1 00:00:00,000 --> 00:00:04,420 Welcome, listeners, to the first episode of our new podcast called Cloud and Culture. 2 00:00:05,000 --> 00:00:06,640 I'm Derek Harris of VMware. 3 00:00:07,220 --> 00:00:08,920 And I'm Danielle Burrow of VMware. 4 00:00:09,320 --> 00:00:15,080 This podcast is focused on VMware Pivotal Labs and the work it does to help organizations 5 00:00:15,080 --> 00:00:20,820 ranging from startups to Fortune 500 enterprises shift their software development into high gear. 6 00:00:21,560 --> 00:00:25,940 As the show's title suggests, that means addressing the technical aspects of building 7 00:00:25,940 --> 00:00:31,160 new applications and modernizing legacy ones, that's the cloud part, as well as the softer 8 00:00:31,160 --> 00:00:36,800 aspects that allow clients to continue thriving after our team of practitioners leaves, that's 9 00:00:36,800 --> 00:00:37,500 the culture part. 10 00:00:38,020 --> 00:00:42,360 So we'll do this by interviewing the people who know this process best, clients both past 11 00:00:42,360 --> 00:00:47,400 and present, and the VMware Pivotal Labs folks who specialize in helping those clients become 12 00:00:47,400 --> 00:00:49,360 proficient in modern software development. 13 00:00:50,140 --> 00:00:53,820 And for our first episode, we're speaking with a startup in the healthcare space, Mental 14 00:00:53,820 --> 00:00:58,660 Health, to be specific, called Alucio, about how Pivotal Labs helped it kickstart building 15 00:00:58,660 --> 00:01:00,940 out its first product and grow its engineering team. 16 00:01:01,340 --> 00:01:06,040 Our guest is Lori Gomer, who talks in detail about the nuances of building a healthcare startup 17 00:01:06,040 --> 00:01:09,760 with just a really good idea and a small team of subject matter experts. 18 00:01:10,320 --> 00:01:15,320 For Alucio, Pivotal Labs was a critical link between those two strengths and an actual functional 19 00:01:15,320 --> 00:01:20,240 product, as well as for establishing an engineering team confident in its ability to deliver high 20 00:01:20,240 --> 00:01:21,960 quality software fast. 21 00:01:21,960 --> 00:01:27,360 When we recorded this episode, Lori was the VP of business operations and strategy at Alucio, 22 00:01:27,360 --> 00:01:29,640 although she has since left the company for a new role. 23 00:01:30,040 --> 00:01:35,360 However, the relationship between VMware and Alucio carries on, and the results Lori discusses 24 00:01:35,360 --> 00:01:36,140 are just as real. 25 00:01:36,580 --> 00:01:39,560 We hope you enjoy listening to this interview as much as we enjoyed doing it. 26 00:01:39,920 --> 00:01:47,400 To learn more about Alucio, you can visit alluceo.com, and to learn more about VMware Pivotal Labs, 27 00:01:47,520 --> 00:01:51,520 you can visit tonsu.vmware.com slash labs. 28 00:01:53,100 --> 00:01:57,720 All right, Lori, so just to kick things off, can you briefly explain to our audience what 29 00:01:57,720 --> 00:02:02,420 Alucio does, what space you guys operate in, and kind of your role at the company? 30 00:02:03,080 --> 00:02:04,200 Sure, happy to. 31 00:02:04,680 --> 00:02:10,480 So Alucio is a digital health platform that helps patients with mental health issues get 32 00:02:10,480 --> 00:02:12,680 those treated right inside primary care. 33 00:02:13,300 --> 00:02:18,160 And the reason that that's important is, as you can imagine, there's a lot of stigma often 34 00:02:18,160 --> 00:02:20,320 with getting help with mental health. 35 00:02:20,400 --> 00:02:26,060 And I think especially during these COVID times, anything that we can do to help improve the 36 00:02:26,060 --> 00:02:31,400 access and affordability for patients who need to get help with a mental health concern, 37 00:02:31,800 --> 00:02:32,400 all the better. 38 00:02:32,900 --> 00:02:37,560 In my role, Alucio, I'm actually the vice president of business operations and strategy, 39 00:02:37,980 --> 00:02:41,860 which at an early stage startup can mean that you do lots of different things, but really 40 00:02:41,860 --> 00:02:47,320 focused on running the internal operations, the recruiting efforts, building out the team 41 00:02:47,320 --> 00:02:48,640 that we have at Alucio. 42 00:02:49,100 --> 00:02:49,560 All right. 43 00:02:49,980 --> 00:02:56,560 And can you talk briefly just about what was the, I guess, the business problem or maybe 44 00:02:56,560 --> 00:03:00,200 the business at the right term or healthcare problem, whatever it is that Alucio was trying 45 00:03:00,200 --> 00:03:02,360 to solve when you engage with pivot? 46 00:03:02,420 --> 00:03:07,340 Like what was the existing process that, that now we, you know, you've built an application 47 00:03:07,340 --> 00:03:08,500 around and digitized? 48 00:03:08,820 --> 00:03:09,160 Absolutely. 49 00:03:09,660 --> 00:03:15,980 So the concept behind Alucio was actually born at Intermountain Healthcare, where one of 50 00:03:15,980 --> 00:03:20,700 the nurse practitioners there, Dr. Brenda Reese Brennan, had been practicing for a number 51 00:03:20,700 --> 00:03:26,500 of years and developed a methodology, just as I described, to help treat mental health inside 52 00:03:26,500 --> 00:03:27,500 of primary care. 53 00:03:27,900 --> 00:03:32,380 The reason, other, other reasons that's important that I haven't already named is there's a severe 54 00:03:32,380 --> 00:03:34,640 shortage of specialists to treat mental health. 55 00:03:35,120 --> 00:03:40,540 And so if you think about it from a supply perspective, just being able to offer the majority 56 00:03:40,540 --> 00:03:41,160 of patients. 57 00:03:41,160 --> 00:03:44,720 And of course there will be those patients that maybe have some high risk needs that need 58 00:03:44,720 --> 00:03:45,540 to be referred out. 59 00:03:45,660 --> 00:03:50,680 But for the majority of the population, if you can offer them treatment inside primary care, 60 00:03:50,680 --> 00:03:55,800 where perhaps they have an existing relationship with their primary care doctor, the data shows 61 00:03:55,800 --> 00:03:58,720 that, that you can, you can improve mental health quite a bit. 62 00:03:58,940 --> 00:04:03,340 And Brenda actually published a study in JAMA, which was really exciting. 63 00:04:03,340 --> 00:04:08,060 And really, I think the foundation of the company when Intermountain decided to spin this out, 64 00:04:08,320 --> 00:04:12,980 which showed not only did patients, their mental health improve, more patients were getting 65 00:04:12,980 --> 00:04:17,980 screened for depression and their mental health risk improved over time, but also that it saved 66 00:04:17,980 --> 00:04:23,420 the health system money, which is always exciting if you can tackle both of those as a company. 67 00:04:24,620 --> 00:04:25,020 Right. 68 00:04:25,440 --> 00:04:25,820 Okay. 69 00:04:25,820 --> 00:04:28,940 And then, and then what was the actual, the process though? 70 00:04:28,960 --> 00:04:32,940 So, I mean, so obviously, Ellucian engaged with Pivotal Labs, but before we get into that, 71 00:04:32,980 --> 00:04:37,700 I just wanted to get into the, the actual process that needed modernizing or updating. 72 00:04:38,000 --> 00:04:38,280 Oh, sure. 73 00:04:38,420 --> 00:04:38,680 Yes. 74 00:04:38,780 --> 00:04:41,980 So if you think about, you know, how was this done? 75 00:04:42,200 --> 00:04:44,780 Brenda started working on this about 20 years ago. 76 00:04:45,160 --> 00:04:49,940 And so, as you can imagine, a lot of it was done with paper processes, probably lots of 77 00:04:49,940 --> 00:04:51,360 faxing and such. 78 00:04:51,520 --> 00:04:56,860 And what we really wanted to do was take the paper-based assessment that Brenda had created, 79 00:04:57,120 --> 00:05:02,380 which score, essentially helps someone score their mental health risk and modernize that 80 00:05:02,380 --> 00:05:05,000 by allowing people to take it on the web, on their phone. 81 00:05:05,380 --> 00:05:07,160 And that's, you know, that's really the first step. 82 00:05:07,160 --> 00:05:12,620 We're also working on some things that will automate the care plan for the physician, such 83 00:05:12,620 --> 00:05:17,800 that after the patient has taken that assessment, which again, in the past would have been done 84 00:05:17,800 --> 00:05:21,280 on paper and would have required a lot of manual scoring in the clinic. 85 00:05:21,700 --> 00:05:27,220 So a lot of time when you'd rather your providers be spending time with patients as opposed to scoring 86 00:05:27,220 --> 00:05:30,320 a paper packet, of course, that gave, that gives them back some time. 87 00:05:30,320 --> 00:05:35,600 And then also being able to serve up the most relevant parts that a physician might need 88 00:05:35,600 --> 00:05:39,600 to make a decision on what the next step is for that patient. 89 00:05:39,960 --> 00:05:45,760 Being able to just serve all that up in an easier, digestible, a better manner for them 90 00:05:45,760 --> 00:05:47,260 to make those decisions more quickly. 91 00:05:47,540 --> 00:05:48,580 That's really our goal. 92 00:05:49,180 --> 00:05:54,920 And so we've started with the assessment and giving those results to the clinician and their 93 00:05:54,920 --> 00:05:55,400 staff. 94 00:05:55,400 --> 00:05:59,780 And then of course, you know, we have a lot of, a lot of other ambitious plans on our 95 00:05:59,780 --> 00:06:03,600 roadmap to just make things easier for both the patient, providing them with resources. 96 00:06:03,600 --> 00:06:08,320 That's something that we're currently offering as well, a resource library that the physicians 97 00:06:08,320 --> 00:06:12,480 and their staff can send to the patients based on how they score on the assessment. 98 00:06:12,880 --> 00:06:12,920 So. 99 00:06:13,700 --> 00:06:14,640 Sounds really interesting, Lori. 100 00:06:14,700 --> 00:06:18,300 I mean, so it sounds like you're both doing this assessment, but then you're also helping 101 00:06:18,300 --> 00:06:23,640 connect the patient to all of their care providers and anyone who needs to be, you know, 102 00:06:23,680 --> 00:06:27,060 helping them through the diagnosis and the treatment process. 103 00:06:27,640 --> 00:06:28,060 Absolutely. 104 00:06:28,060 --> 00:06:28,540 Yeah. 105 00:06:28,660 --> 00:06:29,340 Sounds really interesting. 106 00:06:29,560 --> 00:06:34,540 And that's, you know, in addition to just moving the treatment for mental health inside 107 00:06:34,540 --> 00:06:40,880 of primary care, one of the key things that was central to Brenda's methodology was really 108 00:06:40,880 --> 00:06:42,440 this notion of team-based care. 109 00:06:42,600 --> 00:06:48,900 And so you're spot on in that it's not just the provider and physician, you know, it's the 110 00:06:48,900 --> 00:06:50,860 front desk, it's the medical assistant. 111 00:06:51,200 --> 00:06:57,960 Everyone has a role to play in helping deliver whole person care, if you will, not just physical 112 00:06:57,960 --> 00:07:01,580 care, but also mental health to patients in primary care. 113 00:07:02,300 --> 00:07:02,320 Right. 114 00:07:02,500 --> 00:07:07,300 And digitizing all of that makes it so much more efficient, I would imagine. 115 00:07:07,580 --> 00:07:09,520 So yeah, that's really, that's really interesting. 116 00:07:09,580 --> 00:07:15,380 I would love to know kind of how you came across VMware Pivotal Labs as an option to help 117 00:07:15,380 --> 00:07:16,560 you get started with this. 118 00:07:17,140 --> 00:07:17,380 Sure. 119 00:07:17,600 --> 00:07:23,580 So I joined the company in February 2019 and about a month and a half before I joined, 120 00:07:23,580 --> 00:07:29,040 the CEO had been hired and we were looking at a pretty aggressive timeline. 121 00:07:29,520 --> 00:07:36,280 Our investors and board wanted us to get to pilot, I think, you know, Q4 2019 or Q1 2020. 122 00:07:36,780 --> 00:07:42,760 And having come from a number of startups, you know, it takes a while, especially in a regulated 123 00:07:42,760 --> 00:07:47,920 space to, to build a HIPAA compliant platform, you know, and you have to do a lot of user 124 00:07:47,920 --> 00:07:50,760 research to figure out exactly what you need to be building, of course. 125 00:07:50,920 --> 00:07:55,860 And so when I looked at the timeline and knew that, you know, also investors are going to 126 00:07:55,860 --> 00:08:01,960 want to see that we have our own team built out that can obviously sustain whatever software 127 00:08:01,960 --> 00:08:06,460 it is that we ended up building to support mental health integration and primary care. 128 00:08:07,000 --> 00:08:12,460 I had actually moved from the Bay Area previously after working at a number of digital health 129 00:08:12,460 --> 00:08:12,800 startups. 130 00:08:12,800 --> 00:08:17,380 And actually a couple of my startups had had engagements with Pivotal Labs in the past. 131 00:08:17,960 --> 00:08:24,320 And so when I looked at the tight timeline and I looked at, I had just myself moved to Utah 132 00:08:24,320 --> 00:08:30,780 and our CEO was actually not located in Utah, you know, we didn't have as robust a network there as 133 00:08:30,780 --> 00:08:35,240 perhaps I might have in the Bay Area to recruit some of that initial technology talent. 134 00:08:35,820 --> 00:08:41,100 And so I naturally thought after, you know, spending a few weeks getting up to speed on the problem 135 00:08:41,100 --> 00:08:46,780 and what we, you know, what we wanted to try and do with the company, Pivotal Labs came to mind 136 00:08:46,780 --> 00:08:48,500 and then we reached out. 137 00:08:48,720 --> 00:08:50,900 So that's, that's how we got to you guys. 138 00:08:52,400 --> 00:08:52,920 All right. 139 00:08:52,980 --> 00:08:58,080 And I mean, what type of skills did you have internally or I'm just curious about the scope 140 00:08:58,080 --> 00:08:58,740 of the engagement. 141 00:08:58,900 --> 00:09:04,560 Was this like a, we have nothing and we need to, we need to start to ground up or was this 142 00:09:04,560 --> 00:09:08,340 a, we have some competent people and we need to, I'm just curious what, you know, how, what 143 00:09:08,340 --> 00:09:09,300 the scope was. 144 00:09:10,120 --> 00:09:10,320 Yeah. 145 00:09:10,540 --> 00:09:16,580 So the CEO and I were both, you know, business operators, you know, both of us had a lot of 146 00:09:16,580 --> 00:09:21,360 business development, marketing, you know, operational life roles. 147 00:09:21,360 --> 00:09:25,260 So not, not your software engineers, your designers, your product team. 148 00:09:25,260 --> 00:09:29,840 And so those were, those were a number of the roles that we were going to both need to hire 149 00:09:29,840 --> 00:09:32,800 for as well as need to get help with initially. 150 00:09:32,800 --> 00:09:38,520 And so, you know, in my mind, having worked with Pivotal in the past, that was kind of the 151 00:09:38,520 --> 00:09:45,240 perfect marriage for us is because I knew that if we waited to essentially hire out enough 152 00:09:45,240 --> 00:09:50,800 of a team to get started, it was probably going to be very difficult for us to hit those timelines 153 00:09:50,800 --> 00:09:52,980 that our investors and board wanted us to hit. 154 00:09:53,740 --> 00:09:57,580 So having worked with Pivotal in the past, I knew that we could kind of approach them in 155 00:09:57,580 --> 00:10:04,200 tandem such that we could get started with a lot of that initial discovery and start working 156 00:10:04,200 --> 00:10:06,820 to hire out our team in the same process. 157 00:10:06,820 --> 00:10:08,700 So that's exactly what we did. 158 00:10:08,700 --> 00:10:14,760 And it worked fantastic for us because again, if we had waited to get enough of those core 159 00:10:14,760 --> 00:10:20,160 team members, design, product, you know, at least a few engineers on board, that would 160 00:10:20,160 --> 00:10:24,520 have taken several months before we could have actually gotten started on that, on developing 161 00:10:24,520 --> 00:10:25,160 the platform. 162 00:10:25,480 --> 00:10:30,000 So that was, that was really key for us to be able to hit those timelines that our board 163 00:10:30,000 --> 00:10:30,800 had asked of us. 164 00:10:31,980 --> 00:10:32,380 Right. 165 00:10:32,420 --> 00:10:32,980 That makes sense. 166 00:10:32,980 --> 00:10:39,460 And it sounds like maybe there wasn't a CTO or someone more technical on the ground already. 167 00:10:39,460 --> 00:10:46,220 So, and, and so in terms of, you know, kind of just getting started, how, how did, how 168 00:10:46,220 --> 00:10:47,400 did things kick off? 169 00:10:47,600 --> 00:10:47,840 Yeah. 170 00:10:48,120 --> 00:10:48,560 Yeah. 171 00:10:48,880 --> 00:10:54,340 It was, so we, we were based in Utah and so the closest Pivotal office was in Denver. 172 00:10:54,340 --> 00:11:01,840 So myself, the CEO and Dr. Brenda Reese Brennan, and actually another physician from Intermountain 173 00:11:01,840 --> 00:11:07,720 healthcare and a project manager from Intermountain healthcare all headed out to Denver and we got 174 00:11:07,720 --> 00:11:08,760 to meet our team. 175 00:11:09,040 --> 00:11:13,080 The team was pretty lean, our pivotal team, because we didn't have, of course, our Lucio 176 00:11:13,080 --> 00:11:14,620 product delivery team yet. 177 00:11:15,000 --> 00:11:16,520 And so it was a pretty lean team. 178 00:11:16,520 --> 00:11:22,880 And we spent a lot of time, you know, of course, unpacking the 20 years of research that Brenda 179 00:11:22,880 --> 00:11:28,380 had been working on, combining that with the healthcare, digital health industry knowledge 180 00:11:28,380 --> 00:11:34,440 that the CEO and myself brought to the company, as well as some of the experience that the physician 181 00:11:34,440 --> 00:11:40,660 had had who had been practicing this in sort of the manual paper-based world of having patients 182 00:11:40,660 --> 00:11:45,980 fill out the paper assessment and scoring it and practicing with those methodologies. 183 00:11:46,400 --> 00:11:50,740 And so trying to pull out, you know, what's happening now, what are the areas for improvement? 184 00:11:51,360 --> 00:11:56,300 You know, Pivotal really helped us focus on, I think, our North Star and, you know, trying 185 00:11:56,300 --> 00:12:01,460 not to get too sidetracked because there's always a million things that you want to do and lots 186 00:12:01,460 --> 00:12:02,280 of aspirations. 187 00:12:02,420 --> 00:12:07,880 And you have to really be able to narrow those down so that you can figure out what can make 188 00:12:07,880 --> 00:12:11,220 impact quickly and what can drive value for your end users. 189 00:12:12,020 --> 00:12:17,260 And I think they were really instrumental in helping us figure out what made sense to tackle 190 00:12:17,260 --> 00:12:20,500 first and what was for later. 191 00:12:20,760 --> 00:12:25,660 But, you know, we're not losing the idea, but we will hold that for later because it probably 192 00:12:25,660 --> 00:12:30,540 makes more sense to do perhaps a little bit more research or just from a time perspective, 193 00:12:30,540 --> 00:12:33,920 perhaps on how long it would take to build that concept. 194 00:12:34,400 --> 00:12:39,000 So I think that's so interesting, especially from the startup perspective of getting the 195 00:12:39,000 --> 00:12:44,000 stakeholders, the executives, the business leaders in the room at the same time, even 196 00:12:44,000 --> 00:12:45,140 before anything is built. 197 00:12:45,620 --> 00:12:49,900 Because I think sometimes, right, like if you have a team in place, they're kind of caught 198 00:12:49,900 --> 00:12:52,260 in their own momentum of how things have been going. 199 00:12:52,500 --> 00:12:52,820 Yes. 200 00:12:52,960 --> 00:12:55,340 And the business has its own ideas of what it wants. 201 00:12:55,340 --> 00:12:58,800 But to come in with a neutral third party and just the business team and talk through like, 202 00:12:59,400 --> 00:13:02,820 what do we want and how can we get started getting there in a reasonable way? 203 00:13:03,260 --> 00:13:09,700 That seems like, I think it's a luxury that might frankly be for startups, you know, a lot 204 00:13:09,700 --> 00:13:15,420 easier than getting the, obviously the seed team from a large enterprise. 205 00:13:15,960 --> 00:13:16,360 Absolutely. 206 00:13:17,000 --> 00:13:17,180 Yeah. 207 00:13:17,300 --> 00:13:21,100 Just, you know, that kind of takes me back because it's been several months, of course, 208 00:13:21,160 --> 00:13:23,400 now since we, you know, started our engagement. 209 00:13:23,400 --> 00:13:27,300 But, you know, we all came from very different perspectives. 210 00:13:27,840 --> 00:13:32,340 You know, I had been the only person that had come from, you know, I'll say a traditional 211 00:13:32,340 --> 00:13:33,500 startup background. 212 00:13:34,080 --> 00:13:41,060 You know, the clinical nurse practitioner, she had been, you know, within Intermountain for 213 00:13:41,060 --> 00:13:45,520 a number of years, but really came from an academic clinical research kind of mindset. 214 00:13:45,860 --> 00:13:51,340 The clinician had been practicing in clinic for a long time using this methodology. 215 00:13:51,340 --> 00:13:56,920 And our CEO came from, you know, much larger companies still in the digital health or health 216 00:13:56,920 --> 00:13:59,540 technology space, but much larger scale companies. 217 00:13:59,800 --> 00:14:05,120 So we all brought, you know, different opinions and different thoughts on where we might need 218 00:14:05,120 --> 00:14:05,540 to go. 219 00:14:05,660 --> 00:14:11,120 But I think the process really helped us as a group determine what was truly the most important 220 00:14:11,120 --> 00:14:16,460 and help us, you know, kind of forge a path on, on what we were going to tackle first. 221 00:14:16,460 --> 00:14:20,500 And everybody kind of leave the room and agree that that was, that was a path forward. 222 00:14:20,620 --> 00:14:25,140 Not that we couldn't change our minds, but, you know, at least we had initially started to 223 00:14:25,140 --> 00:14:27,540 kind of chip off on what we were going to tackle first. 224 00:14:28,820 --> 00:14:29,180 Right. 225 00:14:29,240 --> 00:14:30,260 That makes a lot of sense. 226 00:14:30,520 --> 00:14:31,240 It's really interesting. 227 00:14:31,760 --> 00:14:36,860 And then, you know, you mentioned not really having a team, you know, starting out with 228 00:14:36,860 --> 00:14:38,100 this very lean group. 229 00:14:38,260 --> 00:14:45,500 How did, how did labs kind of help Elucio, you know, build up a software capability? 230 00:14:46,500 --> 00:14:46,700 Yeah. 231 00:14:47,000 --> 00:14:53,360 Since, since I was the one in charge of recruiting and I had perhaps never formally had that role 232 00:14:53,360 --> 00:14:53,960 at a company. 233 00:14:54,220 --> 00:14:54,340 Sure. 234 00:14:54,440 --> 00:15:01,140 I had, you know, recruited people to work on, on my teams in the past, but I had never run 235 00:15:01,140 --> 00:15:02,460 a recruiting role at a company. 236 00:15:02,460 --> 00:15:08,240 So I was learning in the process of doing this and, and hadn't specifically, you know, 237 00:15:08,400 --> 00:15:14,440 even, even diving into it more, hadn't specifically recruited for product management design or software 238 00:15:14,440 --> 00:15:20,000 engineers, had been around it, had some friends that I could, could run to and ask a few questions, 239 00:15:20,000 --> 00:15:23,040 but really hadn't had to dive into that before. 240 00:15:23,040 --> 00:15:29,680 And so Pivotal was very helpful to me in helping me understand, you know, I spent a lot of time 241 00:15:29,680 --> 00:15:34,240 with, with all of the people in those various functions, as well as some of the leaders in 242 00:15:34,240 --> 00:15:39,540 the Denver office who really helped me understand how they go about recruiting and what their 243 00:15:39,540 --> 00:15:40,420 process was. 244 00:15:40,420 --> 00:15:45,940 And so then I kind of went back and created what I thought made sense for, for us, 245 00:15:46,000 --> 00:15:47,220 for a company of our size. 246 00:15:47,600 --> 00:15:53,140 And Pivotal also helped us screen some of the applicants that ended up joining our team. 247 00:15:53,700 --> 00:15:59,520 Again, because, you know, I, I should not be the one, you know, deciding whether someone is a good 248 00:15:59,520 --> 00:16:00,520 engineer or not. 249 00:16:00,620 --> 00:16:05,120 You know, a lot of ones and zeros, it probably doesn't mean as much to me as it does to them. 250 00:16:05,120 --> 00:16:08,360 And so you wouldn't want me deciding if you were a good candidate or not. 251 00:16:08,360 --> 00:16:13,200 So for some of the technical screening for each of those roles, Pivotal was really helpful 252 00:16:13,200 --> 00:16:16,460 in helping us kind of get through that technical hurdle. 253 00:16:16,680 --> 00:16:21,840 And then after that, of course, you know, it was a lot of the more personality type questions 254 00:16:21,840 --> 00:16:27,820 that you would typically have, but they had some really, I think, great tips on how to make 255 00:16:27,820 --> 00:16:33,440 sure we were hiring people that could work in a highly collaborative environment, because 256 00:16:33,440 --> 00:16:39,800 that's, you know, one of the distinguishing features of extreme programming and, and agile 257 00:16:39,800 --> 00:16:44,740 that, that Pivotal teaches its customers and practices is it's collaborative. 258 00:16:44,740 --> 00:16:50,820 And so, you know, I think, I think we all learned you can be, you know, perhaps the most brilliant 259 00:16:50,820 --> 00:16:53,760 software engineer, the most brilliant designer, so on. 260 00:16:54,140 --> 00:16:59,580 But if you're not collaborative, you may not be a good fit for, for that type of environment. 261 00:16:59,580 --> 00:17:05,300 So helping get even more granular on the types of questions or activities to draw out those 262 00:17:05,300 --> 00:17:05,720 behaviors. 263 00:17:05,720 --> 00:17:09,860 So we could really see if we thought someone would be a good fit was, was really, really 264 00:17:09,860 --> 00:17:10,240 helpful. 265 00:17:10,820 --> 00:17:15,480 I know you hadn't been in that role before, but what was your sense of what it was like 266 00:17:15,480 --> 00:17:19,880 hiring in Utah, where I, where there is some tech talent, obviously, and some pretty successful 267 00:17:19,880 --> 00:17:25,580 tech companies that have, have been based compared with maybe hiring, you know, your impression, 268 00:17:25,580 --> 00:17:30,120 at least if hiring in the Bay Area, where maybe you get like these, my impression is that you're 269 00:17:30,120 --> 00:17:33,260 not going to get these superstars with these resumes that you might look at and go, I don't know what 270 00:17:33,260 --> 00:17:33,720 that means. 271 00:17:34,220 --> 00:17:35,600 You worked at Netflix, I guess. 272 00:17:35,800 --> 00:17:37,100 So you're a good candidate. 273 00:17:37,620 --> 00:17:45,340 You know, I, I was pleasantly surprised with, you know, I, I will, you know, very much admit 274 00:17:45,340 --> 00:17:50,840 that, you know, I spent the majority of my career and in total about 13 years in San Francisco, 275 00:17:50,840 --> 00:17:55,620 both before and after I went to business school, like did so much I came back, I suppose, but 276 00:17:55,620 --> 00:17:56,180 then I left. 277 00:17:56,320 --> 00:18:04,400 So anyway, I, you know, I think I was surprised at how competitive it was to recruit, not just 278 00:18:04,400 --> 00:18:08,700 the engineers, but also design and product in Salt Lake. 279 00:18:09,040 --> 00:18:13,920 And maybe you don't have quite the density of technology companies. 280 00:18:13,920 --> 00:18:19,400 All I think a lot, a lot of the Bay Area companies are, you know, I probably pre COVID when people 281 00:18:19,400 --> 00:18:23,780 were still going into the office a lot, we're actually setting up some satellite offices here 282 00:18:23,780 --> 00:18:24,400 in Salt Lake. 283 00:18:24,500 --> 00:18:30,940 So I think I was starting to see some of that talent shift, shift here, as well as just was 284 00:18:30,940 --> 00:18:35,560 pleasantly surprised of, you know, how competitive it still was. 285 00:18:35,680 --> 00:18:41,100 I wasn't sure because again, I was new to Utah as well, how competitive it would be to, to 286 00:18:41,100 --> 00:18:44,480 hire an engineer or designer or product here in Salt Lake. 287 00:18:44,480 --> 00:18:50,600 And again, maybe, maybe not the same volume to choose from, but I think we were, we were 288 00:18:50,600 --> 00:18:54,940 happy with the quality of folks that we, that we got on our team. 289 00:18:54,940 --> 00:19:02,020 And, and I, I honestly think part of that was a number of them had either heard of Pivotal 290 00:19:02,020 --> 00:19:06,740 Labs or in fact worked with Pivotal Labs at some of their previous companies and really 291 00:19:06,740 --> 00:19:09,320 had a great experience in that. 292 00:19:09,320 --> 00:19:14,640 And so when we were able to tell them as part of the recruiting process that we were working 293 00:19:14,640 --> 00:19:20,840 with Pivotal Labs, I think that was a real bonus for, you know, a small startup that, you 294 00:19:20,840 --> 00:19:24,200 know, presumably that I, I'm sure they would think wouldn't have much structure. 295 00:19:24,200 --> 00:19:30,540 I think that gave them a lot of confidence that we were serious about developing a well-functioning, 296 00:19:30,600 --> 00:19:32,600 well-oiled product delivery team. 297 00:19:34,200 --> 00:19:34,720 All right. 298 00:19:34,860 --> 00:19:38,980 And that's interesting too, because I think, I mean, not to go too off topic, but I do think 299 00:19:38,980 --> 00:19:44,660 there's a, there's maybe a, a misconception among companies and markets that haven't traditionally 300 00:19:44,660 --> 00:19:49,140 been tech, you know, what you might call tech markets, but like the, the, the skills are 301 00:19:49,140 --> 00:19:53,780 democratizing companies are setting up, setting up offices in various cities and it is a more 302 00:19:53,780 --> 00:19:54,720 competitive landscape. 303 00:19:54,880 --> 00:19:57,680 I mean, if Facebook has an office in your city, right. 304 00:19:57,760 --> 00:20:00,680 You, you don't get to dictate the terms necessarily anymore. 305 00:20:01,280 --> 00:20:01,480 Yes. 306 00:20:02,340 --> 00:20:06,640 It doesn't, it doesn't hurt that in Utah you're, you can, you know, if you're in Salt 307 00:20:06,640 --> 00:20:10,760 Lake or myself, I live in Park City, you can get to the ski slopes a lot easier than you 308 00:20:10,760 --> 00:20:12,000 can when you live in the Bay area. 309 00:20:13,120 --> 00:20:13,440 Yeah. 310 00:20:13,440 --> 00:20:15,360 That's a nice quality of life bonus. 311 00:20:17,060 --> 00:20:22,380 And Laura, I guess I'm curious now kind of what stage are you all at with the product 312 00:20:22,380 --> 00:20:22,860 development? 313 00:20:23,020 --> 00:20:28,220 You know, you explained kind of that early discovery kind of scoping phase where you really 314 00:20:28,220 --> 00:20:31,640 figured out what you wanted to hone in on and focus on first. 315 00:20:31,760 --> 00:20:33,320 And then you've built out this team. 316 00:20:33,460 --> 00:20:33,720 Yeah. 317 00:20:34,040 --> 00:20:35,380 Where, where are things now? 318 00:20:35,700 --> 00:20:36,000 Sure. 319 00:20:36,200 --> 00:20:40,600 So we, so we had sort of multiple versions of our MVP. 320 00:20:41,100 --> 00:20:47,100 I think we finished our first, first, you know, 1A MVP, if you will, in December. 321 00:20:47,260 --> 00:20:49,660 And then we continued to iterate on that. 322 00:20:49,660 --> 00:20:55,580 And we, we kind of had our, you know, as much as you can say final MVP, the features that 323 00:20:55,580 --> 00:20:59,420 we wanted to have in there, we had all of those done in March. 324 00:20:59,420 --> 00:21:05,140 And so since then we did get a little bit delayed starting our pilots as probably a lot 325 00:21:05,140 --> 00:21:09,740 of companies did with COVID because we were going to be starting our pilots right as, right 326 00:21:09,740 --> 00:21:11,560 as COVID hit toward the end of March. 327 00:21:11,560 --> 00:21:13,040 So we got a little bit delayed. 328 00:21:13,760 --> 00:21:18,860 Luckily we'd become very, very much experts I'll say in, in doing a lot of user research. 329 00:21:18,860 --> 00:21:24,140 So we use that time while we were delayed to start our pilots and really digging into some 330 00:21:24,140 --> 00:21:26,640 other areas that we, we knew we need to build anyway. 331 00:21:27,140 --> 00:21:32,620 So we did a lot of user research and we actually started up our pilot at the end of June, beginning 332 00:21:32,620 --> 00:21:34,580 of July, our first pilot. 333 00:21:34,760 --> 00:21:39,360 And so really what we've been doing is getting that pilot feedback and starting to iterate 334 00:21:39,360 --> 00:21:41,980 on that, which is exactly what you want to do. 335 00:21:42,040 --> 00:21:46,080 Making sure that we're listening to the users, understanding their pain points, you know, 336 00:21:46,080 --> 00:21:49,740 when they grunt, when they sigh, figuring out what we can do to make that better. 337 00:21:50,180 --> 00:21:51,780 That's what we've really been focused on. 338 00:21:51,860 --> 00:21:56,060 And of course we have, you know, our longer term roadmap and some items that we know we'll 339 00:21:56,060 --> 00:21:56,780 need to tackle. 340 00:21:56,780 --> 00:21:58,500 And so chipping away at those. 341 00:21:58,660 --> 00:22:03,340 But right now, I think the most important thing is that we figure out and make sure that our, 342 00:22:03,700 --> 00:22:09,240 we can get our core product to, to really deliver the value that we want for both the patient 343 00:22:09,240 --> 00:22:10,580 and the clinic end users. 344 00:22:12,260 --> 00:22:12,780 All right. 345 00:22:12,820 --> 00:22:17,680 So, I mean, that sounds like a, frankly, a pretty impressive timeline, all considering 346 00:22:17,680 --> 00:22:23,120 the delay that COVID had caused on everything that you would be from, it sounds like maybe 347 00:22:23,120 --> 00:22:24,160 seven months-ish. 348 00:22:24,600 --> 00:22:27,080 Yeah, it went pretty fast. 349 00:22:27,180 --> 00:22:31,240 I mean, you know, I, I'm sure there were days if I look back that, you know, it seemed like 350 00:22:31,240 --> 00:22:35,560 it was, it was long because we were trying to make some, some really crucial decisions. 351 00:22:35,560 --> 00:22:36,920 I, you know, it makes me laugh. 352 00:22:37,020 --> 00:22:43,240 I'm thinking back to when, when it was just, you know, the CEO of myself going there on 353 00:22:43,240 --> 00:22:46,040 a regular basis before we had hired the rest of the team. 354 00:22:46,160 --> 00:22:50,420 And we had to kind of, along with the Pivotal team who was helping us, of course, you know, 355 00:22:50,420 --> 00:22:53,300 decide what, what tech stack we were going to go with. 356 00:22:53,340 --> 00:22:56,760 And I, boy, I'd never had to, you know, make those decisions. 357 00:22:56,760 --> 00:23:02,040 Of course, I, I had some friends to, to call, thankfully in the Bay area and Pivotal was 358 00:23:02,040 --> 00:23:04,660 wonderful at kind of giving us the pros and cons. 359 00:23:04,660 --> 00:23:06,960 But, but yeah, it was a fast process. 360 00:23:06,960 --> 00:23:14,720 And, but I think, I think they were also good and kind of pushing us through, they being 361 00:23:14,720 --> 00:23:21,420 Pivotal, pushing us through some of those areas where given, I might not think I have enough 362 00:23:21,420 --> 00:23:25,680 expertise pushing us along because, you know, we did need to move fast. 363 00:23:25,800 --> 00:23:27,620 There were timelines and expectations. 364 00:23:27,620 --> 00:23:31,520 And so I appreciated, we weren't moving fast carelessly. 365 00:23:31,520 --> 00:23:37,540 It was pretty thoughtful, but I think I appreciated having someone move us along and say, okay, 366 00:23:37,680 --> 00:23:41,560 we need a decision by this date because if we don't, it's going to delay this, this, and 367 00:23:41,560 --> 00:23:41,820 this. 368 00:23:42,100 --> 00:23:42,120 So. 369 00:23:43,480 --> 00:23:43,880 Yeah. 370 00:23:43,920 --> 00:23:48,780 And I'll assume just knowing the Pivotal Lab scene that, I mean, the, the, you, even if 371 00:23:48,780 --> 00:23:53,580 it's a, even if it's a fast decision on the tech front that it's designed with modularity 372 00:23:53,580 --> 00:23:55,600 for lack of a better term, right? 373 00:23:55,600 --> 00:23:57,260 So if something needs to change. 374 00:23:59,200 --> 00:24:02,580 So I'm curious too, what, like how big is the team now? 375 00:24:02,660 --> 00:24:05,640 So what, what kind of a tech team do you have in place at this point? 376 00:24:06,260 --> 00:24:06,500 Yeah. 377 00:24:06,500 --> 00:24:08,940 So we've got, we've got three developers. 378 00:24:08,940 --> 00:24:14,180 We have, as far as our product delivery team, we've got three developers, we've got a product 379 00:24:14,180 --> 00:24:21,420 designer and a product manager, all whom were vetted and worked very closely with their Pivotal 380 00:24:21,420 --> 00:24:22,220 Labs counterpart. 381 00:24:22,760 --> 00:24:27,740 And, you know, depending on, depending on when someone joined, you know, one of our engineers 382 00:24:27,740 --> 00:24:29,260 joined in August of last year. 383 00:24:29,260 --> 00:24:33,280 So he probably got the most exposure to working with Pivotal. 384 00:24:33,280 --> 00:24:38,180 So they all got, you know, some exposure, but it varied depending on the length of their, 385 00:24:38,480 --> 00:24:39,780 you know, when their start date was. 386 00:24:39,940 --> 00:24:48,040 But I know that I think each of them really, again, going back to, I think, I think having, 387 00:24:48,360 --> 00:24:52,900 having the knowledge that we were working with Pivotal and letting that be part of the recruiting 388 00:24:52,900 --> 00:24:53,440 process. 389 00:24:53,440 --> 00:24:59,080 And we, we followed one of the, the, well, several of the Pivotal sort of interview steps 390 00:24:59,080 --> 00:25:05,180 and that we, we wanted people to come onsite and spend, depending on the role, half day to 391 00:25:05,180 --> 00:25:07,460 a full day working with our team. 392 00:25:07,540 --> 00:25:12,020 And so for the engineers, that meant coming to Denver at the time, which it sounds like, 393 00:25:12,340 --> 00:25:18,840 Derek, you have been around some of the engineering recruiting in the Bay Area or, or know of it 394 00:25:18,840 --> 00:25:24,280 much like I do, you know, that's, that's a bit abnormal to ask someone to come in for a 395 00:25:24,280 --> 00:25:26,860 day and spend their day pair programming. 396 00:25:27,200 --> 00:25:32,400 But I think that really helped us determine, again, going back to that collaborative piece, 397 00:25:32,520 --> 00:25:35,680 really helped us determine who was going to be a good fit. 398 00:25:35,840 --> 00:25:41,200 So all of that to say, you know, I guess we're still a pretty lean and mean team because we're 399 00:25:41,200 --> 00:25:42,360 at our seed stage. 400 00:25:42,680 --> 00:25:48,420 And so, you know, we'll be continuing to pursue fundraising next year. 401 00:25:48,760 --> 00:25:52,600 But, you know, I, I, I think they're a, they're a pretty mighty team because they've learned 402 00:25:52,600 --> 00:25:58,000 some good practices and I've really been amazed at the speed that they've been able to, to 403 00:25:58,000 --> 00:26:01,420 crank out good software, even after we had finished our engagement. 404 00:26:01,420 --> 00:26:03,760 So that's awesome. 405 00:26:04,220 --> 00:26:10,120 And I was in the Bay Area, it would have been a whole day of flying out and being put through 406 00:26:10,120 --> 00:26:15,380 mental gymnastics that no one could reasonably expect, be expected to answer and solving the 407 00:26:15,380 --> 00:26:17,160 most complex algorithmic problems. 408 00:26:17,300 --> 00:26:18,980 So, yeah, that's probably a better approach. 409 00:26:20,120 --> 00:26:22,000 Yeah, that, that, that's really true. 410 00:26:22,240 --> 00:26:26,920 And Lori, I was going to ask, you know, you talk about the lean and mean team that you've 411 00:26:26,920 --> 00:26:33,080 got and, and kind of getting started with these pivotal labs methodologies that we often help 412 00:26:33,080 --> 00:26:36,540 our, our customers adopt, including pair programming. 413 00:26:36,540 --> 00:26:41,100 And, you know, it's not a fit for everyone, but a lot of our clients actually find it really 414 00:26:41,100 --> 00:26:41,580 effective. 415 00:26:41,640 --> 00:26:49,260 And I was also just curious to hear kind of how the team has adapted to working remotely with 416 00:26:49,260 --> 00:26:49,840 the pandemic. 417 00:26:49,840 --> 00:26:55,500 I mean, maybe they were a distributed team before, maybe not, but how's that gone? 418 00:26:56,180 --> 00:26:57,660 You know, that's a really great question. 419 00:26:57,760 --> 00:27:02,540 I think, you know, and I, I keep in touch, obviously, with a lot of my friends who are 420 00:27:02,540 --> 00:27:03,780 still in the Bay Area. 421 00:27:03,780 --> 00:27:09,580 And I know, you know, it seems like companies have had varying levels of success with that. 422 00:27:09,720 --> 00:27:17,140 I actually think that, you know, working with pivotal set us up really well to be able to 423 00:27:17,140 --> 00:27:19,520 work remotely effectively. 424 00:27:19,920 --> 00:27:23,720 Because essentially, we weren't, you know, we weren't necessarily spending, you know, our 425 00:27:23,720 --> 00:27:29,960 engineers, our designers, our product manager, wasn't spending necessarily every week in Denver. 426 00:27:30,180 --> 00:27:33,120 And so there might be a week where they were there. 427 00:27:33,120 --> 00:27:35,300 And then there might be a week where they were in Salt Lake. 428 00:27:35,300 --> 00:27:40,580 And if they were in Salt Lake, that probably meant that one of the, the Lucio engineers 429 00:27:40,580 --> 00:27:43,360 was pairing with a pivotal engineer in Denver. 430 00:27:43,580 --> 00:27:50,660 And so I think just naturally, the team had had to be able to cope with being in person, but 431 00:27:50,660 --> 00:27:51,540 also being remote. 432 00:27:51,540 --> 00:27:59,940 So, you know, I didn't, I, we haven't noticed a drop in productivity really since the pandemic, 433 00:27:59,940 --> 00:28:05,580 other than, you know, I think everyone, maybe across the world is a little burnout on video 434 00:28:05,580 --> 00:28:11,140 calls, perhaps, but, but I haven't really lost, we haven't really lost any productivity. 435 00:28:11,140 --> 00:28:16,980 And I think the work that they had to do with Pivotal being remote some weeks and in person 436 00:28:16,980 --> 00:28:19,860 some weeks really prepared them well to be able to do that. 437 00:28:20,120 --> 00:28:21,220 We needed to, so. 438 00:28:22,040 --> 00:28:22,300 All right. 439 00:28:22,620 --> 00:28:22,780 Cool. 440 00:28:23,000 --> 00:28:27,800 And Laurie, what, what step, I mean, so obviously you're in the pilot phase with, with this initial 441 00:28:27,800 --> 00:28:34,480 application, I mean, if you look at your overall roadmap, at least the existing roadmap, like 442 00:28:34,480 --> 00:28:40,020 how far along would you say you are and when, what, and what role does Pivotal play or does 443 00:28:40,020 --> 00:28:44,580 LAPS play in going forward in, in that, in, in the, in that future? 444 00:28:45,000 --> 00:28:45,200 Yeah. 445 00:28:45,540 --> 00:28:50,660 I mean, I, you know, I've, I've never, at least I've never worked at a startup that had 446 00:28:50,660 --> 00:28:51,540 an end to their roadmap. 447 00:28:51,540 --> 00:28:57,220 So it's hard to perhaps put it into it, but I think, you know, we started with some of the, 448 00:28:57,220 --> 00:28:58,720 the things that we thought were basics. 449 00:28:58,720 --> 00:29:03,460 And I think, you know, one of the things we're really focused on now is how can we enhance 450 00:29:03,460 --> 00:29:04,620 the patient experience? 451 00:29:04,620 --> 00:29:10,540 And so bringing more value to patients, I've been sitting in on a number of, which when 452 00:29:10,540 --> 00:29:14,960 I have time, I, I still love to do a number of the user research interviews. 453 00:29:14,960 --> 00:29:17,300 And we've been doing those for patients recently. 454 00:29:17,440 --> 00:29:23,360 Before that, we were really doing some work on trying to enhance the experience for the 455 00:29:23,360 --> 00:29:26,980 care team and their staff, you know, the doctors, the nurses. 456 00:29:26,980 --> 00:29:32,660 Really, as anyone who's been in the clinic or perhaps, you know, on a telehealth visit more 457 00:29:32,660 --> 00:29:38,060 recently, you know, they don't have a whole lot of time to prepare for your visit because, 458 00:29:38,260 --> 00:29:40,840 you know, there's someone before you, there's someone after you. 459 00:29:40,920 --> 00:29:45,140 Like there's, there's just not a whole lot of time to do a lot of research before. 460 00:29:45,320 --> 00:29:52,160 And so the name of the game, at least in my experience is trying to make that as easy for 461 00:29:52,160 --> 00:29:56,840 them to digest and making that information that is going to be the most helpful in their 462 00:29:56,840 --> 00:30:00,080 decision-making, making sure that that's surfaced in an easy way. 463 00:30:00,080 --> 00:30:08,040 So making sure that we have a clear next step guidance based on how the patient scored, those 464 00:30:08,040 --> 00:30:12,220 things we want to continue to enhance for the providers as we build out. 465 00:30:12,700 --> 00:30:18,020 And then longer term, I think we see ourselves, we're, we're not a, you know, there's a lot 466 00:30:18,020 --> 00:30:23,660 of mobile apps in mental health, for example, not just telehealth mobile apps, but, you know, 467 00:30:23,700 --> 00:30:27,580 apps that might help you with meditation or, or things like that. 468 00:30:27,580 --> 00:30:33,660 And I think longer term, the vision is to be able to perhaps be part of, you know, enable 469 00:30:33,660 --> 00:30:40,760 an ecosystem where we can support all of those different, those therapies that might help 470 00:30:40,760 --> 00:30:46,000 someone and recognizing that everyone's different, that, you know, some people may prefer some 471 00:30:46,000 --> 00:30:50,700 in-person activities while other people might prefer to use a mobile app. 472 00:30:50,700 --> 00:30:56,720 And we, we want to be the, you know, the enabler that helps people understand if there's a concern 473 00:30:56,720 --> 00:31:01,340 or a risk that they might need to address, that they have a comfortable place to do that, 474 00:31:01,400 --> 00:31:06,340 that we help them ask the right questions with their provider and that we can, even though 475 00:31:06,340 --> 00:31:11,100 it might not be our product, because there, there are plenty of, plenty of apps out there 476 00:31:11,100 --> 00:31:16,060 that had already do a number of great things that we could be sure to refer them to some that 477 00:31:16,060 --> 00:31:19,540 are known to be effective based on what their goals are. 478 00:31:20,260 --> 00:31:24,500 And what kind of a role, and maybe you alluded to this and I missed it, but what kind of a 479 00:31:24,500 --> 00:31:25,140 role do you see? 480 00:31:25,340 --> 00:31:28,840 Do you see labs helping out as you, as you've done that path? 481 00:31:29,300 --> 00:31:29,700 Yes. 482 00:31:29,760 --> 00:31:30,740 I left out that part. 483 00:31:31,120 --> 00:31:37,020 You know, you know, who, who knows down the road, I think while I've had some of my, my 484 00:31:37,020 --> 00:31:42,980 companies that, you know, I've seen start off with Pivotal Labs just as, just as we have, 485 00:31:43,040 --> 00:31:44,760 or known of companies that have done that. 486 00:31:44,900 --> 00:31:50,080 I've also been with startups who, you know, started with an engagement with Pivotal Labs 487 00:31:50,080 --> 00:31:56,000 and then found, you know, at some point later that, that they needed, you know, you know, 488 00:31:56,000 --> 00:31:57,820 two very different work streams perhaps. 489 00:31:58,140 --> 00:32:03,080 And they didn't have all the staff internally to execute on both. 490 00:32:03,080 --> 00:32:08,120 And so I think that's naturally a great place. 491 00:32:08,120 --> 00:32:13,560 If you've maintained a lot, I mean, probably, you know, even if you haven't maybe maintained 492 00:32:13,560 --> 00:32:16,620 the practices that, that Pivotal teaches perfectly. 493 00:32:16,620 --> 00:32:22,640 But I think if, you know, for us, we're, we're really trying to maintain our extreme program 494 00:32:22,640 --> 00:32:23,840 and agile practices. 495 00:32:23,840 --> 00:32:30,100 And so I think if we found ourself in a situation where we signed a big customer contract and 496 00:32:30,100 --> 00:32:36,060 there were a lot of deliverables that it was going to be hard to see how the team by itself 497 00:32:36,060 --> 00:32:41,100 was going to be able to execute on all of those, that that might be a natural place for us to, 498 00:32:41,100 --> 00:32:46,660 you know, go back docking on Pivotal's door and say, okay, we want to tackle both of these 499 00:32:46,660 --> 00:32:47,220 things. 500 00:32:47,220 --> 00:32:50,420 We're thinking we can section this off. 501 00:32:50,420 --> 00:32:53,420 Like, can we define this as a project that we could work on with you? 502 00:32:53,420 --> 00:32:54,380 Something like that. 503 00:32:55,820 --> 00:32:56,300 All right. 504 00:32:56,300 --> 00:32:57,380 Yeah, that sounds fair. 505 00:32:57,560 --> 00:32:59,640 Teach a man to fish and whatnot, right? 506 00:32:59,860 --> 00:33:01,120 And I've heard that from other customers too. 507 00:33:01,220 --> 00:33:06,600 Like actually a big, the big, a big, a big point of pride was we built this on our own. 508 00:33:06,740 --> 00:33:07,060 Yeah. 509 00:33:07,380 --> 00:33:09,200 We got the skills to build this on our own. 510 00:33:09,320 --> 00:33:10,300 So that's a good thing. 511 00:33:10,340 --> 00:33:14,540 I know our developers were, I think, I think it was bittersweet. 512 00:33:14,680 --> 00:33:15,800 They were very sad. 513 00:33:15,880 --> 00:33:21,240 We really enjoyed every single person at the, at the Denver office that we worked with. 514 00:33:21,240 --> 00:33:23,260 They were just, just all fantastic. 515 00:33:23,260 --> 00:33:28,000 And, you know, we had a little farewell Zoom party because I guess that's the best you could 516 00:33:28,000 --> 00:33:33,060 do during COVID and had some, you know, accolade sharing and such. 517 00:33:33,180 --> 00:33:38,540 And so I know that everyone was sad to leave, but they were also really proud of, you know, 518 00:33:38,540 --> 00:33:43,260 the first feature or set of features that they delivered, you know, sort of without the 519 00:33:43,260 --> 00:33:46,480 training wheels, if you will, but we had, we had a fabulous experience. 520 00:33:46,480 --> 00:33:48,960 So I, I think it was bittersweet. 521 00:33:49,040 --> 00:33:50,480 That's probably the best way to describe it. 522 00:33:51,360 --> 00:33:56,960 I had kind of just a higher level question just about, you know, startups or, or maybe 523 00:33:56,960 --> 00:33:59,320 even this applies to larger companies too. 524 00:33:59,780 --> 00:34:05,320 Just in your experience, what do you think is, you know, the biggest disconnect there between 525 00:34:05,320 --> 00:34:11,240 really bridging that domain expertise, you know, like you came in with your business partner 526 00:34:11,240 --> 00:34:17,640 and, and all of this research around these psychological assessments, you came in with all this, all 527 00:34:17,640 --> 00:34:24,000 this really rich domain expertise, but then you needed to kind of bridge that with the technology. 528 00:34:24,540 --> 00:34:29,060 And just kind of wondering, like, where do you see the biggest disconnect there for folks 529 00:34:29,060 --> 00:34:29,960 being able to do that? 530 00:34:30,960 --> 00:34:36,940 Yeah, I think, I think, you know, and speaking from personal spirit, I think it's, it's, it's 531 00:34:36,940 --> 00:34:43,080 often very hard. And I think in healthcare, traditionally, a lot of the software has not 532 00:34:43,080 --> 00:34:50,580 been perhaps as modern or modern built as, as, you know, I don't know, FinTech or the travel 533 00:34:50,580 --> 00:34:57,720 industry or some, you know, where a lot of interesting companies with modern software have, have come 534 00:34:57,720 --> 00:35:05,100 out of, and, and so I think, I think Pivotal's process and structure around, you know, it's, 535 00:35:05,100 --> 00:35:11,480 it's agnostic to industry, right? And I think that's why it's so great, because it really helps 536 00:35:11,480 --> 00:35:18,380 you focus on the most important things. And I think it challenges those of us who, and even 537 00:35:18,380 --> 00:35:23,280 though I've worked in, in healthcare startups, healthcare, as far as technology, has just always 538 00:35:23,280 --> 00:35:29,780 been a little bit behind a lot of other industries. And so you don't want to just bring, you know, 539 00:35:29,820 --> 00:35:34,700 I'll say, some of the bad habits, perhaps of technologies of the past, you want to make 540 00:35:34,700 --> 00:35:39,220 sure that you're challenging yourself and, and building your software such that that's going 541 00:35:39,220 --> 00:35:46,180 to be an advantage and an asset to you, so that you can pivot and, and, and move quicker 542 00:35:46,180 --> 00:35:51,060 than perhaps some of the larger, more established companies. I mean, in the end, that's usually 543 00:35:51,060 --> 00:35:56,380 the advantage for a startup, right? And so I think because the Pivotal process is agnostic, 544 00:35:56,380 --> 00:36:02,640 it sort of challenges even those industry experts. And again, we were not, those of us who started 545 00:36:02,640 --> 00:36:07,140 were not industry experts in building software, but we had been, you know, around a lot of these 546 00:36:07,140 --> 00:36:12,480 companies, it really challenges you to make sure that you're building the right thing. And you're 547 00:36:12,480 --> 00:36:17,060 really focused on the user. And then you're focused on what are the metrics that you're trying to 548 00:36:17,060 --> 00:36:23,100 move as opposed to, this is what we think we should build, because this is what every company 549 00:36:23,100 --> 00:36:27,940 always builds when they start. I think it was a healthy process of challenging us to make sure 550 00:36:27,940 --> 00:36:32,480 that we were, you know, again, staying true to that North Star. So I don't know if that answered 551 00:36:32,480 --> 00:36:35,820 your question exactly, but that's how I think about it, at least. 552 00:36:37,040 --> 00:36:40,540 Interesting. Yeah. I assume some of that too, is just a function of, and healthcare maybe is an 553 00:36:40,540 --> 00:36:45,640 industry where it's prevalent to buy off the shelf software versus building stuff, custom software, 554 00:36:45,640 --> 00:36:49,420 which actually solves the exact problem you have versus kind of. 555 00:36:49,440 --> 00:36:49,920 That's true. 556 00:36:51,600 --> 00:36:54,980 Yeah. You see that in other industries too. And it's just like, yeah, at some point they, 557 00:36:55,140 --> 00:37:01,000 a lot of companies wake up and say, okay, we can't, we can't wait for the, our vendor to address this 558 00:37:01,000 --> 00:37:04,140 issue we need. Right. Or we can't be, or we just want something different. 559 00:37:04,680 --> 00:37:09,120 Right. Like it sounds like kind of what you're alluding to a little bit is, you know, 560 00:37:09,120 --> 00:37:13,260 changing your mindset to, instead of thinking about software is like, oh, we've, 561 00:37:13,260 --> 00:37:18,500 this is something we have to do. It's like thinking about it as how can you leverage your 562 00:37:18,500 --> 00:37:25,700 expertise to your competitive advantage using software as, you know, the medium for that. 563 00:37:26,120 --> 00:37:30,880 You know, the other, the other interesting thing that makes me think of is the, the, 564 00:37:31,000 --> 00:37:37,580 one of the product managers that we worked with in Denver was really good at reminding us. 565 00:37:37,580 --> 00:37:42,240 And I didn't, you know, I didn't pick up on the parallel myself at first. She was really good at 566 00:37:42,240 --> 00:37:49,260 reminding us that we were actually very similar to pivotal labs because we were building the software, 567 00:37:49,260 --> 00:37:55,020 but in the end, you know, this is behavior change that has to happen in primary care. 568 00:37:55,400 --> 00:37:59,620 We're, we're having to teach the team and the clinic how to operate a little bit different 569 00:37:59,620 --> 00:38:06,320 because traditionally mental health has not been a core part of, um, the healthcare delivery in primary care. 570 00:38:06,460 --> 00:38:12,820 And so I remember her telling me one day, you know, yes, we're building software and that's going to solve this problem, 571 00:38:12,820 --> 00:38:20,060 but there's also the services part. And so just as, you know, pivotal labs makes perhaps our software approach sticky, 572 00:38:20,060 --> 00:38:25,740 you know, it's because we've got this services model that really supports that. And that really clicked for me. 573 00:38:25,800 --> 00:38:29,700 And I think we were able to draw a lot of parallels as we were thinking about, 574 00:38:30,040 --> 00:38:34,520 and that is closer to my area of expertise is, is sort of the customer success realm, 575 00:38:34,520 --> 00:38:40,380 thinking about how we were learning things for the first time and how, you know, 576 00:38:40,420 --> 00:38:44,520 the pivotal model helped make some of the practices that we were trying to implement more sticky, 577 00:38:44,520 --> 00:38:47,300 um, because of the way they've married those two. So. 578 00:38:48,500 --> 00:38:51,920 Right. I don't know, Danielle, that seems like a good place to end unless you have any other, 579 00:38:52,080 --> 00:38:56,000 other questions. So once we tie the learning culture and it feels like a complete story. 580 00:38:56,660 --> 00:38:58,700 Yeah, this has been really great. Thank you.