Meeting Title: ABC Data Team Operations Check-in Date: 2025-12-15 Meeting participants: David L, Uttam Kumaran, Amber Lin
WEBVTT
1 00:03:18.860 ⇒ 00:03:20.019 David L: Hey, what’s on?
2 00:03:31.940 ⇒ 00:03:34.069 Uttam Kumaran: Hey, David. Sorry, my,
3 00:03:34.350 ⇒ 00:03:40.319 Uttam Kumaran: my, I’m at a WeWork, and my, like, Wi-Fi just, like, turned off randomly, so sorry about the delay.
4 00:03:40.730 ⇒ 00:03:42.600 David L: All good. Good morning, how are ya?
5 00:03:42.810 ⇒ 00:03:43.959 Uttam Kumaran: Good, how are you?
6 00:03:44.280 ⇒ 00:03:46.900 David L: So far, so good. It’s a Monday, so, you know, staying.
7 00:03:46.900 ⇒ 00:03:47.810 Uttam Kumaran: Yeah.
8 00:03:47.810 ⇒ 00:03:48.180 David L: Yeah.
9 00:03:48.180 ⇒ 00:03:50.000 Uttam Kumaran: How’s the… how’s the month been?
10 00:03:51.120 ⇒ 00:03:58.690 David L: Pretty crazy, but good. Okay. You know, I’d rather stay busy than have nothing to do and be twiddling my thumbs.
11 00:03:58.690 ⇒ 00:04:02.040 Uttam Kumaran: What’s been, what’s, what’s been crazy?
12 00:04:02.490 ⇒ 00:04:13.780 David L: Just the way that everything’s been falling with all the holiday parties and everything coming about, people taking holidays, it’s just kind of been… putting all the puzzle pieces together has been a touch hectic, but…
13 00:04:14.110 ⇒ 00:04:16.339 David L: You know, tis the season.
14 00:04:16.700 ⇒ 00:04:21.529 Uttam Kumaran: Yeah, yeah, that’s awesome. No, we’ve had a… we’ve had a great month, like, I… I don’t know if,
15 00:04:21.829 ⇒ 00:04:36.229 Uttam Kumaran: the team has mentioned, but we’re sort of doing this discovery project, you know, around ABC and finding out, you know, different various areas where data and analytics can be, you know, more helpful.
16 00:04:36.230 ⇒ 00:04:44.630 Uttam Kumaran: And it’s been awesome, like, I got a chance to meet with Les, I met with Julie last week, I met with Bo and Steven a couple times.
17 00:04:44.630 ⇒ 00:04:52.759 Uttam Kumaran: you know, talk to Matt, and sort of… we’re just getting a little bit of a canvas of, you know, where data lives in ABC, and…
18 00:04:52.760 ⇒ 00:04:57.350 Uttam Kumaran: You know, what are different ways that, you know, we can assist in thinking about
19 00:04:57.350 ⇒ 00:05:16.030 Uttam Kumaran: more opportunities to… to use data to understand, like, where customers are coming from, who’s converting, and, like, how do we reduce churn and sort of reactivate some folks. So that’s, like, the broader sort of idea here. I mean, of course, we worked together, you know, on the Andy project, and so everybody mentioned your name throughout the whole process.
20 00:05:16.270 ⇒ 00:05:29.110 Uttam Kumaran: So, kind of like this conversation is just to hear from you and, like, give you an avenue to talk about a couple things, like, and I’m happy to steer. One, I broadly want to hear about what are the…
21 00:05:29.220 ⇒ 00:05:43.169 Uttam Kumaran: daily, weekly, like, monthly reporting activities that you sort of work on. I do have some clarity on that, of course, from some of the stuff I’ve seen from Yvette, from Julie, so that would be helpful. I also just want to hear a little bit, like.
22 00:05:43.170 ⇒ 00:05:55.889 Uttam Kumaran: how easy or hard is it to do data work here? You know, like, are you finding yourself… for a couple example questions are, like, how much time are you spending, like, downloading CSVs? Like, how much time is spent
23 00:05:55.900 ⇒ 00:06:15.659 Uttam Kumaran: Like, if you had access to more data, more up-to-date data, what are some of the things that that can unlock? I also want to hear about, like, okay, given that maybe there’s a lot of time that goes into manipulation or redoing Excel files, if that were solved, like, what would that free you up to do? So part of my job is also explaining to leadership, like.
24 00:06:15.700 ⇒ 00:06:32.809 Uttam Kumaran: the ecosystem of, like, analytics at ABC, like, how hard is it for a data person to take a question on Monday and get an answer by Friday? You know, or is that even possible? So those are, like, kind of the things I want to hear, so I just want to, like, we have a… we have some time booked today, but those are kind of, like.
25 00:06:33.020 ⇒ 00:06:36.230 Uttam Kumaran: The steering questions, you know, for me today.
26 00:06:36.460 ⇒ 00:06:41.540 David L: Yeah, got it. Well, let’s… you laid a lot out on the table, Ludin, so I’m gonna try to…
27 00:06:41.670 ⇒ 00:06:43.810 David L: Shoe it bit by bit.
28 00:06:44.180 ⇒ 00:06:54.190 David L: So, our duties when they come to data is putting together, like, all the KPIs, normally for the call center and for the technicians in the company, pretty much as a whole.
29 00:06:54.210 ⇒ 00:07:06.649 David L: We do, some on weekly basis, which is, like, our pest technician KPIs, and our sales inspectors KPIs, we do on a weekly basis. Everything else is done on a monthly basis.
30 00:07:06.680 ⇒ 00:07:14.420 David L: with the exception of our call center, reporting, which is done on a daily basis. All of those
31 00:07:14.660 ⇒ 00:07:29.930 David L: reports are formulated or generated from various sources. It could be a combination of, like, Involve, and from Dream, or Quasito, whichever one we do it to, that does our sales KPIs are done from that.
32 00:07:30.400 ⇒ 00:07:34.589 David L: 8x8 is where our call center stuff comes from.
33 00:07:34.640 ⇒ 00:07:37.429 David L: And then our go-get quality is a…
34 00:07:37.430 ⇒ 00:07:57.900 David L: third site, which is also run by Quasito, which does our NPS scoring, and our complements are done from there. Compliments are also done weekly as well. So we kind of have to go back and forth between these systems to get what we need, and a pain point that we’re experiencing is that the data is not
35 00:07:58.030 ⇒ 00:08:21.920 David L: at all standardized across any of them, specifically when it comes to the naming conventions. That’s currently the hurdle that we’re trying to tackle and kind of smooth out that wrinkle, because in Evolve, the technicians’ names are one way, in Quasito, they’re different. In 8x8, it’s another way, and then in another system, which I failed to implement, is called Forshaw, which is where technicians go and check out their chemical
36 00:08:21.920 ⇒ 00:08:26.579 David L: or their materials, And it’s different in that, too. And so.
37 00:08:26.580 ⇒ 00:08:27.080 Uttam Kumaran: Yeah.
38 00:08:27.080 ⇒ 00:08:32.830 David L: Finding some sort of standardization where we could automate something makes it a little bit more challenging, because
39 00:08:32.990 ⇒ 00:08:36.780 David L: the information isn’t there. We just have to pretty much…
40 00:08:36.960 ⇒ 00:08:40.999 David L: Create these complex formulas to get the names to all align together, and even then…
41 00:08:41.000 ⇒ 00:08:41.580 Uttam Kumaran: Yeah, yeah, yeah.
42 00:08:41.580 ⇒ 00:08:44.850 David L: not… it’s not clean, you know? Okay.
43 00:08:45.040 ⇒ 00:09:00.789 David L: So that’s currently where we’re at. Then monthly ones are kind of done in the same vein, but because we have to wait for Evolve to close out their data for the month prior, it makes it kind of, a little bit challenging, because it’s kind of that…
44 00:09:01.970 ⇒ 00:09:10.909 David L: shut up and wait sort of thing, and then when the… when the month is closed out, it’s like, go, go, go! Everyone wants their data all at once, and there’s only
45 00:09:10.910 ⇒ 00:09:23.509 David L: so many of us. And so, at that point, downloading the reports does take a hot minute, because at that point, we’re running reports for the whole month, and so for Evolve to batch that data and spit it out to us.
46 00:09:23.540 ⇒ 00:09:32.770 David L: Whilst everyone else is also looking to get that same information across the company, supervisors and managers are also pulling their reports, it does make it a little bit
47 00:09:32.840 ⇒ 00:09:39.909 David L: tedious, or it does make that process a little bit slower. We asked about getting,
48 00:09:40.090 ⇒ 00:09:46.549 David L: scheduled reports out from Evolve, but that has… I don’t know that there’s been much…
49 00:09:47.320 ⇒ 00:09:57.359 David L: in that realm. I don’t know what the possibility of that is. From what I understand, the way that Evolve is built doesn’t really quite have that capability, though that would be…
50 00:09:57.420 ⇒ 00:10:12.809 David L: fantastic. We do have scheduled reports from 8x8 and from, Dream that come in, and that’s really, really helpful, because at that point, we can just come in or set up an automation to download that report and start parsing it.
51 00:10:13.230 ⇒ 00:10:33.169 David L: But for the most part, having to wait on Evolve is the big thing. 8x8, since it’s a pretty limited data set from just the call center agents, it doesn’t really take that long, and again, we have those scheduled anyways, so not really a big deal there. It’s Evolve, where the majority of our data comes for the KPIs, and that’s where it becomes a little bit…
52 00:10:33.260 ⇒ 00:10:36.530 David L: Can slow down to a crawl at that point.
53 00:10:36.530 ⇒ 00:10:38.079 Uttam Kumaran: Okay. Yeah. Okay.
54 00:10:38.660 ⇒ 00:10:43.790 David L: All right, I forgot the other questions, sorry.
55 00:10:43.790 ⇒ 00:10:50.680 Uttam Kumaran: Yeah, I guess my other question also is, like, what is, like, your team structure? Like, how are you working with others and collaborating on…
56 00:10:50.790 ⇒ 00:10:55.110 Uttam Kumaran: You know, reporting, is it pretty isolated, or… yeah, give me a sense of that.
57 00:10:55.600 ⇒ 00:11:05.689 David L: Not so much so. So right now, we definitely… our priority is within the call center, because that’s where we’ve begun, and our responsibility is to start to kind of grow out from there into the other
58 00:11:05.890 ⇒ 00:11:08.299 David L: parts of the company, so… Okay.
59 00:11:08.300 ⇒ 00:11:27.729 David L: we have taken over the KPIs for the whole company, and it started off, like, division by division. The PEST KPIs were pretty well established. That department has been running their KPIs the longest, and that process has been pretty well established. There are some changes, some tweaks that are coming up starting January 1, but for the most part, everything is set as is.
60 00:11:27.730 ⇒ 00:11:28.610 David L: Okay.
61 00:11:28.610 ⇒ 00:11:47.290 David L: when we had that process handed over to us, we did a lot of cleanup efficiency-wise, because the way that it was being pulled and or, like, put together before was not to our standards. So, like, we just kind of redid it, and we made it better, but there’s still some room for improvement there. I have
62 00:11:47.290 ⇒ 00:11:48.950 David L: No doubt.
63 00:11:48.950 ⇒ 00:11:49.570 Uttam Kumaran: Okay.
64 00:11:49.570 ⇒ 00:12:09.450 David L: And so we definitely work with those division managers really closely, not only the pest department, but from the mechanical department, from the home improvement department, from the sales department, because we work with both hand-in-hand on those, and so… but typically, once the KPIs are set, they’re set, we have communication come to us as far as I…
65 00:12:09.450 ⇒ 00:12:12.310 Uttam Kumaran: Is there yearly, or is it quarterly, or monthly?
66 00:12:12.310 ⇒ 00:12:19.049 David L: The KPIs are done monthly for the technicians. Okay. Yeah, except for the pest department. The pest department is done weekly.
67 00:12:19.770 ⇒ 00:12:20.310 Uttam Kumaran: Okay.
68 00:12:20.950 ⇒ 00:12:40.789 David L: But everything else is monthly, yeah. And I’m sure they would like to… I know that some of them would like to see that done more often, but the problem with that is that the majority, again, of our KPRs are measured with data from Evolve, and data from Evolve is never really accurate until the month closes out.
69 00:12:40.900 ⇒ 00:12:59.170 David L: And that’s because tickets could change, repairs could go in, things could be in flux there, so the final numbers that we have are not released until the beginning of the following month, so that does make it a little bit challenging to see an accurate representation of what those KPIs could be as the month progresses.
70 00:12:59.170 ⇒ 00:13:00.230 Uttam Kumaran: Okay, okay.
71 00:13:02.220 ⇒ 00:13:11.679 Uttam Kumaran: I guess, is that, like, a meeting that you’re… you’re owning on a monthly basis? Is that submitted usually, like, 2 weeks before the month? Like, what is the sort of process of collecting those?
72 00:13:12.270 ⇒ 00:13:14.430 David L: of collecting the data from Evolve.
73 00:13:14.610 ⇒ 00:13:15.420 David L: We’re on paper.
74 00:13:15.420 ⇒ 00:13:16.979 Uttam Kumaran: For the KPIs.
75 00:13:16.980 ⇒ 00:13:31.279 David L: Yeah, from the KPIs, we’re just… once the month closes out, we’re just going and we’re fetching that data. We know what the metrics are, we know which categories we’re looking at, we know which data… each metric has, like, a range that will assign a point system
76 00:13:31.280 ⇒ 00:13:41.259 David L: to that metric, so if I had 100% in my photos that I sent out, I’m gonna get, like, 13 points. If I have 70% of my photos sent out, I get 7 points.
77 00:13:41.260 ⇒ 00:13:55.410 David L: Yada. So we know what that template is, because that’s been established with those division managers already, and we kind of put together into everything into a scorecard, so to speak. We upload that for their teams to go in and check, like, on a Google Sheet.
78 00:13:55.550 ⇒ 00:14:05.939 David L: And then, after that, we may get some communication back as far as, like, hey, this was an error, or please disregard this, and we’ll kind of do updates at that point in time.
79 00:14:06.590 ⇒ 00:14:07.210 Uttam Kumaran: Okay.
80 00:14:07.690 ⇒ 00:14:11.610 Uttam Kumaran: Another question I had is, like, so these… are these…
81 00:14:11.730 ⇒ 00:14:17.309 Uttam Kumaran: Are you just sending out the KPIs? Is there, like, a meeting? Like, talk to me more, like.
82 00:14:17.510 ⇒ 00:14:19.070 Uttam Kumaran: I guess I’m more interested in, like.
83 00:14:20.140 ⇒ 00:14:30.880 Uttam Kumaran: more proactive analysis of, like, hey, you missed targets, and, like, here’s why. Julie was showing me the month-over-month KPI spreadsheets that I think, UNT produce.
84 00:14:30.880 ⇒ 00:14:41.620 Uttam Kumaran: like, when there are reds, are… are the branch managers or service leaders, like, are they asking questions? Or, like, what’s the sort of back and forth? Like, does it go beyond
85 00:14:41.640 ⇒ 00:14:44.379 Uttam Kumaran: Just, like, showing what the changes have been.
86 00:14:44.380 ⇒ 00:14:52.660 David L: Yeah, so right now, we currently have set up a monthly meeting with the pest division manager, so he’s the one that runs
87 00:14:52.730 ⇒ 00:15:06.000 David L: all of the past, and we’re meeting with him on a monthly basis to talk about route completion, to talk about those KPIs, and talk about any pain points that we experienced in the prior month, so that we can kind of coach going forward on this next, in the following months.
88 00:15:06.440 ⇒ 00:15:11.130 David L: That’s the only department right now that we have a scheduled monthly meet with.
89 00:15:11.370 ⇒ 00:15:20.749 David L: Since my team has just started doing the KPIs for the rest of the company, we are establishing those meetings moving forward, but we don’t currently have them on the books right now.
90 00:15:20.750 ⇒ 00:15:28.390 Uttam Kumaran: What is your team, David? Like, it’s you, and I, like, who else is, like, supporting, like, the scope, this whole scope as a whole?
91 00:15:28.390 ⇒ 00:15:28.830 David L: Yes.
92 00:15:28.830 ⇒ 00:15:29.150 Uttam Kumaran: time.
93 00:15:29.150 ⇒ 00:15:34.340 David L: So, right now, it is me and Brian Gonzalez. I believe you met him, he was in our initial meet for Andy.
94 00:15:34.380 ⇒ 00:15:49.220 David L: as well, and so it’s him and I that are doing the KPIs for everyone. We do have Austin Weaver on the team as well, but he’s mostly just the call center, real-time management, workforce manager in that realm. So because he’s got his hands full there.
95 00:15:49.220 ⇒ 00:15:49.620 Uttam Kumaran: Yeah.
96 00:15:49.620 ⇒ 00:15:52.760 David L: Right? Try not to give him any of this other stuff, because I know he’ll…
97 00:15:53.050 ⇒ 00:15:59.649 David L: much resources it takes, and I know he needs to be dedicated, so for right now, it’s, Brian and myself.
98 00:16:00.090 ⇒ 00:16:05.650 Uttam Kumaran: Do you feel, like, equipped enough to handle the rest of the business, in terms of, like.
99 00:16:05.860 ⇒ 00:16:09.159 Uttam Kumaran: running these types of reports, or like, what… let’s say the
100 00:16:09.300 ⇒ 00:16:15.220 Uttam Kumaran: let’s say you were just gonna have to, like, run, do the same thing for every part of the business. Like, what breaks first?
101 00:16:17.000 ⇒ 00:16:18.190 Uttam Kumaran: Hypothetically, like, this could be…
102 00:16:18.190 ⇒ 00:16:18.530 David L: Yeah.
103 00:16:18.530 ⇒ 00:16:23.139 Uttam Kumaran: medical with me, but I’m not, you know, I’ve been… I’m a data person as well. I’ve, you know.
104 00:16:23.140 ⇒ 00:16:23.570 David L: Yeah.
105 00:16:23.570 ⇒ 00:16:36.449 Uttam Kumaran: been a data person my whole career, so I understand the fact that, like, one division wants it and they want to scale, and this is actually really, really amazing, because this is the first I’m sort of hearing a little bit about, you know.
106 00:16:36.740 ⇒ 00:16:38.569 Uttam Kumaran: like…
107 00:16:39.170 ⇒ 00:16:48.640 Uttam Kumaran: how you’re thinking about the day-to-day data operations. And so, yeah, I’m wondering, like, let’s say you were to go turn this on for every client, like, what breaks?
108 00:16:49.380 ⇒ 00:16:54.910 David L: Yeah, unfortunately, like, call center stuff.
109 00:16:55.370 ⇒ 00:16:59.660 David L: I feel goes out the window. Not… B.
110 00:17:00.030 ⇒ 00:17:12.780 David L: the ability to go in-depth first, because that’s… that’s kind of like my baby, right? That’s where I started. And so, there’s been a lot of systems that have been created and put in place for the call center that now, as we start to expand.
111 00:17:13.099 ⇒ 00:17:26.139 David L: my attention is needed over here and over here, and so I feel like I’m not able to focus as much with Yvette and the call center if everything else starts to take its… it starts to pull me in those directions, and that sucks, because I…
112 00:17:26.200 ⇒ 00:17:34.200 David L: again, that’s… that’s my day one with Yvette and I. We’ve worked together since literally I’ve been here at the company. So, unfortunately, that stuff does…
113 00:17:35.230 ⇒ 00:17:40.459 David L: it does take a little bit longer, and right now, I do try to keep that as a priority before anything else, because
114 00:17:40.840 ⇒ 00:17:43.260 David L: Yeah, that’s, again, about where I…
115 00:17:43.350 ⇒ 00:18:01.639 David L: where I come from. But yeah, that definitely starts to go first. After that, it’s kind of like a domino effect of the timeline of things… things will still get done, they just won’t get done in… as an efficient or in a time-sensitive manner that I would prefer, or that I think that people expect, too.
116 00:18:02.830 ⇒ 00:18:10.950 Uttam Kumaran: And then, but do you have, like, sort of, like, a priority list? I mean, I… I totally get that, like, pest is the biggest, most well-defined. Do you have…
117 00:18:11.910 ⇒ 00:18:13.290 Uttam Kumaran: Yeah, yeah, yeah, okay, okay.
118 00:18:13.290 ⇒ 00:18:23.809 David L: Yeah, so as far as the priority one, when the month closes, I definitely start working on the call center stuff first, because a lot of that data is pulled from 8x8,
119 00:18:23.810 ⇒ 00:18:35.240 David L: And unlike Evolve, 8Byte doesn’t need to close out. They don’t need a few days to close out. Their data is already there, it’s finalized, I can start pulling that. So technically, the Evolve closes out the month.
120 00:18:35.900 ⇒ 00:18:37.089 David L: Probably on the…
121 00:18:37.200 ⇒ 00:18:44.499 David L: around the third, on average. The third day after the month begins, they close out, depending on when the business days fall, you know?
122 00:18:44.500 ⇒ 00:18:44.970 Uttam Kumaran: Yeah.
123 00:18:44.970 ⇒ 00:19:04.280 David L: So, between that time that Evolve is using to close out their data, I’m doing call center stuff, because I can pull the 8x8 stuff, I can start to put their scorecards together, I can put their KPIs together and get that out. Then, once the month closes and Evolve is official, then I start doing… the PEST stuff is, first and foremost, our biggest
124 00:19:04.280 ⇒ 00:19:07.280 David L: They’re our biggest department, so they go first.
125 00:19:07.280 ⇒ 00:19:14.450 David L: After that, it’s our mechanical and our home improvement department, and then the final one is our lawn department.
126 00:19:14.500 ⇒ 00:19:19.129 David L: Sales, and sales are done on a weekly basis, they just kind of fold in as well.
127 00:19:19.460 ⇒ 00:19:20.120 David L: Yeah.
128 00:19:20.120 ⇒ 00:19:22.219 Uttam Kumaran: Okay, and then… I guess, like.
129 00:19:23.230 ⇒ 00:19:25.549 Uttam Kumaran: I’m trying to think about, like, the broader…
130 00:19:25.910 ⇒ 00:19:28.750 Uttam Kumaran: Sort of process here, like.
131 00:19:29.650 ⇒ 00:19:35.150 Uttam Kumaran: Do you feel like, ultimately, in order to get data to everybody, it will have to…
132 00:19:35.480 ⇒ 00:19:44.719 Uttam Kumaran: be some type of, like, folks start fishing for themselves? Like, do you really feel like you and Brian are gonna be able to support the whole org, or, like.
133 00:19:44.880 ⇒ 00:20:04.829 Uttam Kumaran: you know, I’m just trying to think about things that we’ve seen in the past as, like, okay, maybe you two focus… like, for me, it’s always important that the people with the best understanding of data are focused on the, like, the hairiest problems, the things where the data isn’t very clean, versus we don’t want your time spent on, like, moving things into Excel, because
134 00:20:04.980 ⇒ 00:20:07.400 Uttam Kumaran: You’re, like, way smarter than that.
135 00:20:07.400 ⇒ 00:20:08.840 David L: to do that. Yeah, definitely.
136 00:20:08.840 ⇒ 00:20:16.329 Uttam Kumaran: You know, and so, not that I want to give you more work, but you’re a data person. You know, it’s fun to work on things that actually matter, versus…
137 00:20:16.330 ⇒ 00:20:16.680 David L: Sure.
138 00:20:16.680 ⇒ 00:20:35.700 Uttam Kumaran: dealing with Excel and stuff like that, like, is that… would that be, like, a fair way of thinking about, you know, how you think things should go? Or, like, just trying to… you know, if, like, Bobby were to ask me, okay, like, what’d you learn from conversation with David? Like, what do they need, or what does the data team need? Trying to think about, like, what I can explain to him.
139 00:20:35.930 ⇒ 00:20:55.400 David L: Yeah, so for sure, like, to answer your question about will Brian and I be able to do everything, like, long-term? Absolutely not. I’d ideally like to see at least one other person on board, but I know right now, with the way that the company is, that’s not really at their top of the priority. I feel that in their mind, it’s kind of like.
140 00:20:55.500 ⇒ 00:20:58.909 David L: Hey, things are running smoothly, they’re doing it, so, like.
141 00:20:59.090 ⇒ 00:21:08.189 David L: By all means. And sure, I think right now we are officially in our slow season, but come March, when we start to pick up, things might get a little bit
142 00:21:09.230 ⇒ 00:21:22.530 David L: tighter, for sure. Resources are going to be stretched thin. They already are, but we just have a little bit more breathing room, because we’re not as busy. We’re pretty slow right now. So ideally, I would like to get things in a place where
143 00:21:22.690 ⇒ 00:21:36.819 David L: we have a little bit more breathing room right now, if either Brian or I call out, like, there’s gonna be delays, for sure. Yeah. Because there’s things that he works on that I don’t, and vice versa, so that’s gonna…
144 00:21:37.650 ⇒ 00:21:43.369 David L: Could we each do each other’s? Absolutely, but with what we’ve got on our plate already, it makes it…
145 00:21:43.780 ⇒ 00:21:45.510 David L: pretty tight.
146 00:21:45.510 ⇒ 00:21:46.110 Uttam Kumaran: Okay.
147 00:21:46.350 ⇒ 00:22:00.740 David L: I would ideally like to also have some resources or some time in place to kind of look at everything that you’re talking about as a whole. I can’t really sit down and study the data as much as I’d like to, to identify those trends, to put together resources for the
148 00:22:00.750 ⇒ 00:22:07.569 David L: key players to utilize on a broad scope as I’d like, and that’d be one of the goals that I’d like to do.
149 00:22:07.840 ⇒ 00:22:15.189 David L: Get that moving forward, get that incorporated into our monthly meetings with them, so that they, you know, like, for the people at the executive level.
150 00:22:15.350 ⇒ 00:22:22.249 David L: they don’t have the time to go into the nitty details, you know? Like, that should be something that I’m providing to them, but right now, I’m…
151 00:22:22.970 ⇒ 00:22:25.520 David L: I can… I’m barely getting the bare minimum, and I’d like.
152 00:22:25.520 ⇒ 00:22:26.210 Uttam Kumaran: Yeah.
153 00:22:26.210 ⇒ 00:22:31.760 David L: even more detailed into that, I just… And, like, levers.
154 00:22:31.760 ⇒ 00:22:44.600 Uttam Kumaran: Yeah, and that’s exactly it. Like, even hearing you say that is… is also kind of very similar to the feedback that Julie gave, and that a lot of people are giving, is just the capacity. I mean, this is where, like, I want to support in thinking about
155 00:22:44.650 ⇒ 00:23:01.030 Uttam Kumaran: what would allow you to have that capacity? And so, in the past, I think it’s clear that, okay, there has to be some attention to investment, but also, I just think that there’s also probably some opportunity for, like, some upgrades on tools and how the things… ways things are structured. To give you a little bit of sense of, like, how we’ve…
156 00:23:01.030 ⇒ 00:23:04.830 Uttam Kumaran: Worked with companies in the past is, like, you know, one big part of data is just
157 00:23:04.830 ⇒ 00:23:14.059 Uttam Kumaran: centralizing all of it into one place where folks like you can do analysis. And as you see on the ABC project, we’re actually, like, piping all of that to that real dashboard.
158 00:23:14.060 ⇒ 00:23:14.470 David L: Yeah.
159 00:23:14.470 ⇒ 00:23:28.590 Uttam Kumaran: You know, and so one of the things that I was, you know, thinking about was, like, okay, what other parts of the companies where if we were to at least… if, like, our team, or in collaboration was to at least get the data in a place where you could use SQL to run a query on it.
160 00:23:28.770 ⇒ 00:23:38.639 Uttam Kumaran: how much… like, and that is reliable, right? Just that part, where it’s like, you don’t have to go into a system to pull stuff, it’s landed in a data warehouse where you can run a query.
161 00:23:38.680 ⇒ 00:23:49.679 Uttam Kumaran: does that cut, like, 50%? Does that cut, like, 30%? Does that allow for, like, a little bit more redundancy? Like, maybe let’s just start with that exercise, because that’ll help me sort of quantify
162 00:23:49.750 ⇒ 00:23:54.380 Uttam Kumaran: various ways we can support? Like, what do you think about, like, an idea like that?
163 00:23:54.530 ⇒ 00:24:08.000 David L: Yeah, like, having a database would be fantastic. It’s something that we’ve wanted to do for a while. Unfortunately, what we run to… what we run into is a lot of the red tape. Like, when it… we wanted to build a database to track technicians’ attendance.
164 00:24:08.000 ⇒ 00:24:22.870 David L: But we haven’t yet been given access to that from HR to track in our Paylocity system, because that’s yet another system that we have, you know, like, as far as getting rights to that. We try to kind of onboard,
165 00:24:23.050 ⇒ 00:24:43.039 David L: I tried to onboard Brian into training in SQL, but then we got pushback from IT about the safety concerns of that, and the cybersecurity… or the security risk in that, and so not being able to utilize that’s been on our plate to try to get approval from IT for a year, and we’ve not yet crossed that line. So there’s things that we want to do, but we’re just…
166 00:24:43.040 ⇒ 00:24:50.280 David L: unfortunately limited, because yes, that would be very helpful. It would be, like, dream scenario, but it’s just, yeah.
167 00:24:50.280 ⇒ 00:24:51.629 Uttam Kumaran: Okay, so if I can get…
168 00:24:51.830 ⇒ 00:24:53.840 Uttam Kumaran: I’m gonna knock on wood, but if I.
169 00:24:53.840 ⇒ 00:24:54.210 David L: I can get.
170 00:24:54.210 ⇒ 00:25:09.150 Uttam Kumaran: something done for you. For me, that is also, like, a super clear opportunity, because to tell you the truth, even as part of this phase, we are establishing a data warehouse, because I can’t do my work to look at the company without that.
171 00:25:09.220 ⇒ 00:25:27.710 Uttam Kumaran: Absolutely. And so… so I’m really hopeful that some of the things that we’re driving in just this few-week phase are things that we can invest in. So I heard you on that. So if we can get a single place where we can drop data and to run queries, that saves some percentage of time. Tell me, like, what the aptitude would be for, like.
172 00:25:28.110 ⇒ 00:25:32.569 Uttam Kumaran: I mean, even just having, like, fixed live dashboards.
173 00:25:33.340 ⇒ 00:25:44.870 Uttam Kumaran: I think the one thing I’m understanding, and I… and it… which is helpful, is that, like, ABC leadership doesn’t seem like the cast of characters that is, like, going to be in the data themselves a lot.
174 00:25:44.870 ⇒ 00:25:46.050 David L: No, no.
175 00:25:46.050 ⇒ 00:25:48.699 Uttam Kumaran: You know, and sorry, I’m just trying to say the obvious out loud.
176 00:25:48.700 ⇒ 00:25:58.360 David L: But, like, it’s helpful for me to… because we work with a lot of clients, and some are like that, and so I like to sort of, like, shut doors as we’re sort of going, so I can think about options.
177 00:25:58.360 ⇒ 00:26:11.920 Uttam Kumaran: However, you know, if they could at least be presented with the information, you know, more frequently, that does take off your plate, like, the preparation aspect of, like, KPIs.
178 00:26:11.920 ⇒ 00:26:25.729 Uttam Kumaran: You know? Which I know is a big thing, and instead, maybe frees you to, prep for those meetings, or run more of those meetings, where they’ve already gotten set, like, a dashboard.
179 00:26:25.730 ⇒ 00:26:26.049 David L: And it’s.
180 00:26:26.050 ⇒ 00:26:44.969 Uttam Kumaran: Instead, you’re focusing on, like, okay, let’s all dissect this, like, one… let’s go deeper on this one, like, huge decrease this month. And it’s, for me, it’s like, how do I shift, even on my team, how do I shift data people from spending 80% of their time on prep and, like, cleanup and presentation, and then 20% on, like, actually being, like.
181 00:26:45.080 ⇒ 00:26:46.180 Uttam Kumaran: Okay.
182 00:26:46.530 ⇒ 00:27:05.219 Uttam Kumaran: yes, I’m… I woke up David today, but let’s say I’m Bobby Jenkins. What do I do, right? Like, I want… the data people need to be there, and, you know, how do you and Brian both wake up and do 80% in that world, and 20% in, like, you know, this, like, preparation world?
183 00:27:05.440 ⇒ 00:27:17.019 David L: So, you are making my hearts happy right now, Utam, because, yeah, that is, like, obviously, like, the pie in the sky, the dream scenario that would… Okay. Like, the birds would be singing, the clouds would be partying, the sun would.
184 00:27:17.020 ⇒ 00:27:18.580 Uttam Kumaran: Hey, don’t…
185 00:27:18.580 ⇒ 00:27:19.170 David L: You know, it’d be…
186 00:27:19.170 ⇒ 00:27:20.750 Uttam Kumaran: I’m trying, I’m gonna try.
187 00:27:20.750 ⇒ 00:27:33.179 David L: But yes, even just getting that data to kind of dig into that, because yes, right now we are doing… a lot of our time is just spent preparing, preparing, and even when we’re done preparing, we’re like, whew!
188 00:27:33.310 ⇒ 00:27:40.860 David L: Then we get the flood of, like, corrections of, like, hey, we communicate with you this, so update this, so then we’re back in that preparing phase.
189 00:27:40.860 ⇒ 00:27:59.779 Uttam Kumaran: Because to tell you the truth, like, the one thing that is always tough for a leader to hear is gonna be, hey, I need, like, another person. You know, and so for me, it’s one thing I want to try to do here is, I think there are some obvious wins that don’t rely on headcount changes. I actually think that
190 00:28:00.020 ⇒ 00:28:15.200 Uttam Kumaran: that having a lean, mean team is great, but you guys have been asked to do way too much. And for you guys to scale what you’re doing beyond pests is gonna be very, very challenging, you know, at least for my observation, you know?
191 00:28:15.200 ⇒ 00:28:31.780 David L: Yes, and when you say scorecards, Utam, that also, like, lights me up, and in the best way possible, because we have explored various options when it comes to scorecards. We have engaged multiple companies, one of which was, like, DataCube, to do our scorecards for.
192 00:28:31.780 ⇒ 00:28:32.280 Uttam Kumaran: Yes.
193 00:28:32.280 ⇒ 00:28:45.070 David L: which was just our, like, our sales team, but we want to have that… I know that’s something that the executive team does want to see, like, across the company, and so just having those easily put together to give just, like, that quick
194 00:28:45.520 ⇒ 00:28:53.429 David L: splash of, like, here, this is what’s going on, and then allowing us to delve into those things where, like, the metrics have gone off, or we’ve gone off the rails.
195 00:28:53.430 ⇒ 00:29:09.470 David L: quite right for us to investigate and bring that up, or kind of explain that, or talk that through, would be fantastic. So, but right now, that’s also something that’s fallen to us, right? Of just, like, okay, that’s something that y’all can put together, which just adds that next layer of
196 00:29:09.740 ⇒ 00:29:15.750 David L: Complication of, like, okay, that’s something else on our list of already… of long things to do, of many things to do.
197 00:29:15.750 ⇒ 00:29:16.470 Uttam Kumaran: Yeah.
198 00:29:16.470 ⇒ 00:29:17.020 David L: Yeah.
199 00:29:18.150 ⇒ 00:29:26.120 David L: But again, that could be facilitated with a central database, something that could easily pull all that information.
200 00:29:26.530 ⇒ 00:29:30.139 Uttam Kumaran: Yeah. And then, I guess another thing is, like, so we’re… you’re…
201 00:29:30.360 ⇒ 00:29:47.850 Uttam Kumaran: Are there other, like, process changes that you would propose? Let’s say you had the additional time? Like, it seems clear that on the sales side, you’re running these meetings with Pest. I know Julie also mentioned there’s, like, an executive meeting, on a weekly basis that I think she may be going through metrics
202 00:29:47.860 ⇒ 00:29:54.920 Uttam Kumaran: within. But also, I don’t know if there’s anything being done on the marketing side, like, does that kind of fit under your purview, or…
203 00:29:55.350 ⇒ 00:30:03.069 David L: It does not. Marketing is done by… currently by Les, but I know someone else has taken over that, because he’s getting ready to retire, I think, next month.
204 00:30:03.070 ⇒ 00:30:03.590 Uttam Kumaran: Yes.
205 00:30:03.590 ⇒ 00:30:20.210 David L: But that would be ideally something that I would like to see, because we often run into pain points for marketing in that executive meeting, which I am not a part of. But, you know, you always hear the things going on, where marketing will come out saying, hey, we’ve done this to show improvement, but
206 00:30:20.210 ⇒ 00:30:25.219 David L: the call center hasn’t followed through on their end. And then we’re kind of left, like.
207 00:30:25.510 ⇒ 00:30:30.190 David L: that’s happening? We had no idea. Yeah. You know, like, so having that all kind of
208 00:30:30.380 ⇒ 00:30:40.519 David L: those puzzle pieces fit together would be really useful, I think, not only to give us a new perspective to the executive team, but for us, too, because I have no idea what marketing’s doing, or what.
209 00:30:40.520 ⇒ 00:30:40.990 Uttam Kumaran: Yes.
210 00:30:40.990 ⇒ 00:30:51.709 David L: utilizing. I know that they utilize Google on some level, like, doing their statistics, but I don’t have any insight to that, so I don’t know what’s working and what’s not, or what could change.
211 00:30:51.710 ⇒ 00:30:52.150 Uttam Kumaran: Yes.
212 00:30:52.150 ⇒ 00:30:56.340 David L: input is needed. It’s kind of very much siloed in that… in that way.
213 00:30:56.980 ⇒ 00:30:57.630 Uttam Kumaran: Okay.
214 00:30:58.150 ⇒ 00:31:01.479 Uttam Kumaran: And then, a question there also is,
215 00:31:03.540 ⇒ 00:31:11.610 Uttam Kumaran: what… how do you and Brian work together, like, on a daily basis? Like, tell me how, like, the data team sort of operates. Do you guys…
216 00:31:11.710 ⇒ 00:31:18.170 Uttam Kumaran: Are you guys kind of keeping track of tasks? It’s sort of just, like, you guys are attached to the hip and sort of, like, just moving.
217 00:31:18.170 ⇒ 00:31:18.530 David L: native.
218 00:31:19.560 ⇒ 00:31:26.440 David L: Exactly. So, we are chatting back and forth all day, every day. His office is actually right across the hall.
219 00:31:26.440 ⇒ 00:31:26.900 Uttam Kumaran: Okay.
220 00:31:26.900 ⇒ 00:31:42.229 David L: So when his… when his… when he’s in office, we’re constantly… I’m going to his office, he’s coming to my office, we’re bouncing things off of each other, we’re notifying each other and whatnot. But outside of that, there are… because Brian and I have been working together for about
221 00:31:42.230 ⇒ 00:31:54.659 David L: 3 years now. We’ve kind of fallen into our rhythm. Again, he has his list of tasks that he’s responsible for, and right now he is responsible for the past KPIs and the sales KPIs. I’m in charge of…
222 00:31:54.660 ⇒ 00:32:04.450 David L: everything else in the call center, and so there’s things about go and check his work, we’ll get feedback, I’m looped in on those emails, and so it’s just a constant back and forth.
223 00:32:04.980 ⇒ 00:32:05.570 Uttam Kumaran: Okay.
224 00:32:06.340 ⇒ 00:32:24.070 Uttam Kumaran: So, I think that’s also helpful to understand, because, you know, one thing I… and then… okay, so that’s helpful. I just want to kind of get a sense of the cadence that you guys are working. Are you… you… are… maybe I can talk specifically about the stuff from Andy, like, are you using that… those dashboards that our team produced? Like, what do you think about…
225 00:32:24.440 ⇒ 00:32:30.199 Uttam Kumaran: what’s there? You know, I think, you know, unfortunately, I feel like we could have done more
226 00:32:30.330 ⇒ 00:32:44.360 Uttam Kumaran: collaborating with you on that. I think we did get to a point where it’s working well, but Amber is the one that’s reporting on it. For me, it’s clear… one thing I want to avoid is that anything that our team owns.
227 00:32:44.460 ⇒ 00:32:53.609 Uttam Kumaran: you know, and we of course hope to work with ABC for a long time, but if our team owns it, and you guys are like, we’re not working together, then it sort of dies.
228 00:32:53.610 ⇒ 00:32:53.990 David L: That’s a big.
229 00:32:53.990 ⇒ 00:33:03.829 Uttam Kumaran: thing that I am very, very wary of, and so I want to make sure that, like, just to get your feedback, and even to hear how you thought about those dashboards, and
230 00:33:03.830 ⇒ 00:33:13.289 Uttam Kumaran: as I think a little bit about, okay, what are key changes or investments that management can make on the data side to help you guys, I want to consider
231 00:33:13.290 ⇒ 00:33:23.860 Uttam Kumaran: reporting and business intelligence as something on the table. And so, yeah, just hear… maybe just to hear your… your thoughts on, like, the dashboard we put up there, and like, yeah, start there.
232 00:33:23.860 ⇒ 00:33:32.129 David L: I will say, Unam, when we were first starting to work on the dashboards, I was looped in there, and then I fell off because of everything that was happening.
233 00:33:32.130 ⇒ 00:33:32.680 Uttam Kumaran: Yes.
234 00:33:32.680 ⇒ 00:33:42.549 David L: And so, when I last saw the dashboards, it’s been a few months, I know the data that was fetching wasn’t accurate, and y’all were working on pinpointing.
235 00:33:42.550 ⇒ 00:33:42.970 Uttam Kumaran: Yes.
236 00:33:42.970 ⇒ 00:33:51.519 David L: getting that down through the APIs, so I’ve not really gone back and looked at it, but I know in the grander scheme, I can see the vision of what was there, and I think
237 00:33:51.690 ⇒ 00:34:00.340 David L: if all of that has been hammered down, which again, I’ll just need to go back and, like, check on it, even doing our call center scorecards being…
238 00:34:00.340 ⇒ 00:34:00.990 Uttam Kumaran: Yes.
239 00:34:01.270 ⇒ 00:34:05.219 David L: Aggregated by you all would be a big help for us, too.
240 00:34:05.220 ⇒ 00:34:05.560 Uttam Kumaran: Okay.
241 00:34:05.560 ⇒ 00:34:07.510 David L: So I think that there’s definitely…
242 00:34:07.720 ⇒ 00:34:24.770 David L: work to be done there, or, like, some things that could make it easier for us, because again, a lot of the stuff for the call center comes from 8x8, so… Yeah. So, to answer your question, I’ve not had a chance to go in there recently, so I don’t really know what it looks like, but I know in its first version, I thought that it had a lot of potential.
243 00:34:25.110 ⇒ 00:34:30.739 Uttam Kumaran: Okay, okay. No, that’s helpful, but it’s also helpful to know that, like, you’re really slammed. Like, it’s…
244 00:34:30.739 ⇒ 00:34:31.189 David L: Yeah.
245 00:34:31.310 ⇒ 00:34:37.990 Uttam Kumaran: So, okay, so we have to try to find… so that’s the one thing I want to convey to leadership, is they’re not doing a good job
246 00:34:38.230 ⇒ 00:34:49.919 Uttam Kumaran: You know, we need to do a better job at giving you the time and space to think about doing more proactive, like, opportunity-based analysis versus just keeping the lights on type stuff.
247 00:34:49.929 ⇒ 00:34:54.849 David L: Yes, exactly. Right now, it’s just kind of, like, head just above water type of situation.
248 00:34:54.850 ⇒ 00:34:55.190 Uttam Kumaran: Yeah.
249 00:34:55.190 ⇒ 00:35:06.659 David L: But it would be great if I could do some, like, swimming stunts. Yeah, exactly, exactly, exactly. You know, because I feel like I could really, really knock it out of the park, but right now… Yeah.
250 00:35:07.030 ⇒ 00:35:09.300 David L: on there, it’s… Yeah.
251 00:35:09.300 ⇒ 00:35:15.990 Uttam Kumaran: changed at all in the last 3 years? Like, has it just gotten crazier? Or, like, you know, were there any, like.
252 00:35:16.250 ⇒ 00:35:22.119 Uttam Kumaran: Step functions in the business that you, like, recognize that really change the complexity or the pace?
253 00:35:22.460 ⇒ 00:35:31.390 David L: Yeah, it was difficult for me to say. I know there’s definitely been a lot of change when it comes to the KPIs. It’s difficult for me to say as a whole what those things were, because the
254 00:35:31.530 ⇒ 00:35:36.120 David L: metrics or the KPI and the data were being handled by additional people.
255 00:35:36.120 ⇒ 00:35:58.440 David L: So before, there was Mariah in our pest department that was handling those, and then there was Carrie over in our lawn department, which was handling those KPIs. So that information was kind of unbeknownst to me, I wasn’t involved in that, and then as we started having those responsibilities folded in, and the mechanical department as well, the home department as well, then things started kind of getting under our belt, but
256 00:35:58.560 ⇒ 00:36:11.779 David L: because those responsibilities came on board, we haven’t… I, again, haven’t had the chance to kind of see what those trends are. I know that overall, the company has definitely steered more towards being more data-driven across the board.
257 00:36:11.820 ⇒ 00:36:13.240 David L: Which is why…
258 00:36:13.280 ⇒ 00:36:33.019 David L: all this stuff is coming onto the data team, right? Which is great to see overall, but I still think that we’re at a point where it could definitely be utilized a whole lot better, where I feel like only in the infancy of data at ABC, there’s a lot of room for improvement and for growth.
259 00:36:33.020 ⇒ 00:36:35.750 David L: It’s just kind of… Getting ourselves set up.
260 00:36:35.750 ⇒ 00:36:48.479 David L: there is wrong, but I definitely see more transition towards, hey, let’s look at the data. What does the data say? Let’s make decisions based on that, as opposed to, like, oh, we just feel this, or like, do I think that’ll work? Like.
261 00:36:48.480 ⇒ 00:36:49.100 Uttam Kumaran: Yeah.
262 00:36:49.100 ⇒ 00:36:54.580 David L: And then, can you… so also, confirming, like, are… does your team ladder up into Julie’s team?
263 00:36:54.980 ⇒ 00:36:57.350 David L: We do not, our teams are separate. Okay. Yeah.
264 00:36:57.350 ⇒ 00:37:01.459 Uttam Kumaran: Okay, so then where does the data team, like, fit in the org structure?
265 00:37:01.500 ⇒ 00:37:07.490 David L: We are our own thing. We never existed before I came along with them, so we’re just kind of in.
266 00:37:07.490 ⇒ 00:37:11.880 Uttam Kumaran: Yeah, and also maybe tell me the lore there, like, how did you get involved with the company, and like…
267 00:37:11.970 ⇒ 00:37:20.189 David L: Yeah, okay, so in… I used to be a fitness instructor, so I used to teach yoga and CrossFit, and I did.
268 00:37:20.190 ⇒ 00:37:20.690 Uttam Kumaran: Fair enough.
269 00:37:20.690 ⇒ 00:37:23.270 David L: 10 years until COVID hit.
270 00:37:23.270 ⇒ 00:37:24.410 Uttam Kumaran: In San Antonio?
271 00:37:24.580 ⇒ 00:37:33.559 David L: Yeah, absolutely. Oh, great. I went to LA for my training, and then I taught in a couple studios, but I… here in San Antonio is where I do the majority of my stuff.
272 00:37:33.860 ⇒ 00:37:35.020 David L: COVID hit.
273 00:37:35.130 ⇒ 00:37:47.489 David L: gyms shut down, that wasn’t really a thing, like, I was like, oh, maybe this is my opportunity to switch things up, and so I went into cybersecurity for a year, and then after that, I landed as a sales inspector here at ABC.
274 00:37:47.490 ⇒ 00:37:47.910 Uttam Kumaran: Okay.
275 00:37:47.950 ⇒ 00:37:55.379 David L: And after a year doing that, I noticed that there was an opening for a real-time workforce manager in the call center.
276 00:37:55.380 ⇒ 00:38:13.380 David L: which I applied to, I got it, and there was just… it was just me, a team of one. And then things started growing, so then I hired Brian, things started growing, so I had Austin, and now all these things are being looped in, where it’s like, okay, now let’s have the data team do pretty much everything for the company. And that’s where… that’s a really long…
277 00:38:13.380 ⇒ 00:38:18.769 Uttam Kumaran: Was that on… where was that on that 3-year journey? Like, when did you start to get asked to, like.
278 00:38:19.310 ⇒ 00:38:27.930 Uttam Kumaran: when do you start to, like, decide, okay, I need a Brian, and, like, that… those are sort of milestones that I’m interested in, because for me, it’s not always clear, like, at what point
279 00:38:28.050 ⇒ 00:38:43.659 Uttam Kumaran: at least the team started investing in data, and then that way, I want to basically… I’m gonna build, like, a visual timeline for the executive team to show that, like, how… and this is the thing, they’re very lucky to have you, because you’ve formed a structure in what you could, right?
280 00:38:43.660 ⇒ 00:38:44.440 David L: Right, yeah.
281 00:38:44.440 ⇒ 00:38:52.180 Uttam Kumaran: I could tell that there’s not much leadership in this area and the company, and so you’re doing what you can.
282 00:38:52.180 ⇒ 00:38:52.499 David L: And this is.
283 00:38:52.500 ⇒ 00:38:57.509 Uttam Kumaran: And also, the risk that I tell them is, like, look, if you don’t give someone like David
284 00:38:57.510 ⇒ 00:39:13.859 Uttam Kumaran: you know, clear opportunity, or a way to grow, or, like, strategy, like, dude, some company comes around and is like, David, we love what you’re gonna do. Here’s, like, 20% more. There is a risk, and so that’s what I… when I convey to folks, is that we often come into companies where there is, like, a rogue analysis team.
285 00:39:13.910 ⇒ 00:39:21.210 Uttam Kumaran: And it’s tough, because you often just self-form, you just figure out what it takes to survive, but that’s no way to live, right?
286 00:39:21.210 ⇒ 00:39:21.580 David L: That’s.
287 00:39:21.580 ⇒ 00:39:38.420 Uttam Kumaran: when I go to leadership, I’m… I’m a data person, so I’m very, very of the… of, like, how do you give this team real scope, real understood, like, budget and capacity, and also, like, a North Star, versus just, like, becoming a help desk for data questions.
288 00:39:38.420 ⇒ 00:39:46.289 David L: Absolutely, and I love what you said there, because just last week, I was talking to a friend, and I was like, you know what, like, I’m tired of surviving. I want to switch into thriving.
289 00:39:46.290 ⇒ 00:39:47.060 Uttam Kumaran: I don’t know.
290 00:39:47.060 ⇒ 00:39:50.719 David L: looks like just, yeah, gosh darn it, I’m gonna get the hair.
291 00:39:50.720 ⇒ 00:40:04.689 Uttam Kumaran: I mean, I’m dead serious in that, like, we go to companies, we tell them, look, you survived through this phase, but if, like, a day… if someone like David decides to leave, you’re really screwed, and so you have to… you have to really give him
292 00:40:04.690 ⇒ 00:40:20.709 Uttam Kumaran: a strategy and a path towards, like, what data could look like at ABC, and I also want to share… I want to try to have a path where, like, if that’s our team, like, how can you leverage our team? But the one thing I don’t want to do is, like, we come in and we work, and then it’s like.
293 00:40:20.710 ⇒ 00:40:33.910 Uttam Kumaran: I’m totally separate, because that’s how a lot of, like, consultancies do things. It’s, like, not at all how we think about that. It’s like, in fact, I want to find out and explain to them where my team can support, and then also, I’m like, guys, you have great data people already.
294 00:40:33.910 ⇒ 00:40:34.560 David L: Yeah.
295 00:40:34.560 ⇒ 00:40:40.640 Uttam Kumaran: take the busy work and give it to us. Like, give them the thrive-type work, you know?
296 00:40:40.640 ⇒ 00:40:41.480 David L: Exactly. And that’s how.
297 00:40:41.480 ⇒ 00:40:44.340 Uttam Kumaran: I want to help them think about the sort of, like.
298 00:40:44.660 ⇒ 00:40:48.759 Uttam Kumaran: How does actually the manufacturing process of these, like, insights work, you know?
299 00:40:48.760 ⇒ 00:41:09.490 David L: Sure, yeah. And to go back to that timeline, it was about a year after… so I started in the call center about 2021. It was a year after, in 2022, that we set out on hiring somebody else, which ended up being Brian, and that’s because, again, what started off is like, hey, let’s start tracking this. As you know, with data, you start getting that data, and then you go back in there, you’re like, oh, what about that?
300 00:41:09.490 ⇒ 00:41:20.560 David L: And what about that? Yeah. What about that? So, naturally, we start expanding into the call center, like, well, now we want to track this, now we want to create this, we want scorecards here, so then that became…
301 00:41:20.560 ⇒ 00:41:24.549 David L: a lot for me to handle without things falling off my plates without Brian.
302 00:41:24.830 ⇒ 00:41:31.460 David L: And then, in January, it will be a year that Austin has been with us, so… Okay.
303 00:41:31.720 ⇒ 00:41:41.139 David L: earlier this year, about 2025, early 2025, is when we got Austin, because things started coming up again, where it was already too much for me and Brian to handle, so we got Austin.
304 00:41:41.140 ⇒ 00:41:58.070 David L: And now we’re at that place, too. So, yes, we haven’t really… in the company org right now, I’m nestled in the call center under Yvette, so she is my direct supervisor. And then, from there, we’ve kind of always been our own thing, since the data team was always supposed to be a call center thing, and always historically.
305 00:41:58.070 ⇒ 00:41:58.580 Uttam Kumaran: Yeah, yeah, yeah.
306 00:41:58.580 ⇒ 00:42:15.470 David L: to the call center thing, but now everyone else is getting in on it. They’re like, oh, they can do that? Have them do this. And so, it’s become a way, the data team has kind of become a way of, like, hey, let’s consolidate some things, but again, back to our original point, where it’s become, like, now we’ve had so much things thrown at them that we can’t
307 00:42:15.470 ⇒ 00:42:19.650 David L: necessarily do anything on a broader scale.
308 00:42:19.790 ⇒ 00:42:38.870 David L: So that’s kind of how that… my time here at ABC, and how this has kind of grown. But yeah, so kind of coming from zero to nothing, and so I do have, like, some metrics in the call center, so to speak, as far as, like, what I’m working towards, but this is kind of, like, uncharted territory, so to speak, where now we’re trying… now we’re expanding to the whole company.
309 00:42:38.870 ⇒ 00:42:39.370 Uttam Kumaran: Yeah.
310 00:42:39.370 ⇒ 00:42:45.120 David L: We don’t really know what that looks like. It’s just kind of like, we’re just stuck in the day-to-day stuff, still.
311 00:42:45.120 ⇒ 00:42:54.009 Uttam Kumaran: who do you think, like, the team should move into? And, you know, like, what do you… do you think, like, you’re getting enough supp…
312 00:42:54.190 ⇒ 00:42:59.250 Uttam Kumaran: I mean… Typically, in an engineering… in an organization, like, the data team falls under
313 00:42:59.670 ⇒ 00:43:18.530 Uttam Kumaran: usually either the COO or, like, the engineering organization, right? It often does start like this. It starts in one business unit, but the business unit ends up just one of your clients, right? And you as a data team have multiple clients that you support, you know, you support with reporting and insights with. Do you feel like there’s a logical person that can be that?
314 00:43:18.580 ⇒ 00:43:22.059 Uttam Kumaran: like, champion? Or do you still feel like.
315 00:43:22.400 ⇒ 00:43:25.470 Uttam Kumaran: Everybody’s sort of fighting for themselves, you know?
316 00:43:26.330 ⇒ 00:43:29.130 David L: I would say…
317 00:43:29.510 ⇒ 00:43:39.539 David L: probably the… because, like, on an executive level, when it comes to data, I know Matt is a very data-driven person, you know, he’s a very big numbers guy, as is Beau, although Bo will.
318 00:43:39.540 ⇒ 00:43:39.930 Uttam Kumaran: Yeah.
319 00:43:39.930 ⇒ 00:43:42.440 David L: Like, his realm when it comes to, like, sales.
320 00:43:43.130 ⇒ 00:43:43.620 Uttam Kumaran: Yes.
321 00:43:45.030 ⇒ 00:44:02.310 David L: I would think one of them, but it’s weird the way that things are set up, because it’s, like, so ambiguous right now that everyone’s… Yeah. We will have to tap in Mac to get something done in the past, or we’ll have to type in to get something here, Steven to get something there, and so I don’t know that there is just one person right now,
322 00:44:02.310 ⇒ 00:44:02.890 Uttam Kumaran: Yes.
323 00:44:02.890 ⇒ 00:44:10.930 David L: those… Yvette is a data-driven person through and through, as I’m sure you know. Like, you know, so, so there are…
324 00:44:11.090 ⇒ 00:44:11.930 David L: Hence?
325 00:44:12.060 ⇒ 00:44:20.130 David L: even too, to an exact… so there are those couple people, but I don’t know that one clearly stands out,
326 00:44:20.310 ⇒ 00:44:27.499 David L: as being the person, I would… probably my go-to’s would be those three, like Yvette, Matt, or Bo.
327 00:44:27.930 ⇒ 00:44:30.059 David L: Okay, okay, okay, makes sense.
328 00:44:30.060 ⇒ 00:44:33.269 Uttam Kumaran: And then, another point I had is,
329 00:44:34.860 ⇒ 00:44:43.269 Uttam Kumaran: I wonder if also a way to leverage us is to just help you build, like, that roadmap, because I… what I want to convey to them is, like.
330 00:44:43.420 ⇒ 00:44:47.029 Uttam Kumaran: Part of your time needs to go to sort of thinking about, like.
331 00:44:47.120 ⇒ 00:44:50.329 Uttam Kumaran: What does the data team want to accomplish, like, this quarter?
332 00:44:50.340 ⇒ 00:45:05.259 Uttam Kumaran: And that’s something that… that’s, like, kind of work that we do a lot of, which is setting up that roadmap. Not only the roadmap of, like, okay, we need access to this source, but also, like, we want to answer this question, we want to be able to… we want to say, like, okay, cool, we want to…
333 00:45:05.260 ⇒ 00:45:13.179 Uttam Kumaran: expand from just one team to three teams that we support. So I think that’s another way to leverage us, is, like, for us to help you put together that, like.
334 00:45:13.250 ⇒ 00:45:23.709 Uttam Kumaran: roadmap for the data team, and you guys deserve to… you guys need KPIs and things to, like, hit as well, you know? So that way, you can say no to things, because without a sort of principled approach.
335 00:45:24.050 ⇒ 00:45:30.020 Uttam Kumaran: And, like, a plan, work comes your way, there’s nothing you’re… there’s nothing you can flag as, like, is this important to our…
336 00:45:30.020 ⇒ 00:45:30.680 David L: Right.
337 00:45:30.680 ⇒ 00:45:32.210 Uttam Kumaran: signed off mission, you know?
338 00:45:32.220 ⇒ 00:45:41.619 David L: Yes, and I would very much appreciate that, because obviously, as a data person myself, I’d want to have those, like, clear goals of, like, this is what you’re working towards, where you need to be, what
339 00:45:41.740 ⇒ 00:45:55.010 David L: all those things, and those are things that we’ve tried to incorporate, whether it be through training or expanding what we do here, but again, we just keep getting bogged down. And so, yes, I would personally love that.
340 00:45:55.490 ⇒ 00:45:56.890 Uttam Kumaran: Okay, okay, great.
341 00:45:58.140 ⇒ 00:46:15.280 Uttam Kumaran: So, I mean, the other… so, kind of, like, maybe to just put a bow on a couple things. So, one is we got access to Evolve on Friday. I’m also getting access to some historical data from Julie today. I’ll actually be going and stopping by the office to get some, like… we’re basically trying to get the last, like, 5 years of data.
342 00:46:15.280 ⇒ 00:46:18.509 Uttam Kumaran: I’m putting… we’re putting some stuff into a data warehouse.
343 00:46:18.570 ⇒ 00:46:23.139 Uttam Kumaran: Well, I haven’t yet got access to Dream,
344 00:46:23.390 ⇒ 00:46:30.820 Uttam Kumaran: So I messaged Nitesh, but he hasn’t emailed me back yet, so I’ll have to follow up with him. And then from Les, I’m getting access to, like.
345 00:46:31.050 ⇒ 00:46:36.019 Uttam Kumaran: marketing, all the marketing-related goals and Google Analytics and things like that.
346 00:46:36.140 ⇒ 00:46:41.099 Uttam Kumaran: I know we already have access to some of the 8x8 data,
347 00:46:41.500 ⇒ 00:46:51.950 Uttam Kumaran: So, basically, my job, you know, over the next few weeks is we’re just gonna… we’re kind of exploring a little bit of, like, where the opportunity is, and maybe even I could show you
348 00:46:51.990 ⇒ 00:47:06.260 Uttam Kumaran: the deck that we presented to leadership that actually, like, kind of kicked off this project. And, you know, any feedback you have now, or whenever on this would be helpful, but I feel like I sort of understand the position you’re in, and so for us, it’s like.
349 00:47:06.300 ⇒ 00:47:12.109 Uttam Kumaran: We want to both use the opportunities to also fight for,
350 00:47:12.230 ⇒ 00:47:22.289 Uttam Kumaran: hey, we need to make some changes to how the data team is, like, structured and working today in order to achieve this. So that’s always what I… what I know it’s hard when you’re in the thick of things to, like.
351 00:47:22.290 ⇒ 00:47:41.360 Uttam Kumaran: step back and share, like, if we only had this, we could do this, and that’s what I want, you to be able to leverage our team for. And so part of… part of, like, what we’re doing here is not just saying, okay, there’s, like, X amount of money here, we saw these. It’s actually showing, here’s the time it took for us to do the analysis.
352 00:47:41.420 ⇒ 00:47:45.720 Uttam Kumaran: And that’s, like, exact… and we came in and we just got, like, sort of, like.
353 00:47:45.810 ⇒ 00:47:47.870 Uttam Kumaran: god mode access to things, as Matt.
354 00:47:47.870 ⇒ 00:47:48.250 David L: Yeah.
355 00:47:48.250 ⇒ 00:48:03.899 Uttam Kumaran: through, but, like, think about your team, like, they’re not able to get this, and so I want to translate to folks that, like, what is the culture of analytics at ABC? You know, and show that. And so, here’s just a little bit of, like, the deck we basically went through with them. So…
356 00:48:04.390 ⇒ 00:48:06.979 Uttam Kumaran: Kind of like…
357 00:48:07.220 ⇒ 00:48:17.439 Uttam Kumaran: we basically said these are kind of some of the core challenges. It’s really unclear, like, where people are coming from. It’s unclear, like, where the conversion friction is, and so that’s only at the top level, right?
358 00:48:17.440 ⇒ 00:48:17.800 David L: Yeah.
359 00:48:17.800 ⇒ 00:48:35.899 Uttam Kumaran: it’s… it’s not clear, like, how we are winning clients back. Like, I looked at the, sort of, the subscription numbers that are in and out. It’s kind of like a lot of people going out, you know? Yeah. And so, there’s a lot of that. Second, there’s data silos. There’s, like, you have access to sub stuff, marketing has access to some stuff.
360 00:48:36.000 ⇒ 00:48:51.289 Uttam Kumaran: sort of, like, throwing things around over the fence, you know? I know there’s also talent transition with less going, but also, like, I’m gonna highlight that your team is swapped, and so it is a risk if your team can’t get some breathing room and can’t start to automate some of these.
361 00:48:51.290 ⇒ 00:49:06.990 David L: With that, Utam, we also have Jim that is retiring, and just two weeks ago, I met with him, and I’m taking… have taken over some of his responsibilities. Granted, not big lifts, but still, again, it’s those little time sucks that.
362 00:49:06.990 ⇒ 00:49:07.809 Uttam Kumaran: Yes, exactly.
363 00:49:08.070 ⇒ 00:49:14.060 David L: And more to your point about the priorities of having a clear path forward, right now, I think our… our…
364 00:49:14.410 ⇒ 00:49:19.359 David L: standard for declining new work is, like, can we handle it right now? Unfortunately, we can’t.
365 00:49:19.360 ⇒ 00:49:19.880 Uttam Kumaran: Yes.
366 00:49:19.880 ⇒ 00:49:25.649 David L: And even then, I’ll have that conversation with Yvette, I was like, okay, I’ve got this on my plate, what’s priority? Because I know I’.
367 00:49:25.650 ⇒ 00:49:26.090 Uttam Kumaran: Yeah.
368 00:49:26.090 ⇒ 00:49:34.729 David L: lessen their stuff first, and I know that this also needs to go into, like, how does that fit in? You know, like, where is there breathing room there? But yes, go on.
369 00:49:35.430 ⇒ 00:49:40.939 Uttam Kumaran: And then, this is sort of like, we talked a little bit about these objectives, like, what’s happening today?
370 00:49:41.060 ⇒ 00:49:47.649 Uttam Kumaran: what are the growth opportunities? Like, what is the action plan? And then, like, what is sort of being transferred from less?
371 00:49:47.980 ⇒ 00:49:51.160 David L: Yeah. And then this is sort of how we’re, like, breaking it up, like.
372 00:49:51.730 ⇒ 00:49:54.870 Uttam Kumaran: Pop a funnel, for conversion, and then…
373 00:49:55.060 ⇒ 00:50:03.089 Uttam Kumaran: retaining and bringing back customers, sort of, from the dead. You know, so… so we’re… I think in the conversion side.
374 00:50:03.180 ⇒ 00:50:19.810 Uttam Kumaran: we have access to Evolve, we’re gonna go deep there. On the retention side as well as, like, majority is in Evolve. The awareness is where we’re gonna start to get access to some of the marketing stuff, and… but basically here, again, we’re just, like, doing a high-level audit of, like, are there anything that’s, like, red flags?
375 00:50:19.810 ⇒ 00:50:22.079 David L: But also looking at, like.
376 00:50:22.080 ⇒ 00:50:27.209 Uttam Kumaran: all the tools that we have access to, like, are there cheaper, faster things that we can invest in?
377 00:50:27.670 ⇒ 00:50:28.210 David L: I work.
378 00:50:28.210 ⇒ 00:50:40.409 Uttam Kumaran: You know, but also, again, like, mapping out for the leadership team, like, okay, you’ve expanded to 17 services, you’ve expanded to all these different places, but, like, are you able to segment, and you’re able to prioritize really, really effectively, you know?
379 00:50:40.410 ⇒ 00:50:40.810 David L: Absolutely.
380 00:50:40.890 ⇒ 00:50:45.190 Uttam Kumaran: So, kind of like…
381 00:50:45.520 ⇒ 00:50:51.109 Uttam Kumaran: yeah, I mean, this is, like, really, like, what we’re gonna, sort of, end up at, which is the last piece is actually, like, what
382 00:50:51.340 ⇒ 00:50:54.529 Uttam Kumaran: I think I’ll get a lot of your input on, it’s just like.
383 00:50:54.770 ⇒ 00:51:06.569 Uttam Kumaran: how, like, what is… what is the gap in, like, the existing infrastructure to support reporting? You know, what I’m not interested in doing is coming in and be like, oh, you can report on, like, 100 things, and you’re not doing that.
384 00:51:06.570 ⇒ 00:51:18.339 Uttam Kumaran: I… it’s like, that’s… that’s like not… I already knew that coming into that, and so for us, I need… but for the executive team, I need to sell in order to get us the wins on the… on the… for the data team, right? So…
385 00:51:18.430 ⇒ 00:51:20.339 Uttam Kumaran: Part of this is going to be
386 00:51:20.390 ⇒ 00:51:30.090 Uttam Kumaran: quantifying the lift for certain decisions. Hey, we found that if you were to increase conversions on click-to-buy and drive more traffic there, you could get X.
387 00:51:30.090 ⇒ 00:51:43.329 Uttam Kumaran: the money is what’s gonna get Bobby and, you know, Matt to say, okay, perfect, like, what do you need for that? Then, when I say, okay, great, we need a data warehouse, we need some type of reporting tool, and…
388 00:51:43.470 ⇒ 00:51:52.639 Uttam Kumaran: we need an engagement where our team supports David’s team and, like, moving them out of this, like, day-to-day stuff and more into proactive… like, that’s… so that’s the…
389 00:51:53.050 ⇒ 00:51:55.579 Uttam Kumaran: This is the sort of, like, dance that we’re.
390 00:51:55.580 ⇒ 00:51:55.999 David L: We’re gonna try.
391 00:51:56.000 ⇒ 00:52:04.050 Uttam Kumaran: to do with the team. I do think that also, as part of this, I do want to do some of this analysis alongside you and the team.
392 00:52:04.130 ⇒ 00:52:07.330 Uttam Kumaran: Like, what I don’t want to do is for us to, like.
393 00:52:07.380 ⇒ 00:52:19.460 Uttam Kumaran: miss all the edge cases and things that you guys know about the business, that you guys model into your data, and just have us spin our wheels and figuring things out. So Amber on our team is doing some of this initial analysis.
394 00:52:19.460 ⇒ 00:52:33.139 Uttam Kumaran: I’ve told her that we should start, you know, an email thread together as we start to go down answering one of these questions, like… and this may… again, this is going to be things that may be in your purview or not, but you are just the… you’re just the only sort of data direct
395 00:52:33.140 ⇒ 00:52:41.190 Uttam Kumaran: data partner that we have. And so, like, if we were gonna go answer, like, what is the opportunity of improving our click-to-buy funnel.
396 00:52:41.220 ⇒ 00:52:54.519 Uttam Kumaran: that’s… that’s, like, that’s, like, our open question that we will start to break down and analyze, but I also want to do that alongside… alongside you, so that you can hopefully glean a little bit of, like, what our process is, but then also
397 00:52:54.770 ⇒ 00:53:08.839 Uttam Kumaran: you can immediately be like, okay, that’s already been done, or, like, there’s nothing down there. Or, oh, okay, there is actually some bigger opportunity. You know, like, for example, I was talking to Julie a lot of… and Les about, like, what are the teams that are more receptive to data than others? Like.
398 00:53:08.840 ⇒ 00:53:15.430 Uttam Kumaran: Where… where… where are areas that we’ve already tried to, like, chip at that maybe there’s not much there versus, like.
399 00:53:15.520 ⇒ 00:53:23.610 Uttam Kumaran: okay, we should focus all of our time on, like, figuring out how to grow San Antonio. So those are the things that, like, I want to have discussions with, and actually may, like, end up
400 00:53:24.150 ⇒ 00:53:31.160 Uttam Kumaran: trying to come down, to San Antonio to sit with you guys for a few hours and, like, go through some of this. Yeah.
401 00:53:31.820 ⇒ 00:53:53.370 David L: So, I know what’s challenging for us specifically when it comes to Evolve, and it comes, like, to retention and or cancellation, that’s stuff that we’ve tried to dig into, but unfortunately, Evolve isn’t as comprehensive with the data when it comes to cancellations. I believe there’s currently 5 reasons in Evolve that you can select to when a customer cancels their service.
402 00:53:53.370 ⇒ 00:53:54.300 David L: And…
403 00:53:54.300 ⇒ 00:54:02.799 David L: it’s very just, like, generic overview, it doesn’t give me anything to work with, and so it’s difficult. Other than that, it would have to be
404 00:54:02.870 ⇒ 00:54:13.090 David L: Digging into those accounts, looking at the notes, listening to phone calls, going into 8x8, matching up the date and times to kind of really get a real reason for it, and it’s just obviously inefficient.
405 00:54:13.090 ⇒ 00:54:13.610 Uttam Kumaran: Yeah.
406 00:54:13.610 ⇒ 00:54:14.730 David L: At best.
407 00:54:14.890 ⇒ 00:54:18.920 Uttam Kumaran: Yeah, yeah. So that’s… so that’s the things I want to figure out, like.
408 00:54:19.070 ⇒ 00:54:34.080 Uttam Kumaran: okay, is the op… like, and this is where, for us, we’re gonna… we have to really prioritize and find the things that are doable in short-term and move the needle, but we’re also gonna find these, like, medium and long-term things that, ideally.
409 00:54:34.110 ⇒ 00:54:42.799 Uttam Kumaran: I want to put together as, like, this is, like, the data team’s roadmap, and so it’s important for us to get, like, the blessing from you on that, and then also, like.
410 00:54:43.120 ⇒ 00:54:58.279 Uttam Kumaran: this isn’t just something where we can execute alone, it’s actually… what I’m gonna propose is that, like, I want to give you and your team more ownership over this, but, like, not just ownership without any, like, resourcing. Like, I’m gonna be very clear to them that, like.
411 00:54:58.280 ⇒ 00:54:59.710 David L: Don’t do that, Tom.
412 00:54:59.710 ⇒ 00:55:03.419 Uttam Kumaran: No, no, no, no, no, I won’t, I’m sorry, I just want to be clear that I’m not, like…
413 00:55:03.640 ⇒ 00:55:12.589 Uttam Kumaran: I just think it… with us coming in and also poking around, I wanted to be clear that, like, we’re… we’re trying to get more attention to this problem as…
414 00:55:12.800 ⇒ 00:55:16.710 Uttam Kumaran: and show that data is the true way out of a lot of issues that ABC.
415 00:55:16.710 ⇒ 00:55:17.099 David L: his face.
416 00:55:17.530 ⇒ 00:55:33.239 Uttam Kumaran: And that’s just, like, I’m very biased, I’m a data person, but I really feel that way, and I think the leadership, they feel that way too, but there’s just a gap between how do we get there, you know? And, like, if I can be that glue, like, that’s where, you know, we hope to help.
417 00:55:33.440 ⇒ 00:55:38.449 David L: there have definitely been many instances that I’ve been a part of in which
418 00:55:38.580 ⇒ 00:55:57.030 David L: as you know, with data, like, something will happen, and then I’ll be like, guys, it was here the whole time. Like, you brought it up, and no one took any action on it. Yeah, I know, yeah. But you’re right, getting… closing that gap between the data and the executive team are the key players that can actually drive that change, and have it
419 00:55:57.180 ⇒ 00:56:10.979 David L: be in an easily digestible way is going to be, like, is going to drive some real change, and it is there. We have some of the data, we need other parts, we need to plug some more gaps in some other places, and or make things more efficient, but
420 00:56:12.180 ⇒ 00:56:28.300 David L: we can get there, and I’m sure with your help, it’s gonna be even better, but yes, there’s a lot of opportunity, specifically when it comes to data, and as a data person myself, I’m like, yes, let’s do it! Yeah. Just kind of like, let’s get everyone on board.
421 00:56:28.300 ⇒ 00:56:42.629 Uttam Kumaran: But at least you have the culture of, like, people are open to seeing this, and you have a rich history of data, you know, from a lot of it, and so that’s at least the two things that give me a lot of hope, is that people are really open to it. I think what we’re gonna try to do is, like.
422 00:56:43.070 ⇒ 00:56:50.590 Uttam Kumaran: propose a couple of projects. We’re also gonna propose, like, the structure in which we, like, report. Is that, like, a bi-weekly meeting?
423 00:56:50.700 ⇒ 00:57:09.370 Uttam Kumaran: Where we present a deck with insights, and we’ll walk through how long it takes to do that, and then it’s, like, maybe something that we can hand over to your team, or that we try to think about, okay, let’s just do this for San Antonio and for Steven, and then we sort of scale, like… So that’s kind of, like, for us to sort of put together a couple of these, like.
424 00:57:09.940 ⇒ 00:57:17.330 Uttam Kumaran: these things where we can… we can conduct, because we do this for a lot of companies, but then how do we start to be able to hand that off, you know, so you.
425 00:57:17.330 ⇒ 00:57:17.680 David L: Yeah.
426 00:57:17.680 ⇒ 00:57:20.720 Uttam Kumaran: to use us in, like, the ways that matter.
427 00:57:20.990 ⇒ 00:57:23.890 David L: Yeah, and I think that’s gonna be super important, because, I mean.
428 00:57:24.060 ⇒ 00:57:45.050 David L: people in the company are at kind of varying levels of, like, comprehension when it comes to data. So, case in point, I’m working with our lawn division to help set up KPIs for their department, and they’ve historically not had any KPIs at all. This is going to be the first time that they’re utilizing them. And they’ve been there in the background for, like, a couple of months, but no one’s really ever utilized them or engaged with.
429 00:57:45.050 ⇒ 00:57:45.600 Uttam Kumaran: Yeah.
430 00:57:45.670 ⇒ 00:57:50.840 David L: So, I’m now meeting with the division managers to kind of establish what are we going to measure, how are we going.
431 00:57:50.840 ⇒ 00:57:51.200 Uttam Kumaran: Right.
432 00:57:51.200 ⇒ 00:57:58.639 David L: And there are some people that I’m meeting with that their little questions are, like, what is a KPI, and how is it going to help us?
433 00:57:58.640 ⇒ 00:57:58.980 Uttam Kumaran: Yes.
434 00:57:58.980 ⇒ 00:58:02.370 David L: And so I’m like, you know, like, we’re gonna start from step one, from.
435 00:58:02.370 ⇒ 00:58:03.150 Uttam Kumaran: Yes.
436 00:58:03.150 ⇒ 00:58:03.849 David L: Yes, you know?
437 00:58:03.850 ⇒ 00:58:10.599 Uttam Kumaran: See, like, for… but you… that’s where you have to be with them the whole step of the way, the whole journey.
438 00:58:10.710 ⇒ 00:58:15.659 Uttam Kumaran: But the thing is, if you’re also inundated with, like, pulling random shit.
439 00:58:15.660 ⇒ 00:58:16.629 David L: I feel like there’s no…
440 00:58:16.630 ⇒ 00:58:17.790 Uttam Kumaran: No way, it happens.
441 00:58:17.790 ⇒ 00:58:18.360 David L: Exactly.
442 00:58:18.360 ⇒ 00:58:21.619 Uttam Kumaran: The way it happens. And so that’s what I really… I don’t think…
443 00:58:21.920 ⇒ 00:58:35.519 Uttam Kumaran: I just can tell that the leadership team doesn’t… it’s not because you haven’t explained, I just think they’re from a different world, and I want… I’m gonna go in there and be very concrete with them that, like, their team only has, you know.
444 00:58:35.750 ⇒ 00:58:52.310 Uttam Kumaran: mostly Brian and David, and you’re tasking them to… they want to, and you’re tasking them to go do this across the business, but they haven’t been given the right, you know, tools to do that. But they are the… they’re totally the right people. And so, for me, I’m gonna try to
445 00:58:52.520 ⇒ 00:58:57.910 Uttam Kumaran: Break down to them, like, what it takes to go into a report, to make a report, and then be like.
446 00:58:58.190 ⇒ 00:59:06.780 Uttam Kumaran: This 50%… how can we get… remove 50% of that off, either through new process, or budget, or new tooling, you know?
447 00:59:06.780 ⇒ 00:59:19.759 David L: And a lot of things on the data team have come out, have been born out of necessity, as I’m sure is the standard case with many groups in our thing, but, like, before this.
448 00:59:19.920 ⇒ 00:59:21.140 David L: We didn’t know
449 00:59:21.260 ⇒ 00:59:28.299 David L: Neither Brian or I knew anything about Power Automate, and it took a lot of trial and error, but we’re utilizing that now.
450 00:59:28.300 ⇒ 00:59:28.950 Uttam Kumaran: Yeah.
451 00:59:28.950 ⇒ 00:59:44.519 David L: Power BI, we’re dipping our toes into that, we want to start using Access and SQL, but… and so, again, there’s things we want to do, but being inundated with everything else kind of makes that difficult to kind of grow, and… but a lot of those things have come out of necessity, because, like, we have so much to do, how can we make it easier?
452 00:59:44.520 ⇒ 00:59:45.090 Uttam Kumaran: Yes.
453 00:59:45.090 ⇒ 00:59:53.610 David L: let’s look at Automate. I hear that’s good, let’s try it out. You know, like, a lot of… and we’ve engaged in conversations with, like, 8Byte about their workforce management.
454 00:59:53.610 ⇒ 00:59:54.309 Uttam Kumaran: Yeah, yeah, yeah.
455 00:59:54.310 ⇒ 01:00:07.159 David L: for creating stuff, because we’re still doing a lot of that stuff when it comes to the call center, what we call plotters, and we are doing that manually, which is taking… it used to take about, like, 8 hours. We’ve got it down to 4, but that’s still 4 hours that we could be utilizing.
456 01:00:07.160 ⇒ 01:00:07.990 Uttam Kumaran: Yeah, yeah, yeah, yeah.
457 01:00:07.990 ⇒ 01:00:23.609 David L: elsewhere, you know? So there’s… there’s things that we’re trying to do, it’s just a lot of things, and then we’re given… there’s another project I have on my plate about how to track route completion for our pest technicians, which I know I’ve got a pretty good foundation on that, but I know that once that’s built out.
458 01:00:23.830 ⇒ 01:00:27.329 David L: This department’s gonna have it, then that department’s gonna want it, and that department’s gonna.
459 01:00:27.330 ⇒ 01:00:28.080 Uttam Kumaran: Yeah, yeah, yeah.
460 01:00:28.080 ⇒ 01:00:37.339 David L: Scaling that up to everyone else is going to be another beast entirely. So yes, having the tools or, like, just streamlining things is going to make things a whole lot more…
461 01:00:37.610 ⇒ 01:00:45.480 David L: better, especially as we start to grow, because I think now it’s going to be at… it’s literally at the point where, like, one person has it, they start talking, this person hears it.
462 01:00:45.480 ⇒ 01:00:46.020 Uttam Kumaran: Yeah.
463 01:00:46.020 ⇒ 01:00:48.900 David L: We want that too, and… Yeah.
464 01:00:48.900 ⇒ 01:00:53.700 Uttam Kumaran: Are there things in Power BI, or are you using Power Automate already?
465 01:00:54.160 ⇒ 01:01:08.630 David L: Yes, both Brian and I are using it on a daily basis. I’ve incorporated it into my KPIs, too, that way it just cleans up my report, and I can just drop it into another spreadsheet. It’ll fetch all the data from that, and put it in.
466 01:01:08.870 ⇒ 01:01:25.400 David L: But there’s still cleanup involved, especially with the lawn division. Their naming conventions are just outrageously inconsistent, across systems, and even within systems themselves. So yeah, so we are using Automate. I’m pretty sure we could use it…
467 01:01:25.490 ⇒ 01:01:29.790 David L: Like, at a different level than we’re currently at, but yes, we are.
468 01:01:30.260 ⇒ 01:01:31.950 Uttam Kumaran: And then Power BI, as well.
469 01:01:31.980 ⇒ 01:01:35.329 David L: Power BI, we dipped our toe into it.
470 01:01:35.330 ⇒ 01:01:36.500 Uttam Kumaran: Julie mentioned.
471 01:01:36.500 ⇒ 01:01:44.600 David L: Yeah. I used it to display some data for a few months. I really don’t feel like that… that was being utilized at all, so…
472 01:01:44.600 ⇒ 01:01:46.380 Uttam Kumaran: It’s also very complicated.
473 01:01:46.640 ⇒ 01:01:49.740 Uttam Kumaran: And there’s a lot of better solutions that I would love to share.
474 01:01:49.910 ⇒ 01:01:52.879 Uttam Kumaran: But you guys, it’ll just… the UX is a lot… would be a lot easier.
475 01:01:52.880 ⇒ 01:02:09.090 David L: Yeah, I’m down for learning all the things. Yeah, so we’ve tried to kind of expand and make things a little bit more efficient. I think Power Automate has definitely helped a lot, but there’s still, again, there’s plenty of room to grow here and to do things better, yeah.
476 01:02:09.090 ⇒ 01:02:10.460 Uttam Kumaran: Okay. Okay.
477 01:02:10.910 ⇒ 01:02:21.930 Uttam Kumaran: Okay, great. I feel like I covered everything I need. If there’s anything I can be helpful with in the short term, please let me know. Are you… I assume you guys will be… I don’t know if you’re out the next, like, 2 weeks.
478 01:02:22.150 ⇒ 01:02:27.009 David L: Yes, yeah, I think that everyone in the company, not everyone, but, like, pretty much everyone is, like, the last.
479 01:02:27.010 ⇒ 01:02:27.909 Uttam Kumaran: So then maybe
480 01:02:28.820 ⇒ 01:02:32.730 Uttam Kumaran: Yeah, let me see if I can try to come in, like, the first week of January.
481 01:02:32.730 ⇒ 01:02:33.919 David L: Sure, yeah.
482 01:02:33.920 ⇒ 01:02:47.359 Uttam Kumaran: And, like, just try to… by that point, we will have looked at a lot of things, and at least you can come in and present some of that. We’re not due to sort of wrap up this sort of stuff until, like, mid-January, so that’d be good timing.
483 01:02:47.360 ⇒ 01:02:56.840 Uttam Kumaran: I’m sure there’ll be a lot of, like, stuff on fire coming back in, so I would love to… I would love… not that I, like, want to see… but, like, it would be helpful for me to, like.
484 01:02:56.860 ⇒ 01:02:57.899 Uttam Kumaran: Just get a little bit of.
485 01:02:57.900 ⇒ 01:02:59.659 David L: That’s what it’s really like, yeah.
486 01:02:59.660 ⇒ 01:03:09.350 Uttam Kumaran: Yeah, and then also just spend some time with you guys and try to, again, just make sure I have the… what we’re gonna go pitch for really, really clear. But I do think that we can…
487 01:03:09.520 ⇒ 01:03:13.960 Uttam Kumaran: I think we can help out in a lot of ways, so I’m really, really looking forward to it.
488 01:03:14.260 ⇒ 01:03:20.309 David L: Okay, sweet, I’m down, and let me know if you have any other questions or need any other information. I’ll try my best to help out as.
489 01:03:20.310 ⇒ 01:03:20.970 Uttam Kumaran: Okay.
490 01:03:20.970 ⇒ 01:03:21.970 David L: Yeah. Thank you.
491 01:03:21.970 ⇒ 01:03:22.970 Uttam Kumaran: Thank you so much.
492 01:03:22.970 ⇒ 01:03:25.199 David L: Of course, Navidal, thanks for taking the time.
493 01:03:25.440 ⇒ 01:03:26.590 Uttam Kumaran: Thank you, David. Appreciate it.
494 01:03:26.590 ⇒ 01:03:27.240 David L: I…