Meeting Title: sync on LMNT needs re: modeling and ingestion Date: 2026-05-04 Meeting participants: Greg Stoutenburg, Jasmin Multani, Awaish Kumar
WEBVTT
1 00:01:15.110 ⇒ 00:01:17.960 Jasmin Multani: Morning, Greg. I’m gonna be camera off.
2 00:01:17.960 ⇒ 00:01:18.630 Greg Stoutenburg: Yep.
3 00:01:18.670 ⇒ 00:01:20.880 Jasmin Multani: No problem.
4 00:01:21.530 ⇒ 00:01:27.450 Greg Stoutenburg: I put the, first version of this meeting at 9am my time, and now this one is at 9am.
5 00:01:27.450 ⇒ 00:01:32.660 Jasmin Multani: Yeah, I saw that, I was like, 6 AM on a Monday feels aggressive.
6 00:01:32.660 ⇒ 00:01:36.159 Greg Stoutenburg: Wait, it just… it’s time to let it rip. This is how you lean into the week.
7 00:01:36.160 ⇒ 00:01:37.370 Jasmin Multani: I know.
8 00:01:37.370 ⇒ 00:01:39.239 Greg Stoutenburg: data modeling, 6 AM Monday.
9 00:01:39.240 ⇒ 00:01:40.460 Jasmin Multani: Oh my god.
10 00:01:47.400 ⇒ 00:01:51.679 Jasmin Multani: I’m gonna also walk to get coffee, so…
11 00:01:51.680 ⇒ 00:01:53.569 Greg Stoutenburg: I mean, we’re just waiting for…
12 00:01:54.170 ⇒ 00:01:57.919 Greg Stoutenburg: Awashin, you guys can just fill me in on where we’re at, just trying to get caught up.
13 00:01:59.450 ⇒ 00:02:01.969 Greg Stoutenburg: I sort of kept things at arm’s length when.
14 00:02:02.520 ⇒ 00:02:03.140 Jasmin Multani: Yeah.
15 00:02:03.140 ⇒ 00:02:13.570 Greg Stoutenburg: when you and Garrett came on, and then just was basically looking for, you know, basically a quality check, and how are we communicating with the client was top of mind, and the specifics of things like supply chain issues.
16 00:02:13.880 ⇒ 00:02:17.059 Greg Stoutenburg: I really, you know, have not been, staying up on.
17 00:02:17.230 ⇒ 00:02:19.330 Greg Stoutenburg: Until we had our sink.
18 00:02:19.540 ⇒ 00:02:20.320 Greg Stoutenburg: Friday.
19 00:02:33.220 ⇒ 00:02:35.300 Greg Stoutenburg: Well, they’re not there.
20 00:04:08.380 ⇒ 00:04:10.360 Jasmin Multani: I’m gonna ping a wage real quick.
21 00:04:10.710 ⇒ 00:04:12.069 Greg Stoutenburg: Yeah, sounds good.
22 00:05:01.260 ⇒ 00:05:02.040 Awaish Kumar: Hello.
23 00:05:02.160 ⇒ 00:05:03.500 Greg Stoutenburg: Hey, Wish…
24 00:05:03.990 ⇒ 00:05:04.789 Awaish Kumar: Right, right.
25 00:05:05.190 ⇒ 00:05:06.729 Greg Stoutenburg: Hey, how you doing today?
26 00:05:07.860 ⇒ 00:05:09.250 Awaish Kumar: Sounds good. How about you?
27 00:05:11.080 ⇒ 00:05:12.000 Greg Stoutenburg: Pretty good.
28 00:05:15.930 ⇒ 00:05:20.820 Greg Stoutenburg: It’s one of those days where even though it’s, even though it’s noon my time, I still feel like I’m struggling to feel fully awake.
29 00:05:22.690 ⇒ 00:05:25.439 Greg Stoutenburg: Maybe I should stand up. That’s what I should do. I’ll stand up.
30 00:05:26.940 ⇒ 00:05:29.000 Awaish Kumar: Yeah, you have a desk that…
31 00:05:29.120 ⇒ 00:05:31.470 Greg Stoutenburg: Oh, man. Yeah, I… when I,
32 00:05:32.490 ⇒ 00:05:43.410 Greg Stoutenburg: when I got a job at Stack Overflow, they had a very generous new hire stipend to set up your home office. It was, like, $2,000, and so I bought two things, mainly. I bought this
33 00:05:43.410 ⇒ 00:05:55.009 Greg Stoutenburg: this standing desk, I just push a button to make it go up or down, which is sweet, and then I bought a pretty nice chair. So, and then everything else, I was like, I don’t care about any other office tech, I just want to be able to stand up.
34 00:05:56.240 ⇒ 00:05:57.070 Greg Stoutenburg: So…
35 00:05:58.000 ⇒ 00:06:04.680 Greg Stoutenburg: I wrote most of my dissertation standing up, I just… I don’t know. I can do about half an hour sitting, half an hour standing, and then need to switch.
36 00:06:08.630 ⇒ 00:06:09.940 Greg Stoutenburg: And it wouldn’t go back.
37 00:06:12.540 ⇒ 00:06:13.270 Jasmin Multani: Nice.
38 00:06:13.450 ⇒ 00:06:18.980 Jasmin Multani: So… This meeting that we’re gathered for.
39 00:06:19.110 ⇒ 00:06:27.909 Jasmin Multani: I’m trying to, like… sorry, I’m also sick this morning, it’s, like, slow. So…
40 00:06:28.120 ⇒ 00:06:39.019 Jasmin Multani: Greg is now the CSO for Element, I wish, and he and I were chatting last Friday, and we realized, like, oh, we should probably be more in sync.
41 00:06:39.400 ⇒ 00:06:44.899 Jasmin Multani: the three of us as the projects unfold. Does that make sense?
42 00:06:45.750 ⇒ 00:06:47.049 Awaish Kumar: Yeah, yeah, sure.
43 00:06:47.900 ⇒ 00:06:49.940 Jasmin Multani: Okay, so,
44 00:06:50.360 ⇒ 00:07:00.299 Jasmin Multani: what are… maybe we can, like, quickly touch base on, like, Awash, what would data modeling need from us for Element, like, as of this week?
45 00:07:00.460 ⇒ 00:07:04.210 Jasmin Multani: To move forward, and then… what…
46 00:07:04.550 ⇒ 00:07:12.610 Jasmin Multani: I can also tell you, like, what data strategy is gonna pass on to… is, like, planning on passing on to data modeling this week.
47 00:07:14.880 ⇒ 00:07:18.489 Awaish Kumar: Okay, so you’re saying what are…
48 00:07:19.550 ⇒ 00:07:22.820 Awaish Kumar: We are trying to achieve this week, in terms of data modeling.
49 00:07:22.940 ⇒ 00:07:29.729 Awaish Kumar: Then, I have… yeah, starting with ingestion, I have, like, we are… we have…
50 00:07:30.250 ⇒ 00:07:35.829 Awaish Kumar: I have created a SOP document that I sent out to tech team.
51 00:07:37.630 ⇒ 00:07:42.919 Awaish Kumar: for Amazon, so if it is, Approved, or…
52 00:07:44.090 ⇒ 00:07:50.520 Awaish Kumar: like, we will be starting with ingestion of Amazon data, backfilling the last two years.
53 00:07:50.760 ⇒ 00:07:56.160 Awaish Kumar: From using Amazon Export, so that will be a little bit of manual exercise.
54 00:07:56.400 ⇒ 00:08:00.500 Awaish Kumar: Along with, yeah, loading to…
55 00:08:01.260 ⇒ 00:08:05.450 Awaish Kumar: snowflake. So, that’s one thing that I…
56 00:08:06.430 ⇒ 00:08:10.370 Awaish Kumar: I will be doing… second thing is, I’m also blogged.
57 00:08:10.710 ⇒ 00:08:16.419 Awaish Kumar: On what, I already shared with you, Jasmine, the QA.
58 00:08:16.420 ⇒ 00:08:17.690 Jasmin Multani: Yeah, yeah.
59 00:08:17.750 ⇒ 00:08:23.610 Awaish Kumar: The only… the issue… what the issue is, the issue is that we are having…
60 00:08:24.060 ⇒ 00:08:25.999 Awaish Kumar: We have this,
61 00:08:26.730 ⇒ 00:08:34.870 Awaish Kumar: some… a few tables from Polytomic, called order and order item, that has some data, but it does not have any financial data.
62 00:08:34.870 ⇒ 00:08:35.250 Jasmin Multani: Oh, God.
63 00:08:35.600 ⇒ 00:08:38.789 Awaish Kumar: The totals, there is nothing. So I’m trying to…
64 00:08:39.280 ⇒ 00:08:41.850 Awaish Kumar: I’m trying to fill that in using
65 00:08:42.039 ⇒ 00:08:46.879 Awaish Kumar: a table called Financial Events, which gives us a little bit more information.
66 00:08:47.080 ⇒ 00:08:55.200 Awaish Kumar: Regarding all the finance-related data, it includes, like, order sale amount, then,
67 00:08:55.430 ⇒ 00:09:11.599 Awaish Kumar: discounts, refunds, adjustments, and also includes taxes, shipping costs, feces. So there’s a lot of these things. And I don’t know what makes, upper order total feel.
68 00:09:11.730 ⇒ 00:09:13.510 Awaish Kumar: Okay. For… for an order.
69 00:09:13.810 ⇒ 00:09:23.109 Awaish Kumar: So, yeah, so the thing is that I need someone to QA it against the platform itself.
70 00:09:23.970 ⇒ 00:09:27.299 Awaish Kumar: Into the platform and see, like, the… what is the…
71 00:09:27.580 ⇒ 00:09:32.140 Awaish Kumar: Subtotal, total, whatever, and then, like, kind of a…
72 00:09:33.500 ⇒ 00:09:41.610 Awaish Kumar: doing a QA and figuring out, okay, what works as a data tool, because if I can bring in something, but it might not be correct?
73 00:09:42.130 ⇒ 00:09:46.110 Jasmin Multani: Okay, yeah, I can… yeah, that can be prioritized before Wednesday.
74 00:09:46.860 ⇒ 00:10:02.139 Awaish Kumar: So, that QA… and I think I shared a document, something with you, right? So it has a little bit more information on what exact tables you have to look at to figure… to get the data for individual owners.
75 00:10:02.310 ⇒ 00:10:05.669 Awaish Kumar: And from there, you can basically, just…
76 00:10:06.530 ⇒ 00:10:09.719 Awaish Kumar: Compare it with the platform, and just, like, write
77 00:10:10.050 ⇒ 00:10:16.470 Awaish Kumar: write the, like, the exact QA path, or the definition of, like, what makes up order total, or something.
78 00:10:17.780 ⇒ 00:10:35.150 Awaish Kumar: If that is done, we can model, number one. Second, I’m also backfilling this data, so we will have more data in now. That’s part number two, and then the target is to, finalize, e-commerce,
79 00:10:36.050 ⇒ 00:10:43.620 Awaish Kumar: I would like to, at least building these order-order item tables for Amazon and Shopify, a unified version of these both.
80 00:10:44.190 ⇒ 00:10:45.740 Jasmin Multani: Okay.
81 00:10:46.500 ⇒ 00:10:51.360 Awaish Kumar: So… That is a priority. Second thing is,
82 00:10:51.640 ⇒ 00:10:58.010 Awaish Kumar: I’m… like, those are just communications, so right now, there is a…
83 00:10:58.770 ⇒ 00:11:04.969 Awaish Kumar: Walmart, there is some communication going on for the Walmart, and also for Spins API.
84 00:11:07.170 ⇒ 00:11:16.959 Awaish Kumar: Yeah, Utap also added me some of the emails, so I’m not sure. Like, it’s… right now in the communication stage, so I’m not sure how it will unfold, during the week.
85 00:11:17.440 ⇒ 00:11:17.990 Jasmin Multani: Okay.
86 00:11:19.020 ⇒ 00:11:27.550 Awaish Kumar: Third thing is about, modeling of the… Shipping data?
87 00:11:30.050 ⇒ 00:11:31.110 Awaish Kumar: Right?
88 00:11:32.500 ⇒ 00:11:37.230 Awaish Kumar: And that is, like, I think you at Dashmini are jamming on it, so…
89 00:11:37.980 ⇒ 00:11:39.930 Awaish Kumar: Yeah, let me know if…
90 00:11:39.930 ⇒ 00:11:40.330 Jasmin Multani: Pearl.
91 00:11:40.690 ⇒ 00:11:47.040 Awaish Kumar: if there is anything for me, right? Like, I will… Yeah, I will, like,
92 00:11:47.660 ⇒ 00:11:53.880 Awaish Kumar: make sure that I should need, like, given your requirements, he should be able to build all the mods and everything.
93 00:11:54.220 ⇒ 00:11:56.400 Awaish Kumar: Let me know if there’s anything.
94 00:11:57.360 ⇒ 00:12:01.470 Jasmin Multani: Yeah, ugh, I wanted to, like, quickly go back to…
95 00:12:02.910 ⇒ 00:12:07.519 Jasmin Multani: the Amazon portion? The first thing you mentioned?
96 00:12:07.910 ⇒ 00:12:12.309 Jasmin Multani: So once we get that data flowing, what type of…
97 00:12:12.410 ⇒ 00:12:17.180 Jasmin Multani: data fields, is that gonna update? Is that gonna impact the wholesale?
98 00:12:18.060 ⇒ 00:12:19.040 Jasmin Multani: Dashboards?
99 00:12:19.040 ⇒ 00:12:23.769 Awaish Kumar: It’s a new e-com modeling that we are doing, e-commerce.
100 00:12:24.180 ⇒ 00:12:27.269 Awaish Kumar: It does not affect retail or wholesale.
101 00:12:27.680 ⇒ 00:12:29.410 Jasmin Multani: Okay, okay, okay, alright.
102 00:12:29.630 ⇒ 00:12:33.870 Jasmin Multani: Okay, and then I’m also trying to understand, like.
103 00:12:34.060 ⇒ 00:12:44.050 Jasmin Multani: There’s a line in each of the wholesale and retail reporting called omnichannel growth sales.
104 00:12:44.050 ⇒ 00:12:59.190 Awaish Kumar: that is… that comes into play when we are done with individual level of modeling. So what element says a channel is, their business channel, right? So they’re, like, they have wholesale.
105 00:12:59.260 ⇒ 00:13:08.610 Awaish Kumar: like, there are… that’s, like, kind of a channel through which they generate revenue. Second is, retail, selling through retailers, and third is…
106 00:13:10.070 ⇒ 00:13:14.620 Awaish Kumar: e-commerce, selling online, using Shopify, Walmart, and Amazon.
107 00:13:14.750 ⇒ 00:13:18.289 Awaish Kumar: So these are 3 channels through which they are…
108 00:13:18.520 ⇒ 00:13:25.530 Awaish Kumar: like, generating revenue. So once… we are done with retail, we are done with wholesale. Now we are working on…
109 00:13:25.750 ⇒ 00:13:28.819 Awaish Kumar: e-commerce. Once e-commerce is done.
110 00:13:29.020 ⇒ 00:13:36.329 Awaish Kumar: We will be creating a unified view across all these Channels. McDonald’s awesome.
111 00:13:36.470 ⇒ 00:13:41.999 Awaish Kumar: So, like, you open a dashboard, you see the full total revenue for Element.
112 00:13:42.310 ⇒ 00:13:54.770 Awaish Kumar: not broken down, like, at the top level by any channel. We can then, like, maybe you can drill whatever ways you are the best at showing in the dashboards, but, like, whatever the…
113 00:13:54.790 ⇒ 00:14:06.310 Awaish Kumar: The idea is that, like, you can see the total amount, the revenue generated in this month across all channels. Then you can dig into, okay, what is my revenue for e-com, wholesale, retail, and then…
114 00:14:06.310 ⇒ 00:14:07.010 Jasmin Multani: cover.
115 00:14:07.320 ⇒ 00:14:08.060 Awaish Kumar: Okay.
116 00:14:08.490 ⇒ 00:14:09.100 Jasmin Multani: Yeah.
117 00:14:10.030 ⇒ 00:14:11.480 Jasmin Multani: Okay, sounds good.
118 00:14:11.600 ⇒ 00:14:20.269 Jasmin Multani: Alright, that makes sense to me. On my end, we’re prioritizing closing out the wholesale dashboards.
119 00:14:20.380 ⇒ 00:14:27.020 Jasmin Multani: And I’m working on, creating the roadmap for supply chain.
120 00:14:27.290 ⇒ 00:14:38.040 Jasmin Multani: and trying to understand, like, okay, what… because supply chain is very, very hairy, and there are a lot of reports that the internal team uses. So, I’m just going back…
121 00:14:39.150 ⇒ 00:14:47.249 Jasmin Multani: with Robert and saying, hey, these are the core, things we need to accomplish, so that we can land our…
122 00:14:47.360 ⇒ 00:14:51.940 Jasmin Multani: Our supply chain milestone in July.
123 00:14:52.870 ⇒ 00:14:53.550 Awaish Kumar: Okay.
124 00:14:53.550 ⇒ 00:14:56.849 Jasmin Multani: Wants to jam on that, like, the next hour, in the next 45 minutes.
125 00:14:56.850 ⇒ 00:14:58.370 Awaish Kumar: The hardest thing I’ve…
126 00:15:00.760 ⇒ 00:15:01.570 Greg Stoutenburg: Okay.
127 00:15:02.300 ⇒ 00:15:03.270 Greg Stoutenburg: Another supplier.
128 00:15:03.780 ⇒ 00:15:12.000 Greg Stoutenburg: We’re gonna have to… oops, sorry, I’m gonna have to hop for another call here. So, I mean, it… I mean, it sounds like we’re in good shape as far as the…
129 00:15:12.260 ⇒ 00:15:22.350 Greg Stoutenburg: As far as the topic areas that are being developed, is there anything, like, blocked, or anything that needs to be anticipated here to make sure that we stay on time and on target?
130 00:15:23.020 ⇒ 00:15:24.240 Greg Stoutenburg: It doesn’t sound like it.
131 00:15:24.790 ⇒ 00:15:28.939 Awaish Kumar: Yeah, for me, blocker is the QA part. Yeah.
132 00:15:30.150 ⇒ 00:15:34.769 Greg Stoutenburg: Okay. Can you make sure to raise that and just tag me in it?
133 00:15:35.980 ⇒ 00:15:41.400 Awaish Kumar: It’s kind of internal, so I don’t know. Like, we don’t need to tell it to customer, right?
134 00:15:41.400 ⇒ 00:15:48.429 Greg Stoutenburg: No, no, no, I agree. No, but just, like, in our internal element channel, can you just surface that ticket, so we make sure that it gets prioritized?
135 00:15:49.310 ⇒ 00:15:50.000 Awaish Kumar: Sure.
136 00:15:50.150 ⇒ 00:15:54.360 Awaish Kumar: And then, second thing is,
137 00:15:54.840 ⇒ 00:15:59.880 Awaish Kumar: Yeah, all the ingestion things, right? Walmart is a blocker for…
138 00:16:00.440 ⇒ 00:16:06.269 Awaish Kumar: Like, it’s already mentioned in our slides everywhere, that it’s a blocker for e-com modeling.
139 00:16:06.520 ⇒ 00:16:17.440 Awaish Kumar: Not in a sense that we can’t do the modeling, but it’s a… we won’t have the Walmart data in yet, so it’s, like, full Ecom will include the Walmart data as well.
140 00:16:19.440 ⇒ 00:16:23.620 Awaish Kumar: I don’t know how to… if it issues a blocker, or maybe I don’t know how to…
141 00:16:24.570 ⇒ 00:16:25.630 Awaish Kumar: Like, phrase it.
142 00:16:27.480 ⇒ 00:16:41.209 Jasmin Multani: Can you, can you write that summary, that whole summary and put it in the Omni element in our internal chat, and then, or you can Slack it over to me? I think once I read through it, I’ll be able to, like, able to summarize, like…
143 00:16:41.960 ⇒ 00:16:45.359 Jasmin Multani: Workshop it to say if this is a blocker or something.
144 00:16:45.360 ⇒ 00:16:53.819 Awaish Kumar: just updating you on that Walmart ingestion is blocked, but we already have surfaced it to the client, and it’s in our text, so we don’t need to…
145 00:16:53.820 ⇒ 00:16:57.880 Jasmin Multani: Yeah, yeah. Okay, so it’s nothing new. Okay.
146 00:16:59.360 ⇒ 00:17:04.799 Jasmin Multani: Yeah, I just wanted to reassure Greg that, like, everything’s… everything’s in good shape.
147 00:17:04.800 ⇒ 00:17:14.399 Greg Stoutenburg: Yeah, yeah, yeah. And I, you know, I trust the team. I also just, I’m just coming back online, and this is, you know, Elements, project is just…
148 00:17:14.900 ⇒ 00:17:16.230 Greg Stoutenburg: big, so…
149 00:17:16.230 ⇒ 00:17:16.569 Jasmin Multani: Sure.
150 00:17:16.579 ⇒ 00:17:25.629 Greg Stoutenburg: Trying to get it all done and understand everything again in the course of a couple hours, so… Cool. Alright, I better hop. Thank you both for this, I appreciate it.
151 00:17:25.630 ⇒ 00:17:27.129 Jasmin Multani: Alright, take care, thank you!
152 00:17:27.130 ⇒ 00:17:27.820 Greg Stoutenburg: Talk later. Bye.