise and I was looking 409 00:25:34,280 --> 00:25:37,660 at, you know, getting into like the infrastructure as a service space, right? 410 00:25:37,660 --> 00:25:41,120 There was a while where it looked like startups maybe could make a dent and I'm not sure that 411 00:25:41,120 --> 00:25:41,760 really happened. 412 00:25:42,700 --> 00:25:46,480 But are there other spaces where it's like, or maybe that's the one where it's like, yeah, 413 00:25:46,480 --> 00:25:47,660 it's just, it's not worth it. 414 00:25:47,660 --> 00:25:52,460 Or, you know, it's very hard to imagine the startup really having a competitive offering 415 00:25:52,460 --> 00:25:52,920 in that area. 416 00:25:54,040 --> 00:25:57,160 I mean, I think you hit the nail on the head with some of the stuff going on in the cloud 417 00:25:57,160 --> 00:25:58,100 infrastructure world. 418 00:25:58,480 --> 00:26:04,300 And in order for someone to consider a startup, they'd have to have a very different and nuanced 419 00:26:04,300 --> 00:26:06,980 answer for why you should work together. 420 00:26:08,100 --> 00:26:13,180 I would say there's a lot of big vendor hype to flip that question a bit. 421 00:26:13,560 --> 00:26:16,860 So, and look, this is kind of beating a dead horse at this point, but the whole IBM Watson 422 00:26:16,860 --> 00:26:21,640 thing four or five years ago, a lot of people were saying, hey, we already have these engagements 423 00:26:21,640 --> 00:26:22,600 with, with IBM. 424 00:26:22,760 --> 00:26:25,600 Should we look at that to them for our MLAI needs? 425 00:26:25,640 --> 00:26:27,780 And people learned that that wasn't the solution. 426 00:26:28,260 --> 00:26:33,240 So I do think it's just about being thoughtful and saying, hey, in this category, is there a 427 00:26:33,240 --> 00:26:38,840 leader in this space like an AWS or an Audra, is there, are they meeting our need? 428 00:26:38,940 --> 00:26:40,120 Do we have existing relationships? 429 00:26:40,560 --> 00:26:47,300 And should we just work with them and focus potentially maybe riskier efforts or more time 430 00:26:47,300 --> 00:26:51,400 to unpack potential efficiency gains in another sector? 431 00:26:51,580 --> 00:26:53,020 Because at the end of the day, it's all resources. 432 00:26:53,740 --> 00:26:58,540 The one thing startups forget a lot is that even if their product is free to evaluate and 433 00:26:58,540 --> 00:27:04,040 use for a period of time, it takes people and people have limited capacity in a big enterprise 434 00:27:04,040 --> 00:27:07,500 to, to explore and do stuff more than their regular day job. 435 00:27:08,240 --> 00:27:08,640 Great. 436 00:27:08,900 --> 00:27:10,060 Well, that's a great place to end it. 437 00:27:10,240 --> 00:27:11,320 Thank you so much, John and Jessica. 438 00:27:11,680 --> 00:27:12,540 And there you have it. 439 00:27:12,600 --> 00:27:13,560 I hope you learned something. 440 00:27:14,120 --> 00:27:20,760 For more information about Workbench, you can visit them online at work-bench.com. 441 00:27:20,880 --> 00:27:23,420 Again, that's work-bench.com. 442 00:27:23,480 --> 00:27:26,160 They also have a great enterprise newsletter you can subscribe to there. 443 00:27:26,540 --> 00:27:31,440 And for more information about Pivotal and our broad suite of products for building and 444 00:27:31,440 --> 00:27:36,140 managing and running cloud-native applications, as well as transforming how you build software, 445 00:27:36,660 --> 00:27:38,340 check out Pivotal.io. 446 00:27:38,780 --> 00:27:43,580 And if you like this podcast and want to keep up with all things digital transformation, including 447 00:27:43,580 --> 00:27:48,160 blog posts, guides, and some other stuff, you can visit the home of this podcast, Intersect, 448 00:27:48,320 --> 00:27:51,680 at Pivotal.io slash Intersect. 449 00:27:51,880 --> 00:27:54,060 And again, leave a review on Apple. 450 00:27:54,320 --> 00:27:55,120 We appreciate it. 451 00:27:55,120 --> 00:27:55,740 Thank you. 452 00:27:56,540 --> 00:27:57,540 Thank you.