Meeting Title: USxBF | Inventory Meeting Date: 2025-07-03 Meeting participants: Felipefaria, Emily Giant, Demilade Agboola, Amber Lin
WEBVTT
1 00:00:20.090 ⇒ 00:00:21.240 Amber Lin: Hi.
2 00:00:22.950 ⇒ 00:00:24.120 Emily Giant: Hello!
3 00:00:24.120 ⇒ 00:00:32.579 Amber Lin: So we have Felipe and Jesse that will be joining, so let’s wait for them. Oh, Hi! Felipe!
4 00:00:34.170 ⇒ 00:00:38.249 felipefaria: Hello! Sorry I was having some issues with the zoom here.
5 00:00:39.050 ⇒ 00:00:39.820 Amber Lin: I’m good.
6 00:00:39.820 ⇒ 00:00:43.840 Emily Giant: You have a like a funny short week. Is this your only day?
7 00:00:44.480 ⇒ 00:00:46.190 Amber Lin: Yeah, basically yeah.
8 00:00:47.920 ⇒ 00:00:53.559 felipefaria: Yeah, I came back just because of a meeting that I had to to present something so.
9 00:00:53.820 ⇒ 00:00:54.340 Amber Lin: Oh!
10 00:00:54.340 ⇒ 00:00:55.080 Emily Giant: Gosh! Well.
11 00:00:55.080 ⇒ 00:00:56.640 Amber Lin: Oh, I appreciate you coming to the
12 00:00:56.640 ⇒ 00:01:05.979 Amber Lin: yeah, no worries. Yeah. It’s probably gonna be. I don’t know if everybody accepted right, because there’s some people out of office.
13 00:01:05.980 ⇒ 00:01:09.349 Amber Lin: Perry and Pk. Are out of office.
14 00:01:09.500 ⇒ 00:01:10.290 felipefaria: Yeah.
15 00:01:10.850 ⇒ 00:01:14.409 Amber Lin: But I mean, you guys are the the most important ones.
16 00:01:17.490 ⇒ 00:01:26.060 Amber Lin: So quickly. I’ll run through the agenda today, and then I’ll let them. Lotte and Emily lead. So we want to. 1st
17 00:01:26.300 ⇒ 00:01:38.429 Amber Lin: give you guys a view on the progress that what what we’re actually doing and how that’s gonna affect you. And we’re gonna we want to gather any feedback on how you actually want to see the data, any adjustment we should make.
18 00:01:38.600 ⇒ 00:01:43.149 Amber Lin: The second most important thing I want to get is the top
19 00:01:43.230 ⇒ 00:02:09.199 Amber Lin: dashboards and analysis is that your you guys are using that’s impacted by inventory. And we want to. After we gather this, we want to work with you guys together to see how we can best rebuild them and how we can support you in that process using the new inventory marks. So we will be by your side. As we rebuild those analysis as well.
20 00:02:10.620 ⇒ 00:02:11.769 felipefaria: Sounds good.
21 00:02:11.770 ⇒ 00:02:19.119 Amber Lin: Yeah. So I’ll hand up to demalade and Emily to update you guys on how the progress is and what it looks like.
22 00:02:23.910 ⇒ 00:02:24.500 Emily Giant: Paint.
23 00:02:24.660 ⇒ 00:02:30.844 Demilade Agboola: Hmm, okay. So we’ve been able to build up models that allow us to be able to calculate the
24 00:02:31.795 ⇒ 00:02:36.590 Demilade Agboola: the numbers for each of the. Let me share my screen.
25 00:02:37.210 ⇒ 00:02:40.350 Demilade Agboola: The the numbers for each of the lot. Ids.
26 00:02:41.030 ⇒ 00:02:44.430 Demilade Agboola: so I’m using the query we looked at earlier today.
27 00:02:45.780 ⇒ 00:02:47.100 Demilade Agboola: So for this.
28 00:02:47.630 ⇒ 00:03:06.090 Demilade Agboola: But these lot ids. We have the quantity sold, the subscription quantity, the delivery quantity, the sale, spoilage, shrinkage system, mismatch receiving rejected damage, logistics, career quantity and the marketing, and all that that was based off, the the
29 00:03:06.400 ⇒ 00:03:14.150 Demilade Agboola: one that you filled, or like the mapping that you created for us for the day, and that’s been super helpful. So that’s been allowing us to do this.
30 00:03:14.636 ⇒ 00:03:35.259 Demilade Agboola: So one thing we did notice, though, is, and I think Emily will be better at explaining it, since she handles this more consistently. One of one of the things we did notice, though, is that when a forced upgrade occurs, or when people are trying to order one particular
31 00:03:35.310 ⇒ 00:03:44.409 Demilade Agboola: item id associated with the lot. Id the inventory number. Id once that changes to a different item.
32 00:03:44.810 ⇒ 00:03:50.059 Demilade Agboola: It still seems to count this on this item. Id.
33 00:03:51.360 ⇒ 00:03:54.959 felipefaria: So discount, the original product ordered.
34 00:03:55.670 ⇒ 00:03:59.179 felipefaria: and the and the product that it was upgraded to.
35 00:03:59.660 ⇒ 00:04:00.160 Demilade Agboola: Exactly.
36 00:04:00.960 ⇒ 00:04:11.039 Demilade Agboola: Yes. So that’s what’s going on here. So obviously we could filter that out. But I was talking to Emi today, and one of the things she was saying is, potentially, it could also be
37 00:04:11.150 ⇒ 00:04:16.620 Demilade Agboola: important to know when that was happening or like the count of when that’s happening.
38 00:04:17.940 ⇒ 00:04:24.165 felipefaria: Yes, yes, we would definitely wanna know like at least have it flagged.
39 00:04:25.430 ⇒ 00:04:26.500 felipefaria: What?
40 00:04:26.700 ⇒ 00:04:35.950 felipefaria: What’s what? Order that shipped as a forced upgrade, and it will be helpful like if we can know like which skew was was upgraded.
41 00:04:37.053 ⇒ 00:04:48.050 felipefaria: It would be good, too, because that should correlate to something related to either, like a quality issue that we had at receiving. And then we had some pre-orders for it.
42 00:04:48.240 ⇒ 00:04:54.200 felipefaria: That’s usually kind of, I think, that the main main reason, or
43 00:04:54.780 ⇒ 00:04:57.916 felipefaria: it could always happens that we have kind of like
44 00:04:59.060 ⇒ 00:05:02.200 felipefaria: on on what I would call it a natural
45 00:05:02.930 ⇒ 00:05:07.929 felipefaria: oversell, and that could be caused by a variety of reasons right like the
46 00:05:08.240 ⇒ 00:05:32.600 felipefaria: they either damaged out some product during the week. That was claimed already, or it could be some misforment that happened during the week. But usually the majority of the cases for forest upgrades, at least in non holiday weeks, is because of quality issues that we see for items that are already
47 00:05:33.020 ⇒ 00:05:37.460 felipefaria: claimed right already reserved. For in a pre-sale.
48 00:05:38.520 ⇒ 00:05:45.590 felipefaria: So yeah, ideally, we we would wanna like, if the product that the customer originally ordered
49 00:05:45.720 ⇒ 00:05:54.929 felipefaria: didn’t actually ship, we would definitely wanna have the sales table adjusted not to reflect that essentially.
50 00:05:55.230 ⇒ 00:05:57.390 felipefaria: And that’s sort of the main thing.
51 00:05:58.880 ⇒ 00:06:13.510 Emily Giant: So as a follow up to that, these these 3 lots were intentionally pulled from, like the Monday after mother’s day, because we knew that there would be a lot of activity. We saw a lot of oversell that these would be the most complicated to balance.
52 00:06:13.610 ⇒ 00:06:26.949 Emily Giant: So one of the things we’re seeing like, for instance, the the 3rd line where the shrinkage negative, 12 and system mismatch negative 8. When you
53 00:06:27.630 ⇒ 00:06:34.759 Emily Giant: consider those adjustments against the total sales. It does give you
54 00:06:35.210 ⇒ 00:06:41.039 Emily Giant: an closer to accurate balance of what happened.
55 00:06:41.580 ⇒ 00:06:42.080 felipefaria: -
56 00:06:42.080 ⇒ 00:06:47.619 Emily Giant: So if you know that 10 units of the sales
57 00:06:47.770 ⇒ 00:07:02.340 Emily Giant: were not available. The actual balance is that sale number minus the 20, the 12 plus 8, and that gives you the actual units that were shipped from that lot.
58 00:07:03.060 ⇒ 00:07:03.400 felipefaria: And.
59 00:07:03.400 ⇒ 00:07:05.400 Emily Giant: Currently what’s being represented
60 00:07:05.640 ⇒ 00:07:12.829 Emily Giant: is Demoleti. Can you scroll to the left a little bit so we can see the sale quantity. So we’re seeing quantity sold? 39.
61 00:07:13.090 ⇒ 00:07:17.570 Emily Giant: If you look at that lot in Netsuite 39
62 00:07:17.820 ⇒ 00:07:22.160 Emily Giant: that many were received. That was possible.
63 00:07:22.270 ⇒ 00:07:31.710 Emily Giant: But because there were these inventory discrepancies. We know that the 12 plus 8 was moved off of that lot. So
64 00:07:32.390 ⇒ 00:07:34.290 Emily Giant: my my question is.
65 00:07:34.560 ⇒ 00:07:52.776 Emily Giant: quantity sold is 39. That is true. However, it’s 39, minus 20, which is actually the units that were delivered to customers from that lot. So I’m guessing, that you want all of that represented somehow in this table.
66 00:07:53.440 ⇒ 00:08:02.160 Emily Giant: but I wanted just some feedback on the best way to represent
67 00:08:03.530 ⇒ 00:08:08.459 Emily Giant: those different cases of what happened to the inventory.
68 00:08:08.922 ⇒ 00:08:13.580 Emily Giant: Given that 39 of this, this product was not sent out. The door.
69 00:08:14.700 ⇒ 00:08:15.460 felipefaria: Yeah,
70 00:08:18.000 ⇒ 00:08:26.500 felipefaria: like you, said the the mother’s day is a little bit tricky because of just the sheer volume and I think that the adjustments used my
71 00:08:27.140 ⇒ 00:08:38.760 felipefaria: ferry a little bit, and they might not be using the correct adjustment. And it’s very hard to validate like when I was looking at all the adjustments that took place during mother’s day. It’s like
72 00:08:38.919 ⇒ 00:08:41.059 felipefaria: over a thousand. So
73 00:08:44.130 ⇒ 00:08:55.659 felipefaria: we would wanna have it represented. And this might be a larger discussion, because I honestly don’t know what is the current process from care. When our 1st upgrade happens
74 00:08:57.380 ⇒ 00:09:19.449 felipefaria: we need to align on kind of like what adjustment they are using. And for to to remove that inventory out right ideally, it would be an adjustment that is specific for forest upgrades. We. We had a adjustment type, that is, that was forced upgrades. I’m gonna have to check if it’s still in use.
75 00:09:20.495 ⇒ 00:09:29.869 felipefaria: Because and I would say they could, and and they could
76 00:09:29.990 ⇒ 00:09:40.899 felipefaria: they? They probably use this a variety of adjustment types to into essentially remove that inventory. It could be like, reconcile or a system mismatch or.
77 00:09:40.900 ⇒ 00:09:41.620 Emily Giant: Exactly.
78 00:09:41.620 ⇒ 00:09:43.132 felipefaria: Something like that right?
79 00:09:43.880 ⇒ 00:09:51.270 felipefaria: So I don’t know if we’ll be able to get that great granular for Mother’s Day. Specifically, I would just
80 00:09:51.940 ⇒ 00:09:57.530 felipefaria: put like I would just have. We would just have to consider kinda sales and then
81 00:09:57.630 ⇒ 00:10:11.007 felipefaria: adjustments out of the lot as as a whole, at least for mother’s Day for other weeks. Then we can have kind of like the delineation of what is shrinkage, and then what is rejections and what is
82 00:10:11.690 ⇒ 00:10:29.855 felipefaria: system mismatch with system mismatch. Hopefully, we shouldn’t be having to use that much moving forward if this, if the systems are working properly. But for now and I’ll I’ll probably just have to lump everything together into into one group of like adjustments. And for
83 00:10:30.570 ⇒ 00:10:38.710 felipefaria: and for mother’s day, right? The the sales. Yeah, like. The most important thing for me is really to have an accurate
84 00:10:38.900 ⇒ 00:10:42.067 felipefaria: idea of what actually shipped to the customers.
85 00:10:43.090 ⇒ 00:10:47.681 felipefaria: And that would be kind of like the the main metric, because then.
86 00:10:48.870 ⇒ 00:10:54.019 felipefaria: what I do is I just reconcile kinda all the inventory that was confirmed as received.
87 00:10:54.160 ⇒ 00:11:08.689 felipefaria: And then I just need to put the inventory into into one of the buckets right, either sales or rollover, or shrinkage, or other adjustments, essentially and right now, for mother’s day. I am seeing
88 00:11:08.870 ⇒ 00:11:22.300 felipefaria: sort of like a big variance. Still, right? I think that there’s a 10,000 gap that either like sales, is inflated by 10,000 or adjustments are inflated by 10,000. So what you guys are saying makes sense
89 00:11:22.650 ⇒ 00:11:29.689 felipefaria: so kind of like what I’m seeing on the reconciliation for mother’s day. So separating those 2 would be
90 00:11:30.150 ⇒ 00:11:31.419 felipefaria: would be ideal.
91 00:11:31.740 ⇒ 00:11:39.910 Emily Giant: So what I’m thinking, and we can use like clearer, better language is like quantity adjusted
92 00:11:40.090 ⇒ 00:11:42.350 Emily Giant: before forced upgrades.
93 00:11:43.131 ⇒ 00:11:50.250 Emily Giant: Something along those lines that captures every sale unit that was ever adjusted on that lot, and then
94 00:11:50.410 ⇒ 00:11:54.730 Emily Giant: quantity sold would represent what you said is the most important, which is
95 00:11:54.910 ⇒ 00:11:58.339 Emily Giant: the units that were sent to the customer once.
96 00:11:58.340 ⇒ 00:11:58.770 felipefaria: Yeah.
97 00:11:58.770 ⇒ 00:12:00.170 Emily Giant: Lot was balanced out.
98 00:12:01.280 ⇒ 00:12:02.020 felipefaria: Yeah.
99 00:12:02.020 ⇒ 00:12:02.630 Emily Giant: Okay.
100 00:12:04.190 ⇒ 00:12:07.239 Demilade Agboola: Just to be clear when you said the unit sold?
101 00:12:07.750 ⇒ 00:12:12.940 Demilade Agboola: Are we seeing the number of the appropriate like, item Id
102 00:12:13.140 ⇒ 00:12:20.780 Demilade Agboola: for that lot? Id that was actually sold? Or are we seeing the sum of the 1st upgrades as well as
103 00:12:21.030 ⇒ 00:12:24.079 Demilade Agboola: the appropriate item Id, so like
104 00:12:24.500 ⇒ 00:12:28.540 Demilade Agboola: the entire quantity sold, doesn’t really matter what the item Id was.
105 00:12:28.700 ⇒ 00:12:38.020 Emily Giant: It definitely matters. The quantity sold would be the item Id and the inventory number Id.
106 00:12:38.900 ⇒ 00:12:44.370 Emily Giant: And those should not vary. There should never be 2 item ids for one inventory number. Id.
107 00:12:44.780 ⇒ 00:12:47.900 Demilade Agboola: So number Id Felipe is a a lot number.
108 00:12:48.110 ⇒ 00:12:48.560 felipefaria: So.
109 00:12:48.560 ⇒ 00:12:57.010 Emily Giant: Wouldn’t want like the dove and the Juliet in the same lot, because that’s not how we inventory. So
110 00:12:57.340 ⇒ 00:13:00.309 Emily Giant: one of these would be
111 00:13:02.020 ⇒ 00:13:09.100 Emily Giant: and there’s probably a more elegant way to do this, I think. What is the priority? Is removing all of those stale
112 00:13:09.300 ⇒ 00:13:13.220 Emily Giant: orders that were forced upgraded from the lots they don’t belong on.
113 00:13:14.310 ⇒ 00:13:19.331 Emily Giant: That seems like priority one. And then as like a secondary measure,
114 00:13:20.160 ⇒ 00:13:29.420 Emily Giant: And there’s many ways to do this. But we also want to quantify the number of sale adjustments that were made on that lot that didn’t stay on that lot.
115 00:13:29.680 ⇒ 00:13:43.271 Emily Giant: and those would be the forced upgrades. So when you see an item Id that doesn’t match that inventory number record, those should not be in like that final lot balance
116 00:13:44.810 ⇒ 00:13:47.250 Demilade Agboola: Okay, that that makes a lot of sense.
117 00:13:47.250 ⇒ 00:13:47.560 Emily Giant: Okay.
118 00:13:48.149 ⇒ 00:13:59.880 Demilade Agboola: I was going to also say so. But like right now, that’s that’s what we need to do to the numbers. The numbers do seem to match. We have looked at it, and that’s kind of how we saw like
119 00:14:00.710 ⇒ 00:14:07.780 Demilade Agboola: this, for instance, everything should be the melody. But we’re seeing like the dove and all that, and the flora.
120 00:14:08.250 ⇒ 00:14:15.422 Demilade Agboola: and those obviously inflated, the number of the quantities sold given the fact that they shouldn’t be on this
121 00:14:15.910 ⇒ 00:14:18.160 Demilade Agboola: lots. They shouldn’t be on this invention number.
122 00:14:19.307 ⇒ 00:14:31.400 Demilade Agboola: So yes, in that case, what we would have we’ll end up having is, we’ll have account or quantity, both for everything which happens to be the melody and every other thing else. We can also have accounts for that as well.
123 00:14:33.340 ⇒ 00:14:39.791 Emily Giant: And Felipe, all of those that you see that aren’t the melody. Those were the melody. Those were
124 00:14:40.580 ⇒ 00:14:51.679 Emily Giant: just orders that couldn’t be fulfilled because of those inventory mismatch adjustments. So this wasn’t like this wasn’t a concurrency issue with netsuite and shopify. This was actual like
125 00:14:52.515 ⇒ 00:14:59.640 Emily Giant: something happened to the inventory in the facility, and they ran out before they could fulfill what had sold.
126 00:14:59.850 ⇒ 00:15:03.330 felipefaria: Yeah, yeah, makes sense. And then they ship those products instead.
127 00:15:04.200 ⇒ 00:15:05.579 felipefaria: Yeah, okay.
128 00:15:07.840 ⇒ 00:15:18.620 Emily Giant: So that’s a good like 2 birds, one stone with, like your forced upgrades. And being able to better quantify those we just need to figure out there are a couple like
129 00:15:18.980 ⇒ 00:15:26.990 Emily Giant: questions as to why that inventory number record didn’t update in the data when the 1st upgrade happened.
130 00:15:27.430 ⇒ 00:15:28.390 felipefaria: Yeah, in my.
131 00:15:28.780 ⇒ 00:15:50.780 Emily Giant: Those should never have that inventory number should have erased or canceled that record when the forced upgrade occurred. The good news is, I guess you can call it good news that there is a record in the data for the correct lot like it didn’t not move it to the lot that it wound up getting sent from
132 00:15:51.589 ⇒ 00:15:56.989 Emily Giant: so there is that additional record. That is true.
133 00:15:57.140 ⇒ 00:15:58.010 Emily Giant: The
134 00:15:59.350 ⇒ 00:16:12.869 Emily Giant: the one missing piece still, though, is, when an order is not assigned to a lot, but it gets sent out the door anyway, and how we quantify that, or what you want that
135 00:16:12.990 ⇒ 00:16:15.619 Emily Giant: to look like in that final table.
136 00:16:16.280 ⇒ 00:16:17.980 felipefaria: Hmm! Is there?
137 00:16:18.270 ⇒ 00:16:20.630 felipefaria: Is there a lot of those? Do you know.
138 00:16:21.130 ⇒ 00:16:21.720 Emily Giant: Yeah.
139 00:16:22.740 ⇒ 00:16:25.869 felipefaria: That they shipped out, but they’re not assigned to a lot.
140 00:16:28.920 ⇒ 00:16:30.065 felipefaria: Thanks.
141 00:16:34.610 ⇒ 00:16:40.570 felipefaria: I don’t know exactly how we would have to deal with that cause. I I’m wondering
142 00:16:40.940 ⇒ 00:16:44.250 felipefaria: it’s not assigned to a lot, because a lot is already full.
143 00:16:46.725 ⇒ 00:16:47.510 felipefaria: Okay.
144 00:16:47.510 ⇒ 00:17:00.950 Emily Giant: And it’s a little mind, Bendy, because it’s the inventory shouldn’t exist, and that unit will absolutely be represented in the system. But it won’t be represented as a sale. It will be represented as
145 00:17:01.430 ⇒ 00:17:24.319 Emily Giant: system mismatch, or some other adjustment to say like, we don’t have this, but the reason we don’t have it in many cases is because it wasn’t successfully, because an order went out the door that wasn’t successfully assigned to a lot now, just to calm any it happens a lot during Mother’s Day and Valentine’s Day. It does not happen a lot during a normal week.
146 00:17:24.560 ⇒ 00:17:29.609 felipefaria: Yeah, exactly. I was gonna say, because yeah, mother’s day, just for the sheer volume. And then
147 00:17:30.170 ⇒ 00:17:36.550 felipefaria: all of the carrier issues kind of tend to happen more or less at the same time. So it doesn’t surprise me that we have.
148 00:17:36.760 ⇒ 00:17:41.439 Emily Giant: This wonky situations with adjustments and things like that.
149 00:17:42.260 ⇒ 00:17:48.030 felipefaria: And I would say, I I mean the priority on my end is really
150 00:17:48.150 ⇒ 00:17:52.470 felipefaria: just knowing everything that actually shipped out.
151 00:17:53.276 ⇒ 00:17:54.650 Emily Giant: By skew.
152 00:17:55.175 ⇒ 00:18:15.305 felipefaria: And I know that there might be some variances where, like, you know, some Fcs, I would imagine that they might have shipped a different product instead of the original one, because it was a last minute. And they just had to put something in the box. But hopefully, that’s like a small percentage of like an allowable variance that that we deal with. But then,
153 00:18:16.470 ⇒ 00:18:26.880 felipefaria: I, I should be able to kind of backtrack, looking at all the adjustments to happen in that suite and and get a sense of
154 00:18:27.190 ⇒ 00:18:29.400 felipefaria: of what was the actual
155 00:18:29.830 ⇒ 00:18:41.510 felipefaria: shrinkage in the actual rollover. As long as I have kinda an one certain data point which should be the sales right? Like everything that actually shipped out of the door.
156 00:18:43.140 ⇒ 00:18:50.710 felipefaria: So yeah, it’s tricky. But if we could get to that point at least, for from mother’s day would be ideal.
157 00:18:51.050 ⇒ 00:19:00.870 Emily Giant: So quantity sold would include, then an order that was not committed to the lot.
158 00:19:01.440 ⇒ 00:19:02.280 Emily Giant: Okay.
159 00:19:02.280 ⇒ 00:19:07.960 felipefaria: Yeah, yeah, I mean, if it actually shipped yeah.
160 00:19:08.130 ⇒ 00:19:13.199 felipefaria: And if you guys wanna create like a different measure, because I don’t know how
161 00:19:13.760 ⇒ 00:19:19.209 felipefaria: how many orders you guys are seeing this on a regular week aside from mother’s day.
162 00:19:19.520 ⇒ 00:19:24.382 felipefaria: But if you want to be another measure like, you know units sold
163 00:19:25.610 ⇒ 00:19:40.439 felipefaria: total, or like, inclusive of no like items that that are not assigned to lots. That’s fine as long as I have access to to that kind of measure, and I can put that into the
164 00:19:41.230 ⇒ 00:19:49.160 felipefaria: like into my weekly recap files, and see if the numbers make make more sense with that essentially.
165 00:19:49.360 ⇒ 00:19:53.650 Emily Giant: Yeah, what should always be true is that the number of
166 00:19:54.136 ⇒ 00:20:00.729 Emily Giant: reconciliations that aren’t spoilage should match the number of sales that went out the door without the commitment.
167 00:20:01.320 ⇒ 00:20:02.230 Emily Giant: If that.
168 00:20:02.470 ⇒ 00:20:03.550 felipefaria: Wait! Say it again!
169 00:20:04.256 ⇒ 00:20:09.199 Emily Giant: The number of adjustments that aren’t spoilage.
170 00:20:09.200 ⇒ 00:20:09.590 felipefaria: Okay.
171 00:20:09.590 ⇒ 00:20:21.579 Emily Giant: Which is like a different thing. Should match the number of orders that went out the door. The the lot should always balance to the number that was received right like.
172 00:20:21.920 ⇒ 00:20:30.479 Emily Giant: So what’s still anonymous right now is whether shrinkage was due to an order getting sent out the door
173 00:20:30.780 ⇒ 00:20:38.149 Emily Giant: without being committed to a lot, or whether it was damaged or something, or disappeared. That’s what’s unclear so.
174 00:20:38.150 ⇒ 00:20:38.590 felipefaria: Yeah.
175 00:20:38.590 ⇒ 00:20:46.009 Emily Giant: Just like getting that finer detail. But what I was trying to summarize was that
176 00:20:46.530 ⇒ 00:20:51.420 Emily Giant: the adjustments should always match the received at the.
177 00:20:51.420 ⇒ 00:20:51.810 felipefaria: And.
178 00:20:51.810 ⇒ 00:20:58.610 Emily Giant: Of the day, and we’re losing the detail of when shrinkage is actually a sale.
179 00:20:59.300 ⇒ 00:21:06.399 felipefaria: Yeah, yeah, and I’m assuming.
180 00:21:06.840 ⇒ 00:21:21.460 felipefaria: do, do you have an idea of how many units are like, or how many sales are in this category, or this bucket that are not assigned to a lot like for mother’s day week.
181 00:21:24.300 ⇒ 00:21:25.580 Emily Giant: I’m.
182 00:21:25.980 ⇒ 00:21:31.050 felipefaria: Well, you don’t need to give it to me right now, but maybe it would be would be
183 00:21:31.530 ⇒ 00:21:33.010 felipefaria: interesting to see.
184 00:21:34.330 ⇒ 00:21:39.719 Emily Giant: It would be in the hundreds. I don’t think it’s in the thousands, but I would think it’s
185 00:21:39.940 ⇒ 00:21:42.440 Emily Giant: more than 500.
186 00:21:43.130 ⇒ 00:21:45.320 felipefaria: Okay, okay.
187 00:21:45.946 ⇒ 00:21:47.890 felipefaria: Yeah. So that wouldn’t.
188 00:21:49.300 ⇒ 00:21:54.760 felipefaria: That wouldn’t really account for the majority of the variance that I’m still seeing.
189 00:21:54.940 ⇒ 00:22:03.865 felipefaria: What could account for part of that, too, is, it’s just the sales being duplic duplicate right.
190 00:22:04.390 ⇒ 00:22:11.660 Emily Giant: I think, is the problem is that we have a high amount of forced upgrades, and that you’re seeing more than one record for a sub order.
191 00:22:11.910 ⇒ 00:22:13.480 felipefaria: Yeah, yeah.
192 00:22:14.543 ⇒ 00:22:17.360 Demilade Agboola: Quick! Quick question on like how to go forward
193 00:22:17.520 ⇒ 00:22:27.509 Demilade Agboola: right now. Will these numbers be useful to you? I mean the fix to like filter it out by like the appropriate item and the appropriate invention number
194 00:22:27.640 ⇒ 00:22:30.300 Demilade Agboola: shouldn’t be like we don’t do.
195 00:22:30.630 ⇒ 00:22:38.329 Demilade Agboola: It’ll be it can be released by like early next week, because we don’t really want to make huge changes before the weekend. But,
196 00:22:39.120 ⇒ 00:22:45.389 Demilade Agboola: I’m curious as to at what point will these numbers be like numbers you will be able to utilize.
197 00:22:45.925 ⇒ 00:22:53.619 Demilade Agboola: Is this something you can use right now? Or do you? Would you like us to make those like changes to those 3 before you start using it.
198 00:22:59.620 ⇒ 00:23:00.730 felipefaria: I mean.
199 00:23:02.040 ⇒ 00:23:07.209 felipefaria: And and I need to complete in that weekly recap file. It’s not a thing that is
200 00:23:07.980 ⇒ 00:23:16.409 felipefaria: super pressing right now, but for Mother’s day, and just to have our files, our records done. I I kinda need to
201 00:23:16.560 ⇒ 00:23:30.123 felipefaria: to have that done. And as I said, like the we are right. Now. We have a big variance in the things, and it seems like either the shrinkage is inflated or the sales is inflated right
202 00:23:31.090 ⇒ 00:23:34.627 felipefaria: and I can wait until next week. But
203 00:23:36.040 ⇒ 00:23:43.869 felipefaria: what I really need is just like an accurate record of the of what actually shipped out the door and that’s kind of like my.
204 00:23:44.030 ⇒ 00:23:50.260 felipefaria: the the one thing that that I would want, and
205 00:23:50.990 ⇒ 00:23:56.140 felipefaria: and I guess, and all of those would be under the sales
206 00:23:56.810 ⇒ 00:24:06.339 felipefaria: report Emily cause. And now we have a subscription and the deliveries in the sales right? I don’t know if we would be able to separate that.
207 00:24:06.440 ⇒ 00:24:13.689 felipefaria: But and and I don’t know if that answers the question, then Melody, but like on my end, it’s really.
208 00:24:14.860 ⇒ 00:24:37.129 felipefaria: if you guys give me that measure today I’ll be able to use it because I I and I like I can pull the majority of the information right like the the shrinkage and all the adjustment types, everything I can pull it from that suite. The one thing that I’m looking for is like the final accurate information in terms of what actually shipped, and what was the bouquet that actually shipped out?
209 00:24:37.842 ⇒ 00:24:42.187 felipefaria: And and that’s the I guess the missing piece.
210 00:24:42.880 ⇒ 00:24:44.551 felipefaria: This on my end.
211 00:24:46.420 ⇒ 00:24:50.469 Demilade Agboola: Okay? So I guess this
212 00:24:50.580 ⇒ 00:24:54.040 Demilade Agboola: gets you almost there again, because the
213 00:24:54.230 ⇒ 00:25:08.329 Demilade Agboola: the criss cross between the different items is where, like the inflation kind of comes in, but once we do that fix, it will be able to partition it by the appropriate like items. But you can see that this lot
214 00:25:08.530 ⇒ 00:25:09.980 Demilade Agboola: with this item.
215 00:25:10.430 ⇒ 00:25:15.400 Demilade Agboola: We sold this, and it’s it’s much easier to be able to understand what’s going on.
216 00:25:16.024 ⇒ 00:25:19.300 Demilade Agboola: In there rather than have like still, slight inflation.
217 00:25:21.240 ⇒ 00:25:21.740 felipefaria: Okay.
218 00:25:21.740 ⇒ 00:25:32.359 Emily Giant: Yeah, that second piece would just be quantifying. What inventory reconciliations were actually
219 00:25:32.570 ⇒ 00:25:41.620 Emily Giant: sales that didn’t have a lot. But that’s going to be way smaller than the forced upgrades, like what demalade is mentioning will be the majority of the fix.
220 00:25:42.620 ⇒ 00:25:43.550 felipefaria: Got it.
221 00:25:44.460 ⇒ 00:25:45.460 felipefaria: Okay?
222 00:25:45.700 ⇒ 00:25:52.559 felipefaria: Yeah. And I, I’m assuming that this really pertains mainly to mother’s day, right? Like, it’s not impacting things on a
223 00:25:52.920 ⇒ 00:25:58.000 felipefaria: on a daily basis, because I and I’ve been doing for the past 2 weeks
224 00:25:58.260 ⇒ 00:26:08.200 felipefaria: or 3 weeks. Really, the the weekly recaps with the new data, Emily and things have been lining up like we have small variances. But I think that
225 00:26:08.940 ⇒ 00:26:30.869 felipefaria: it’s it’s something that might not be related to the forest upgrades. It’s more like a start. Start date of some shipments in the local market that is accounting for sale for same week sales. But that’s a separate conversation in general, things are lining up much better. So I’m assuming that this is just from mother’s day. So it’s it’s just a matter for me to
226 00:26:31.090 ⇒ 00:26:34.120 felipefaria: backtrack and have kind of at least a
227 00:26:35.240 ⇒ 00:26:40.480 felipefaria: a close to accurate picture of what happened during mother’s day. Yeah.
228 00:26:40.480 ⇒ 00:26:59.780 Demilade Agboola: So the number. We looked at some other records outside the mother’s day window, and those were fine. It’s when we started looking at the mother’s day window, where, like, you know, these numbers, I guess, inflated. But this fix will be largely oriented to like accounting for that level of variance. And that’s why I said like, if
229 00:27:00.030 ⇒ 00:27:04.350 Demilade Agboola: do you want us to like look to get these numbers like to you
230 00:27:04.560 ⇒ 00:27:10.690 Demilade Agboola: as soon as possible, or do you would you want us to do the fix and then get those numbers like, get the
231 00:27:11.010 ⇒ 00:27:15.299 Demilade Agboola: the models and the dashboard, of course, to you like next week, instead.
232 00:27:15.300 ⇒ 00:27:18.636 felipefaria: Yeah, if if it’s next weekend, and that should be fine,
233 00:27:18.940 ⇒ 00:27:19.470 Demilade Agboola: Okay.
234 00:27:19.470 ⇒ 00:27:20.430 felipefaria: That should be fine.
235 00:27:21.150 ⇒ 00:27:35.070 Demilade Agboola: Alright, then sounds good. Yes, we’re definitely on track with this. We’re looking forward to getting you all the inventory numbers you need all in one spot. You don’t have to keep going across multiple spaces to get the numbers.
236 00:27:35.410 ⇒ 00:27:36.020 Emily Giant: Yeah.
237 00:27:36.160 ⇒ 00:27:42.279 felipefaria: Thank you. Yeah. And and one thing that I mentioned to I’m not sure is like because right now we have
238 00:27:43.050 ⇒ 00:27:52.689 felipefaria: a measure of like units sold units in. We delivered in units, in subscription, if we could have one that is like the total
239 00:27:53.244 ⇒ 00:28:08.180 felipefaria: and I don’t know if you already have this or not, Emily, but just like one that is like the total quantity shipped, or something like that. It will be helpful, because right now, I just have to kinda add everything from those tables.
240 00:28:08.707 ⇒ 00:28:15.369 felipefaria: And for some activities it would be helpful to just have, like, you know, one table that has the total numbers.
241 00:28:15.490 ⇒ 00:28:16.799 felipefaria: and I shipped out.
242 00:28:17.280 ⇒ 00:28:33.919 Emily Giant: What he’s saying exist in Dbt. I just haven’t added it to Looker, because I always have. Whenever we make updates I have to like, go into looker and then update those as well. So that’s actually we can do additional Qa, but that does exist. So.
243 00:28:34.610 ⇒ 00:28:56.340 Demilade Agboola: We should also let me look into the flow because we do have a lot. We have done a bunch of stuff with inventory and just kind of know what has been exposed to you on the look at end, because it’s possible some of these numbers do exist, and we just need to add that to you. That’s also something we’ll look at next week. And just so you can start having these numbers right at your fingertips.
244 00:28:57.400 ⇒ 00:29:05.920 Emily Giant: Amber. That would be a good ticket. To add for me is to make sure that all of demote’s updates are reflected in Looker so that the have access.
245 00:29:07.130 ⇒ 00:29:12.139 Emily Giant: I can. I can create that I just like. So that one person has that in their brain. I wanted to say.
246 00:29:12.140 ⇒ 00:29:15.112 Amber Lin: Okay, okay, sounds good.
247 00:29:16.030 ⇒ 00:29:37.359 Amber Lin: yes, a few things that I I wanna make sure that we accomplish before we end. This meeting is one. I want to see if it’s okay, Felipe, for us to add you to if we sometimes, outside of our stand ups and sprint rituals, we have working sessions between our team and Emily. And I was wondering.
248 00:29:37.832 ⇒ 00:29:49.439 Amber Lin: for Jesse and Philippe. If it’s about the area that you’re working in, is it. Okay? If we add you to the inventory working session, so you can see what’s going on.
249 00:29:49.690 ⇒ 00:29:50.600 felipefaria: Sure.
250 00:29:51.380 ⇒ 00:29:59.149 Amber Lin: Okay, I’ll let Emily and Demolanti coordinate you on that. I believe it’s usually at 9 Am. Est.
251 00:30:00.130 ⇒ 00:30:07.679 Amber Lin: Okay, yeah, awesome. So that’s good. I think the second part is.
252 00:30:07.850 ⇒ 00:30:31.069 Amber Lin: I just, I was just want to record the top. Say, the top 3 dashboards or analysis that is going to be impacted. And so we can start thinking about a plan and how we can rebuild them based on the new inventory marks. I wasn’t sure if we got them, but if not, I’ll love to just document them and keep that in mind as we build inventory.
253 00:30:35.240 ⇒ 00:30:47.583 Emily Giant: Felipe. I think that I have them captured in the brain. Forge board in Looker. I’ll send you the link, and you can take a look if there are any that are missing from your main inventory dashboards.
254 00:30:48.220 ⇒ 00:30:55.160 Emily Giant: you can just like plop the link into the board. But we did this like a long time ago, so things may have changed.
255 00:30:55.870 ⇒ 00:31:00.269 felipefaria: Yeah, send me the link, and I’ll take a look. I think like
256 00:31:00.720 ⇒ 00:31:25.229 felipefaria: the the sales was kind of like the main priority for me the because the adjustments and stuff I can pull it from that suite. We did a Qa on the hard goods, and like add ons and basis sales that. Emily shared the file with me last week. I did flag some variances, even though the numbers were
257 00:31:25.350 ⇒ 00:31:36.579 felipefaria: mostly aligned we fixed kind of like the issue with the locations that was going on. There is still kind of like a like a variance there, right? That we kind of need to look into. Why, that is
258 00:31:38.410 ⇒ 00:31:47.670 felipefaria: Aside from that, I think that the main, the main thing that I’m looking for is is it’s kind of like a report with the sub order
259 00:31:47.860 ⇒ 00:31:56.950 felipefaria: suborder showing the components. Queue, the parents queue, and then the delivery, the delivery map, or just the map type.
260 00:31:57.967 ⇒ 00:32:05.484 felipefaria: That’s kind of like one report that we used to have that right now. I I don’t have visibility into
261 00:32:06.200 ⇒ 00:32:11.670 Emily Giant: Close. Felipe, this close. There’s still some issues with those like custom.
262 00:32:12.470 ⇒ 00:32:17.060 Emily Giant: But it’s it’s almost usable right now. It’s like.
263 00:32:17.060 ⇒ 00:32:17.600 felipefaria: Nice.
264 00:32:17.820 ⇒ 00:32:18.920 Emily Giant: But yeah, it’s getting.
265 00:32:18.920 ⇒ 00:32:34.220 felipefaria: Okay, yeah, yeah. And that report is is not needed as frequently as the sales one. But I do use it kinda ideally once a month. Really, when we reconcile packaging right? Like I wanna look at the map type just to see like
266 00:32:34.890 ⇒ 00:32:45.159 felipefaria: which, like the suborder, I need to know, because I need to know which product shipped as a single versus a double and things like that. And then the map type tells me if it was a
267 00:32:45.614 ⇒ 00:32:59.329 felipefaria: same day delivery versus a nationwide delivery. And that impacts the packaging that we used essentially. And it’s it’s more like a utilization, a packaging utilization exercise that we and that we do that right now, we’re kind of like
268 00:32:59.620 ⇒ 00:33:02.689 felipefaria: a little bit blind in terms of how many.
269 00:33:03.030 ⇒ 00:33:10.260 felipefaria: how many units of each packaging each of the Fcs should have used versus how many they actually use, based on their end of month. Count.
270 00:33:10.530 ⇒ 00:33:40.180 Amber Lin: Hmm! I see. So to summarize what I heard, the most important one is related to sales. And you use that every single day. And currently it’s still using the previous old inventory march. And you we can rebuild that using the new marts. And then the second one is once a month. You want to reconcile packaging, and you need the reports. With sub orders showing like the components, delivery map types, etc.
271 00:33:40.180 ⇒ 00:33:47.379 felipefaria: Yes, correct. And and as as far as I know, I think that the sales is using the the updated
272 00:33:47.740 ⇒ 00:33:49.370 felipefaria: Hmm, okay, right?
273 00:33:49.880 ⇒ 00:33:55.210 felipefaria: The only thing is there are those small variances. I think that for the
274 00:33:55.750 ⇒ 00:34:01.710 felipefaria: and for the floral side usually sales are a little bit
275 00:34:03.110 ⇒ 00:34:10.379 felipefaria: overstated. In the reports, and then on the hard goods is understated.
276 00:34:11.330 ⇒ 00:34:35.960 felipefaria: So something to look at, and I I provided Emily with a couple of examples of that. It’s not a big variance. But it will be interesting to know like why. That is because, especially with skews, that we have very little sales off, like even 2, 3 units. Variance is a big percentage of the overall sales. So that kind of gets flagged on on my end. So.
277 00:34:36.329 ⇒ 00:34:37.350 felipefaria: okay, yeah.
278 00:34:37.719 ⇒ 00:34:56.449 Amber Lin: Sounds good. Are you happy with all how the dashboard is presented? Do you feel confident to? If there’s an issue to dig into where the source is. If not, we would love to schedule some sessions, to walk you through it, and make sure that you feel confident to navigate.
279 00:34:57.509 ⇒ 00:35:01.299 felipefaria: Yeah, I mean, I’m I’m comfortable.
280 00:35:01.719 ⇒ 00:35:23.969 felipefaria: knowing where the data is, and and building the reports with the, with the, with the information there like I don’t know exactly like the specifics I haven’t digged into, like, you know, the the script, or of of how those are are created. But I usually would touch base with Emily. If I have a question on on those right.
281 00:35:23.969 ⇒ 00:35:38.349 felipefaria: Usually, what I do is I look at the data presented in Looker, and if there is a way for me to validate manually like, whether using dash or netsuite, I’ll try to do it, and then I’ll flag if there’s a variance, but sometimes like.
282 00:35:38.459 ⇒ 00:35:43.739 felipefaria: and I don’t really know how to go about. For example, like, you know, differentiating a sale
283 00:35:44.169 ⇒ 00:35:55.479 felipefaria: from whether it’s a redelivery or subscription. I know. I know that now we we have those flagged in dash as whether our product is a redelivery or sales. So so that does help
284 00:35:57.369 ⇒ 00:36:05.589 felipefaria: But yeah, so sometimes it might be a little bit different difficult for me to to validate on my own right, like, just
285 00:36:05.970 ⇒ 00:36:08.170 felipefaria: I kind of see dashes
286 00:36:09.748 ⇒ 00:36:16.980 felipefaria: as the source of truth in a way, because that’s what the Ops teams are using. And that’s what actually is being fulfilled and shipped out
287 00:36:17.707 ⇒ 00:36:21.459 felipefaria: so I usually try to compare things with dash
288 00:36:21.710 ⇒ 00:36:25.210 felipefaria: when I’m validating reports. But yeah.
289 00:36:26.280 ⇒ 00:36:39.509 Amber Lin: Okay, yeah. I’ll talk with someone and Emily on. If there’s anything we can assist with to make that even easier. But it’s great to hear that that you know how the marks are currently working.
290 00:36:40.650 ⇒ 00:37:06.490 Amber Lin: Awesome. That is all for this meeting. I know. We ran a little bit over and sorry, Jesse, we didn’t get to the parts of Fxu, I think, moving forward, I’ll let them lot of Emily contact you guys on if there’s any working sessions that will be great to involve you guys in, and I’ll probably see if I can have a meeting with Superi Mpk. Next week.
291 00:37:08.280 ⇒ 00:37:09.120 felipefaria: Sounds good.
292 00:37:09.120 ⇒ 00:37:09.450 Amber Lin: Okay.
293 00:37:09.450 ⇒ 00:37:10.260 Demilade Agboola: Okay.
294 00:37:10.740 ⇒ 00:37:11.340 Amber Lin: Thanks. Everyone.
295 00:37:11.340 ⇒ 00:37:11.990 felipefaria: Guys.
296 00:37:12.240 ⇒ 00:37:13.160 Demilade Agboola: Alright, bye.
297 00:37:13.160 ⇒ 00:37:13.960 Amber Lin: Bye.