Meeting Title: US x BF | Standup Date: 2025-06-25 Meeting participants: Amber Lin, Caio Velasco, Demilade Agboola, Emily Giant
WEBVTT
1 00:00:08.940 ⇒ 00:00:10.030 Amber Lin: Hi.
2 00:00:16.780 ⇒ 00:00:18.990 Caio Velasco: I am a high end with Speaker.
3 00:00:20.900 ⇒ 00:00:22.060 Amber Lin: That’d be fine.
4 00:00:23.600 ⇒ 00:00:25.570 Caio Velasco: Okay.
5 00:00:33.990 ⇒ 00:00:39.675 Amber Lin: I’m not sure I I thought I heard 2 people. Never mind.
6 00:00:41.720 ⇒ 00:00:49.419 Amber Lin: Oh, Kyle, I saw that you sent something in the chat about the Heavo and stitch tables.
7 00:00:51.130 ⇒ 00:00:52.080 Caio Velasco: About? What.
8 00:00:52.867 ⇒ 00:00:56.599 Amber Lin: About the hevo and stitch tables that we turned off. I’m not sure.
9 00:00:56.970 ⇒ 00:00:57.340 Caio Velasco: Yes.
10 00:00:57.340 ⇒ 00:00:59.729 Amber Lin: Letter today. I haven’t read it fully yet.
11 00:01:00.902 ⇒ 00:01:08.519 Caio Velasco: Okay, no. I just mentioned, because I remember today that we turned off a few pipelines almost 2 weeks ago, and
12 00:01:09.070 ⇒ 00:01:15.520 Caio Velasco: then we were. I remember Utah saying about something about, we should wait a week or so
13 00:01:16.360 ⇒ 00:01:20.460 Caio Velasco: to see if every if anyone complains right after we we shut them down.
14 00:01:20.927 ⇒ 00:01:25.089 Caio Velasco: Yeah. So I don’t know like what would be next, like the next procedure.
15 00:01:26.410 ⇒ 00:01:27.799 Amber Lin: I see I see.
16 00:01:29.530 ⇒ 00:01:30.360 Amber Lin: Hmm!
17 00:01:32.180 ⇒ 00:01:50.439 Amber Lin: I was thinking that we could also cause there’s a few that we marked as tentative. Right? Do you think we’re close to arriving at a decision for those 2, we could wait until everything is decently deprecated, and then we could just turn everything off together.
18 00:01:52.480 ⇒ 00:02:01.459 Caio Velasco: Which ones. But I think we have final finalized the the ingestion ones from evil and stitch. Basically.
19 00:02:01.770 ⇒ 00:02:03.570 Caio Velasco: I don’t remember anything pending.
20 00:02:08.350 ⇒ 00:02:10.390 Amber Lin: See if I share my screen.
21 00:02:13.300 ⇒ 00:02:23.419 Amber Lin: So I was looking at current cycle and for redshift.
22 00:02:24.079 ⇒ 00:02:29.810 Amber Lin: There’s this one of the tentative, the ones that we have tentative decisions on.
23 00:02:33.370 ⇒ 00:02:36.440 Caio Velasco: Unconventional complication. Decision.
24 00:02:37.261 ⇒ 00:02:41.628 Caio Velasco: I’m not sure exactly. What is this about, because it can be so many things.
25 00:02:42.280 ⇒ 00:02:50.839 Caio Velasco: maybe this is after the the rules for dashboard deprecation are done.
26 00:02:51.020 ⇒ 00:02:57.099 Caio Velasco: since they are also pointing to the Bt models that are also pointing to metric tables.
27 00:02:57.380 ⇒ 00:02:58.160 Caio Velasco: Maybe.
28 00:02:58.160 ⇒ 00:03:20.379 Amber Lin: I I believe this is something. I believe this is something during the initial deprecation frowned, that we still have certain things that we weren’t too sure upon. I do have a different ticket for the dashboard, related one. So I believe this is related to the original ones. That we didn’t finish deprecating. Is that still the case?
29 00:03:21.846 ⇒ 00:03:26.363 Caio Velasco: Not sure, because at least we when we started with the ingestion
30 00:03:27.706 ⇒ 00:03:36.050 Caio Velasco: sheet there were that sheet had all, all pipelines from all 3 sources, like.
31 00:03:36.630 ⇒ 00:03:49.919 Caio Velasco: And then we finalize it amber. And I’m not sorry, Emily and Alex. And then we should. Decision made the email. The email was sent.
32 00:03:49.920 ⇒ 00:03:54.639 Amber Lin: Okay, okay? So it’s nothing is still tentative. Right?
33 00:03:55.570 ⇒ 00:03:56.160 Caio Velasco: I don’t think so.
34 00:03:56.160 ⇒ 00:03:59.540 Amber Lin: Far from the okay. Sounds good. I’m gonna say
35 00:03:59.940 ⇒ 00:04:02.860 Amber Lin: it’s canceled. I’ll move the other.
36 00:04:02.860 ⇒ 00:04:12.009 Caio Velasco: Because one thing, and then just to add, because since it was written ratches, because those things were the pipelines from the ingestion tools. But we might.
37 00:04:12.010 ⇒ 00:04:12.580 Amber Lin: Also have.
38 00:04:12.580 ⇒ 00:04:19.760 Caio Velasco: Other things in the redshift as well, and would be kind of like a second layer. But it’s not
39 00:04:20.529 ⇒ 00:04:26.310 Caio Velasco: directly related to ingestion, because the ingestion tools were were deprecated. Already.
40 00:04:31.120 ⇒ 00:04:31.690 Caio Velasco: Yeah.
41 00:04:32.180 ⇒ 00:04:36.820 Amber Lin: So I’ll keep this. I’ll keep this ticket. I don’t know if it’s 3 story points.
42 00:04:37.020 ⇒ 00:04:43.239 Amber Lin: I don’t. It is it gonna be 3 story points is gonna be 1 point, because we just turn, we just drop it off.
43 00:04:44.450 ⇒ 00:04:51.850 Caio Velasco: The ones related to those that were off. Maybe that could be something easy to do. I believe.
44 00:04:52.210 ⇒ 00:04:52.900 Amber Lin: Okay.
45 00:04:53.460 ⇒ 00:04:54.270 Caio Velasco: Yes.
46 00:05:04.400 ⇒ 00:05:11.010 Amber Lin: Aim for that Thursday. I can make a note Thursday to also confirm
47 00:05:12.850 ⇒ 00:05:16.249 Amber Lin: also confirm if there’s any ingestion tables.
48 00:05:19.800 ⇒ 00:05:23.480 Amber Lin: and then, after the meeting, we can probably turn the rest off.
49 00:05:24.590 ⇒ 00:05:32.770 Amber Lin: Okay, anything that you guys started that I should move from to do to in progress?
50 00:05:34.190 ⇒ 00:05:37.869 Amber Lin: Or can you guys take a moment and update the tickets.
51 00:05:39.340 ⇒ 00:05:46.470 Caio Velasco: So, at least on my end. I think I marked in progress the the explorers and views one.
52 00:05:46.470 ⇒ 00:05:46.890 Amber Lin: Oh!
53 00:05:46.890 ⇒ 00:05:47.469 Caio Velasco: Can I mark it?
54 00:05:47.470 ⇒ 00:05:47.800 Amber Lin: Awesome.
55 00:05:47.800 ⇒ 00:05:51.590 Caio Velasco: And the which one.
56 00:05:51.590 ⇒ 00:05:52.320 Amber Lin: Oh, it’s not showing.
57 00:05:52.320 ⇒ 00:05:53.030 Caio Velasco: The unused.
58 00:05:53.030 ⇒ 00:05:53.530 Amber Lin: It’s.
59 00:05:53.530 ⇒ 00:05:54.164 Caio Velasco: Yeah.
60 00:05:54.800 ⇒ 00:05:55.710 Amber Lin: Yeah.
61 00:05:57.180 ⇒ 00:05:58.050 Amber Lin: Oh, I see.
62 00:05:58.050 ⇒ 00:05:58.810 Caio Velasco: I don’t know.
63 00:05:59.160 ⇒ 00:06:06.630 Caio Velasco: Yeah, the number one yet, because well, we already did this when Emily did the
64 00:06:07.010 ⇒ 00:06:09.819 Caio Velasco: the the Yes or no, for the for the.
65 00:06:09.820 ⇒ 00:06:10.140 Amber Lin: Yeah.
66 00:06:10.140 ⇒ 00:06:10.730 Caio Velasco: I see.
67 00:06:10.730 ⇒ 00:06:11.120 Amber Lin: I see.
68 00:06:11.120 ⇒ 00:06:11.950 Caio Velasco: Can’t go see the day.
69 00:06:11.950 ⇒ 00:06:12.450 Amber Lin: Good night.
70 00:06:12.450 ⇒ 00:06:13.480 Caio Velasco: Usage? Yeah.
71 00:06:13.480 ⇒ 00:06:16.850 Amber Lin: I see? I can move this.
72 00:06:17.720 ⇒ 00:06:19.630 Amber Lin: Okay, sounds good.
73 00:06:22.850 ⇒ 00:06:26.900 Amber Lin: We move this to the previous cycle. Actually.
74 00:06:26.900 ⇒ 00:06:27.240 Caio Velasco: Yep.
75 00:06:28.810 ⇒ 00:06:30.640 Amber Lin: And then let’s look at this.
76 00:06:33.000 ⇒ 00:06:33.930 Amber Lin: Okay,
77 00:06:37.300 ⇒ 00:06:41.720 Amber Lin: So we’re doing. You’re doing the views. And then.
78 00:06:43.250 ⇒ 00:06:48.110 Amber Lin: has Emily been able to complete? Oh, Hi, Emily.
79 00:06:48.310 ⇒ 00:06:49.160 Emily Giant: Hi.
80 00:06:49.160 ⇒ 00:06:53.300 Amber Lin: I was just talking about you new hairstyle today. I like it.
81 00:06:53.300 ⇒ 00:06:55.439 Emily Giant: Just my, it’s a comb over. It’s.
82 00:06:56.330 ⇒ 00:06:57.790 Amber Lin: Falling in the wrong spot.
83 00:06:58.180 ⇒ 00:07:01.220 Emily Giant: Also everybody for you today. This is the not cat.
84 00:07:01.220 ⇒ 00:07:02.360 Amber Lin: Are we done?
85 00:07:02.670 ⇒ 00:07:04.140 Amber Lin: Could you say.
86 00:07:04.140 ⇒ 00:07:06.509 Emily Giant: He’s scrunchy. He’s my bulldog.
87 00:07:06.680 ⇒ 00:07:08.790 Emily Giant: He’s got a really cute nose.
88 00:07:09.220 ⇒ 00:07:10.050 Amber Lin: Oh!
89 00:07:10.050 ⇒ 00:07:15.950 Emily Giant: Everybody no complete note, but I’m actively working on it. I detailed out most of the problem.
90 00:07:16.110 ⇒ 00:07:20.326 Emily Giant: So I started with the big ones, so that, like the rest, I could buzz through.
91 00:07:20.830 ⇒ 00:07:25.829 Emily Giant: But I the revenue based models are almost done.
92 00:07:26.230 ⇒ 00:07:26.780 Amber Lin: Oh!
93 00:07:27.050 ⇒ 00:07:39.759 Emily Giant: And then I’m adding examples to a Google sheet that’s like that we’re using during our working session. So I’m trying to like really crush it with these revenue models so that everyone feels powered I also was able.
94 00:07:39.760 ⇒ 00:07:41.010 Amber Lin: I see.
95 00:07:41.010 ⇒ 00:07:48.560 Emily Giant: All of those fixes yesterday that were like blocking me from being productive, contributing society, and
96 00:07:49.090 ⇒ 00:07:53.930 Emily Giant: so far so good. So so I should be able to finish that today.
97 00:07:53.930 ⇒ 00:08:06.000 Amber Lin: Okay, can I help by breaking this ticket down? I know I just kept it as as such, but I think it would be makes more sense if I break it down, how is the best way to break it down?
98 00:08:06.000 ⇒ 00:08:09.650 Emily Giant: I think we should break it down by like the mark that we’re focusing on.
99 00:08:09.650 ⇒ 00:08:12.640 Amber Lin: Okay, so we’re done with inventory.
100 00:08:16.360 ⇒ 00:08:17.460 Amber Lin: And.
101 00:08:17.780 ⇒ 00:08:18.840 Emily Giant: So then revenue.
102 00:08:21.140 ⇒ 00:08:22.560 Amber Lin: Then.
103 00:08:24.630 ⇒ 00:08:27.660 Emily Giant: I forget mark care Ops.
104 00:08:27.660 ⇒ 00:08:28.770 Amber Lin: Customer, care.
105 00:08:30.250 ⇒ 00:08:31.000 Emily Giant: Yes.
106 00:08:39.710 ⇒ 00:08:44.369 Amber Lin: Is this really by March, or sorry you were saying.
107 00:08:45.620 ⇒ 00:08:59.257 Emily Giant: There are a ton of marketing models like the Google ads and Facebook and stuff that I like don’t know a ton about. I would bump that up above customer care because I worked on customer care for 2 years, so I can do those with my eyes closed.
108 00:09:00.850 ⇒ 00:09:06.436 Emily Giant: Also, we’re migrating to a new customer service platform. So it’s all gonna change
109 00:09:07.070 ⇒ 00:09:11.059 Emily Giant: like next week we’re migrating to a new customer care platform. So.
110 00:09:12.177 ⇒ 00:09:18.769 Emily Giant: There’s a lot of unknowns and super knowns. But yeah, marketing is gonna be like that lingering
111 00:09:21.470 ⇒ 00:09:22.450 Amber Lin: I see.
112 00:09:22.710 ⇒ 00:09:23.050 Emily Giant: But yeah.
113 00:09:23.050 ⇒ 00:09:23.800 Amber Lin: Oh, yeah.
114 00:09:23.800 ⇒ 00:09:26.900 Emily Giant: Revenue done today. They’re almost.
115 00:09:26.900 ⇒ 00:09:27.560 Amber Lin: Oh, okay.
116 00:09:27.560 ⇒ 00:09:28.030 Emily Giant: Okay.
117 00:09:28.030 ⇒ 00:09:36.280 Amber Lin: Okay. Sounds good I was thinking about is is the march by March segmentation. The best way to go, because just based on my
118 00:09:36.650 ⇒ 00:09:44.130 Amber Lin: very little impression of the different marks we have. I thought they were based on the sources, and not really by mart.
119 00:09:45.050 ⇒ 00:09:48.899 Amber Lin: Would it be easier if we segmented by that source.
120 00:09:50.860 ⇒ 00:10:07.739 Amber Lin: So like, if I just remember, say, there’s not really a specific inventory mark, there’s only things that kind of lead to inventory. So I wasn’t sure if this would be the easiest segmentation for you, because you have to jump between different sources.
121 00:10:07.740 ⇒ 00:10:08.710 Emily Giant: So
122 00:10:11.130 ⇒ 00:10:22.900 Emily Giant: I don’t know. Like to me. They’re also intermingled, because, like the postgres tables and the Hebo tables all join dimensions in an intermediate table, and then they join with polytomic. So
123 00:10:23.370 ⇒ 00:10:27.599 Emily Giant: in my head, like thinking about it like a mart, is
124 00:10:27.760 ⇒ 00:10:32.390 Emily Giant: probably the most cohesive strategy, since they all are joined together already.
125 00:10:33.290 ⇒ 00:10:34.190 Amber Lin: Okay.
126 00:10:34.190 ⇒ 00:10:39.160 Emily Giant: Some are legacy, some are inner like in between, and some are like current day.
127 00:10:41.900 ⇒ 00:10:44.079 Emily Giant: But I do. I’m trying to like.
128 00:10:44.190 ⇒ 00:10:48.939 Emily Giant: Consider what you’re saying, because I have to like get out of my own
129 00:10:49.130 ⇒ 00:10:52.939 Emily Giant: way with how I’m thinking about it to make sure it’s the best way.
130 00:10:54.170 ⇒ 00:10:58.410 Amber Lin: Any any comments from Dum Lade. I’m also not the best person to comment.
131 00:11:01.450 ⇒ 00:11:04.700 Demilade Agboola: Let me see, is this this
132 00:11:07.320 ⇒ 00:11:11.139 Demilade Agboola: Just quick question. How far along are we with this, like how many models are left.
133 00:11:11.460 ⇒ 00:11:12.139 Emily Giant: Let me!
134 00:11:12.700 ⇒ 00:11:18.700 Demilade Agboola: Percentage wise doesn’t have to be like accurate 20%, 30%.
135 00:11:22.770 ⇒ 00:11:24.230 Emily Giant: Let me unfilter here.
136 00:11:34.150 ⇒ 00:11:42.780 Emily Giant: it’s all like quickbooks junk, and then intermediate and staging inventory models from polytomic, which
137 00:11:43.230 ⇒ 00:11:45.342 Emily Giant: those are all accurate.
138 00:11:47.530 ⇒ 00:11:54.070 Emily Giant: so yeah, like on its face, there’s a lot left. But most of them are like Google sheets.
139 00:11:55.050 ⇒ 00:11:55.780 Amber Lin: Oh!
140 00:11:57.030 ⇒ 00:12:01.509 Demilade Agboola: Hmm, so, and also like the goal sheets don’t necessarily.
141 00:12:01.900 ⇒ 00:12:03.650 Demilade Agboola: So the Google sheets.
142 00:12:07.040 ⇒ 00:12:17.590 Demilade Agboola: I’m not sure how, how, where you will be of like the Google sheets, though cause like at the end of the day, it’s like people doing certain things on certain ends. And I’m not sure if you necessarily use all that?
143 00:12:18.010 ⇒ 00:12:37.170 Demilade Agboola: So what I would say is, we should probably try and like, categorize them like what’s left into like maybe 3 or 4 different spaces that we can have. Like the Google sheets, we can have the polytomic stuff. I think the stuff we can. We can just basically mark them as like good and then potentially
144 00:12:37.340 ⇒ 00:12:57.590 Demilade Agboola: any other like sources. I think sources might be one of the fastest way to tackle it, because, especially when you know, some sources are fine. We can like knock that out. The park. Google sheets might be a bit Dicey, because then you have to go through the stakeholders, and maybe figure out like what exactly is going on there. Who updates it? When last year updated things like that.
145 00:12:59.181 ⇒ 00:13:08.140 Demilade Agboola: So that might be a bit slower. But I think without the Google sheets, we can start to action like some of the other parts of it.
146 00:13:11.370 ⇒ 00:13:17.909 Emily Giant: Yeah. So in business unit column a would like
147 00:13:18.690 ⇒ 00:13:23.169 Emily Giant: if I put like revenue affecting or inventory affecting.
148 00:13:23.280 ⇒ 00:13:25.789 Emily Giant: would that help clarify? Kind of what
149 00:13:26.200 ⇒ 00:13:30.810 Emily Giant: the processes I’m trying to think of a good way to like, communicate my
150 00:13:31.160 ⇒ 00:13:34.089 Emily Giant: flow of work, or rather to like, have y’all
151 00:13:34.400 ⇒ 00:13:38.149 Emily Giant: give input on what the work order should be.
152 00:13:40.024 ⇒ 00:13:48.209 Demilade Agboola: Sure like, if the things are. If there are things that inventory affecting like, I think we can mark them higher, like we can mark.
153 00:13:48.430 ⇒ 00:13:51.870 Demilade Agboola: because, like inventory and revenue are things we’re working on.
154 00:13:52.370 ⇒ 00:13:55.880 Demilade Agboola: At least work right in the next couple of sprints.
155 00:13:56.400 ⇒ 00:14:05.369 Demilade Agboola: But ideally, I think the important thing is, we just want to have a sense of like what is fine right now, and what isn’t fine right now.
156 00:14:07.070 ⇒ 00:14:12.869 Demilade Agboola: And that allows us to have some headway in like, what what things need to change and what things are
157 00:14:12.980 ⇒ 00:14:23.249 Demilade Agboola: static. So things like, if it’s a 3, and it’s like, it’s a 3 in importance. And it’s like reliability. Over 7.
158 00:14:23.470 ⇒ 00:14:25.700 Demilade Agboola: We can start to go like, okay.
159 00:14:26.210 ⇒ 00:14:31.510 Demilade Agboola: do we need to change the sources like, do we need to like just effectively move things around?
160 00:14:32.026 ⇒ 00:14:49.120 Demilade Agboola: And if it’s like a 1, for instance, it’s very important. And the reliability is 4 by 7. That’s also like high priority, like things we can flesh out. What does the effect if it’s that important? And the reliability is that low, like, for instance, the component Xf, I can see right there.
161 00:14:49.580 ⇒ 00:14:52.840 Emily Giant: Which is like Row 14. Right now. It’s.
162 00:14:52.940 ⇒ 00:15:05.493 Demilade Agboola: One. It’s used for the executive summary dashboard, but it has a reliability of 10 which is worrisome, so like those sort of things, allow us to be able to like quickly, go to like the most important and most impactful
163 00:15:05.800 ⇒ 00:15:06.310 Emily Giant: Yes.
164 00:15:06.680 ⇒ 00:15:13.320 Demilade Agboola: Things in here, so I I don’t want it to be like, I don’t want it to take so long that we lose sight of that
165 00:15:13.690 ⇒ 00:15:38.610 Demilade Agboola: right? Like, ultimately, if it’s a 9 or a 10, it’s still unreliable. Like, I, I just want us to get in that scope of like, okay, this is a, this is a 5, right? Whether it’s a 5 or a 6 or a 4 like ultimately doesn’t matter that much. We just want to get a scope of like? Is it 10 in unreliability? Is it a an 8? Is it a 5? Is it a 2 in reliability where we know it’s very reliable.
166 00:15:39.100 ⇒ 00:15:41.740 Demilade Agboola: So I I guess the idea is like
167 00:15:43.940 ⇒ 00:15:53.560 Demilade Agboola: we just want to be able to have like a high view of things and just be able to categorize the models and go like, okay, we have our matrix. And we can say, this is very important.
168 00:15:53.850 ⇒ 00:16:02.989 Demilade Agboola: Oh, this is not as important, and this is unreliable. This is as reliable. And we can start to talk about that and how to action and move forward, based off that.
169 00:16:03.190 ⇒ 00:16:05.180 Emily Giant: Okay, so
170 00:16:05.680 ⇒ 00:16:25.470 Emily Giant: I on that note like components. Xf, that was the model that I deployed all fixes on yesterday. So it was 10. It was not functioning at all now it is, but it still doesn’t take into account like the problems that were happening right after the migration, which is like anytime. There’s a forced upgrade on a kit.
171 00:16:25.963 ⇒ 00:16:39.060 Emily Giant: It doesn’t recognize that that item has been canceled and is counting an item that was never sent against revenue. But that’s 1 problem, whereas, like 15 were fixed, so are we calling that an 8
172 00:16:39.170 ⇒ 00:16:41.260 Emily Giant: are we calling that like a 5?
173 00:16:42.380 ⇒ 00:16:45.850 Emily Giant: It’s hard to rank. It’s a very important model.
174 00:16:46.690 ⇒ 00:16:52.939 Demilade Agboola: Yeah. So it’s a very important model. And I think because of the level of importance. If we cannot
175 00:16:54.020 ⇒ 00:17:18.090 Demilade Agboola: confidently say what our revenue is, I think we should lean slightly higher, like I mean ballpark. But obviously, if we cannot see, this is our exact revenue with 100% confidence, I think we might want to lean slightly higher because of the importance of that model. Because we want model, we want to get in in like everything should be fine, right?
176 00:17:18.710 ⇒ 00:17:28.309 Emily Giant: Yeah, that’s what I’ve been doing. So I’m glad we’re on the same page there, like, if it’s critical, I’m marking it high, even if there’s only like 2 things broken with it.
177 00:17:28.750 ⇒ 00:17:36.049 Emily Giant: But those are the things that people will create a new ticket for every day. Because it like disrupts forecasting.
178 00:17:37.460 ⇒ 00:17:48.429 Demilade Agboola: Okay, sounds good. I I just I just wanna be able to get on the same page and at least knock this out. The Park. I think you know, we can actually love great things off this document.
179 00:17:48.740 ⇒ 00:18:00.830 Emily Giant: Yeah, I added a ton of notes. Kyle, the notes that I said I would send to you about components xf, and that whole lineage. I’ve added it to this
180 00:18:01.180 ⇒ 00:18:08.889 Emily Giant: in the models that it references just so that it’s all like in one place. But I’m trying to like really flush out
181 00:18:09.050 ⇒ 00:18:13.120 Emily Giant: the problem models here so that we’ve we’ve got it down.
182 00:18:14.060 ⇒ 00:18:30.490 Caio Velasco: No problem. Thank you. Just quick. Last thing about the last, about the discussion. Bear in mind that the last column, the accurate column. It’s considering this idea of 3 and 7. So if anything, it’s within the thing, we will be with a yes
183 00:18:30.670 ⇒ 00:18:32.380 Caio Velasco: or sorry we don’t know.
184 00:18:33.042 ⇒ 00:18:36.000 Caio Velasco: Or yes, yeah, yes, cause it’s
185 00:18:36.300 ⇒ 00:18:43.858 Caio Velasco: gonna be marked as accurate. So just bearing that that in mind. That’s why we want at the end of the day just to have a 1st day of yeah.
186 00:18:44.110 ⇒ 00:18:55.219 Emily Giant: I was. I was like just toggling back and forth between things, to watch when it would change, because I was being lazy and not looking at the formula. But I was like, what what’s going on? Okay, that makes sense.
187 00:18:57.267 ⇒ 00:19:03.290 Amber Lin: So should I break this down by source, or break it down by marked? What was the conclusion here.
188 00:19:03.630 ⇒ 00:19:05.160 Emily Giant: I want y’all to make the call.
189 00:19:05.690 ⇒ 00:19:07.809 Amber Lin: Because oftentimes I’m stuck in my own way.
190 00:19:08.240 ⇒ 00:19:10.130 Emily Giant: I don’t need to be stuck in my own place.
191 00:19:12.370 ⇒ 00:19:13.120 Emily Giant: Demo, out of your.
192 00:19:13.120 ⇒ 00:19:14.272 Amber Lin: Brother, you’re on mute.
193 00:19:16.770 ⇒ 00:19:28.370 Demilade Agboola: My bad. I’ll I’ll see, I think, for the written it depends like certain sources. We can knock them all off the park in one go so polytomic, we know like that, that like, we can just mark them as reliable
194 00:19:28.480 ⇒ 00:19:33.549 Demilade Agboola: models, and important as well, like
195 00:19:33.920 ⇒ 00:20:01.709 Demilade Agboola: Google, sheets that might vary, depending on the different like sheets. Some might be good, some might be bad, so I think that would require that for certain, like business domains. Again. You might have to go in there. And just I think it’s going to be a mix right? I think being able to like so certain things like revenue, you know, like, okay, let me just go to the revenue models. You can see them and go. Actually, no, these ones are faulty. These ones are good, and these are all important. So like
196 00:20:01.720 ⇒ 00:20:09.220 Demilade Agboola: potentially all the revenue models you can just go. All of them are important because I mean revenue is an important field, so the importance is one.
197 00:20:09.300 ⇒ 00:20:23.979 Demilade Agboola: But for reliability. So you know, this from experience, is, you know, very reliable. So 2. This from experience is very unreliable. So it’s an 8. You know that that way, I think a combination basically will be will be.
198 00:20:24.360 ⇒ 00:20:35.470 Amber Lin: I see. So to take it in ways can I put? Can we put something here? Say, if it’s about revenue? Can we also add a drop down, that this is revenue or inventory.
199 00:20:36.860 ⇒ 00:20:39.120 Emily Giant: I was adding that to business unit.
200 00:20:39.410 ⇒ 00:20:42.780 Emily Giant: But if we want a different column for that.
201 00:20:43.110 ⇒ 00:20:45.480 Amber Lin: Yeah, I think we can add it to business unit
202 00:20:45.600 ⇒ 00:20:54.330 Amber Lin: that will make that will make the next step for revenue also a lot easier, but that will. That won’t be the main focus.
203 00:20:56.680 ⇒ 00:20:57.390 Emily Giant: Okay.
204 00:21:00.920 ⇒ 00:21:07.260 Demilade Agboola: Also just an idea of like how we will be looking at things. So if it’s between like
205 00:21:07.670 ⇒ 00:21:15.480 Demilade Agboola: like one, if it’s a model importance of one, and it’s like the reliability is under 5. I think
206 00:21:15.670 ⇒ 00:21:17.290 Demilade Agboola: we’ll be fine.
207 00:21:17.760 ⇒ 00:21:19.869 Demilade Agboola: It will be like push further back.
208 00:21:20.390 ⇒ 00:21:31.320 Demilade Agboola: But if it’s actually no, if it’s like a 3 importance of 3. So it’s not very important, and the reliability on the 5, it will be pushed way back like those are the last things we’ll ever try and look at, because they’re not that important.
209 00:21:31.860 ⇒ 00:21:36.589 Demilade Agboola: and they’re fairly accurate. But things that I won
210 00:21:36.710 ⇒ 00:21:42.900 Demilade Agboola: and have a reliability of over 7. Those are like high priority things we need to look into just because
211 00:21:43.290 ⇒ 00:21:45.140 Demilade Agboola: these are very important models.
212 00:21:45.640 ⇒ 00:21:56.649 Demilade Agboola: and that, you know, they’re very inaccurate things are like a 2 or a 3, and also above 7. We need to now start asking questions. Do we need to replace things? Do we need to like
213 00:21:56.780 ⇒ 00:22:02.580 Demilade Agboola: like what? Exactly. But obviously the most important things for us will be things that are a 1
214 00:22:03.070 ⇒ 00:22:09.229 Demilade Agboola: and have your liability higher than a 7 equals to higher than a 7.
215 00:22:09.570 ⇒ 00:22:17.690 Demilade Agboola: So at that point, we just know that like, okay, if this is very important, but it’s unreliable. We we definitely need to have that on our our map.
216 00:22:17.850 ⇒ 00:22:18.670 Demilade Agboola: So.
217 00:22:20.850 ⇒ 00:22:21.390 Emily Giant: Cool.
218 00:22:22.260 ⇒ 00:22:26.750 Amber Lin: Would this? Would this be helpful in a session together.
219 00:22:28.330 ⇒ 00:22:29.969 Emily Giant: I don’t think so. It it
220 00:22:30.380 ⇒ 00:22:33.448 Emily Giant: it just needs to be knocked out by me.
221 00:22:34.390 ⇒ 00:22:35.770 Emily Giant: And having
222 00:22:36.180 ⇒ 00:22:43.179 Emily Giant: this kind of restructured way of finishing it. I think I’ll be able to do it faster. It’s it’s.
223 00:22:43.610 ⇒ 00:22:46.459 Emily Giant: I guess. How much time do you want me to take
224 00:22:46.910 ⇒ 00:23:01.380 Emily Giant: for the more complicated issues. Building out the examples and making sure you have points of reference. Because I think that’s what’s also taking a long time is that I’m trying to like back up the descriptions with visuals and like examples that you can query
225 00:23:02.510 ⇒ 00:23:03.589 Emily Giant: things like that.
226 00:23:04.330 ⇒ 00:23:09.360 Amber Lin: In my not engineering. Mind, if it’s not accurate, doesn’t matter if we have.
227 00:23:09.360 ⇒ 00:23:09.930 Emily Giant: Oh, yeah.
228 00:23:12.270 ⇒ 00:23:14.360 Amber Lin: But devil, and he has something to say.
229 00:23:14.530 ⇒ 00:23:17.197 Demilade Agboola: I was looking to see, can we? Can we get the rating?
230 00:23:18.420 ⇒ 00:23:21.739 Demilade Agboola: done? At least that allows us to create like a
231 00:23:22.020 ⇒ 00:23:43.440 Demilade Agboola: a roadmap and go like, okay, these are the models that seem to be high priority. These are low priority, and these are mid priority. And then it’s easier to now flesh that out because we cannot working sessions where we can go. Okay? So you see, these models are high priority models. Because they are of importance. And they are like, you know.
232 00:23:43.660 ⇒ 00:23:49.259 Demilade Agboola: you have low reliability. How can we like what are the issues? And we can kind of flesh that out
233 00:23:49.880 ⇒ 00:23:53.649 Demilade Agboola: once we have that fleshed out, it’s easier for us to then work
234 00:23:53.800 ⇒ 00:24:14.349 Demilade Agboola: and get the results back to you and go. Okay. So we’ve been testing this models. We think this models are like in a much better state. Now, can you help us test and just validate those tests? But I I don’t want us to get like so bogged down by trying to do everything in one step that we don’t actually make any like huge progress, or we’re stuck on on one step.
235 00:24:14.500 ⇒ 00:24:20.970 Emily Giant: Yeah, that’s a good point. I’ll leave the comments out for now and just do the rating and the business unit.
236 00:24:20.970 ⇒ 00:24:21.550 Amber Lin: No.
237 00:24:21.550 ⇒ 00:24:26.660 Emily Giant: And then that will make it go fast. It’s the comments that’s killing the progress.
238 00:24:27.900 ⇒ 00:24:38.839 Demilade Agboola: I mean, if there’s like easy comments, you can make sure. But like, if it’s you need to like, start going in and trying to find this, and like find some documentation from here and a snippet of code from there.
239 00:24:40.900 ⇒ 00:24:48.959 Demilade Agboola: potentially, those are kind of things that we will, because you could be doing that for a model that might be if a model of importance. 3.
240 00:24:49.100 ⇒ 00:24:51.010 Demilade Agboola: Right? So it’s not the most important
241 00:24:51.860 ⇒ 00:24:58.429 Demilade Agboola: liability might be 5. So we’re not necessarily going to look at it right now. It will be further like further down the line. So
242 00:24:58.880 ⇒ 00:25:04.460 Demilade Agboola: we I want us to get to a spot where we know the models that we want to like hone in on, and then
243 00:25:04.670 ⇒ 00:25:07.400 Demilade Agboola: start doing that level of like details.
244 00:25:08.040 ⇒ 00:25:10.080 Emily Giant: Cool. All right. That will make it go a lot faster.
245 00:25:10.200 ⇒ 00:25:12.009 Amber Lin: A lot faster
246 00:25:13.170 ⇒ 00:25:13.870 Caio Velasco: With this.
247 00:25:13.870 ⇒ 00:25:14.570 Amber Lin: Be.
248 00:25:14.570 ⇒ 00:25:22.649 Caio Velasco: Let’s say also to this, just because for me and this I’m looking at the models. Yes, but for me now, this is how I would
249 00:25:23.160 ⇒ 00:25:25.389 Caio Velasco: let’s say, backfill to
250 00:25:26.240 ⇒ 00:25:36.419 Caio Velasco: to the dashboard deprecations. So that’s for me. I for me what matters is like what is not important here, and what is not accurate, they’ll bring it back to the dashboards to flag that.
251 00:25:36.980 ⇒ 00:25:39.379 Caio Velasco: So that’s it. Just so that we don’t forget.
252 00:25:40.820 ⇒ 00:25:44.880 Amber Lin: Yeah, would would it be possible to have this
253 00:25:45.110 ⇒ 00:26:08.489 Amber Lin: done by sometime today so that Kyle has time to cause? We want to present to the stakeholders what is not accurate tomorrow? So I know it’s a little bit short on time, but hopefully, if we have it all ranked, Kyle can do like a spreadsheet manipulation, and we can probably see what dashboards are not so accurate.
254 00:26:08.820 ⇒ 00:26:12.399 Emily Giant: Yes, if I’m not doing the comments, I can have this done in an hour.
255 00:26:12.400 ⇒ 00:26:14.130 Amber Lin: Okay, that will be awesome.
256 00:26:14.130 ⇒ 00:26:14.780 Emily Giant: Okay.
257 00:26:15.910 ⇒ 00:26:25.290 Emily Giant: cool. And then I can. I’ll go back and start adding, like, where I have a lot of context, the one thing that I don’t know a lot about is like the Facebook and Bing stuff.
258 00:26:25.470 ⇒ 00:26:28.359 Emily Giant: and I don’t know how to read that.
259 00:26:28.900 ⇒ 00:26:33.480 Emily Giant: because I just have never had tickets that
260 00:26:34.270 ⇒ 00:26:40.200 Emily Giant: are associated with those models. So I’m guessing they’re fine, but like, I don’t know if that’s true.
261 00:26:41.040 ⇒ 00:26:46.070 Amber Lin: I see we can put like 5, and then we’ll go look into them, and we can always re-rank them.
262 00:26:46.070 ⇒ 00:26:49.740 Amber Lin: Yeah, I definitely wouldn’t prioritize them. But I, yeah.
263 00:26:49.890 ⇒ 00:26:50.440 Emily Giant: Okay.
264 00:26:50.950 ⇒ 00:26:55.750 Amber Lin: Sounds good. Yeah.
265 00:26:56.590 ⇒ 00:27:03.799 Amber Lin: Looking at these, I know Demo. You’ll be working on inventory. And then for Kyle, I know it’s
266 00:27:05.450 ⇒ 00:27:12.749 Amber Lin: waiting. I think these these 2 oh, I see.
267 00:27:13.280 ⇒ 00:27:22.700 Caio Velasco: Yeah, I’m working on the used explores. I already added another sheet. And then I’m gonna be adding another one. So a lot of sheet, yeah.
268 00:27:23.080 ⇒ 00:27:24.810 Caio Velasco: awesome. Okay.
269 00:27:25.450 ⇒ 00:27:39.080 Amber Lin: Okay, yeah. And then we also have a ticket for you to define the revenue march scaffolding us, how we want to the structure how we want to rebuild them. I think that will be a very a great ticket for you to handle.
270 00:27:40.290 ⇒ 00:27:40.950 Caio Velasco: Okay.
271 00:27:42.070 ⇒ 00:27:49.560 Amber Lin: Okay, thanks. Everybody. Tomorrow meeting. Hopefully, we have all the dashboards ratings done.
272 00:27:49.870 ⇒ 00:27:54.029 Emily Giant: Yeah, alright, I’ll ping everyone in the Channel when I’m done with the Google sheet.
273 00:27:54.480 ⇒ 00:27:55.140 Caio Velasco: Okay.
274 00:27:55.140 ⇒ 00:27:55.760 Emily Giant: And in the ticket.
275 00:27:55.760 ⇒ 00:27:57.470 Emily Giant: Okay, alright, thank you.
276 00:27:57.833 ⇒ 00:27:58.559 Caio Velasco: Thank you.
277 00:27:58.830 ⇒ 00:27:59.840 Amber Lin: Bye, bye.