Meeting Title: [Pool-Parts-to-Go]-Weekly-Sprint-Review Date: 2024-02-15 Meeting participants: Ryan Luke Daque, Patrick Trainer, Uttam Kumaran
WEBVTT
1 00:01:49.790 ⇒ 00:01:52.970 Uttam Kumaran: Hey, Pat, what’s up? Very good morning.
2 00:01:54.480 ⇒ 00:01:55.500 Patrick Trainer: How’s it going?
3 00:01:56.660 ⇒ 00:01:58.850 Uttam Kumaran: Good! How are you?
4 00:01:59.080 ⇒ 00:02:00.470 Patrick Trainer: Not too bad.
5 00:02:02.950 ⇒ 00:02:05.210 Patrick Trainer: not too bad, too. Ryan.
6 00:02:05.850 ⇒ 00:02:09.719 Ryan Luke Daque: Hi, Patrick, welcome. Yeah, thank you. Thank you. Good to meet you.
7 00:02:10.060 ⇒ 00:02:11.639 Ryan Luke Daque: Nice to meet you as well.
8 00:02:12.850 ⇒ 00:02:14.340 Uttam Kumaran: Yeah.
9 00:02:14.560 ⇒ 00:02:32.089 Uttam Kumaran: So maybe we just do a little bit of brief intro. So Pat Ryan, has been helping me on the pool parts accounts. Basically, I was handling a lot of modeling, for, you know, maybe like 3 or 4 months, and then
10 00:02:32.520 ⇒ 00:02:50.139 Uttam Kumaran: sort of reached out and and found out about Ryan. And he’s been working on modeling pretty much everything related to modeling within light dash and within. Dbt, and so we’ve been working together on that for a few months now.
11 00:02:50.380 ⇒ 00:02:59.029 Uttam Kumaran: And then Ryan, as I mentioned, Pat is coming on to kind of help with pretty much everything visualization and dashboarding.
12 00:02:59.060 ⇒ 00:03:12.560 Uttam Kumaran: and that’s kind of his his main expertise. So I know, Ryan. We’ve been working on a lot on a bunch of other dashboards, and I think we have a good foundation. But I’m excited to to see kind of Patrick’s impact.
13 00:03:12.680 ⇒ 00:03:33.829 Uttam Kumaran: And then, yeah, I guess you know, I think it’s it’s mainly been me and Ryan so far. So we’ll kind of see how you know communication and things need to evolve a little bit if it’s the 3 of us. But basically, you know, we just do these meetings at the start of every week. We’re we’re running like one week sprints, basically because I usually talk to.
14 00:03:34.270 ⇒ 00:03:39.759 Uttam Kumaran: I usually talk to Ben or Dan every Friday like Friday morning. So we usually run like
15 00:03:39.940 ⇒ 00:03:53.689 Uttam Kumaran: Monday to Friday, and then we have like check in on Monday to kind of plan out the week. And then Thursday, just because we’ll kind of see where we end up before my call tomorrow with them, where I kind of do Demos.
16 00:03:54.270 ⇒ 00:03:58.639 Uttam Kumaran: I think, Pat, as we kind of like make progress. I’ll probably just add you to that
17 00:03:58.780 ⇒ 00:04:03.209 Uttam Kumaran: call, or we can kind of see what stuff is is
18 00:04:03.230 ⇒ 00:04:06.469 Uttam Kumaran: more visual, or if we need to do another meeting cause
19 00:04:06.790 ⇒ 00:04:09.000 Uttam Kumaran: usually that’s like 30 min to an hour. But
20 00:04:09.700 ⇒ 00:04:17.650 Patrick Trainer: yeah, no, that that that makes sense. And I think that like in a consulting kind of context, to like one week sprint, sir, like.
21 00:04:18.040 ⇒ 00:04:38.579 Patrick Trainer: it’s quick iteration. And then it’s like things happen faster. I think. Yeah, I wanted to avoid, you know, again, like, I just want to avoid like doing anything on like a daily basis. Cause it’s just like hair on fire mentality. But at the same time I think it’s good cause I meet with them on Friday. I kind of get a download of like, okay, here, like some
22 00:04:38.600 ⇒ 00:04:49.590 Uttam Kumaran: short medium and long term priorities. How does that differ from what we already plan? And then let’s go ahead and look at the backlog, and and then make some moves.
23 00:04:49.750 ⇒ 00:04:52.820 Patrick Trainer: So I think, then, sorry. Go on.
24 00:04:53.660 ⇒ 00:05:04.710 Patrick Trainer: Okay, I was gonna say so like, I saw that we’re using like github like projects in all of that. How
25 00:05:05.200 ⇒ 00:05:16.520 Patrick Trainer: how do you think of that? In terms of like like? Does the client have insight into that, or viewership into into that? How are
26 00:05:16.630 ⇒ 00:05:30.270 Patrick Trainer: sprints planned? And then like, wh, how do you go through the backlog like? Is it like kind of like a traditional like agile grooming thing without the ritual, I assume, or is it more of a
27 00:05:30.330 ⇒ 00:05:35.400 Patrick Trainer: Async type? Effort? Yeah.
28 00:05:35.470 ⇒ 00:05:41.909 Uttam Kumaran: So usually on. The way it works is on Friday. I usually get a whole batch of like
29 00:05:42.240 ⇒ 00:05:51.780 Uttam Kumaran: like updates from them, and I’m able to give them like a whole host of updates. And in that Github project. You’ll see that there is, you know, like a typical
30 00:05:52.270 ⇒ 00:05:55.630 Uttam Kumaran: work flow for how tickets move from like
31 00:05:55.730 ⇒ 00:05:59.679 Uttam Kumaran: like triage to backlog, to actually getting like scheduled
32 00:05:59.700 ⇒ 00:06:11.960 Uttam Kumaran: Github Project doesn’t have like, we’re mainly relying on some of their labels to do priorities and like sizing. But all that kind of happens on Monday.
33 00:06:11.990 ⇒ 00:06:23.130 Uttam Kumaran: and we’re not working with like too many tickets, because it’s just a couple of us. So it’s usually like 3 to 5 tickets. Each is like usually, and then I try to leave some gap, for like
34 00:06:23.210 ⇒ 00:06:26.900 Uttam Kumaran: things that come up, because during the week I may get like
35 00:06:27.030 ⇒ 00:06:39.279 Uttam Kumaran: kind of urgent modeling asks or like analysis, and so try to just leave a little bit of gap for that. And then everything kind, everything else we kind of just go through. And then again, the goal is to see. To make sure we wrap everything up
36 00:06:39.920 ⇒ 00:06:49.800 Uttam Kumaran: by the end of Thursday or by the end of Friday, if it’s something that doesn’t need to be demoed like bug fixes or things like that.
37 00:06:49.880 ⇒ 00:06:59.049 Uttam Kumaran: And then so I would say, Monday is where we do a lot of grooming. I’ll just try to get everything in, usually by Sunday or or before the meeting Monday morning.
38 00:06:59.140 ⇒ 00:07:08.660 Uttam Kumaran: and then we can kind of walk through all the tasks again. A lot of this isn’t is, they’re not looking at the Github project. They know we have project management. But
39 00:07:08.810 ⇒ 00:07:20.470 Uttam Kumaran: those guys are just like, however, you guys wanna do it mainly for me to articulate to them like I, I’ll try to send an update in the middle of the week, or, as we do, releases for stuff.
40 00:07:20.530 ⇒ 00:07:30.390 Patrick Trainer: it’s good for me to just be able to see, like what else we have on our plate. So you don’t have to think about it. Really, you can just see it.
41 00:07:30.470 ⇒ 00:07:38.960 Uttam Kumaran: Yeah, that’s exactly right. So a lot of the project management is like my philosophy on it is like as lightweight. but like
42 00:07:39.050 ⇒ 00:07:47.379 Uttam Kumaran: as lightweight as possible, but also as effective as possible. To like. Take off a lot of thought on our plate, for example. I don’t want.
43 00:07:47.930 ⇒ 00:07:53.460 Uttam Kumaran: I don’t want to like, have everybody maintaining their own to do list, and then having to think about their own sprints. It’s like this
44 00:07:53.610 ⇒ 00:08:09.869 Uttam Kumaran: sort of architecture, I think, takes a lot of that burden off at the same time, I think, of course, like just like any team we can get better with. Like task descriptions. Things like that again. I’m it’s got kind of me and Ryan. I’ve been switching off doing some of that. So it’s a little bit of like.
45 00:08:09.890 ⇒ 00:08:15.240 Uttam Kumaran: manage your own stuff. And then, as a team like, let’s just make sure we all.
46 00:08:15.290 ⇒ 00:08:29.379 Uttam Kumaran: if there need to do. If there’s cross functional work we can all get it done. I would say. Ryan has been handling most of it. I’ve been slowing down a little bit I handle really like some. If there’s like a lot of ad hoc stuff that comes up.
47 00:08:29.420 ⇒ 00:08:32.619 Uttam Kumaran: I’ll kind of sub in or
48 00:08:32.640 ⇒ 00:08:44.489 Uttam Kumaran: I’m kind of like. Of course I’m I’m kind of spending a lot of time on the business on the sales side. So Ryan will really be your like main counterpart on the modeling. And then but but like
49 00:08:44.600 ⇒ 00:08:56.859 Uttam Kumaran: we can hopefully, you can get a good sense of the code base and everything and stuff is relatively clean. I think we could do. We could, of course, do a little bit of better job. But everything’s like Dbt and
50 00:08:56.910 ⇒ 00:08:58.410 Uttam Kumaran: everything’s workflows.
51 00:08:58.430 ⇒ 00:09:05.769 Patrick Trainer: if you want to invite me to those repos. The only one that I can see is like.
52 00:09:06.450 ⇒ 00:09:09.109 Patrick Trainer: think it’s called like, eat lunch or something.
53 00:09:09.240 ⇒ 00:09:19.389 Uttam Kumaran: Oh, okay, let me invite you. Yeah, yeah, I think that may be like a public repo or something. But yeah, let me let me invite you.
54 00:09:20.330 ⇒ 00:09:26.320 Uttam Kumaran: And I guess in the meantime, Ryan, do you want to drive for today? And we can just go through this branch?
55 00:09:26.880 ⇒ 00:09:30.100 Ryan Luke Daque: Yeah, sure, I can share my screen. Then
56 00:09:30.910 ⇒ 00:09:33.729 Ryan Luke Daque: what we’ve been doing for this week.
57 00:09:40.480 ⇒ 00:09:42.450 Ryan Luke Daque: Are you able to see my screen? Now?
58 00:09:43.230 ⇒ 00:09:44.350 Patrick Trainer: Yeah.
59 00:09:44.870 ⇒ 00:09:52.660 Ryan Luke Daque: nice. So. yeah, this is this is our current sprint like
60 00:09:56.440 ⇒ 00:10:00.669 Ryan Luke Daque: so basically, this is the the 2 parts to the project that we have
61 00:10:02.130 ⇒ 00:10:05.279 Ryan Luke Daque: for current sprint. We have these
62 00:10:06.590 ⇒ 00:10:10.620 Ryan Luke Daque: think it’s available. So.
63 00:10:11.360 ⇒ 00:10:17.010 Ryan Luke Daque: But like most of what we did this week, basically was to answer like a couple of
64 00:10:17.040 ⇒ 00:10:21.529 Ryan Luke Daque: questions regarding sales discounts refunds as well as
65 00:10:21.620 ⇒ 00:10:28.709 Ryan Luke Daque: marketing. Basically, we’re trying to brainstorm unlike what are like.
66 00:10:29.100 ⇒ 00:10:31.040 Ryan Luke Daque: good questions to answer.
67 00:10:31.540 ⇒ 00:10:36.919 Ryan Luke Daque: well, good good questions to ask. Basically like for for marketing.
68 00:10:37.160 ⇒ 00:10:43.160 Patrick Trainer: that we can show show the client like, like different kind of metrics.
69 00:10:43.410 ⇒ 00:10:46.330 Ryan Luke Daque: Yeah. Metrics. And then
70 00:10:46.750 ⇒ 00:10:49.380 Ryan Luke Daque: well, we. We are trying to categorize them.
71 00:10:49.750 ⇒ 00:10:56.779 Ryan Luke Daque: These questions, whether we all? Have we have the data for these questions to answer these questions.
72 00:10:57.320 ⇒ 00:11:00.079 Ryan Luke Daque: or or we have the data, but we don’t.
73 00:11:00.350 ⇒ 00:11:03.740 Ryan Luke Daque: We are missing some of the metrics and dimensions.
74 00:11:04.380 ⇒ 00:11:06.730 or if we don’t have them at all
75 00:11:06.780 ⇒ 00:11:11.659 Ryan Luke Daque: like, for example, this one like site, graphic profiles, for example, we don’t have that
76 00:11:11.730 ⇒ 00:11:13.150 Ryan Luke Daque: specific data.
77 00:11:14.120 ⇒ 00:11:28.709 Ryan Luke Daque: So that’s what I’m I’ve been doing for marketing. And currently, I’m also doing. It’s still in progress. But for sales as well. I have a couple of questions here that I’m still trying to figure out. Like, if we have this data, or if we don’t
78 00:11:28.970 ⇒ 00:11:35.679 Ryan Luke Daque: stuff like that, and for refunds I believe. Yeah, Google, Thomas is also like, doing this
79 00:11:35.970 ⇒ 00:11:37.290 Ryan Luke Daque: on his end as well.
80 00:11:37.740 ⇒ 00:11:51.380 Uttam Kumaran: Yeah. Yeah. And to kind of give you a little bit of like the onus of over this, Patrick. We’ve been spending probably the last like couple of months on like really hardcore modeling. And now we have.
81 00:11:51.610 ⇒ 00:12:06.729 Uttam Kumaran: you know a of course, like Sansa couple like smaller bugs, we have most of the business models for all the way from sales to return to shipments to Zendesk, you know the whole thing, and so I kind of wanted to take a week
82 00:12:06.790 ⇒ 00:12:22.740 Uttam Kumaran: or 2 and switch to more like analysis mode, especially while you’re kind of here, asking like a ton of really core second and third degree questions like about customer Ltv, about retention, about
83 00:12:22.850 ⇒ 00:12:34.150 Uttam Kumaran: bundling like asking a ton of really interesting questions. because we’ve been doing a little bit of that here and there. But I think now that all the data is model that want us to kind of use the tool, and
84 00:12:34.670 ⇒ 00:12:42.510 Uttam Kumaran: to see number one, can we answer all those? Do we have all the data to answer those, and then to of course, like share the insight back.
85 00:12:42.720 ⇒ 00:12:45.239 Uttam Kumaran: so yeah, I was, gonna say, I imagine, like
86 00:12:45.350 ⇒ 00:12:52.540 Patrick Trainer: breaking into cohorts and going from there is gonna be like a huge huge win.
87 00:12:52.800 ⇒ 00:13:01.799 Uttam Kumaran: Exactly, and conversations like that, you know, I was even texting. Ben yesterday is like understanding like what are their customer time as well. They have like pool service guys. And they have like
88 00:13:02.020 ⇒ 00:13:28.289 Uttam Kumaran: people that are residential. I’m like, Okay, cool. That’s some. This is segment. That’s a flag that we can try and maintain. Okay, can we look at that? And can we look at the average order value for each of those like, are there different characteristics we did expect for both those repeat buyers, etc., and then how to like discounts. So the one thing Ben always stressed to me is like we have a couple of different levers like
89 00:13:28.470 ⇒ 00:13:35.179 Uttam Kumaran: they can. They can affect shipping costs, they can affect marketing, and they can affect pricing of the products
90 00:13:35.220 ⇒ 00:13:49.949 Uttam Kumaran: right? And those are the key levers that they have on their end. For example, they could lower the prices of things, offer discounts, do promotions and then they can, you know, cut or expand Skus to different regions. So
91 00:13:50.330 ⇒ 00:13:57.230 Uttam Kumaran: a lot of it’s it’s great, because I it’s like it’s refreshing to hear that those are the levers that the thing we have to do is understand?
92 00:13:57.290 ⇒ 00:14:04.580 Uttam Kumaran: Okay, how does pricing affect sales? Okay, that’s a really broad question. Can we get a sense of that. Okay, how do like
93 00:14:04.780 ⇒ 00:14:09.510 Uttam Kumaran: does does marketing channel? Does the marketing channel from which a customer
94 00:14:09.700 ⇒ 00:14:11.740 Uttam Kumaran: tame effects
95 00:14:11.930 ⇒ 00:14:20.180 Uttam Kumaran: the way they purchase, you know, don’t purchase right. And so those are all like, okay, now that we have everything. And we have, like
96 00:14:20.210 ⇒ 00:14:26.489 Uttam Kumaran: the joins between everything we can pretty much answer. So I wanted to take a week or 2 and like, gather a ton of that data.
97 00:14:26.550 ⇒ 00:14:32.839 Patrick Trainer: Okay, cool. How? How big is there like underlying data set?
98 00:14:33.890 ⇒ 00:14:41.680 Uttam Kumaran: Is it pretty big or like. Are they dealing with like, what? How? How many orders are these guys shipping out?
99 00:14:42.640 ⇒ 00:14:58.149 Uttam Kumaran: I think it may be like a hundred or 200 orders a day, the the part about the tough part about this business. So it’s about like a 20 million dollar annual business. The big part of this. That’s the toughest pat is that it’s a very, very seasonal business.
100 00:14:58.330 ⇒ 00:15:10.780 Uttam Kumaran: Of course. Yeah. So I would say, a majority of their sales happens within 4 months in the summer so starting about March until like
101 00:15:11.290 ⇒ 00:15:16.160 Uttam Kumaran: October or the month before, like September.
102 00:15:16.180 ⇒ 00:15:26.830 Uttam Kumaran: is where most of their business happens. and you’ll. And that’s what I think. Number one, you really unique about this business. And they’re very concentrated in terms of geography.
103 00:15:26.960 ⇒ 00:15:31.670 Uttam Kumaran: So most of their sales are California, Texas, New York, Florida.
104 00:15:32.090 ⇒ 00:15:34.699 Uttam Kumaran: like places where there there are pools.
105 00:15:34.740 ⇒ 00:15:48.969 Uttam Kumaran: Arizona. And so there’s a ton of like really interesting, like 80 20 concentration going on right? so that’s what we took. So there, there’s some stuff on the shipping side that I really help them understand with that.
106 00:15:49.000 ⇒ 00:15:54.529 Uttam Kumaran: But I think there’s a ton of other like interesting things we could find because of that seasonality.
107 00:15:54.760 ⇒ 00:16:08.549 Uttam Kumaran: However, I’m glad that this year we’ve helped them have all this data before that busy season starts, because I want to provide them with that as much data as possible to make decisions to really maximize this year.
108 00:16:08.570 ⇒ 00:16:28.010 Uttam Kumaran: The last thing I’ll mention is I talked, you know I talked to Dan and Ben, and both of them are kind of have, like different views of like the company, which is interesting. Dan, I think, is like really concentrated on like growth. And how do you and you know he he’s able to do partnerships and a lot of interesting things. Ben is much more focused on like, can we be profitable every day?
109 00:16:28.020 ⇒ 00:16:54.540 Uttam Kumaran: Profitable? And so it’s like an interesting dynamic one that, I think is good. And it’s also tough on that data side. Cause it’s like each care about different things. So I think that’ll be an interesting challenge for you to kind of understand, like how to display information for them. But for me, those are 2 thoughts that I can have in my head at the same time on the analysis side, and kind of be like.
110 00:16:54.600 ⇒ 00:17:20.390 Uttam Kumaran: let’s identify like, which are your growing segments of people, regions, things like that. And then let’s also understand. Okay, where the really costs driving from like, for example, we know this year that discounts are very high compared to the same time last year. Great like, let’s go through and really make sure we understand, like, what products are getting refunded, what products are getting discounted is that expected? Like, let’s go do all that stuff. So
111 00:17:20.420 ⇒ 00:17:22.099 Uttam Kumaran: yeah, basically
112 00:17:22.410 ⇒ 00:17:23.380 Patrick Trainer: cool.
113 00:17:27.230 ⇒ 00:17:33.359 Uttam Kumaran: Well, I guess Ryan, is there anything else on this break that we need to go through?
114 00:17:33.900 ⇒ 00:17:35.330 Ryan Luke Daque: I guess we can.
115 00:17:35.730 ⇒ 00:17:41.799 Ryan Luke Daque: Well, II can. The the other tickets that were left from last spring. I can.
116 00:17:42.300 ⇒ 00:17:46.299 Ryan Luke Daque: Lisa, already done. I believe the the one where we just
117 00:17:46.740 ⇒ 00:17:49.040 Ryan Luke Daque: made thecipient names, and
118 00:17:49.480 ⇒ 00:17:50.539 Ryan Luke Daque: in it the cap.
119 00:17:50.930 ⇒ 00:17:53.920 Uttam Kumaran: Oh, yeah, yeah, let’s mark that is done
120 00:17:54.060 ⇒ 00:18:03.730 Ryan Luke Daque: aren’t matching between
121 00:18:04.070 ⇒ 00:18:07.979 Ryan Luke Daque: our logic and and and the
122 00:18:09.180 ⇒ 00:18:20.100 Uttam Kumaran: the one from Amazon basically, is that log? Is that new logic in? Yes, it is already. Okay. Let’s mark it as done. And maybe you can. Can you create like a bug ticket to just like
123 00:18:20.470 ⇒ 00:18:23.859 Uttam Kumaran: to just say, like, Come back and identify those
124 00:18:24.800 ⇒ 00:18:30.619 Uttam Kumaran: those issue fees because the impact is very low. So I just wanna move on.
125 00:18:34.210 ⇒ 00:18:41.159 Ryan Luke Daque: Yeah, I’ll add a ticket for that later. One more that we have is this one where we’re supposed to like add
126 00:18:41.970 ⇒ 00:18:45.000 Uttam Kumaran: like a dropdown for yeah.
127 00:18:45.330 ⇒ 00:18:47.490 Yeah. But like, like, dash
128 00:18:47.830 ⇒ 00:18:49.909 Ryan Luke Daque: support mentioned that it’s not.
129 00:18:51.530 ⇒ 00:18:58.129 Ryan Luke Daque: They don’t have the capability for this one. So I guess, did. Do they have like parameterized queries.
130 00:18:58.220 ⇒ 00:19:00.510 Uttam Kumaran: I don’t think they have parameters.
131 00:19:02.550 ⇒ 00:19:03.540 Ryan Luke Daque: Yeah.
132 00:19:03.900 ⇒ 00:19:05.770 Uttam Kumaran: I think that’s unfortunate.
133 00:19:05.820 ⇒ 00:19:10.459 Uttam Kumaran: Yeah, I’ll have to check cause I don’t. II don’t know whether you can.
134 00:19:11.750 ⇒ 00:19:19.200 Uttam Kumaran: You could do SQL within the metric definition. But basically what I’m gonna I don’t think you can take a filter value and
135 00:19:19.820 ⇒ 00:19:24.360 Uttam Kumaran: like, apply it to the drop an enum in there. Yeah.
136 00:19:26.140 ⇒ 00:19:27.920 Patrick Trainer: interesting. Okay?
137 00:19:28.470 ⇒ 00:19:32.920 Uttam Kumaran: So the solve for this one is like, basically we need to just go through and create
138 00:19:33.460 ⇒ 00:19:35.180 Uttam Kumaran: each of these metrics.
139 00:19:36.260 ⇒ 00:19:38.599 Ryan Luke Daque: Yeah, we can do that like one
140 00:19:39.180 ⇒ 00:19:42.540 Ryan Luke Daque: chart for 7 day, one for 30 day.
141 00:19:42.910 ⇒ 00:19:48.629 Uttam Kumaran: Yeah, one for you thinking, yeah, something like that it’s tough, because I just wanna see.
142 00:19:50.950 ⇒ 00:19:55.190 Uttam Kumaran: I want to see all the kpis with these different metrics.
143 00:19:56.290 ⇒ 00:19:56.980 Uttam Kumaran: That’s
144 00:19:57.100 ⇒ 00:19:58.920 Uttam Kumaran: sorry.
145 00:19:59.120 ⇒ 00:20:02.449 Uttam Kumaran: But yeah, we have to create a metric for each one. So
146 00:20:03.650 ⇒ 00:20:04.550 Uttam Kumaran: I don’t know.
147 00:20:09.280 ⇒ 00:20:12.160 Uttam Kumaran: Okay, let’s leave that for now.
148 00:20:12.950 ⇒ 00:20:13.650 Ryan Luke Daque: okay.
149 00:20:14.130 ⇒ 00:20:20.349 Ryan Luke Daque: yeah, And aside from that, that’s basically what we have for this week.
150 00:20:21.050 ⇒ 00:20:31.220 Uttam Kumaran: So on the marketing stuff like, are you working through? like the links for all these questions? Or were you like actually saving the analysis.
151 00:20:33.000 ⇒ 00:20:42.020 Ryan Luke Daque: for the ones that we have. For example, I just did a light dash preview, and just try
152 00:20:42.040 ⇒ 00:20:43.270 Ryan Luke Daque: creating a
153 00:20:43.840 ⇒ 00:20:45.800 Ryan Luke Daque: you know tables for this.
154 00:20:45.950 ⇒ 00:20:50.280 Ryan Luke Daque: But I didn’t save them. Do do. I can save them.
155 00:20:50.440 ⇒ 00:20:53.090 Ryan Luke Daque: That’s new queries, I guess.
156 00:20:53.460 ⇒ 00:21:11.910 Uttam Kumaran: Yeah, maybe if you can just create like a folder and save them. I mean again, the goal here is to actually answer these questions. So III not only just wanna, go through and understand, can we. But anything where there are updates need to be made. If they’re quick, let’s just make them
157 00:21:12.090 ⇒ 00:21:22.729 Uttam Kumaran: I wanna I wanna be able to send them some analysis tomorrow. With some of these, put some of these answers. So maybe even like moving beyond.
158 00:21:23.620 ⇒ 00:21:36.970 Uttam Kumaran: like, I know, we’re moving over to sales. But if you can just quickly categorize the sales and then try to just knock out as much as possible that way. Later. Today I can review and then try to get some stuff together to show them tomorrow morning.
159 00:21:37.200 ⇒ 00:21:40.880 Ryan Luke Daque: Yeah. Sounds good. Yeah. I’ll prioritize the
160 00:21:41.020 ⇒ 00:21:46.760 Ryan Luke Daque: the things that we have like the day. The questions that can be answered by what we currently have.
161 00:21:46.940 ⇒ 00:21:54.459 Ryan Luke Daque: And then, if, like, some of these are easy to to do a data model on like, maybe just a quick join. Then maybe I’ll do that as well.
162 00:21:55.190 ⇒ 00:21:57.980 Ryan Luke Daque: and I’ll just save them in light dash as a new
163 00:21:58.620 ⇒ 00:22:05.020 Uttam Kumaran: like folder here space, I guess.
164 00:22:05.410 ⇒ 00:22:10.679 Uttam Kumaran: and then, if in figma, if you can just add links. So that’s easy to navigate.
165 00:22:11.050 ⇒ 00:22:11.840 Ryan Luke Daque: sure.
166 00:22:13.210 ⇒ 00:22:15.289 Ryan Luke Daque: Yeah, I’ll add the links here.
167 00:22:15.630 ⇒ 00:22:21.099 Uttam Kumaran: Yeah. Just go through and see how as many as you can do, and then we can have a discussion about
168 00:22:21.960 ⇒ 00:22:23.380 Uttam Kumaran: how things are looking.
169 00:22:24.240 ⇒ 00:22:25.520 Ryan Luke Daque: Sure sounds good
170 00:22:27.030 ⇒ 00:22:38.760 Uttam Kumaran: and then I guess for Pat. So maybe one thing we can do is if you wanna go in here. And I just added you to the repo as well. If you wanna go in here and begin to add stuff to the backlog
171 00:22:38.880 ⇒ 00:22:40.609 Uttam Kumaran: again, just like as
172 00:22:40.790 ⇒ 00:22:47.940 Uttam Kumaran: you know as best as you need to. That would maybe great for just tracking, and then
173 00:22:47.950 ⇒ 00:22:51.729 Uttam Kumaran: I know we mentioned I mentioned to Ben that you kind of really get started
174 00:22:52.010 ⇒ 00:23:05.449 Uttam Kumaran: on stuff next weekend, but let me know what you think about scheduling stuff with their team. And I mean again, we have 2 days today. So I think there’s still time to get stuff done. So let me know what you think.
175 00:23:05.960 ⇒ 00:23:07.170 Patrick Trainer: Okay, cool.
176 00:23:08.750 ⇒ 00:23:14.910 Uttam Kumaran: yeah. I think the best thing is I’ll I’ll kind of leave it to you to think about
177 00:23:14.960 ⇒ 00:23:24.309 Uttam Kumaran: If we need to meet with anyone for their side, I would say, I have a ton of context about the business like in my brain. So I’m happy to give you
178 00:23:24.340 ⇒ 00:23:31.020 Uttam Kumaran: as much as I know. And then, if there’s the remaining questions for Dan and Ben.
179 00:23:31.120 ⇒ 00:23:33.810 Uttam Kumaran: can either email them.
180 00:23:33.890 ⇒ 00:23:37.630 Uttam Kumaran: which I think is easier for everybody, or we can hop on the phone with them.
181 00:23:37.780 ⇒ 00:23:44.699 Uttam Kumaran: I know Dan is out, but Ben is really responsive. But if you just email him, he’ll really get back to you pretty quick.
182 00:23:44.940 ⇒ 00:23:47.419 Uttam Kumaran: And then.
183 00:23:47.940 ⇒ 00:23:53.600 Patrick Trainer: yeah, we can go from there. What? What do you. What do you think? So far? I mean, that sounds good to me.
184 00:23:53.790 ⇒ 00:24:02.750 Patrick Trainer: Yeah, everything’s everything. Seems I mean very straightforward. And I mean it’s all similar workflows to.
185 00:24:02.890 ⇒ 00:24:03.760 Patrick Trainer: But
186 00:24:03.970 ⇒ 00:24:14.179 Uttam Kumaran: I’m used to. So, okay, cool, yeah, my goal with this sort of project management stuff is, it needs to work for us and to do as little of it as possible.
187 00:24:14.190 ⇒ 00:24:37.910 Uttam Kumaran: pretty much like there’s there’s nobody like looking at ticket quality and stuff like that. I’m just like, what do we need to be able to get the job done and let’s go do the job. Yeah, I mean again, I was one for like 2 years. No, I mean, II actually was very. I would tell people that like
188 00:24:38.000 ⇒ 00:24:41.309 Uttam Kumaran: the only reason I existed in that role is because
189 00:24:41.640 ⇒ 00:24:52.710 Uttam Kumaran: we people couldn’t like keep to do lists. And so I’m like, I have to be like the company to do list person, you know. And I was like, and it was tough, because, like, I’m an engineer, and I’m like this is like.
190 00:24:53.270 ⇒ 00:24:58.450 Uttam Kumaran: I don’t know. I don’t want to be engineering like Jira boards like
191 00:24:58.620 ⇒ 00:25:05.030 Uttam Kumaran: There’s some stuff in where, if we have to collaborate or there’s like a ton of different components, makes a lot of sense. But
192 00:25:05.310 ⇒ 00:25:24.430 Uttam Kumaran: I think everybody, if they have agency, they can handle this stuff. And you know, we could just keep moving forward. And I’m trying to have some consistency like this sort of structure across every project we do at the company. So again, it has like we get more stuff, and everybody works on a couple of different things. Just want to have like one consistent process by which we do every project. And then
193 00:25:24.470 ⇒ 00:25:31.300 Uttam Kumaran: again, ideally, the client is in here looking at like how much we’re tracking and things like that. Cause I think it looks pretty good. So
194 00:25:32.620 ⇒ 00:25:34.759 Patrick Trainer: yeah, no, this sounds looks good.
195 00:25:35.040 ⇒ 00:25:40.319 Uttam Kumaran: cool. Okay, so let’s just talk in slack. And then, yeah, I think that’s it for today.
196 00:25:41.180 ⇒ 00:25:42.510 Uttam Kumaran: All right, all right.
197 00:25:42.640 ⇒ 00:25:45.120 Ryan Luke Daque: Awesome. Thanks. Everyone.
198 00:25:45.360 ⇒ 00:25:47.760 Patrick Trainer: Cool.