Meeting Title: Eden | Standup Date: 2025-08-19 Meeting participants: Henry Zhao, Awaish Kumar, Amber Lin, Annie Yu, Demilade Agboola
WEBVTT
1 00:00:50.920 ⇒ 00:00:52.419 Henry Zhao: Hi, Wade, how’s it going?
2 00:00:55.250 ⇒ 00:00:57.529 Awaish Kumar: Oh, I’m good, how about you?
3 00:01:08.970 ⇒ 00:01:14.720 Henry Zhao: I’ve asked Andrew for help, also, to just check if the server side is working for Polycomic.
4 00:01:14.950 ⇒ 00:01:16.099 Henry Zhao: Just as FYI.
5 00:01:18.190 ⇒ 00:01:22.720 Awaish Kumar: Yeah, I think it is… It’s, …
6 00:01:25.250 ⇒ 00:01:31.050 Awaish Kumar: like, we can ask North Beam, like, when we send a request.
7 00:01:31.490 ⇒ 00:01:32.260 Amber Lin: Hello!
8 00:01:32.260 ⇒ 00:01:36.380 Awaish Kumar: Send an order with a… Hi, …
9 00:01:37.950 ⇒ 00:01:45.249 Awaish Kumar: Yeah, we were just discussing about North Beam. So, like, whenever we send a request… order through an API,
10 00:01:45.750 ⇒ 00:01:49.760 Awaish Kumar: where to find it out in the North Beam?
11 00:01:49.960 ⇒ 00:01:52.960 Awaish Kumar: dashboard, because… The API?
12 00:01:52.960 ⇒ 00:01:54.769 Henry Zhao: I’ll ask him, I’ll ask them right now.
13 00:01:56.410 ⇒ 00:02:00.539 Awaish Kumar: The Northview API says it is successfully inserted.
14 00:02:01.070 ⇒ 00:02:03.750 Awaish Kumar: But I, like, where to find it all?
15 00:02:05.530 ⇒ 00:02:09.269 Henry Zhao: Yeah, like, I can see an exam… I can see an example, but I can’t, …
16 00:02:09.650 ⇒ 00:02:14.429 Henry Zhao: see if the one that you pushed is in there, so I’ll ask Northam, just so that we give him time to respond.
17 00:02:21.930 ⇒ 00:02:24.090 Amber Lin: Okay, hello, Tint.
18 00:02:24.550 ⇒ 00:02:31.310 Amber Lin: Sharing screen here… Let’s go through it by person.
19 00:02:32.020 ⇒ 00:02:37.949 Amber Lin: Andrew is not here. Do we know if this one’s done? The two pixel IDs?
20 00:02:38.100 ⇒ 00:02:40.409 Amber Lin: I know there was something, Harry, you thought to.
21 00:02:40.410 ⇒ 00:02:44.140 Henry Zhao: Yeah, it’s… it’s done on… it’s done on his end, I just need to check the data’s flowing in.
22 00:02:44.330 ⇒ 00:02:49.199 Henry Zhao: Oh, okay. So, maybe you can actually assign that to me for now. I thought I’ll take a look at that today.
23 00:02:49.200 ⇒ 00:02:49.860 Amber Lin: Okay.
24 00:02:49.860 ⇒ 00:02:51.149 Henry Zhao: Today or tomorrow, actually.
25 00:02:51.930 ⇒ 00:02:53.280 Amber Lin: Alright, awesome.
26 00:02:53.890 ⇒ 00:02:55.090 Amber Lin: …
27 00:02:58.360 ⇒ 00:03:02.249 Amber Lin: Annie, did they get back to you? I saw you sent the…
28 00:03:02.520 ⇒ 00:03:05.729 Amber Lin: No, did they give back saying anything we need to change?
29 00:03:05.730 ⇒ 00:03:10.539 Annie Yu: Cutter said thank you. I think he just wanted to know if that was relevant.
30 00:03:10.540 ⇒ 00:03:11.560 Amber Lin: This is good.
31 00:03:11.970 ⇒ 00:03:13.000 Amber Lin: …
32 00:03:13.310 ⇒ 00:03:21.669 Amber Lin: I assume the one for Danny is done, right? We had some additional requests, and then we finished that. Danny seemed to be happy.
33 00:03:22.270 ⇒ 00:03:31.799 Annie Yu: Yeah, for the Danny’s part, I think he’s happy with that, and yeah, I think Rebecca does have something else, but Danny said, like, don’t change that.
34 00:03:31.800 ⇒ 00:03:34.890 Amber Lin: I know, I… so, so I think this is done.
35 00:03:34.890 ⇒ 00:03:35.459 Annie Yu: So we can.
36 00:03:35.460 ⇒ 00:03:36.489 Amber Lin: or something else for….
37 00:03:36.490 ⇒ 00:03:37.710 Annie Yu: Rebecca, yeah, but….
38 00:03:37.710 ⇒ 00:03:38.070 Amber Lin: Yeah.
39 00:03:38.070 ⇒ 00:03:39.139 Annie Yu: I think partisan.
40 00:03:39.140 ⇒ 00:03:42.949 Amber Lin: They’re talking about the same thing, so I think it’s… it’s…
41 00:03:43.070 ⇒ 00:03:52.730 Amber Lin: we’ll go after what Danny is looking for, because Rebecca is reporting for Danny, so as long as Danny sees what he needs, I think we’re fine.
42 00:03:52.870 ⇒ 00:03:55.359 Amber Lin: I’m gonna close that one.
43 00:03:59.660 ⇒ 00:04:00.470 Amber Lin: Okay.
44 00:04:01.340 ⇒ 00:04:07.240 Amber Lin: At table… okay, this is the one we did. So, close that.
45 00:04:07.820 ⇒ 00:04:13.340 Amber Lin: … Total quarters… Okay, awesome.
46 00:04:13.600 ⇒ 00:04:14.949 Amber Lin: That’s also done.
47 00:04:15.820 ⇒ 00:04:16.800 Amber Lin: Great.
48 00:04:18.459 ⇒ 00:04:23.489 Amber Lin: So, looks like today we have…
49 00:04:24.310 ⇒ 00:04:28.460 Amber Lin: a request from Jonah that I was wondering if you can…
50 00:04:28.620 ⇒ 00:04:38.559 Amber Lin: scope it out. I did go over the requirements. It does look like we do have all of these in different dashboards in different places, so I think he wants a…
51 00:04:39.190 ⇒ 00:04:44.579 Amber Lin: wants to have these pieces in one place so he can make financial decisions. …
52 00:04:46.150 ⇒ 00:04:58.310 Amber Lin: So there’s a actuals dashboard and a forecasting dashboard. We’ll do the actuals first, but I was wondering, Annie, if you can help me scope out, how long these would take, and if there’s any modeling needs that we can get started.
53 00:04:59.140 ⇒ 00:05:05.749 Annie Yu: Okay, and so one question, do I still need to go through his message, or that’s something….
54 00:05:06.570 ⇒ 00:05:14.430 Amber Lin: You can take a look. I… I passed it through AI, I tried to read it. I add… these are quotes.
55 00:05:14.620 ⇒ 00:05:23.559 Amber Lin: From him, so I hope this covers everything. I think once we finish it, we can double-check, like, hey, is there anything that we missed?
56 00:05:24.260 ⇒ 00:05:24.900 Amber Lin: Okay.
57 00:05:25.310 ⇒ 00:05:35.069 Annie Yu: Okay, yeah, because I… yeah, I just imagine if I have to go through his message, that will take a lot of time, but I will trust what you have here.
58 00:05:35.270 ⇒ 00:05:36.500 Amber Lin: Okay, I see.
59 00:05:36.660 ⇒ 00:05:39.960 Amber Lin: I have it broken down by section.
60 00:05:40.450 ⇒ 00:05:44.950 Amber Lin: So, it might be easier, but let me know.
61 00:05:45.120 ⇒ 00:05:45.970 Annie Yu: Okay.
62 00:05:45.970 ⇒ 00:05:54.080 Amber Lin: Yeah, and also, I have a… I booked a placeholder with you to review the Tableau reports. You want to do that
63 00:05:54.290 ⇒ 00:05:59.389 Amber Lin: Do that meeting and sort out the Tableau reports, or do you want to record a loom?
64 00:06:00.250 ⇒ 00:06:02.600 Annie Yu: Wait, can you repeat that again?
65 00:06:02.730 ⇒ 00:06:11.430 Amber Lin: To organize the Tableau reports and folders and archive the old ones, I have a… ….
66 00:06:11.430 ⇒ 00:06:16.879 Annie Yu: I think I’ll record a loom after that’s done, but not during.
67 00:06:18.250 ⇒ 00:06:28.070 Amber Lin: Sure, both works. I think I just want to understand what dashboards are currently existing, so that when people, ask me, I can
68 00:06:28.210 ⇒ 00:06:32.020 Amber Lin: actually respond, oh, hey, I know what this one looks like.
69 00:06:33.650 ⇒ 00:06:39.599 Amber Lin: Yeah, ping me after… Maybe ping me after you’re done organizing it.
70 00:06:40.240 ⇒ 00:06:40.930 Annie Yu: Yeah.
71 00:06:40.930 ⇒ 00:06:41.600 Amber Lin: Okay.
72 00:06:43.470 ⇒ 00:06:44.560 Amber Lin: Alright.
73 00:06:45.620 ⇒ 00:06:51.630 Amber Lin: That’s still blocked. Alright, a wish looking at these…
74 00:06:53.660 ⇒ 00:06:57.469 Amber Lin: I know yesterday, Robert asked to…
75 00:06:57.790 ⇒ 00:07:02.059 Amber Lin: Finish up Jonah’s stuff with him. Can I close them, then?
76 00:07:02.920 ⇒ 00:07:05.180 Awaish Kumar: No, like, it’s, …
77 00:07:05.850 ⇒ 00:07:12.910 Awaish Kumar: it’s not yet, like, completed. Like, I’ve been… I spend most of my time with the, …
78 00:07:13.420 ⇒ 00:07:18.389 Awaish Kumar: like, setting up lots being, with polyatomic, and…
79 00:07:18.790 ⇒ 00:07:23.429 Awaish Kumar: So basically, now we are able to push data to North Beam.
80 00:07:23.540 ⇒ 00:07:36.070 Awaish Kumar: And I created the model needed to push that data, but yeah, but the only thing now is on, like, Hallie to verify that the data we are sending is on the North Beam platform.
81 00:07:36.490 ⇒ 00:07:41.120 Amber Lin: Okay, so this one is not assigned to you now, right?
82 00:07:41.360 ⇒ 00:07:43.729 Amber Lin: Confirm your orders, receiving of data.
83 00:07:43.730 ⇒ 00:07:54.099 Awaish Kumar: Yeah, I’ve been doing that, like, I’ve been trying to figure out if it is there, but yeah, I can’t… I couldn’t find anything, so Henry already submitted a ticket, so I will just assign it to Henry.
84 00:07:54.310 ⇒ 00:07:57.559 Amber Lin: Okay, sounds good. And then….
85 00:07:57.560 ⇒ 00:07:58.349 Awaish Kumar: Which one is done.
86 00:07:58.350 ⇒ 00:08:00.149 Amber Lin: And it’s done.
87 00:08:03.040 ⇒ 00:08:04.010 Amber Lin: Wait.
88 00:08:04.420 ⇒ 00:08:06.690 Awaish Kumar: Model is done, character is done, ….
89 00:08:07.340 ⇒ 00:08:15.280 Awaish Kumar: And then for Jonah, I… I did work on it, so now the ad spend looks the same as in other models.
90 00:08:15.280 ⇒ 00:08:15.770 Amber Lin: Bye.
91 00:08:15.770 ⇒ 00:08:17.760 Awaish Kumar: But there are, like, quite a few…
92 00:08:17.980 ⇒ 00:08:22.230 Awaish Kumar: things here, so I need to… Like, work on others.
93 00:08:22.580 ⇒ 00:08:27.890 Amber Lin: Yeah, I hear you. I think there are a lot of small tasks …
94 00:08:28.340 ⇒ 00:08:32.549 Amber Lin: I can combine them to the same ticket, if that’s helpful.
95 00:08:33.090 ⇒ 00:08:37.120 Amber Lin: But they are, different small things.
96 00:08:37.539 ⇒ 00:08:38.480 Amber Lin: And….
97 00:08:38.480 ⇒ 00:08:42.970 Awaish Kumar: Yeah, I will try to finish it today, but yeah, ….
98 00:08:44.430 ⇒ 00:08:53.280 Amber Lin: Okay, sounds good. There was this one, a quick spike. Are we doing that, or are we…
99 00:08:53.510 ⇒ 00:08:54.329 Amber Lin: Are we.
100 00:08:54.330 ⇒ 00:08:59.650 Awaish Kumar: I’m not sure, like, it’s, … Is there, like, polytro…
101 00:08:59.800 ⇒ 00:09:08.060 Awaish Kumar: I haven’t asked Polytromic, to get If they have any Reddit… ….
102 00:09:10.060 ⇒ 00:09:14.519 Awaish Kumar: add data, but yeah, like, it’s in a spike, I need to figure out what, …
103 00:09:15.590 ⇒ 00:09:22.369 Awaish Kumar: what the… actually, what the ask is, like, the data from Reddit, I don’t know if we might have it already somewhere.
104 00:09:24.740 ⇒ 00:09:26.590 Amber Lin: I see. And then, ….
105 00:09:28.070 ⇒ 00:09:34.010 Awaish Kumar: Push it. If, like, if we have some data somewhere, we can use the existing connector to push it.
106 00:09:34.030 ⇒ 00:09:36.969 Amber Lin: Okay. To the, yeah, so I just have to….
107 00:09:37.120 ⇒ 00:09:38.180 Awaish Kumar: spike on.
108 00:09:38.460 ⇒ 00:09:54.229 Amber Lin: Okay, the architecture diagram, I heard, I think from yesterday, I remember you’ve already started. I know that some part is updated, some part is not. I put a placeholder today, but I think you can just ping me when you’re done.
109 00:09:54.230 ⇒ 00:09:57.460 Awaish Kumar: I can actually loom, basically, on the outside. Oh, that would be awesome.
110 00:09:57.460 ⇒ 00:09:58.080 Amber Lin: hospital.
111 00:09:58.580 ⇒ 00:10:05.249 Awaish Kumar: Because, yeah, right now, as I mentioned in my… in Manager’s Slack channel that, yeah.
112 00:10:05.450 ⇒ 00:10:05.890 Amber Lin: Okay.
113 00:10:05.890 ⇒ 00:10:13.320 Awaish Kumar: I might be dead offline sometime, so I will create a room whenever I’m ready, I will share it with the team.
114 00:10:13.320 ⇒ 00:10:18.139 Amber Lin: That’s awesome. Great. … And then…
115 00:10:18.550 ⇒ 00:10:23.319 Amber Lin: So I’m a lot of the… on your side, that’s bought by Basque.
116 00:10:23.490 ⇒ 00:10:29.790 Amber Lin: I saw that Basque got back to us, but I don’t really know what they’re talking about.
117 00:10:30.850 ⇒ 00:10:37.400 Demilade Agboola: Long story short, he thinks we have data, and I’ve pointed out we don’t have the data, and he has not responded.
118 00:10:37.740 ⇒ 00:10:51.399 Demilade Agboola: But you can, if you go through, he’s telling us the webhooks that have that data, and I pointed out that the webhooks that he’s pointed me to, I sent the documentation, it doesn’t have that data. He also said anything about the North Pharmacies.
119 00:10:52.190 ⇒ 00:10:55.899 Demilade Agboola: So, that’s also another problem that he has not addressed.
120 00:10:56.300 ⇒ 00:10:59.390 Amber Lin: I, I read it. I know, we’re blocked.
121 00:10:59.450 ⇒ 00:11:00.560 Demilade Agboola: ….
122 00:11:01.560 ⇒ 00:11:04.110 Amber Lin: This one….
123 00:11:04.330 ⇒ 00:11:06.350 Demilade Agboola: I’m currently working on it.
124 00:11:06.350 ⇒ 00:11:07.000 Amber Lin: Oh, I see.
125 00:11:07.000 ⇒ 00:11:11.969 Demilade Agboola: analyzed it, but I will… I should finish that today. I will finish that today.
126 00:11:12.260 ⇒ 00:11:12.900 Amber Lin: Okay.
127 00:11:13.150 ⇒ 00:11:17.090 Amber Lin: I think… That one.
128 00:11:18.070 ⇒ 00:11:20.580 Amber Lin: Include, exclude channels.
129 00:11:22.300 ⇒ 00:11:24.120 Demilade Agboola: ….
130 00:11:24.120 ⇒ 00:11:31.730 Amber Lin: I don’t think it’s high priority. Like, we wish… do you want Demlade’s help on the Jonah tickets?
131 00:11:33.240 ⇒ 00:11:38.980 Amber Lin: Or… how do you guys want to distribute tasks between you guys?
132 00:11:39.170 ⇒ 00:11:42.410 Awaish Kumar: Yeah, and I guess just the same model, …
133 00:11:42.770 ⇒ 00:11:46.629 Awaish Kumar: So, like, we can’t distribute it, basically, because….
134 00:11:46.630 ⇒ 00:11:47.260 Amber Lin: seed.
135 00:11:47.660 ⇒ 00:11:52.209 Awaish Kumar: It just depends on… the things are on top of each other, so, like, yeah.
136 00:11:52.890 ⇒ 00:11:57.290 Awaish Kumar: and help each other, but yeah, we can… Okay. Yep.
137 00:11:57.590 ⇒ 00:11:58.900 Amber Lin: I hear you. Okay.
138 00:11:59.260 ⇒ 00:12:03.790 Amber Lin: Henry, on your… Late.
139 00:12:04.000 ⇒ 00:12:06.520 Amber Lin: What can be closed? What’s going on?
140 00:12:06.860 ⇒ 00:12:10.799 Henry Zhao: Yeah, so I’m working on the urgent one, which is fixed treatment check-in workflow.
141 00:12:11.410 ⇒ 00:12:15.760 Henry Zhao: Reduce overage costs, I’m gonna sync with Robert on that today, …
142 00:12:16.430 ⇒ 00:12:21.960 Henry Zhao: After that, I’m gonna sync with probably the Eden leadership tomorrow, and probably get that closed.
143 00:12:23.500 ⇒ 00:12:27.220 Henry Zhao: And then I’m also today working on confirming Northbeam is receiving the data.
144 00:12:29.600 ⇒ 00:12:32.360 Henry Zhao: And then the other ones, I think, are for later on.
145 00:12:32.850 ⇒ 00:12:34.040 Amber Lin: Yeah, okay.
146 00:12:34.040 ⇒ 00:12:38.849 Henry Zhao: Yeah, I’m also starting to do initial research on that last one, which is send webhook to CIO every time Zendesk.
147 00:12:39.160 ⇒ 00:12:47.240 Henry Zhao: has a ticket opened, but Awash, I was just curious if, Awash, you were able to help me with the webhooks? Were you the ones to set up the Basque webhooks?
148 00:12:49.150 ⇒ 00:12:54.119 Awaish Kumar: No, like, Basque… implements the webhook. We just connect it.
149 00:12:54.220 ⇒ 00:12:59.660 Awaish Kumar: Which segment, and that was someone in the agents team who set up the segment stuff.
150 00:12:59.850 ⇒ 00:13:03.440 Henry Zhao: Oh, okay, so I’ll check with Robert to see how we can get that webhook ready.
151 00:13:03.440 ⇒ 00:13:07.160 Awaish Kumar: But, I think, like, it’s…
152 00:13:07.580 ⇒ 00:13:12.899 Awaish Kumar: like, if you need my help, I can figure it out, how to add the…
153 00:13:14.760 ⇒ 00:13:18.070 Awaish Kumar: The… the book, like, the connection and the….
154 00:13:18.440 ⇒ 00:13:18.970 Henry Zhao: Yeah.
155 00:13:18.970 ⇒ 00:13:27.480 Awaish Kumar: Like, it’s basically reverse ETL to CIO, right? It’s not a webhook, it’s basically the Zendesk data.
156 00:13:28.060 ⇒ 00:13:38.739 Awaish Kumar: What I understand from the task is that there is some resentless data coming in in our warehouse. We just need to figure out when a ticket is created.
157 00:13:38.740 ⇒ 00:13:48.259 Awaish Kumar: get the data in the format the CIO wants, like, in the format that we want to push to CIO, and then just send…
158 00:13:48.440 ⇒ 00:13:54.279 Awaish Kumar: just send the request as you send for, like, other CIO reverse CTL tickets.
159 00:13:54.280 ⇒ 00:14:03.410 Henry Zhao: Another way we could do it, Awash, is to send this data to BigQuery, and then we can write a… we can add it to your customer enriched profiles, where if they have a ticket open.
160 00:14:03.740 ⇒ 00:14:04.580 Henry Zhao: data field.
161 00:14:05.830 ⇒ 00:14:11.250 Awaish Kumar: That’s what I’m saying. So, we already have Zendesk data in the warehouse, Right?
162 00:14:11.250 ⇒ 00:14:11.770 Henry Zhao: Oh, great.
163 00:14:11.770 ⇒ 00:14:14.089 Awaish Kumar: What we need to figure out is that
164 00:14:14.420 ⇒ 00:14:16.769 Awaish Kumar: What fields do you need?
165 00:14:17.070 ⇒ 00:14:22.320 Awaish Kumar: to push… to push it to, like, CIO, right?
166 00:14:22.980 ⇒ 00:14:29.239 Awaish Kumar: If you need count of tickets created, count of active tickets created, whatever it is.
167 00:14:29.460 ⇒ 00:14:38.690 Awaish Kumar: And we can put it in the same model, and you can push it, and if you want, we can put… create a new model, and then you can reverse ETL tools, there you go.
168 00:14:38.690 ⇒ 00:14:43.120 Henry Zhao: Okay, just give me the table where this data is, and I will take a look. It might be pretty easy, then.
169 00:14:43.120 ⇒ 00:14:46.949 Awaish Kumar: Yeah, you can search Zendesk, right, in the BigQuery.
170 00:14:46.950 ⇒ 00:14:48.820 Henry Zhao: Okay, good. Good to know. Alright, thanks.
171 00:14:50.130 ⇒ 00:14:50.860 Amber Lin: Okay.
172 00:14:51.400 ⇒ 00:14:55.010 Amber Lin: … Alright.
173 00:14:56.070 ⇒ 00:15:03.070 Amber Lin: … I think, since Vashdelev is not here, we was just wondering how we can…
174 00:15:04.620 ⇒ 00:15:07.969 Amber Lin: Okay, we’ll wait for him to come back to connect those.
175 00:15:08.630 ⇒ 00:15:09.860 Amber Lin: …
176 00:15:12.860 ⇒ 00:15:14.620 Amber Lin: That’s blocked.
177 00:15:16.250 ⇒ 00:15:17.360 Amber Lin: Right.
178 00:15:17.990 ⇒ 00:15:25.549 Amber Lin: Is there… Anything here? Because this one’s… Annie, is this still needed?
179 00:15:30.700 ⇒ 00:15:32.070 Annie Yu: …
180 00:15:34.050 ⇒ 00:15:45.229 Annie Yu: So… I would think so, because they are… when they talk about, like, less than 3 days, they pointed out they want that to be based on business days.
181 00:15:45.250 ⇒ 00:15:48.680 Amber Lin: I can’t filter out the weekend.
182 00:15:49.180 ⇒ 00:15:51.169 Annie Yu: Correctly in Tableau.
183 00:15:51.450 ⇒ 00:15:56.249 Annie Yu: So I’m using just calendar day-based 3 days now.
184 00:15:56.430 ⇒ 00:16:01.099 Amber Lin: Okay, gotcha. Denali, is this something you can take?
185 00:16:04.350 ⇒ 00:16:10.750 Demilade Agboola: … So, we need to change it from, like, regular days to business. Yeah, I could take this.
186 00:16:11.280 ⇒ 00:16:12.060 Amber Lin: Okay.
187 00:16:12.500 ⇒ 00:16:16.720 Demilade Agboola: But, like, how does this rank in priorities with my early existing tasks?
188 00:16:16.930 ⇒ 00:16:19.500 Amber Lin: Let me go check right now.
189 00:16:22.470 ⇒ 00:16:23.500 Amber Lin: Alright.
190 00:16:24.060 ⇒ 00:16:26.830 Amber Lin: I think prioritize…
191 00:16:27.390 ⇒ 00:16:44.870 Amber Lin: Yeah, bad stuff, investigate… I think you do investigation, and then the task for Danny. I think the one for Josh is medium priority, based on what he said. Okay. Yeah, so I will just say this one for…
192 00:16:45.000 ⇒ 00:16:48.529 Amber Lin: Tomorrow. So we want to close off the Danny task.
193 00:16:48.660 ⇒ 00:16:53.580 Amber Lin: As soon as we can, and Varsha’s not back until… Later.
194 00:16:54.620 ⇒ 00:16:55.859 Demilade Agboola: Okay, sounds good.
195 00:16:55.860 ⇒ 00:16:56.410 Amber Lin: Yeah.
196 00:16:57.430 ⇒ 00:17:00.830 Amber Lin: Showing up finance dashboard.
197 00:17:03.000 ⇒ 00:17:07.420 Amber Lin: Wow. I wish this is something… is this something that you were also looking at?
198 00:17:09.180 ⇒ 00:17:09.930 Amber Lin: Or….
199 00:17:09.930 ⇒ 00:17:11.250 Awaish Kumar: Oh, nope, nope.
200 00:17:11.400 ⇒ 00:17:11.849 Amber Lin: Okay.
201 00:17:11.859 ⇒ 00:17:13.419 Awaish Kumar: 10 different cup.
202 00:17:13.609 ⇒ 00:17:18.669 Amber Lin: I see. Annie, is this something very critical, or can it wait for a little bit?
203 00:17:21.920 ⇒ 00:17:24.309 Annie Yu: Did I create this?
204 00:17:25.560 ⇒ 00:17:36.789 Amber Lin: This is the modeling needs for the finest dashboard for Jonah, which we closed the Finest Dashboard ticket, but I think we had something on the page channel spend table.
205 00:17:37.660 ⇒ 00:17:42.860 Annie Yu: Wait, I thought this one was for me, for the dashboard side, which should be done.
206 00:17:42.860 ⇒ 00:17:44.050 Amber Lin: Oh, I see.
207 00:17:45.170 ⇒ 00:17:46.040 Amber Lin: Okay.
208 00:17:49.170 ⇒ 00:17:50.150 Amber Lin: Great.
209 00:17:51.570 ⇒ 00:17:59.400 Amber Lin: Okay, okay. So when Vashtag comes back, there’s the affiliate, Items… And that…
210 00:18:01.400 ⇒ 00:18:08.059 Amber Lin: Is this something that we’re still doing? Have we… Looked into this….
211 00:18:12.460 ⇒ 00:18:16.790 Henry Zhao: Yeah, I signed it to Vash, because Awash, that’s what you told me to do, but are you able to work on that?
212 00:18:17.500 ⇒ 00:18:20.020 Henry Zhao: I don’t think this is high priority, because I found out….
213 00:18:20.020 ⇒ 00:18:20.440 Awaish Kumar: Bye.
214 00:18:20.440 ⇒ 00:18:20.960 Henry Zhao: way to….
215 00:18:20.960 ⇒ 00:18:22.039 Awaish Kumar: What a commercial.
216 00:18:22.670 ⇒ 00:18:28.229 Awaish Kumar: Yeah, I asked a question of this ticket, right? Do we want to throw it, right? I…
217 00:18:28.930 ⇒ 00:18:31.190 Awaish Kumar: I, I informed.
218 00:18:31.190 ⇒ 00:18:32.199 Henry Zhao: Alright, take care.
219 00:18:32.200 ⇒ 00:18:34.640 Awaish Kumar: that, … this…
220 00:18:35.460 ⇒ 00:18:55.240 Awaish Kumar: Basically, right now, we are using the combination of keys to find out those user profiles, right? So, do you want it to be just on a user ID and email, or just the email, or how we want it to be? You mentioned that you are going to confirm that with Robert.
221 00:18:55.340 ⇒ 00:18:56.900 Awaish Kumar: So, did you confirm?
222 00:18:59.600 ⇒ 00:19:01.300 Henry Zhao: Yeah, let me talk to him again today.
223 00:19:02.370 ⇒ 00:19:17.920 Amber Lin: Okay. One la- I think last thing here, I know there was a thread, Henry, between you and Josh. Is this part of any other ticket? I just created it because I don’t want to miss it, but is this ticket needed?
224 00:19:21.020 ⇒ 00:19:23.150 Henry Zhao: … Attention.
225 00:19:24.550 ⇒ 00:19:26.710 Henry Zhao: I think this is a duplicate.
226 00:19:26.940 ⇒ 00:19:27.610 Amber Lin: Okay.
227 00:19:27.990 ⇒ 00:19:31.969 Amber Lin: Which ticket is this a part of, the treatment?
228 00:19:31.970 ⇒ 00:19:33.680 Henry Zhao: Urgent one, yeah,
229 00:19:33.680 ⇒ 00:19:34.960 Amber Lin: Okay, awesome.
230 00:19:35.430 ⇒ 00:19:36.550 Amber Lin: Alright.
231 00:19:36.650 ⇒ 00:19:40.509 Amber Lin: I think… a wish… can I…
232 00:19:41.680 ⇒ 00:19:46.259 Amber Lin: Can we maybe stay over for the next 10 minutes to talk about the COGS?
233 00:19:46.900 ⇒ 00:19:47.900 Awaish Kumar: Okay, yep.
234 00:19:48.170 ⇒ 00:19:51.539 Amber Lin: Okay, everybody, thank you for joining Stand Up.
235 00:19:52.660 ⇒ 00:19:53.980 Demilade Agboola: Alright, thank you.
236 00:19:53.980 ⇒ 00:19:55.030 Amber Lin: Alright, thanks.
237 00:19:55.030 ⇒ 00:19:55.999 Henry Zhao: Thank you, guys.
238 00:19:59.440 ⇒ 00:20:07.959 Amber Lin: Okay. How can I… best create tickets so I can ping people and then move things along.
239 00:20:08.950 ⇒ 00:20:17.810 Awaish Kumar: Yeah, so… Two… I created two tickets. They are mail… these are mainly the placeholders. …
240 00:20:18.010 ⇒ 00:20:22.420 Awaish Kumar: for the future improvements, what I want
241 00:20:22.570 ⇒ 00:20:26.570 Awaish Kumar: From… like, this… these… the tickets followed…
242 00:20:26.710 ⇒ 00:20:38.010 Awaish Kumar: like, the subtasks we are going to create there, they are for Demelade. So, for the future improvements, what I need from, basically, Demolade and Notion document.
243 00:20:38.130 ⇒ 00:20:44.000 Awaish Kumar: Which basically says we need this data as part of which table? For example.
244 00:20:44.480 ⇒ 00:20:48.790 Awaish Kumar: For example, order data. For example, when an order is placed.
245 00:20:49.320 ⇒ 00:20:50.540 Amber Lin: ….
246 00:20:50.540 ⇒ 00:21:03.569 Awaish Kumar: Oh, and, like, with a confirmed… confirmed order is placed, and when we get this data, should we get these… this information, like, vial sizes and, …
247 00:21:04.200 ⇒ 00:21:06.970 Awaish Kumar: Whatever is shipped as part of the order.
248 00:21:08.170 ⇒ 00:21:09.010 Amber Lin: And this is….
249 00:21:09.010 ⇒ 00:21:17.880 Awaish Kumar: part of that Notion doc or not. So, basically, it will be kind of a… creating a Notion doc, which basically has the table schema.
250 00:21:18.020 ⇒ 00:21:22.710 Awaish Kumar: Right? Which will say, like, I need,
251 00:21:22.930 ⇒ 00:21:34.990 Awaish Kumar: orders data, along with these fields, right? And the description for each field, like, what this means. It can be anything. I just mentioned order data as an example, but
252 00:21:35.110 ⇒ 00:21:41.560 Awaish Kumar: like, whatever… He thinks it should be part of okay.
253 00:21:42.290 ⇒ 00:21:42.650 Amber Lin: I’m long.
254 00:21:42.650 ⇒ 00:21:43.830 Awaish Kumar: I think that one.
255 00:21:43.830 ⇒ 00:21:44.470 Amber Lin: cake.
256 00:21:44.470 ⇒ 00:21:47.299 Awaish Kumar: It should take maybe an hour.
257 00:21:47.710 ⇒ 00:21:50.669 Amber Lin: Okay. And then he’s sending this to Basque.
258 00:21:52.170 ⇒ 00:21:58.569 Awaish Kumar: No, it’s… so basically, we are, like, what I understand from Robert’s communication.
259 00:21:58.670 ⇒ 00:22:06.209 Awaish Kumar: is that, like, Basque is slow, we can share it with the Basque, but… We are not, …
260 00:22:07.040 ⇒ 00:22:13.230 Awaish Kumar: concerned about that. We want this to be created for EMR, basically.
261 00:22:13.430 ⇒ 00:22:19.230 Awaish Kumar: So that we can share it with the EMR team, and they… the data we get from EMR.
262 00:22:19.430 ⇒ 00:22:19.890 Amber Lin: Whoa.
263 00:22:19.890 ⇒ 00:22:23.769 Awaish Kumar: Good enough, because, … that’s going to be the feature.
264 00:22:24.150 ⇒ 00:22:25.690 Amber Lin: Got it.
265 00:22:25.690 ⇒ 00:22:26.470 Awaish Kumar: Yep.
266 00:22:26.870 ⇒ 00:22:29.290 Amber Lin: Alright, so that’s the first one.
267 00:22:29.410 ⇒ 00:22:31.410 Amber Lin: What’s next?
268 00:22:33.410 ⇒ 00:22:37.799 Awaish Kumar: Yeah, and for the Basque, like, we already have a ticket, which is, ….
269 00:22:38.290 ⇒ 00:22:46.110 Awaish Kumar: I’m getting the wild cycin and all from Basque, and, like, that’s stuck, so that’s already part of it.
270 00:22:46.110 ⇒ 00:22:46.970 Amber Lin: Okay.
271 00:22:46.970 ⇒ 00:22:48.390 Awaish Kumar: We don’t need… yeah.
272 00:22:48.910 ⇒ 00:22:50.620 Amber Lin: And then, snapshot model.
273 00:22:50.620 ⇒ 00:22:51.609 Awaish Kumar: Jen, what?
274 00:22:51.750 ⇒ 00:22:59.040 Awaish Kumar: Yeah, then one is creating a snapshot model based on a… say, we have a COGS sheet, Right?
275 00:22:59.220 ⇒ 00:23:08.139 Awaish Kumar: And, yeah, we have a cog sheet, and we have the cogs there, so any… every… anytime someone comes in.
276 00:23:08.330 ⇒ 00:23:16.439 Awaish Kumar: and updates the cogs, we should be able to capture it, because we… and the way to capture it is that, like, we have…
277 00:23:16.510 ⇒ 00:23:31.040 Awaish Kumar: that version of sheet in our warehouse, like, every day we have a new snapshot of that Google Sheet, so that any change made at any time will be captured, and that’s what we need.
278 00:23:32.260 ⇒ 00:23:37.630 Amber Lin: Okay, awesome. And how long would this one take? So, one point, or….
279 00:23:37.660 ⇒ 00:23:40.400 Awaish Kumar: It can be… 3….
280 00:23:40.470 ⇒ 00:23:41.680 Amber Lin: Okay. Tiage.
281 00:23:42.200 ⇒ 00:23:47.180 Amber Lin: Oh, 3 hours. That would be… I’ll say… 2.
282 00:23:47.640 ⇒ 00:23:48.440 Amber Lin: Okay.
283 00:23:52.780 ⇒ 00:23:53.540 Amber Lin: Alright.
284 00:23:53.540 ⇒ 00:23:54.760 Awaish Kumar: So, meals.
285 00:23:55.500 ⇒ 00:23:57.850 Awaish Kumar: And then, we have, …
286 00:23:58.110 ⇒ 00:24:05.960 Awaish Kumar: Yeah, this is a bit more difficult. So I want all the ad hoc requests which come in for COGS to just go in there.
287 00:24:06.210 ⇒ 00:24:08.070 Amber Lin: Like, I wanna be only….
288 00:24:08.360 ⇒ 00:24:22.430 Awaish Kumar: So, all COGS-related investigations or tasks that Emilada is working on, because he’s working on a lot of manual things, for example. Like, he showed me a sheet which, basically, from
289 00:24:22.770 ⇒ 00:24:27.550 Awaish Kumar: some input from Jonah, he, or Rebec, Rebecca.
290 00:24:27.620 ⇒ 00:24:44.340 Awaish Kumar: He tries to figure out things and builds a Google Sheet, which is really very manual exercise, and it takes time to do that, so it just goes in. So the reason why I have this ticket is
291 00:24:44.510 ⇒ 00:24:48.770 Awaish Kumar: We have… we should put all the investigation tickets.
292 00:24:48.770 ⇒ 00:24:49.920 Amber Lin: in there.
293 00:24:50.010 ⇒ 00:25:00.440 Awaish Kumar: so that we have, the, the last, like, the… like, the efforts we spend on COGS-related manual, manual tasks.
294 00:25:00.440 ⇒ 00:25:00.960 Amber Lin: Oh, boy.
295 00:25:00.960 ⇒ 00:25:07.100 Awaish Kumar: You can easily see, like, how much hours we spent on this, and we can easily share that with the.
296 00:25:07.100 ⇒ 00:25:07.470 Amber Lin: Okay.
297 00:25:07.470 ⇒ 00:25:13.489 Awaish Kumar: That if they don’t, like, push for more automated solutions, then.
298 00:25:13.490 ⇒ 00:25:13.930 Amber Lin: Go.
299 00:25:13.930 ⇒ 00:25:19.430 Awaish Kumar: It’s going to be manual, and it’s going to take time, and it will delay other
300 00:25:19.580 ⇒ 00:25:21.980 Awaish Kumar: Tickets, which are in pipeline.
301 00:25:22.150 ⇒ 00:25:31.149 Amber Lin: I see. Are any of these… oh, … These tickets still valid.
302 00:25:40.190 ⇒ 00:25:44.270 Amber Lin: Like, are there still duplicate cogs?
303 00:25:45.070 ⇒ 00:25:46.759 Amber Lin: Who we need to handle.
304 00:25:51.830 ⇒ 00:25:52.810 Awaish Kumar: Alright, study?
305 00:25:53.040 ⇒ 00:25:56.989 Amber Lin: Are there still duplicate cogs that we need to handle?
306 00:25:58.660 ⇒ 00:26:01.220 Awaish Kumar: Yeah, that Google Sheet basically have…
307 00:26:01.730 ⇒ 00:26:10.299 Awaish Kumar: I have some, duplicates, but it should be handled as part of this new model, snapshot model, right?
308 00:26:10.300 ⇒ 00:26:11.050 Amber Lin: Okay.
309 00:26:11.390 ⇒ 00:26:29.139 Awaish Kumar: So right now, directly use this sheet, and it goes everywhere in downstream models. Now, with the snapshot model, what will be happening is that we have a model which gets updated data from Google Sheet and updates itself if there are new changes.
310 00:26:29.300 ⇒ 00:26:34.350 Awaish Kumar: And then, basically, that goes, into the downstream models.
311 00:26:34.350 ⇒ 00:26:39.429 Amber Lin: I see, so that’s a duplicate, the COGS model, granular fields, fields, right?
312 00:26:40.470 ⇒ 00:26:42.620 Amber Lin: So I’ll say that’s a duplicate.
313 00:26:43.400 ⇒ 00:26:51.000 Amber Lin: And then… Same thing, right? I’m just gonna… Copy this.
314 00:26:51.530 ⇒ 00:26:55.619 Amber Lin: And then… Added to the model.
315 00:26:56.070 ⇒ 00:26:56.970 Amber Lin: Ticket.
316 00:26:58.420 ⇒ 00:26:59.500 Amber Lin: ….
317 00:27:01.180 ⇒ 00:27:02.730 Awaish Kumar: And in the chat….
318 00:27:02.730 ⇒ 00:27:03.290 Amber Lin: Explorer.
319 00:27:03.290 ⇒ 00:27:06.949 Awaish Kumar: In the chat, I also… share a doc… Notion doc.
320 00:27:07.060 ⇒ 00:27:10.130 Awaish Kumar: At the bottom of it, you will see a list of tickets.
321 00:27:11.040 ⇒ 00:27:14.640 Awaish Kumar: We also need to create those tickets as well.
322 00:27:15.060 ⇒ 00:27:19.959 Amber Lin: Wait, trying to see… Okay, Notion Doc….
323 00:27:21.170 ⇒ 00:27:25.870 Awaish Kumar: Oh, not this… in the… this… it was just an upgrade for…
324 00:27:26.090 ⇒ 00:27:31.309 Awaish Kumar: It’s not related to just COGS, but in the Zoom meeting chat.
325 00:27:31.660 ⇒ 00:27:38.309 Awaish Kumar: I shared a Notion… link of a Notion document, and at the bottom of it, there’s a list of, …
326 00:27:39.250 ⇒ 00:27:40.450 Awaish Kumar: tasks.
327 00:27:40.990 ⇒ 00:27:44.330 Amber Lin: Oh… ….
328 00:27:44.520 ⇒ 00:27:46.100 Awaish Kumar: So….
329 00:27:46.100 ⇒ 00:27:46.640 Amber Lin: Am I looking.
330 00:27:46.640 ⇒ 00:27:47.230 Awaish Kumar: Yeah.
331 00:27:47.230 ⇒ 00:27:48.299 Amber Lin: I think about a plane.
332 00:27:48.300 ⇒ 00:27:56.009 Awaish Kumar: So all the… so all the objectives are, like, high level, we want to achieve, but these… all these well-liners are basically the task.
333 00:27:56.170 ⇒ 00:27:58.090 Amber Lin: Aha.
334 00:27:58.730 ⇒ 00:28:07.219 Amber Lin: So… ad hoc requests… Current task, awesome, okay.
335 00:28:07.340 ⇒ 00:28:08.800 Amber Lin: the…
336 00:28:12.970 ⇒ 00:28:13.790 Amber Lin: Okay.
337 00:28:14.170 ⇒ 00:28:20.350 Amber Lin: I think only these are related to… this one, essentially, is related to COGS.
338 00:28:20.870 ⇒ 00:28:23.830 Amber Lin: These are the elite ones, how….
339 00:28:23.830 ⇒ 00:28:32.269 Awaish Kumar: We wanted to optimize our efforts on all the ad hocs. So, COGS stickers come as ad hoc.
340 00:28:32.380 ⇒ 00:28:45.069 Awaish Kumar: And there are some other improvements, like, on the product side, we get escalations. So we wanted to optimize the ad hoc plus escalations, and as part of discussion, we got some of these tickets here.
341 00:28:45.070 ⇒ 00:28:47.740 Amber Lin: Gotcha, okay. …
342 00:28:51.730 ⇒ 00:28:53.529 Amber Lin: I’ll just add it here.
343 00:28:54.680 ⇒ 00:28:57.310 Amber Lin: Alright.
344 00:28:57.590 ⇒ 00:29:08.860 Amber Lin: Okay, so… I’m just gonna cancel this main… Ticket…
345 00:29:13.030 ⇒ 00:29:13.690 Amber Lin: Shit.
346 00:29:18.170 ⇒ 00:29:21.740 Amber Lin: Is this something that we’re gonna do this cycle?
347 00:29:24.220 ⇒ 00:29:25.650 Amber Lin: Not that one.
348 00:29:26.880 ⇒ 00:29:27.680 Awaish Kumar: Which one?
349 00:29:28.750 ⇒ 00:29:32.930 Amber Lin: the Notion doc and the snapshot model.
350 00:29:36.080 ⇒ 00:29:37.010 Amber Lin: Wow.
351 00:29:37.490 ⇒ 00:29:41.169 Awaish Kumar: Yeah, Notion Doc we can have… have in the cycle.
352 00:29:41.530 ⇒ 00:29:42.140 Amber Lin: Huh.
353 00:29:42.140 ⇒ 00:29:45.570 Awaish Kumar: Snapshot model can also be in this
354 00:29:46.900 ⇒ 00:29:52.350 Awaish Kumar: Cycle, if we have availability, like, not… not… this is not an urgent… urgent task, but….
355 00:29:52.350 ⇒ 00:29:53.050 Amber Lin: Okay.
356 00:29:53.400 ⇒ 00:29:53.950 Amber Lin: So….
357 00:29:53.950 ⇒ 00:29:56.769 Awaish Kumar: Oh, yeah. This can be assigned to us.
358 00:29:57.120 ⇒ 00:29:58.319 Amber Lin: Oh, okay.
359 00:29:58.800 ⇒ 00:30:02.060 Awaish Kumar: A snapshot model, he can build as well, if….
360 00:30:02.060 ⇒ 00:30:03.920 Amber Lin: Gotcha. Okay.
361 00:30:04.030 ⇒ 00:30:08.980 Amber Lin: Priority on this one, the Notion doc, is it high or a medium?
362 00:30:11.190 ⇒ 00:30:13.910 Awaish Kumar: I can buy high, you can say hi.
363 00:30:15.050 ⇒ 00:30:17.619 Amber Lin: And then I’ll say the snapshot is medium.
364 00:30:18.020 ⇒ 00:30:18.950 Awaish Kumar: Alright.
365 00:30:18.950 ⇒ 00:30:20.810 Amber Lin: Great. …
366 00:30:22.200 ⇒ 00:30:29.940 Amber Lin: Thank you, that was productive. And then, do you want me to create tickets for these, or do I… should I just keep it in mind? Okay, I’ll make tickets for them then.
367 00:30:30.580 ⇒ 00:30:31.650 Amber Lin: Alright.
368 00:30:32.290 ⇒ 00:30:35.490 Awaish Kumar: We want tickets, and then we can, like, again….
369 00:30:36.500 ⇒ 00:30:37.859 Amber Lin: I see. Oh, cool.
370 00:30:40.100 ⇒ 00:30:45.289 Amber Lin: I can put some in our internal tasks and put some in our tech depth, …
371 00:30:45.820 ⇒ 00:30:48.950 Amber Lin: Yeah, I’ll put it there, and then we can discuss.
372 00:30:50.010 ⇒ 00:30:50.750 Awaish Kumar: Okay.
373 00:30:50.750 ⇒ 00:30:52.159 Amber Lin: Alright, thank you so much.
374 00:30:52.570 ⇒ 00:30:53.280 Awaish Kumar: Thank you.
375 00:30:53.460 ⇒ 00:30:54.529 Amber Lin: Alright, bye!