Meeting Title: Brainforge x Phil Project Planning Date: 2026-03-11 Meeting participants: Uttam Kumaran, Shivani Amar
WEBVTT
1 00:00:08.420 ⇒ 00:00:09.430 Shivani Amar: Hello!
2 00:00:12.100 ⇒ 00:00:13.350 Uttam Kumaran: Nive! Okay.
3 00:00:13.890 ⇒ 00:00:14.550 Shivani Amar: Okay.
4 00:00:16.040 ⇒ 00:00:28.020 Uttam Kumaran: Alright, so… This is… what we put together, so… just basically…
5 00:00:28.470 ⇒ 00:00:32.500 Uttam Kumaran: To kind of just jump in, we had… we kind of broke down the three options into…
6 00:00:32.800 ⇒ 00:00:35.369 Uttam Kumaran: Like, a week-by-week view.
7 00:00:35.960 ⇒ 00:00:36.390 Shivani Amar: Hmm.
8 00:00:36.390 ⇒ 00:00:38.700 Uttam Kumaran: Kind of like what you described, which is, like.
9 00:00:38.970 ⇒ 00:00:42.500 Uttam Kumaran: we’ve been talking about, basically, a couple things. One.
10 00:00:42.640 ⇒ 00:00:52.929 Uttam Kumaran: 3 or 4 work streams, and 3 or 4 work streams ahead of schedule. And so those are, like, the key differences, and those are sort of highlighted here.
11 00:00:53.190 ⇒ 00:00:53.590 Shivani Amar: Yeah.
12 00:00:53.870 ⇒ 00:00:58.210 Uttam Kumaran: We’ve walked through this and basically shown And…
13 00:00:58.710 ⇒ 00:01:09.990 Uttam Kumaran: it’s as accurate as, like, sort of we see it, but of course, like, assume there will be some bullets that move, but generally, what are the… what’s the workstream that’s being affected? What are the inputs?
14 00:01:10.190 ⇒ 00:01:12.600 Uttam Kumaran: What is the output, and, like, what is the…
15 00:01:12.790 ⇒ 00:01:16.600 Uttam Kumaran: business outcome, as well as, like, who from the Brainforge team is involved.
16 00:01:16.950 ⇒ 00:01:27.390 Uttam Kumaran: We put some definitions here at the bottom on, like, kind of, like, some… some details as needed. And then each option, we’ve also indicated, sort of, like.
17 00:01:27.580 ⇒ 00:01:28.920 Uttam Kumaran: What is net new?
18 00:01:29.490 ⇒ 00:01:34.790 Uttam Kumaran: So you can see that, like, okay, this is everything related to supply chain.
19 00:01:34.790 ⇒ 00:01:37.329 Shivani Amar: It’s really hard for… I’m on my laptop, can you just send me the.
20 00:01:37.330 ⇒ 00:01:38.659 Uttam Kumaran: Oh, yeah, yeah, yeah.
21 00:01:38.660 ⇒ 00:01:39.140 Shivani Amar: I’m like.
22 00:01:39.140 ⇒ 00:01:44.259 Uttam Kumaran: Sorry. Woo! I’m just like, I don’t know what we’re looking at. I thought you were pumped!
23 00:01:44.260 ⇒ 00:01:48.279 Shivani Amar: No, I was like, I was like, oh, I can’t read it! It’s a lot of words.
24 00:01:48.410 ⇒ 00:01:50.440 Uttam Kumaran: One second. Alright, take a look.
25 00:01:50.650 ⇒ 00:01:56.910 Shivani Amar: Open it… I think it’s denying me access.
26 00:01:57.610 ⇒ 00:01:58.740 Uttam Kumaran: Oh, okay, hold on.
27 00:02:01.360 ⇒ 00:02:02.710 Shivani Amar: Who is this person?
28 00:02:03.570 ⇒ 00:02:06.719 Uttam Kumaran: Brile’s on our team. He’s, like, on our delivery team.
29 00:02:07.110 ⇒ 00:02:08.030 Shivani Amar: Okay, gotcha.
30 00:02:08.699 ⇒ 00:02:11.409 Uttam Kumaran: He’s gonna… he’ll join us, like, yeah.
31 00:02:13.700 ⇒ 00:02:15.830 Shivani Amar: Okay, let me try clicking in again.
32 00:02:22.060 ⇒ 00:02:22.860 Shivani Amar: Okay.
33 00:02:25.520 ⇒ 00:02:26.175 Shivani Amar: Mmm…
34 00:02:26.980 ⇒ 00:02:31.690 Shivani Amar: Okay, so I’m just gonna look at option B and not look at option A for a second. Okay.
35 00:02:31.990 ⇒ 00:02:37.830 Shivani Amar: So, just so… I have dates, I have work streams.
36 00:02:38.160 ⇒ 00:02:42.449 Shivani Amar: I have inputs, I have outputs.
37 00:02:43.240 ⇒ 00:02:45.550 Shivani Amar: But, like,
38 00:02:47.550 ⇒ 00:02:52.280 Shivani Amar: Let’s just look at this really slowly together, actually. Yeah. Can I share my screen, if you have.
39 00:02:52.280 ⇒ 00:02:54.019 Uttam Kumaran: Oh, yeah, yeah. Yeah, yeah, yeah.
40 00:02:55.470 ⇒ 00:02:57.970 Shivani Amar: So, like, Okay.
41 00:02:58.180 ⇒ 00:03:03.399 Shivani Amar: The outputs might not always be the same time as the inputs, right?
42 00:03:04.380 ⇒ 00:03:05.470 Uttam Kumaran: Correct, so…
43 00:03:05.470 ⇒ 00:03:13.139 Shivani Amar: So, so I’m almost, like, like, I’m thinking that the outputs from the week… like, I get that these are the outputs from this.
44 00:03:13.330 ⇒ 00:03:14.080 Uttam Kumaran: Yes.
45 00:03:14.370 ⇒ 00:03:18.629 Uttam Kumaran: Yeah, I see what you mean. I agree, it’s not.
46 00:03:18.630 ⇒ 00:03:28.000 Shivani Amar: Like, business outcome unlocked, I’m not expecting at the end of this week I’m gonna suddenly have D2C e-commerce ingestion incomplete. I don’t even know when Walmart.com is coming.
47 00:03:28.540 ⇒ 00:03:29.150 Uttam Kumaran: Yeah.
48 00:03:29.880 ⇒ 00:03:35.389 Shivani Amar: like, when is Walmart coming? So… so the Walmart 3P, what is that?
49 00:03:36.440 ⇒ 00:03:41.910 Uttam Kumaran: Walmart, it’s, like, anything that’s, like, third-party fulfillment, and…
50 00:03:41.910 ⇒ 00:03:43.979 Shivani Amar: What about Walmart.com data?
51 00:03:44.750 ⇒ 00:03:48.969 Uttam Kumaran: Yeah, so the connector, we’re expecting it this week.
52 00:03:49.230 ⇒ 00:03:50.860 Uttam Kumaran: And then we’ll turn it on.
53 00:03:50.860 ⇒ 00:03:54.539 Shivani Amar: So, so, you see, like, I’m like, I don’t even see that here.
54 00:03:55.600 ⇒ 00:03:57.529 Shivani Amar: I just see Walmart 3P.
55 00:03:58.000 ⇒ 00:03:58.580 Uttam Kumaran: Yeah.
56 00:03:59.080 ⇒ 00:04:05.790 Shivani Amar: and I see Walmart as retail, but the Walmart, like, e-commerce ingestion complete as D2C plus Amazon is incomplete.
57 00:04:05.970 ⇒ 00:04:14.480 Shivani Amar: Which is… this is very helpful for us to, like, go through this in detail, right? So, let’s actually just, like… I’m gonna make a copy, okay?
58 00:04:15.030 ⇒ 00:04:21.879 Shivani Amar: Let’s actually just, like, play with it, that way I’m not messing with your previous version, okay? Let’s just say…
59 00:04:22.700 ⇒ 00:04:29.789 Shivani Amar: like, the outputs that we think we can actually get. These are, like, inputs, and, like, Phil might be like, no, I want the outputs to be…
60 00:04:31.300 ⇒ 00:04:32.629 Uttam Kumaran: When they’re gonna come.
61 00:04:33.540 ⇒ 00:04:35.569 Uttam Kumaran: Versus, like, when we’re working on the thing.
62 00:04:35.570 ⇒ 00:04:37.820 Shivani Amar: Right, like, or like, I want…
63 00:04:37.990 ⇒ 00:04:48.659 Shivani Amar: I’m trying to get it to be when they’re actually gonna come, but he might be like, I want the outputs from the inputs, like, to be very clear, which is what you recently had, which is why I’m making a copy and not editing the original thing.
64 00:04:48.850 ⇒ 00:04:53.909 Shivani Amar: But for my brain, I’m like, okay, when are you gonna unlock certain outputs, right? So, we’re saying…
65 00:04:54.750 ⇒ 00:04:56.899 Shivani Amar: Shopify Mark QA.
66 00:04:59.230 ⇒ 00:05:00.910 Shivani Amar: Is that happening this week?
67 00:05:02.110 ⇒ 00:05:09.089 Uttam Kumaran: On our side, yes. So we have the first part of the Shopify Mart, and, like, we’re QAing it.
68 00:05:09.420 ⇒ 00:05:12.419 Uttam Kumaran: But again, it’s not like… this isn’t e-commerce…
69 00:05:12.590 ⇒ 00:05:16.829 Uttam Kumaran: This isn’t like an e-commerce dashboard, this is just… we’re doing an internal QA.
70 00:05:17.100 ⇒ 00:05:18.060 Uttam Kumaran: So this is what we worked on.
71 00:05:18.060 ⇒ 00:05:23.649 Shivani Amar: This is a little bit too detailed for me. Too detailed. Okay, so I’m gonna be… I’m just, like, gonna.
72 00:05:23.650 ⇒ 00:05:26.670 Uttam Kumaran: No, no, no, that’s fair, we… we can… yeah.
73 00:05:26.920 ⇒ 00:05:34.660 Shivani Amar: Okay, so, like, the output might be a Shopify Mart, okay? Like, Shopify Mart might be an output this week.
74 00:05:35.110 ⇒ 00:05:35.690 Uttam Kumaran: Okay.
75 00:05:35.690 ⇒ 00:05:39.130 Shivani Amar: Okay? But, like… orders…
76 00:05:39.320 ⇒ 00:05:47.259 Shivani Amar: like, I know I’m going even detailed, but, like, orders, orders, customers, and, like, nobody did anything wrong. I think we’re just trying to figure out a.
77 00:05:47.260 ⇒ 00:05:52.270 Uttam Kumaran: No, no, no, no, that’s fine, yeah, yeah. I’d rather us be too… too far, and then we can.
78 00:05:52.270 ⇒ 00:05:55.460 Shivani Amar: Yeah, so orders, customers, transactions, or something?
79 00:05:56.300 ⇒ 00:05:57.190 Uttam Kumaran: Okay.
80 00:05:57.490 ⇒ 00:05:59.390 Shivani Amar: Is that… is that what you’re working on?
81 00:05:59.390 ⇒ 00:06:01.330 Uttam Kumaran: Yes, yes, yes, yes.
82 00:06:01.510 ⇒ 00:06:05.790 Uttam Kumaran: Sorry, yes. No, I’m saying okay to, like, the format, but yeah.
83 00:06:06.020 ⇒ 00:06:10.209 Shivani Amar: Okay, then inputs is, like…
84 00:06:12.770 ⇒ 00:06:22.910 Uttam Kumaran: So, like, this is, like, this is… I felt like this was very narrow, but it is something that we’re doing, which is, like, what are we trying to deliver, and then what is the outcome?
85 00:06:24.090 ⇒ 00:06:28.310 Uttam Kumaran: So, like, previously, we were, like.
86 00:06:30.320 ⇒ 00:06:34.739 Shivani Amar: I see, I see, okay, so you’re saying, like, business outcome unlock, okay?
87 00:06:35.160 ⇒ 00:06:37.569 Shivani Amar: Okay. Like, you’re saying…
88 00:06:37.910 ⇒ 00:06:38.850 Uttam Kumaran: Yeah.
89 00:06:39.010 ⇒ 00:06:48.420 Uttam Kumaran: The business outcome is actually maybe more, at Phil’s view, relevant, and maybe the outputs is confusing.
90 00:06:50.280 ⇒ 00:06:52.890 Uttam Kumaran: Like, I don’t know if you feel the same way.
91 00:06:52.890 ⇒ 00:06:53.780 Shivani Amar: Okay.
92 00:06:54.550 ⇒ 00:06:56.869 Uttam Kumaran: Because the business outcomes are, like.
93 00:06:57.530 ⇒ 00:07:00.660 Uttam Kumaran: there’s a VP level, like, on… there’s, like.
94 00:07:00.810 ⇒ 00:07:04.670 Uttam Kumaran: Omni’s being adopted at the VP level, and, like, we’re starting to do that.
95 00:07:04.870 ⇒ 00:07:08.469 Uttam Kumaran: The marketing ingestion pipelines, like, come online.
96 00:07:09.030 ⇒ 00:07:09.730 Shivani Amar: Hmm.
97 00:07:09.730 ⇒ 00:07:14.330 Uttam Kumaran: Versus the… The data mart is out, or, like, this.
98 00:07:14.330 ⇒ 00:07:22.800 Shivani Amar: Yeah, like, this is all, like, stuff that you’re doing, right? Yes. Like, in detail, which is fine. That’s, like, a double-click into this, but, like.
99 00:07:22.950 ⇒ 00:07:31.189 Shivani Amar: outputs for the unlocked in this week, maybe… maybe you get Shopify Marts this week, okay? And maybe you get…
100 00:07:31.350 ⇒ 00:07:43.889 Shivani Amar: like, if we’re… I’m gonna think of outputs and business outcomes as the same for a second, okay? Okay. Finalized wholesale… finalized wholesale,
101 00:07:46.360 ⇒ 00:07:51.550 Shivani Amar: sales… Refunds numbers.
102 00:07:51.880 ⇒ 00:07:59.080 Shivani Amar: to save finance time at month end, okay? Like, maybe that’s what will be done this week. TBD, I don’t know if that’s exactly right.
103 00:07:59.230 ⇒ 00:07:59.920 Uttam Kumaran: Yeah.
104 00:08:00.220 ⇒ 00:08:11.460 Shivani Amar: Then, like, then, okay, so Amazon settlements modeling, like, already I’m like, like, it’s like, what has been settled, you’re starting to model, is what you’re saying, okay?
105 00:08:11.460 ⇒ 00:08:12.180 Uttam Kumaran: Yeah.
106 00:08:12.180 ⇒ 00:08:18.569 Shivani Amar: Okay, but, like, Amazon modeling kickoff, right? Like, not a hundred…
107 00:08:18.770 ⇒ 00:08:21.360 Shivani Amar: Not off 100% of the data.
108 00:08:21.490 ⇒ 00:08:22.770 Uttam Kumaran: Okay. Okay.
109 00:08:22.980 ⇒ 00:08:26.840 Shivani Amar: Retail Comparison Model QA. What is Comparison Model?
110 00:08:27.430 ⇒ 00:08:31.990 Uttam Kumaran: This is, like, comparing, all of the retail channels.
111 00:08:32.940 ⇒ 00:08:40.429 Uttam Kumaran: So, like, we have Target, Yeah, like, basically any retail models that we have, we’re gonna start to…
112 00:08:40.659 ⇒ 00:08:47.489 Uttam Kumaran: show them side by side and basically QA the entire retail mart. So I think you’re right in that I think one thing we could do is just, like.
113 00:08:47.600 ⇒ 00:08:56.750 Uttam Kumaran: consolidate to, like, the core keywords, like mart, dashboard, like, model…
114 00:08:57.560 ⇒ 00:09:01.380 Uttam Kumaran: You know, and then just start to… start to align with business domains.
115 00:09:02.020 ⇒ 00:09:07.490 Shivani Amar: Should we start… I’m trying to figure out the best way to do this with them, and you have a call soon?
116 00:09:08.780 ⇒ 00:09:13.019 Uttam Kumaran: That’s fine, I can keep going. I just… this is… it’s an internal one, I told him I’m gonna be late.
117 00:09:13.020 ⇒ 00:09:19.789 Shivani Amar: I was thinking that it would just be kind of like…
118 00:09:22.200 ⇒ 00:09:25.050 Shivani Amar: The inputs are when you’re tackling these.
119 00:09:25.620 ⇒ 00:09:26.010 Uttam Kumaran: Okay.
120 00:09:26.010 ⇒ 00:09:28.890 Shivani Amar: Or, like, metrics or dashboards that you’re unlocking?
121 00:09:29.280 ⇒ 00:09:30.280 Shivani Amar: So…
122 00:09:33.660 ⇒ 00:09:35.179 Shivani Amar: - so it’s like…
123 00:09:35.180 ⇒ 00:09:36.400 Uttam Kumaran: Like, I think, yeah, I think.
124 00:09:36.400 ⇒ 00:09:38.269 Shivani Amar: Output might be, like…
125 00:09:38.970 ⇒ 00:09:39.490 Uttam Kumaran: What do you think.
126 00:09:39.490 ⇒ 00:09:39.870 Shivani Amar: Seven.
127 00:09:39.870 ⇒ 00:09:43.060 Uttam Kumaran: What do you think about the outcomes column, the one on the far right?
128 00:09:43.470 ⇒ 00:09:45.820 Uttam Kumaran: Like, is it too business… is it too…
129 00:09:47.780 ⇒ 00:09:54.529 Shivani Amar: Like, ingestion complete just feels like you’re naming that an input is complete, so it’s, like, too many words on a page.
130 00:09:54.530 ⇒ 00:09:55.120 Uttam Kumaran: Okay.
131 00:09:55.730 ⇒ 00:10:00.569 Shivani Amar: Right? And, like, it’s not even complete, because we’re not even putting Walmart.com here.
132 00:10:00.830 ⇒ 00:10:08.490 Shivani Amar: So, it’s wrong. But then, wholesale partner view available, it’s like, kind of like, again, that’s word salad. I’m like, what does that actually mean?
133 00:10:08.620 ⇒ 00:10:11.009 Uttam Kumaran: One order taxonomy in place.
134 00:10:11.010 ⇒ 00:10:14.310 Shivani Amar: Again, that’s, like, a process thing that you’re doing.
135 00:10:14.550 ⇒ 00:10:21.479 Shivani Amar: Right? Omni Self Service started for both channels? Okay, that’s… that’s actually, like, makes sense to me.
136 00:10:22.160 ⇒ 00:10:24.140 Shivani Amar: But I don’t even think that’s happening this week.
137 00:10:24.500 ⇒ 00:10:25.020 Shivani Amar: Based on.
138 00:10:25.020 ⇒ 00:10:28.800 Uttam Kumaran: Yeah, so it’s… it’s an… it’s an outcome of the… of that…
139 00:10:28.800 ⇒ 00:10:31.089 Shivani Amar: Yeah, yeah, I forgot. Okay, so you’re doing…
140 00:10:31.430 ⇒ 00:10:36.110 Uttam Kumaran: Yeah, so it’s not necessarily, like, when… that’s the tough part, because you can’t show…
141 00:10:36.350 ⇒ 00:10:42.489 Uttam Kumaran: you can’t show start, end, delivery, like, not on a Gantt, basically, because it’s not on a Gantt, so…
142 00:10:42.490 ⇒ 00:10:47.709 Shivani Amar: So… So let’s just go, like, we’re going super high level, okay?
143 00:10:47.710 ⇒ 00:10:48.260 Uttam Kumaran: Yeah.
144 00:10:48.400 ⇒ 00:10:49.830 Shivani Amar: Amazon…
145 00:10:56.640 ⇒ 00:10:59.419 Shivani Amar: Fine. You want to call that out, that’s fine.
146 00:10:59.580 ⇒ 00:11:04.030 Shivani Amar: Is anything else new being ingested this week?
147 00:11:04.880 ⇒ 00:11:05.500 Shivani Amar: like, the.
148 00:11:05.500 ⇒ 00:11:06.010 Uttam Kumaran: Right.
149 00:11:06.010 ⇒ 00:11:06.850 Shivani Amar: Whatever.
150 00:11:07.260 ⇒ 00:11:09.490 Uttam Kumaran: Yeah, so Fa- so we did Facebook.
151 00:11:10.130 ⇒ 00:11:17.269 Uttam Kumaran: Actually, all of that finished, yeah, Monday, so Facebook, GA4, and one other.
152 00:11:17.570 ⇒ 00:11:20.929 Uttam Kumaran: And then we’re… we kicked off Amazon today.
153 00:11:21.110 ⇒ 00:11:21.970 Shivani Amar: Okay.
154 00:11:23.060 ⇒ 00:11:24.990 Uttam Kumaran: Facebook, Google Ads, GA4.
155 00:11:26.160 ⇒ 00:11:27.030 Shivani Amar: Okay.
156 00:11:41.320 ⇒ 00:11:43.150 Shivani Amar: Okay, so…
157 00:11:49.210 ⇒ 00:11:50.920 Shivani Amar: Let me let it go.
158 00:11:52.310 ⇒ 00:11:53.869 Shivani Amar: Okay, then…
159 00:11:54.600 ⇒ 00:12:00.470 Shivani Amar: You’re saying we’re starting to… starting to model something doesn’t get me an output, to be honest, right?
160 00:12:01.240 ⇒ 00:12:04.690 Shivani Amar: So… It’s kind of moot.
161 00:12:05.660 ⇒ 00:12:07.400 Shivani Amar: comparison, QA.
162 00:12:08.810 ⇒ 00:12:14.049 Shivani Amar: Inputs to me is, like, what you’re ingesting that’s net new.
163 00:12:14.050 ⇒ 00:12:16.589 Uttam Kumaran: I see. Okay. I see. Alright, then…
164 00:12:16.590 ⇒ 00:12:16.930 Shivani Amar: I think.
165 00:12:16.930 ⇒ 00:12:17.500 Uttam Kumaran: Okay.
166 00:12:17.500 ⇒ 00:12:24.350 Shivani Amar: Okay, so, like, I’m like, what are the new inputs that you have, and what are the outputs you can unlock?
167 00:12:24.980 ⇒ 00:12:26.849 Shivani Amar: Right? So…
168 00:12:27.370 ⇒ 00:12:33.350 Uttam Kumaran: Okay, so then we would say, like, new data available, new models available, omni available.
169 00:12:34.530 ⇒ 00:12:40.500 Shivani Amar: No, no, no, don’t overcomplicate it. We’re going super simple. We’re just gonna do it together. That’s just what we’re gonna do, okay?
170 00:12:40.500 ⇒ 00:12:41.450 Uttam Kumaran: Okay.
171 00:12:41.450 ⇒ 00:12:52.880 Shivani Amar: So, Amazon data ingestion Kickoff, Facebook and GA4, like, whatever, ingestion, like, ingested, wholesale, da-da-da.
172 00:12:54.010 ⇒ 00:12:55.669 Shivani Amar: again, whatever.
173 00:12:56.880 ⇒ 00:13:01.599 Shivani Amar: And then other, like, mini outputs is, like, you’re getting the Shopify tables this week.
174 00:13:03.000 ⇒ 00:13:04.570 Shivani Amar: Tables V1.
175 00:13:04.730 ⇒ 00:13:10.270 Shivani Amar: This is still a little bit too detailed, but it’s just, like, finalized wholesale sales, refunds.
176 00:13:10.400 ⇒ 00:13:18.040 Shivani Amar: To save Finance Standard at the end of the month. I’m kind of blending business outcomes, because I don’t want 3 columns. So, then you say…
177 00:13:18.860 ⇒ 00:13:27.730 Shivani Amar: again, like, validation and stuff is, like, it’s all part of your process. I get it, like, this is, like, why these things take a long time.
178 00:13:28.010 ⇒ 00:13:33.149 Shivani Amar: Right? But it’s like, at what point do you think you’ll have, like, e-commerce, like, output?
179 00:13:33.380 ⇒ 00:13:37.329 Shivani Amar: On forgetting marketing, Forget marketing.
180 00:13:37.460 ⇒ 00:13:38.050 Shivani Amar: You have…
181 00:13:38.050 ⇒ 00:13:38.560 Uttam Kumaran: Yeah.
182 00:13:38.560 ⇒ 00:13:46.040 Shivani Amar: at what point do you think you can say, I have linked sales for Walmart, Amazon, and Shopify.
183 00:13:47.300 ⇒ 00:13:48.749 Uttam Kumaran: Yeah, we put it.
184 00:13:52.740 ⇒ 00:13:59.409 Shivani Amar: Initially, we were thinking this would happen, like, July, like, I don’t even remember, right? So it’s like, in your Gantt, kind of, like, if you…
185 00:14:00.010 ⇒ 00:14:01.399 Shivani Amar: go there.
186 00:14:01.840 ⇒ 00:14:07.149 Shivani Amar: Yeah, this is all… too detailed. It’s okay, we’re gonna just do it together.
187 00:14:07.640 ⇒ 00:14:13.539 Shivani Amar: Okay, like, when do you… let’s just go output by output, like, when do you think you can get that?
188 00:14:15.170 ⇒ 00:14:16.570 Uttam Kumaran: Yeah, let me check…
189 00:14:23.700 ⇒ 00:14:29.469 Uttam Kumaran: Yeah, I mean, again, we’re gonna start with Shopify, and we’re hoping, for the most part, it’s, like.
190 00:14:30.170 ⇒ 00:14:33.820 Uttam Kumaran: Four to six weeks, end-to-end, for just one source.
191 00:14:33.930 ⇒ 00:14:38.380 Uttam Kumaran: But again, it’s not like we just work on that, and then we work on Amazon, it’s like…
192 00:14:38.500 ⇒ 00:14:41.739 Uttam Kumaran: Modeling starts for that. Amazon lands.
193 00:14:41.870 ⇒ 00:14:43.690 Uttam Kumaran: Modeling starts for Amazon.
194 00:14:43.900 ⇒ 00:14:48.229 Uttam Kumaran: Walmart lands, and starts for… for Walmart.
195 00:14:48.350 ⇒ 00:14:51.880 Uttam Kumaran: And then we have to combine, and then we have, like, all of e-comm.
196 00:14:52.530 ⇒ 00:15:01.249 Shivani Amar: So let’s say you were saying by, like, mid-July, you have, like, e-commerce. I’m just planting a flag right now, and we can rework this. E-commerce,
197 00:15:01.740 ⇒ 00:15:13.660 Shivani Amar: e-commerce, kind of, I don’t know the right terminology, but it’s, like, e-commerce.
198 00:15:14.710 ⇒ 00:15:17.720 Shivani Amar: Apples to apples, like, tables, basically.
199 00:15:17.850 ⇒ 00:15:18.890 Shivani Amar: Right? Like…
200 00:15:18.890 ⇒ 00:15:20.320 Uttam Kumaran: Yeah, it’s a, like…
201 00:15:22.620 ⇒ 00:15:30.200 Uttam Kumaran: Yeah, you can just say, like, robust e-commerce data tables, or the e-commerce data mart, or combined e-commerce.
202 00:15:32.330 ⇒ 00:15:33.570 Uttam Kumaran: data marts…
203 00:15:40.920 ⇒ 00:15:53.630 Shivani Amar: Okay? So it’s like, we’re hoping that that can be whatever. But then, at what point, like, if we keep going down this thread, at what point do you think you could model some of the marketing efficiency ratios as they tie to e-commerce?
204 00:15:54.710 ⇒ 00:15:59.109 Uttam Kumaran: Yeah, so that’s… so that’s gonna base… I mean, we will have some of that earlier.
205 00:15:59.260 ⇒ 00:15:59.840 Shivani Amar: Yeah.
206 00:15:59.840 ⇒ 00:16:06.229 Uttam Kumaran: It’s just gonna depend on the… on the channel. So, what we kind of had is…
207 00:16:06.420 ⇒ 00:16:09.499 Uttam Kumaran: There’s… there’s some outcomes for, like.
208 00:16:09.750 ⇒ 00:16:15.600 Uttam Kumaran: hey, we can actually start to… like, as soon as… as soon as Shopify has landed.
209 00:16:15.930 ⇒ 00:16:24.199 Uttam Kumaran: and we have some marketing spend, we can start to do that. So you can see in, like, April, we’re like, cool, we’re gonna start to get this marketing data.
210 00:16:24.760 ⇒ 00:16:31.250 Uttam Kumaran: By that… by… by that point, we are gonna have marketing data, and…
211 00:16:31.360 ⇒ 00:16:35.220 Uttam Kumaran: we should have both Shopify and Amazon, already.
212 00:16:35.380 ⇒ 00:16:39.050 Uttam Kumaran: But we’re not gonna have the combined view until all of…
213 00:16:39.650 ⇒ 00:16:42.920 Uttam Kumaran: All of that, all three core e-comm.
214 00:16:43.350 ⇒ 00:16:52.619 Uttam Kumaran: is all three are modeled, QA’d, and then all combined. So that’s why the delay is until July, but channel-specific wins, we can get before that.
215 00:16:53.360 ⇒ 00:16:54.200 Shivani Amar: Okay.
216 00:16:54.460 ⇒ 00:16:55.600 Shivani Amar: So…
217 00:16:56.630 ⇒ 00:16:59.330 Uttam Kumaran: I hear you, and I’m like…
218 00:17:03.110 ⇒ 00:17:04.790 Shivani Amar: So you have a mare model.
219 00:17:05.119 ⇒ 00:17:11.829 Shivani Amar: Right? B1. So, let’s say… Initial error model.
220 00:17:12.280 ⇒ 00:17:13.220 Shivani Amar: Okay?
221 00:17:13.390 ⇒ 00:17:15.839 Shivani Amar: At what point am I ingesting Walmart.com?
222 00:17:17.130 ⇒ 00:17:19.689 Uttam Kumaran: in the… in… This week or next week?
223 00:17:19.890 ⇒ 00:17:20.670 Shivani Amar: Okay.
224 00:17:24.940 ⇒ 00:17:26.089 Uttam Kumaran: Okay.
225 00:17:26.300 ⇒ 00:17:31.180 Shivani Amar: e-commerce… Emerson point-of-sale validated doesn’t mean much to me.
226 00:17:31.620 ⇒ 00:17:32.109 Shivani Amar: I’m delivering.
227 00:17:32.110 ⇒ 00:17:32.690 Uttam Kumaran: Yeah, we…
228 00:17:32.690 ⇒ 00:17:33.759 Shivani Amar: For this version? Okay.
229 00:17:35.880 ⇒ 00:17:44.870 Shivani Amar: And Spin said they’re not gonna, like, be able to give this even access until, like, April, right? In that email. It’s like… did you see that email?
230 00:17:44.870 ⇒ 00:17:47.319 Uttam Kumaran: Oh, really? No, I didn’t see the…
231 00:17:51.340 ⇒ 00:17:51.870 Shivani Amar: Awareness.
232 00:17:51.870 ⇒ 00:17:53.889 Uttam Kumaran: Oh, I saw your reply, but…
233 00:17:54.570 ⇒ 00:17:55.589 Shivani Amar: She was like.
234 00:17:56.410 ⇒ 00:17:57.830 Uttam Kumaran: Unbelievable. Why?
235 00:17:57.830 ⇒ 00:18:00.919 Shivani Amar: There’s a start date of any time between 4-1 and 6-1?
236 00:18:02.250 ⇒ 00:18:03.220 Uttam Kumaran: So…
237 00:18:03.220 ⇒ 00:18:07.399 Shivani Amar: So you don’t… you can’t do spins, anything with spins until a little bit later?
238 00:18:07.400 ⇒ 00:18:09.139 Uttam Kumaran: Yeah. Right? So let’s say, like.
239 00:18:09.240 ⇒ 00:18:11.220 Shivani Amar: Spins becomes here.
240 00:18:12.230 ⇒ 00:18:16.410 Uttam Kumaran: And then it will really… then it’s, like, spins, ingestion starts there.
241 00:18:18.310 ⇒ 00:18:22.870 Uttam Kumaran: yeah.
242 00:19:00.200 ⇒ 00:19:09.800 Shivani Amar: Like, revenue definitions confirmed is so detailed, not fill level at all, versus saying, like, at some point you’ll be able to report out on revenue.
243 00:19:10.250 ⇒ 00:19:20.859 Shivani Amar: And then you know that your process is that you need to define the, like, define and do the documentation and everything, but it’s like, you’re basically trying to put a line in
244 00:19:21.040 ⇒ 00:19:26.490 Shivani Amar: outputs to say, like, by April 21st, I should have
245 00:19:26.800 ⇒ 00:19:32.460 Shivani Amar: I should be able to report out on revenues across all the sources that I have so far.
246 00:19:33.140 ⇒ 00:19:33.700 Uttam Kumaran: Yeah.
247 00:19:34.600 ⇒ 00:19:38.200 Shivani Amar: Right? So it’s like, I’m just making shit up, you’re gonna have to.
248 00:19:38.200 ⇒ 00:19:38.650 Uttam Kumaran: Yeah, yeah, yeah.
249 00:19:38.650 ⇒ 00:19:43.930 Shivani Amar: But, like, revenue reporting for…
250 00:19:44.220 ⇒ 00:19:50.370 Shivani Amar: retail, and… but then you might be like, oh, I’m deducting trade spend from revenue.
251 00:19:50.570 ⇒ 00:19:54.700 Shivani Amar: So I can’t, like, I just have to know that my revenue number is not right.
252 00:19:55.040 ⇒ 00:19:55.960 Shivani Amar: Right?
253 00:19:56.180 ⇒ 00:20:06.470 Shivani Amar: So, revenue reporting for retail… And… wholesale… And Shopify…
254 00:20:07.580 ⇒ 00:20:11.280 Shivani Amar: Amazon, or something. Okay? Or it’s like…
255 00:20:14.490 ⇒ 00:20:21.470 Shivani Amar: OKR revenue reporting… Or…
256 00:20:34.370 ⇒ 00:20:42.189 Shivani Amar: And then at some point, you’re like, okay, if DSD is, like, I don’t know, he said, like, DSD would come in, like, April. I don’t remember what it is.
257 00:20:42.540 ⇒ 00:20:46.479 Shivani Amar: set, right? But then it’s like, do we have anything that says DSD here?
258 00:20:48.850 ⇒ 00:20:54.360 Uttam Kumaran: I don’t think it says DSD, it might be under… And…
259 00:20:56.240 ⇒ 00:21:02.410 Shivani Amar: So, okay, so you see, what I’m doing is, like, do you actually have all the inputs listed? Maybe we have Encompass?
260 00:21:04.520 ⇒ 00:21:08.990 Shivani Amar: So you have next phase scoping deeper… so you have encompass at the very end.
261 00:21:10.950 ⇒ 00:21:19.229 Uttam Kumaran: Yeah, so for Encompass, I guess we… I mean, we… this is somewhat based on, like, we… I don’t know yet whether we have that snowflake data.
262 00:21:19.760 ⇒ 00:21:20.330 Uttam Kumaran: So…
263 00:21:20.330 ⇒ 00:21:28.029 Shivani Amar: Well, like, let’s assume that we will, right? And yes, there’s no tendency, but then you could say, like, okay, based off what Jeff Warren said, he was like.
264 00:21:28.200 ⇒ 00:21:39.599 Shivani Amar: What did he say? He was like… I’m gonna get dimensions da-da-da-da-da, it’ll replace QuickBooks.
265 00:21:39.870 ⇒ 00:21:43.630 Shivani Amar: so…
266 00:21:46.660 ⇒ 00:21:48.920 Shivani Amar: I guess each dimension.
267 00:21:49.110 ⇒ 00:22:02.880 Shivani Amar: And it’s like, okay, so if he’s changing dimensions, we could say, like, we’ll try to get DSD in, right? DSD8 in early May, which is fine. That gives him time to change his dimensions. DSD data from Encompass.
268 00:22:03.370 ⇒ 00:22:04.410 Shivani Amar: Okay.
269 00:22:04.600 ⇒ 00:22:09.580 Shivani Amar: Govern dashboards finalized in Omni. I don’t know.
270 00:22:23.410 ⇒ 00:22:29.459 Shivani Amar: So, life analysis, and it doesn’t have to be every week is, like, a thing, right? Like, we can… you could make it, like…
271 00:22:30.780 ⇒ 00:22:36.300 Shivani Amar: whatever. Even if you made it a monthly checklist of inputs and outputs like that, like.
272 00:22:36.530 ⇒ 00:22:38.879 Shivani Amar: Be less crazy for you, but…
273 00:22:38.880 ⇒ 00:22:39.420 Uttam Kumaran: Okay.
274 00:22:40.420 ⇒ 00:22:44.909 Uttam Kumaran: The inputs… the inputs are… are truly, like, what is… what is unlocked?
275 00:22:45.060 ⇒ 00:22:49.670 Uttam Kumaran: For us, from the business, or from an external stakeholder, that… that week.
276 00:22:50.540 ⇒ 00:22:52.809 Uttam Kumaran: And then, what is the output from…
277 00:22:52.960 ⇒ 00:22:58.640 Uttam Kumaran: So the… what is the output? Like, the thing about output unlocked in that week, Is that…
278 00:22:59.520 ⇒ 00:23:05.670 Uttam Kumaran: There’s, as you mentioned, there’s gonna be outputs in future weeks, unlocked from past weeks.
279 00:23:06.270 ⇒ 00:23:07.290 Uttam Kumaran: So…
280 00:23:19.480 ⇒ 00:23:24.800 Shivani Amar: I didn’t know that was part of the pilot. Isn’t that part of the pilot? Or is there some… what does that mean, AI querying?
281 00:23:24.800 ⇒ 00:23:29.259 Uttam Kumaran: It is part of the pilot, it’s just, like, there… it’s kind of just the finishing of…
282 00:23:29.720 ⇒ 00:23:32.320 Uttam Kumaran: setting it up. Like, in our doc, there’s, like, a bunch of steps.
283 00:23:33.100 ⇒ 00:23:33.470 Uttam Kumaran: Yeah.
284 00:23:35.460 ⇒ 00:23:41.399 Uttam Kumaran: So we can put, like, Abil… use AI to query Omni. Available.
285 00:23:55.090 ⇒ 00:24:02.250 Shivani Amar: It’s like, at what point do we think we’ll have a full view of revenue? Maybe it’s not for a while, like, and then it could be, like, dependency.
286 00:24:03.720 ⇒ 00:24:05.500 Shivani Amar: on retailers.
287 00:24:06.890 ⇒ 00:24:09.970 Uttam Kumaran: Yeah, it’s gonna be on… yeah, outside of the… yeah.
288 00:24:10.410 ⇒ 00:24:17.549 Shivani Amar: Okay? But, like, that’s kind of, like, I’m like, at what point will we be able to answer certain questions?
289 00:24:17.820 ⇒ 00:24:18.860 Shivani Amar: is, like, how I think.
290 00:24:18.860 ⇒ 00:24:19.350 Uttam Kumaran: Okay.
291 00:24:19.350 ⇒ 00:24:24.210 Shivani Amar: about it, and so I don’t care, like, right now, I’m just totally messing with this.
292 00:24:24.320 ⇒ 00:24:27.700 Shivani Amar: But, it’s like, I don’t think we need…
293 00:24:28.210 ⇒ 00:24:32.010 Shivani Amar: cross-channel revenue marked to be too, like.
294 00:24:32.010 ⇒ 00:24:33.490 Uttam Kumaran: Yeah, that’s… yeah.
295 00:24:33.490 ⇒ 00:24:45.579 Shivani Amar: we think we’re gonna have a full view of revenue across our channels by June, or whatever, I’m just sort of making… combine… if… combine e-commerce… So separate… so separate the inputs and outputs, basically, like…
296 00:24:45.580 ⇒ 00:24:52.989 Uttam Kumaran: Inputs are, like, new inputs when we expect them to get unlocked, and when the outputs expect to get unlocked. They… those don’t necessarily, like.
297 00:24:53.350 ⇒ 00:24:56.260 Uttam Kumaran: Same week, if possible, sure, but, like.
298 00:24:56.260 ⇒ 00:24:59.470 Shivani Amar: No, they’re not ever gonna… they’re rarely gonna be a second week, right?
299 00:24:59.470 ⇒ 00:25:00.789 Uttam Kumaran: So, okay, that makes sense.
300 00:25:00.790 ⇒ 00:25:13.050 Shivani Amar: So this should just be, like, if you’re like, all my P0P down to P2 things are listed here, then I’m putting my inputs correctly, because these are all the things inputting into my warehouse.
301 00:25:13.050 ⇒ 00:25:13.420 Uttam Kumaran: Yeah.
302 00:25:13.420 ⇒ 00:25:27.340 Shivani Amar: And so it’s like, that’s where I’d start, like, okay, when are we gonna make sure we have everything? And then from that, after… yes, there’s the… just the ingestion, and I get that there’s the modeling. I don’t need to know all the steps of the modeling, but you’re basically saying.
303 00:25:27.510 ⇒ 00:25:36.659 Shivani Amar: like, yeah, I’m kicking off Amazon ingestion, I’m kicking off these data sources by, like, I’ll probably start, like,
304 00:25:37.030 ⇒ 00:25:40.719 Shivani Amar: I’ll probably start ingesting these next week, or, like, 2 weeks from now.
305 00:25:40.720 ⇒ 00:25:48.209 Uttam Kumaran: So if I was to think about each phase of the input, it would be, like, the data is available, like, we have access.
306 00:25:48.430 ⇒ 00:25:50.179 Uttam Kumaran: like, there is…
307 00:25:50.180 ⇒ 00:25:53.400 Shivani Amar: That’s your… that’s your background stuff, right?
308 00:25:53.570 ⇒ 00:25:54.550 Uttam Kumaran: Yeah, so…
309 00:25:54.550 ⇒ 00:25:58.960 Shivani Amar: need to show up on this, it’s just, like, I would just say that this is when you’re kicking off ingestion.
310 00:25:59.390 ⇒ 00:26:06.980 Uttam Kumaran: Okay, so, like, ingestion kicked off, modeling kicked off, dashboard, And then…
311 00:26:06.980 ⇒ 00:26:07.570 Shivani Amar: Oh my god.
312 00:26:07.610 ⇒ 00:26:08.770 Uttam Kumaran: But then, yeah.
313 00:26:08.990 ⇒ 00:26:10.779 Shivani Amar: Okay, let’s take a breath.
314 00:26:12.570 ⇒ 00:26:26.199 Shivani Amar: The thing I’m saying is, like, just keep inputs when you start ingesting, and make it really simple. That’s like, this is when we’re gonna just start ingesting everything. I’m trying to make it, like, super simple for you. I know that there will be modeling, I know that there will be…
315 00:26:26.200 ⇒ 00:26:34.009 Shivani Amar: And then you’re kind of, like, going, like, there’s gonna be modeling in QA, so then, like, 6 weeks from the input is when you’re gonna get some output.
316 00:26:34.940 ⇒ 00:26:38.029 Uttam Kumaran: And it’s… and you’re saying, don’t worry about,
317 00:26:38.770 ⇒ 00:26:41.139 Uttam Kumaran: Don’t… don’t put the stuff in between.
318 00:26:41.140 ⇒ 00:26:44.339 Shivani Amar: Or what you could do is you could say, ingestion.
319 00:26:45.030 ⇒ 00:26:51.050 Shivani Amar: like, ingestion kickoff, okay? You can say modeling, like, if you really wanted to.
320 00:26:51.050 ⇒ 00:26:51.990 Uttam Kumaran: But, yeah.
321 00:26:51.990 ⇒ 00:27:01.719 Shivani Amar: model, if this helps your brain, right? Like, you’d be like, I’m starting to kick off ingestion, I’m starting to model Shopify, like, what’s in my queue right now, right?
322 00:27:01.720 ⇒ 00:27:05.620 Uttam Kumaran: Probably just do ingestion, QA, dashboard.
323 00:27:05.870 ⇒ 00:27:08.839 Shivani Amar: That’s, like, much… that’s a little bit easier for me, and then…
324 00:27:08.930 ⇒ 00:27:15.550 Uttam Kumaran: maybe we can… if you’re, like, still QA is, like, too much, then,
325 00:27:17.040 ⇒ 00:27:20.619 Uttam Kumaran: Because I think ultimately, like, dashboard.
326 00:27:21.400 ⇒ 00:27:29.530 Uttam Kumaran: is sort of the same indication for, like, these are certified, they’re… they’ve all been QA’d, it’s usable now by the company.
327 00:27:29.710 ⇒ 00:27:35.740 Shivani Amar: Yeah, and like, imagine your fill, and you’re like, I’m paying $90K a month. And so I just want to say, like, did all these things happen?
328 00:27:35.990 ⇒ 00:27:36.610 Uttam Kumaran: Yeah.
329 00:27:36.610 ⇒ 00:27:38.149 Shivani Amar: This month? If not, why?
330 00:27:38.500 ⇒ 00:27:39.160 Uttam Kumaran: Okay.
331 00:27:39.160 ⇒ 00:27:49.759 Shivani Amar: And your Gantt chart’s too high level, this is too detailed, so we’re meeting somewhere in the middle, where you’re saying, Amazon, blah blah blah, wholesale mart discounts, returns finalized.
332 00:27:49.760 ⇒ 00:27:51.060 Uttam Kumaran: Yeah, yeah, I see.
333 00:27:51.060 ⇒ 00:28:10.869 Shivani Amar: this is, like, an out… that is an outcome, right? Finalized wholesales, this is great. Like, if you’re like, hey, by the way, this is a win that we unlocked, great, but you’ve already done the ingestion for wholesale. You’ve already started the QA for wholesale, right? So you could be like, QA that’s happening is, like, wholesale,
334 00:28:10.930 ⇒ 00:28:20.770 Shivani Amar: refunds and discounts, okay? Which is, like, a new level of rigor there. And then you could say finalized da-da-da is, like, by this week, okay?
335 00:28:21.170 ⇒ 00:28:21.970 Shivani Amar: So it gives best.
336 00:28:21.970 ⇒ 00:28:31.290 Uttam Kumaran: Yeah, so another outcome is, like, we’re gonna start to basically also go backwards. So, like, data is now… data is now confirmed back through 2024.
337 00:28:31.370 ⇒ 00:28:42.040 Uttam Kumaran: Right? So, like, that is another outcome that we’re, like, gunning for. So some of the outcomes I think I wrote are in line, but some are definitely, like, too much. So let me…
338 00:28:42.800 ⇒ 00:28:43.810 Uttam Kumaran: Let me…
339 00:28:44.840 ⇒ 00:28:47.699 Shivani Amar: And, like, I don’t know if you want QA versus modeling.
340 00:28:48.220 ⇒ 00:28:57.739 Uttam Kumaran: No, I don’t… I don’t. I, I think I get it. I would rather have one… I just think there’s so much in between that it’s almost tough to be, like…
341 00:28:59.130 ⇒ 00:29:00.470 Uttam Kumaran: Like, yeah.
342 00:29:00.470 ⇒ 00:29:03.660 Shivani Amar: modeling and then outcomes, and I know that there are steps in between.
343 00:29:03.660 ⇒ 00:29:09.409 Uttam Kumaran: Okay, if you… I think modeling and QA is, like, that’s fine, and the dashboard is fine.
344 00:29:09.410 ⇒ 00:29:20.130 Shivani Amar: Yeah, so then you’re just saying, like, okay, I know I’m ingesting Amazon and Facebook this week, and then this is just, like, by the way, another thing that’s happening, right? This is not an ingestion, this is just, like…
345 00:29:20.130 ⇒ 00:29:20.690 Uttam Kumaran: S.
346 00:29:20.690 ⇒ 00:29:26.909 Shivani Amar: Okay? Then… Walmart.com ingestion kicks off? Ingestion kick off.
347 00:29:27.110 ⇒ 00:29:36.019 Shivani Amar: Okay? It’s not completion. I’m not saying I’m done ingesting. It’s like, when I believe that the connector is built, we can start ingesting.
348 00:29:36.020 ⇒ 00:29:36.410 Uttam Kumaran: Yeah.
349 00:29:36.410 ⇒ 00:29:44.569 Shivani Amar: explaining it. So you’re like, okay, why didn’t we start ingesting Walmart next week? Oh, Gob was slow, or we didn’t communicate.
350 00:29:44.570 ⇒ 00:29:45.020 Uttam Kumaran: We didn’t get…
351 00:29:45.020 ⇒ 00:29:47.340 Shivani Amar: next in line, then you’re learning, right?
352 00:29:47.850 ⇒ 00:29:52.239 Shivani Amar: So, Walmart.com ingestion, then you’re like, okay, well, when am I getting…
353 00:29:52.470 ⇒ 00:29:55.219 Shivani Amar: Spins… well, that’s not coming for…
354 00:29:55.930 ⇒ 00:29:57.000 Uttam Kumaran: Wow.
355 00:29:57.000 ⇒ 00:30:02.219 Shivani Amar: Right? We can… spins… data quality scorecard is… nothing.
356 00:30:02.220 ⇒ 00:30:05.060 Uttam Kumaran: Yeah, I’m gonna put… I’m gonna put Spins API access.
357 00:30:05.060 ⇒ 00:30:05.580 Shivani Amar: Right?
358 00:30:05.580 ⇒ 00:30:07.100 Uttam Kumaran: It’s API ingestion, yeah.
359 00:30:07.100 ⇒ 00:30:16.040 Shivani Amar: Yeah, ingestion… you don’t have to use the word ingestion over and over, but you can… you can just play with it. Retail VP dashboard to be QA’d.
360 00:30:16.260 ⇒ 00:30:20.530 Shivani Amar: I don’t even remember what that means anymore, but, like, that’s kind of what’s happening now.
361 00:30:21.210 ⇒ 00:30:31.760 Uttam Kumaran: Yeah, so… so then I would just say, like, I would say, like, retail overview, Dashboard… But…
362 00:30:32.470 ⇒ 00:30:36.040 Uttam Kumaran: I would guess I would say, like, like, minus…
363 00:30:36.460 ⇒ 00:30:42.210 Shivani Amar: I mean, I’m trying to basically… That’s the retail thing, right? So it’s just, like, you’ve done it, it’s just, like, in QA right now.
364 00:30:42.210 ⇒ 00:30:42.590 Uttam Kumaran: Yeah.
365 00:30:42.590 ⇒ 00:30:44.819 Shivani Amar: Right? Like, modeling, like…
366 00:30:46.140 ⇒ 00:30:51.440 Uttam Kumaran: But I guess I would say, like, the dashboard is gonna be… the outcome of Omni.
367 00:30:52.410 ⇒ 00:30:56.860 Uttam Kumaran: Right, so then I wanna… I kinda wanna say, like, Google… I kinda do wanna say Google Sheet.
368 00:30:57.230 ⇒ 00:31:02.790 Uttam Kumaran: versus, like, the OmniDash. It’s similar data, but the dashboard is gonna have, like.
369 00:31:03.890 ⇒ 00:31:05.889 Uttam Kumaran: Viz and stuff like that, so…
370 00:31:13.920 ⇒ 00:31:15.280 Uttam Kumaran: Like this one.
371 00:31:18.190 ⇒ 00:31:26.689 Shivani Amar: this is kind of nice, like, this really helps me understand what’s going on. Okay, you’re doing Shopify V1 table modeling, and then you’re queuing a couple things this week.
372 00:31:27.640 ⇒ 00:31:32.499 Shivani Amar: And then you can kind of see the flow, right? You’re like, okay, at some point you’re like.
373 00:31:32.740 ⇒ 00:31:47.400 Shivani Amar: I’m modeling, like, amazon tables modeling, right? And, like, if you’re starting, then you’re, like.
374 00:31:47.400 ⇒ 00:31:48.130 Uttam Kumaran: Yeah.
375 00:31:51.480 ⇒ 00:31:52.409 Uttam Kumaran: How’s not too.
376 00:32:00.670 ⇒ 00:32:05.910 Shivani Amar: If you’re just gonna do this, you might as well do this. Okay, we’ll just play with it later, but modeling…
377 00:32:06.300 ⇒ 00:32:14.180 Shivani Amar: Shopify… QAs, these… And I’ll probably do consider it.
378 00:32:16.050 ⇒ 00:32:17.920 Shivani Amar: You end up needing to split it up.
379 00:32:25.150 ⇒ 00:32:43.330 Shivani Amar: And then at some point, you have an output, kind of, like, an initial output that has to be Q8, but you have, like, Amazon table modeling, Shopify V1 table modeling, right? Then, at some point, you’re like, okay, join. Like, you’re, you’re, like, exploring the joins of these two, right? Then you’re, like, Walmart…
380 00:32:43.470 ⇒ 00:32:51.690 Shivani Amar: dot com, tables, modeling, right? And then you’re like, Doing the joins of e-commerce.
381 00:32:54.080 ⇒ 00:33:00.779 Shivani Amar: channels? Like… joins of e-commerce? I’m bullshitting. Yes. Okay? Then you’re…
382 00:33:00.780 ⇒ 00:33:03.020 Uttam Kumaran: I think e-commerce modeling is… yeah.
383 00:33:03.020 ⇒ 00:33:06.540 Shivani Amar: Yeah, then you’re doing, like, e-commerce combined.
384 00:33:07.080 ⇒ 00:33:07.600 Shivani Amar: I’m…
385 00:33:07.600 ⇒ 00:33:07.920 Uttam Kumaran: Yeah.
386 00:33:07.920 ⇒ 00:33:23.519 Shivani Amar: modeling, right? And then at some point, you’re like, okay, now, like, I’m starting to get somewhere, and that’s, like, in QA, because, like, I’m at a place where I can, like, actually show this to people, and, like, reference things, and, like, you can figure out, like, okay, are we doing some Amazon
387 00:33:23.750 ⇒ 00:33:30.510 Shivani Amar: table queuing, like, pretty soon, because you’re starting with the most recent data that I can actually see doesn’t map to the OKRs.
388 00:33:30.510 ⇒ 00:33:45.940 Shivani Amar: And then you could be like, yeah, like, we’re hoping to do some Amazon QA with Carlos later, we’re hoping to do some Walmart QA, we’re hoping to do some Shopify QA, because all of this is just, like, you can look at the most recent revenue and see, like, are we talking about it the right way?
389 00:33:45.940 ⇒ 00:33:49.680 Shivani Amar: Right? So then it can be kind of like this, like, waterfall of things that.
390 00:33:49.680 ⇒ 00:33:50.090 Uttam Kumaran: Yeah.
391 00:33:50.450 ⇒ 00:34:04.519 Shivani Amar: And you can make it more realistic to you. You might be like, no, this is gonna take 2 weeks, like, before I want to show it to anybody. And then it might be, like, combined e-commerce modeling just for recent data. It’s not for the full thing.
392 00:34:04.520 ⇒ 00:34:10.550 Shivani Amar: Yeah. It’s like, there’s initial QA that’s happening here. And then, like, then you’re like, okay, can I get…
393 00:34:10.699 ⇒ 00:34:22.669 Shivani Amar: you know, this reporting done, and, like, what is the thing that I’ve unlocked? Like, I have a view of OKR revenue reporting, or sales reporting for Walmart, Target, e-commerce, wholesale.
394 00:34:22.679 ⇒ 00:34:26.249 Uttam Kumaran: So ideally, naturally, you should see something that’s, like, more diagonal, like this.
395 00:34:26.250 ⇒ 00:34:30.630 Shivani Amar: Exactly, right? And it’s not always even perfect diagonal, because it might be.
396 00:34:30.639 ⇒ 00:34:31.029 Uttam Kumaran: Yes.
397 00:34:31.030 ⇒ 00:34:40.530 Shivani Amar: two weeks here, but that’s kind of the flow, is you’re like, okay, I get my Spins API, and then I’m able to, like, kind of do some modeling that, like, layers in competitive analysis.
398 00:34:40.920 ⇒ 00:34:41.440 Uttam Kumaran: Yeah.
399 00:34:41.810 ⇒ 00:34:43.729 Shivani Amar: Okay, yeah.
400 00:34:44.520 ⇒ 00:34:52.380 Shivani Amar: Point-of-sale modeling, like, point-of-sale, modeling for…
401 00:34:53.110 ⇒ 00:34:56.899 Shivani Amar: Actually, no, like, Spins is really just about competitive analysis, right?
402 00:34:56.909 ⇒ 00:35:00.379 Uttam Kumaran: It’s all, yeah, it’s all competitive and, like, in-store.
403 00:35:00.569 ⇒ 00:35:04.819 Uttam Kumaran: stuff, so… Yeah, competitive market intelligence.
404 00:35:10.380 ⇒ 00:35:22.709 Shivani Amar: Like, what do we want that table to look like? And so then you’re kind of just like, okay, and there’s all this other stuff. You’re like, I’m trying to get connectors built for these things. You’re like, okay, Google Ads, LinkedIn.
405 00:35:22.710 ⇒ 00:35:23.640 Uttam Kumaran: Yeah.
406 00:35:23.640 ⇒ 00:35:29.579 Shivani Amar: So for those, like, do you… should we just go to the source? I was gonna put marketing costs and campaign ingestion.
407 00:35:29.670 ⇒ 00:35:30.400 Uttam Kumaran: And just, like.
408 00:35:30.400 ⇒ 00:35:32.410 Shivani Amar: Oh, perfect.
409 00:35:32.410 ⇒ 00:35:38.020 Uttam Kumaran: We’re gonna do… we’re gonna do this for the next 3 weeks, and I’m gonna try to get through all of them.
410 00:35:38.550 ⇒ 00:35:41.620 Uttam Kumaran: Right, so I’m just gonna put it as another item.
411 00:35:41.900 ⇒ 00:35:44.530 Uttam Kumaran: Because when spins comes, we’ll kick off spins.
412 00:35:44.690 ⇒ 00:35:45.170 Shivani Amar: Yeah.
413 00:35:45.170 ⇒ 00:35:47.700 Uttam Kumaran: And… Yeah.
414 00:35:48.790 ⇒ 00:35:49.780 Uttam Kumaran: Exactly.
415 00:35:50.680 ⇒ 00:35:54.700 Uttam Kumaran: So then that way, like, if anything doubles, it’ll just come as another item.
416 00:35:55.360 ⇒ 00:35:56.120 Shivani Amar: Yeah.
417 00:35:56.120 ⇒ 00:35:58.450 Uttam Kumaran: Because, for example, right now, we’re still doing…
418 00:35:58.810 ⇒ 00:36:04.829 Uttam Kumaran: like, this week, we’re doing the wholesale QA, we’re doing the retail.
419 00:36:05.870 ⇒ 00:36:09.749 Uttam Kumaran: just, like, broad retail QA and the Omni kickoff.
420 00:36:10.010 ⇒ 00:36:12.199 Uttam Kumaran: Next week, we’re doing the Omni topic.
421 00:36:12.420 ⇒ 00:36:16.150 Uttam Kumaran: building… And then the third week will be…
422 00:36:16.300 ⇒ 00:36:23.449 Uttam Kumaran: putting it, like, the next two weeks we’ll be putting out dashboards. So I kind of see, like, a little bit of, like, the diagonal. I think this…
423 00:36:23.630 ⇒ 00:36:26.729 Uttam Kumaran: Yeah, so some diagonals start above the fold, but yeah.
424 00:36:27.010 ⇒ 00:36:34.379 Shivani Amar: Yeah. And, like, you’ve already started something, so it makes sense that I’m not saying you’re ingesting Shopify anywhere, because you’ve already done it, right? Yeah, yeah, yeah.
425 00:36:34.380 ⇒ 00:36:47.640 Shivani Amar: then this gives you, like, a full list of, like, okay, this is, like, everything that they think they want to ingest, and this is everything that they think they can help unlock and win. And so then, when we’re, like, checking in in, like, April, like, okay, do we feel like now we have, like.
426 00:36:47.850 ⇒ 00:36:48.420 Shivani Amar: We’ve achieved.
427 00:36:48.420 ⇒ 00:36:54.470 Uttam Kumaran: Yeah, on a weekly basis, we should just cut this, and basically say, like, this moved, or, like, this got added, and, like.
428 00:36:54.660 ⇒ 00:37:06.100 Uttam Kumaran: this… yeah, like, in a similar way on the Gantt, like, this is what gets adjusted, and then it’s clear, like, across these… this is the fa… this is the supply chain of the output, which is the dashboard.
429 00:37:07.090 ⇒ 00:37:10.009 Uttam Kumaran: what got shifted? Okay, spins took another week.
430 00:37:10.220 ⇒ 00:37:13.630 Uttam Kumaran: Sure. She didn’t get access to this, so then, like, its dependencies moved.
431 00:37:13.630 ⇒ 00:37:27.800 Shivani Amar: this isn’t gonna be perfect ever, but it’s like, are we starting to get progress on these things? And if so, how? So it’s like, starting with, like, what are we actually unlocking here, right? If you even start from the output, it’s like, okay, I think I can get you finalized.
432 00:37:27.840 ⇒ 00:37:36.359 Shivani Amar: Like, I can save finance time. Okay, great. But then I can also, like, start giving you a view of e-commerce, or, like, I can…
433 00:37:36.650 ⇒ 00:37:37.810 Uttam Kumaran: I can, like.
434 00:37:37.810 ⇒ 00:37:44.330 Shivani Amar: have e-commerce OKRs for sales be pulled from my reporting.
435 00:37:44.330 ⇒ 00:37:45.820 Uttam Kumaran: pulled from… yeah.
436 00:37:46.310 ⇒ 00:37:55.320 Shivani Amar: And that’s, like, a nice output. Or it’s, like… or it’s kind of what Phil said, where it’s, like, vP-level dashboard for…
437 00:37:55.510 ⇒ 00:37:56.840 Shivani Amar: e-commerce.
438 00:37:57.170 ⇒ 00:37:58.200 Shivani Amar: Drafted.
439 00:37:58.660 ⇒ 00:37:59.590 Shivani Amar: Right?
440 00:38:00.060 ⇒ 00:38:00.690 Uttam Kumaran: Yeah.
441 00:38:01.090 ⇒ 00:38:16.239 Shivani Amar: And then it’s like, okay, that’s, like, a milestone that we’re, like, shooting for. And you kind of have the understanding now, it’s, like, flows of ins and outs, and it’s, like, not the full funnel, maybe it’s not… doesn’t include marketing, but it has, like, customers…
442 00:38:16.240 ⇒ 00:38:21.369 Uttam Kumaran: Well, at any moment, yeah, and I think it’s still probably helpful to have that column B.
443 00:38:21.660 ⇒ 00:38:23.540 Uttam Kumaran: Like, the work stream.
444 00:38:24.420 ⇒ 00:38:26.699 Uttam Kumaran: Just in, like, what workstream is…
445 00:38:26.700 ⇒ 00:38:31.000 Shivani Amar: The work stream, to me, like, doesn’t flow with… you can think about it, the work stream…
446 00:38:31.000 ⇒ 00:38:34.200 Uttam Kumaran: is more like, we’re not gonna… yeah, okay, I see what you mean.
447 00:38:34.200 ⇒ 00:38:34.710 Shivani Amar: It just isn’t.
448 00:38:34.710 ⇒ 00:38:36.610 Uttam Kumaran: At this point, like, we’ll be working on all four.
449 00:38:36.610 ⇒ 00:38:40.410 Shivani Amar: Yeah, like, you’re gonna be working on all the work streams all the time.
450 00:38:44.470 ⇒ 00:38:47.869 Shivani Amar: Like, when I see data foundation, I don’t even know what that means.
451 00:38:49.060 ⇒ 00:38:53.700 Uttam Kumaran: Do you feel like this, the column I let the outcome unlock?
452 00:38:53.980 ⇒ 00:38:56.309 Uttam Kumaran: Is that so relevant as, like, another…
453 00:38:56.440 ⇒ 00:39:01.159 Uttam Kumaran: piece, or should I just stop everything at the F? I’m not gonna have this level of detail, but, like…
454 00:39:03.300 ⇒ 00:39:04.860 Shivani Amar: It’s so detailed that it’s, like.
455 00:39:04.860 ⇒ 00:39:09.799 Uttam Kumaran: Okay, I’m gonna… I’m just gonna put… it’s gonna… so F is gonna be a mix of, like.
456 00:39:10.810 ⇒ 00:39:14.479 Uttam Kumaran: If there are data, like, if there’s a dashboard on lock, if there’s, like, an…
457 00:39:14.480 ⇒ 00:39:18.530 Shivani Amar: Or, like, a time-saving… Or a, like, a win.
458 00:39:18.980 ⇒ 00:39:19.900 Uttam Kumaran: Okay, okay.
459 00:39:20.210 ⇒ 00:39:20.650 Shivani Amar: Okay.
460 00:39:20.650 ⇒ 00:39:21.200 Uttam Kumaran: Okay.
461 00:39:22.940 ⇒ 00:39:26.729 Shivani Amar: I think you’ve got it. I, like, I, I, like, it’s just… I’m like, I’m gonna hide this.
462 00:39:26.730 ⇒ 00:39:38.169 Uttam Kumaran: No, no, no, I mean, this is actually closer, but you’re… you’re right in that, like, I think this view is good. It’s closer to, like, a deeper Gantt, but I think this is fine. Let me just… just… we’ll just… we’ll do this. I’ll just go overwork on it.
463 00:39:38.170 ⇒ 00:39:39.719 Shivani Amar: Okay, cool. Okay, perfect.
464 00:39:39.720 ⇒ 00:39:41.900 Uttam Kumaran: I should probably send you a version today.
465 00:39:42.010 ⇒ 00:39:46.160 Uttam Kumaran: If you… whenever you’re back, you’re back up away.
466 00:39:46.160 ⇒ 00:39:49.290 Shivani Amar: for it on Monday, but I just want it to be good. I don’t, like…
467 00:39:49.290 ⇒ 00:39:52.390 Uttam Kumaran: No, no, no, I also want it to be, like, helpful.
468 00:39:52.390 ⇒ 00:39:53.450 Shivani Amar: go.
469 00:39:53.790 ⇒ 00:40:09.109 Shivani Amar: doc, like, be like, did I… did I check every box here, and if not, why? And, like, at what point do we think we’re gonna ingest Confido? And then I would say, like, Confido would be an input, we think, in, like, June, because this… and then you get…
470 00:40:09.110 ⇒ 00:40:12.229 Uttam Kumaran: Once you get Confido, you get retail revenue.
471 00:40:12.630 ⇒ 00:40:16.980 Shivani Amar: Because you’re able to, like, reduce the chargebacks, or the trade spend, or whatever.
472 00:40:17.210 ⇒ 00:40:29.310 Shivani Amar: Right? And it shows that, like, until then, you have sales, retail sales, retail sales, point of sales, but, like, you’re actually able to get retail revenue once you have A, B, and C, or whatever.
473 00:40:29.480 ⇒ 00:40:39.969 Shivani Amar: And then it shows your understanding of the metrics, which right now I’m like… I don’t know how many times I’ve said, like, sales and revenue is still confusing to me, but, like, if it’s still confusing to you, then that’s a problem.
474 00:40:40.250 ⇒ 00:40:51.020 Shivani Amar: And it’s like, then, like, what do we need to do to unblock ourselves so that, like, we feel very crisp on when revenue… how revenue is defined for each channel, and when we’ll be able to.
475 00:40:51.020 ⇒ 00:40:55.900 Uttam Kumaran: It’s mainly this next month, because, like, finally you’re actually gonna be able to queue… you’re actually gonna, like, query
476 00:40:56.350 ⇒ 00:41:00.589 Uttam Kumaran: And it’s like… Yeah, that’s gonna help us lock that definition.
477 00:41:00.590 ⇒ 00:41:01.319 Shivani Amar: Yeah. Bye.
478 00:41:01.320 ⇒ 00:41:01.940 Uttam Kumaran: Yeah.
479 00:41:02.110 ⇒ 00:41:02.890 Uttam Kumaran: Okay.
480 00:41:03.320 ⇒ 00:41:07.739 Shivani Amar: Okay, so… yeah, like, leadership dashboard review…
481 00:41:08.060 ⇒ 00:41:13.269 Shivani Amar: Annual definitions, council kickoff. I mean, like, I like… I like the concept of a…
482 00:41:14.160 ⇒ 00:41:19.340 Uttam Kumaran: But I think, again, like, we’re forecasting, like, okay, if we need to sort of, like.
483 00:41:19.600 ⇒ 00:41:24.569 Uttam Kumaran: get ahead of September, we need, like, you need to start doing, like, KPIs by June, but…
484 00:41:24.570 ⇒ 00:41:35.570 Shivani Amar: what Phil said to me is, like, look, like, we’re probably gonna do OKR planning even earlier than October this year, like, we’re gonna just do it soon, and it’s gonna be based off what we can.
485 00:41:35.570 ⇒ 00:41:36.200 Uttam Kumaran: Whenever we ask.
486 00:41:36.750 ⇒ 00:41:39.269 Shivani Amar: He’s like, we might do OKR planning in, like, May.
487 00:41:39.380 ⇒ 00:41:47.320 Shivani Amar: So he was like, it’s less about, like, enabling OKRs, it’s about making sure everything’s ingested. He’s like, I really want 2027 to start with, like.
488 00:41:47.320 ⇒ 00:41:47.970 Uttam Kumaran: Yeah.
489 00:41:48.250 ⇒ 00:41:55.649 Shivani Amar: clean, good data. So I don’t even want to orient us to, like, the OKR thing as much, but, like, yes.
490 00:41:55.650 ⇒ 00:41:56.140 Uttam Kumaran: Okay.
491 00:41:56.140 ⇒ 00:42:05.330 Shivani Amar: OKRs being populated by our data, and, like, people not having to spend 5 hours a month trying to make sense of what their numbers are, that is something I want done by September.
492 00:42:06.060 ⇒ 00:42:06.980 Uttam Kumaran: Yeah. Right?
493 00:42:07.120 ⇒ 00:42:13.340 Shivani Amar: So, then, like, if… then… then we don’t need to get into, like, the… all the…
494 00:42:14.230 ⇒ 00:42:31.589 Shivani Amar: he’s basically like, let’s imagine we’re playing Brainforge, the 90K for April, May, June, July, August, okay? Yeah. Because we haven’t figured it out yet for March, so I’m imagining March is… let’s say it’s the same rate, because we haven’t figured it out, like, what March is. But, like, then it’s like, okay.
495 00:42:32.140 ⇒ 00:42:41.940 Shivani Amar: That’s 5 months, that’s like 500K, let’s call it, right? And… or 450, 500K, and then we say,
496 00:42:42.890 ⇒ 00:42:53.460 Shivani Amar: From there, my goal is to taper you back down to 15 or something, and I have my internal hire. It’s like, what are all the things that need to have been modeled and QA’d?
497 00:42:53.990 ⇒ 00:42:58.519 Uttam Kumaran: Yeah, so that’s, I mean, we’ve put that, yeah, so that’s also…
498 00:42:59.380 ⇒ 00:43:11.250 Uttam Kumaran: We also have that too, but yeah, okay, fair. So, I mean, yeah, our job, I mean, really is gonna be landing and making sure data continues to land, and getting everything modeled, and getting, like, the first
499 00:43:11.390 ⇒ 00:43:17.379 Uttam Kumaran: Dashboard out for as many things as possible is, like, what we’re trying to hit, net-net.
500 00:43:20.350 ⇒ 00:43:29.930 Uttam Kumaran: And, yeah, okay, that makes sense. And then, I mean, we’re basically, like, look, if we can… in… in one of the options, we basically said, like, look, if we can get all of the…
501 00:43:30.660 ⇒ 00:43:35.179 Uttam Kumaran: The data platform ready by, like, yeah, by… by August.
502 00:43:35.930 ⇒ 00:43:39.310 Uttam Kumaran: a lot of the… what the back half was, was, like, OKR,
503 00:43:39.430 ⇒ 00:43:45.830 Uttam Kumaran: And, like, exact dashboard and stuff like that. So maybe come June, that’s what we’re like, okay, where are we?
504 00:43:46.190 ⇒ 00:43:46.910 Shivani Amar: Yeah.
505 00:43:46.910 ⇒ 00:43:47.280 Uttam Kumaran: You know?
506 00:43:47.280 ⇒ 00:43:55.169 Shivani Amar: But it’s like, when are you ingesting supply chain? When are you ingesting, like, whatever? And if you’ve already ingested stored, it’s just then when are you, when are you modeling stored?
507 00:43:55.170 ⇒ 00:43:56.469 Uttam Kumaran: Yeah, yeah, yeah, yes.
508 00:43:56.470 ⇒ 00:44:09.869 Shivani Amar: Okay? So, like, that’s, like, the flow. I just want to be like, when are we modeling what… when are we making sure that things are apples to apples? When are we making sure that, like, because you’ve made things apples to apples, you can now report out on a metric at large?
509 00:44:10.020 ⇒ 00:44:14.140 Uttam Kumaran: Yeah, so that… so again, similar to, like, ingestion, we are always modeling.
510 00:44:14.350 ⇒ 00:44:27.379 Uttam Kumaran: And then, now that we have… now we model things, we’re always gonna be QAing. So, I think to think about it similar to ingestion, where you’re like, always have four things. Like, last week we modeled Shopify, this week we’re doing, where to go stored.
511 00:44:27.660 ⇒ 00:44:28.010 Shivani Amar: Yeah.
512 00:44:28.010 ⇒ 00:44:31.989 Uttam Kumaran: Right? And then we’ll come back on a little bit of Shopify, and then Amazon picks up.
513 00:44:31.990 ⇒ 00:44:37.899 Shivani Amar: was, like, if they already have where to go in the store, like, why are we suddenly seeing that supply chain
514 00:44:38.320 ⇒ 00:44:40.109 Shivani Amar: like… is either…
515 00:44:40.110 ⇒ 00:44:41.060 Uttam Kumaran: additional?
516 00:44:41.060 ⇒ 00:44:44.370 Shivani Amar: Yeah, because he’s… you’ve already ingested it, but that’s, like…
517 00:44:45.130 ⇒ 00:44:49.519 Uttam Kumaran: Yeah, yeah. It’s… it’s less… it’s the… the ingestion is…
518 00:44:49.780 ⇒ 00:44:53.669 Uttam Kumaran: Like, the easiest part of this piece, but…
519 00:44:53.830 ⇒ 00:44:56.890 Uttam Kumaran: again, that’s why I wanted to show that, like, there is…
520 00:44:57.470 ⇒ 00:45:05.079 Uttam Kumaran: So I think we went too deep on, like, our supply chain, more about, like, what are the milestones, but I still think showing the input, the models.
521 00:45:05.380 ⇒ 00:45:07.850 Uttam Kumaran: and the output… Makes sense.
522 00:45:07.850 ⇒ 00:45:24.740 Shivani Amar: You can totally get rid of QA call him. If it helps your brain, then it’s great, but if you’re like, hey, things are always gonna be in QA, and like, we can call that out when we share it with him, right? Like, just like, hey, modeling means that modeling has kicked off, ingestion means that ingestion has kicked off, output is when we’re, like, trying to commit to, like, the QA…
523 00:45:24.740 ⇒ 00:45:28.630 Uttam Kumaran: on the overview a little bit, because I’m going to say, look, any modeling is going to take
524 00:45:29.050 ⇒ 00:45:34.109 Uttam Kumaran: like, two to four weeks. Yeah. Even that, I’m, like, kind of, like, choking on, like.
525 00:45:34.110 ⇒ 00:45:34.430 Shivani Amar: Yeah.
526 00:45:34.430 ⇒ 00:45:35.260 Uttam Kumaran: 4 weeks.
527 00:45:35.600 ⇒ 00:45:41.670 Uttam Kumaran: So really, the pace is… meaning we’re gonna add more people to modeling, because that becomes the bottleneck.
528 00:45:41.670 ⇒ 00:45:42.410 Shivani Amar: Yeah.
529 00:45:42.760 ⇒ 00:45:52.830 Uttam Kumaran: And then dashboarding, again, like, we’re gonna do some, I think the element team will rely on the AI piece, and if new person comes in, that person will do it, but the modeling is the bottleneck.
530 00:45:53.010 ⇒ 00:45:57.569 Uttam Kumaran: Yeah. So I’ll… I’ll put… I’ll put some assumptions in the first page.
531 00:45:58.100 ⇒ 00:45:59.330 Uttam Kumaran: played.
532 00:45:59.330 ⇒ 00:46:00.840 Shivani Amar: And it doesn’t have to be a memo.
533 00:46:01.150 ⇒ 00:46:04.170 Uttam Kumaran: No, no, no, no. We’re always… I’m gonna say we’re always…
534 00:46:04.170 ⇒ 00:46:23.189 Shivani Amar: Funny, it’s like, it’s like I’m learning, it’s like, some people are super into, like, very thoughtful, long-form written communication, and that’s, like, been the culture here. The CEO is like that, as you’ve seen in those emails, and I think Phil is just kind of, like, more standard, like, why am I… why do I just keep saying so many words out of the page? I’m like, I know, it’s a lot.
535 00:46:23.950 ⇒ 00:46:24.740 Shivani Amar: So…
536 00:46:24.740 ⇒ 00:46:32.439 Uttam Kumaran: I… I will read anything that comes out, and I’m sort of just… yeah, I mean, we mold to… we mold to y’all, so…
537 00:46:32.440 ⇒ 00:46:32.980 Shivani Amar: Yeah.
538 00:46:32.980 ⇒ 00:46:34.430 Uttam Kumaran: I think I kind of…
539 00:46:35.270 ⇒ 00:46:39.929 Uttam Kumaran: Depends on the audience. So, okay, let me, let me take a crack at this and try to get you another copy.
540 00:46:40.120 ⇒ 00:46:42.190 Shivani Amar: And, like, imagine it’s almost like…
541 00:46:42.480 ⇒ 00:46:51.519 Shivani Amar: a checklist that we’re just like, boop, boop, boop, yep, we started that, okay, no, that was delayed, okay, what did we learn? And then it’s like, okay, can we report out on revenue yet?
542 00:46:51.520 ⇒ 00:47:01.600 Uttam Kumaran: Or, like, okay, Confido happened earlier, or, like, a random other tool came in, or, like, NetSuite, so then it’ll be, like, we slotted this in, we slotted this out. So I think this is a… yeah, okay.
543 00:47:02.580 ⇒ 00:47:03.300 Shivani Amar: Okay.
544 00:47:03.510 ⇒ 00:47:04.060 Uttam Kumaran: Okay.
545 00:47:04.420 ⇒ 00:47:11.809 Shivani Amar: We’re getting there. Okay, I’ll… Okay. Let’s imagine that, like, we’re talking through this with Jason tomorrow.
546 00:47:12.830 ⇒ 00:47:13.420 Uttam Kumaran: Okay.
547 00:47:13.570 ⇒ 00:47:16.129 Shivani Amar: Okay. If you want to send it to me earlier, I’ll look.
548 00:47:16.130 ⇒ 00:47:17.599 Uttam Kumaran: I’ll send you a copy, yeah.
549 00:47:17.600 ⇒ 00:47:22.369 Shivani Amar: But I think that it’s, like, it would be nice to bring him into the fold, and
550 00:47:22.930 ⇒ 00:47:34.950 Shivani Amar: And I think tomorrow our, like, three… three-person meeting or whatever will be, like, a good time to be like, hey, this is kind of what Phil asked for, like, this is how we’re thinking about the full flow in terms of, like, what we’re trying to unlock.
551 00:47:35.520 ⇒ 00:47:36.120 Uttam Kumaran: Okay, okay.
552 00:47:36.120 ⇒ 00:47:36.830 Shivani Amar: Okay?
553 00:47:37.020 ⇒ 00:47:40.260 Shivani Amar: And then it’ll be a pressure test of some perspective that’s not just mine.
554 00:47:40.560 ⇒ 00:47:41.150 Uttam Kumaran: Sure.
555 00:47:41.640 ⇒ 00:47:42.960 Shivani Amar: Okay, thank you.
556 00:47:42.960 ⇒ 00:47:43.990 Uttam Kumaran: Okay, thank you.
557 00:47:43.990 ⇒ 00:47:44.899 Shivani Amar: Bye. Bye.