Meeting Title: Brainforge Final Interview Date: 2026-03-31 Meeting participants: Fanu Sisay, Greg Stoutenburg, Amber Lin
WEBVTT
1 00:01:48.560 ⇒ 00:01:50.440 Greg Stoutenburg: Hey, Fanny, good to see you again.
2 00:01:50.710 ⇒ 00:01:51.800 Fanu Sisay: Hey, Greg, how are you?
3 00:01:52.070 ⇒ 00:01:53.370 Greg Stoutenburg: Doing alright, how are you?
4 00:01:53.690 ⇒ 00:01:54.590 Fanu Sisay: Good, good.
5 00:01:54.990 ⇒ 00:01:59.360 Greg Stoutenburg: Give me one second, well… Amber’s joining us.
6 00:02:00.400 ⇒ 00:02:01.110 Fanu Sisay: Nope.
7 00:02:05.520 ⇒ 00:02:07.080 Fanu Sisay: How’s your Tuesday going?
8 00:02:07.750 ⇒ 00:02:12.129 Greg Stoutenburg: It is good, it is good.
9 00:02:15.290 ⇒ 00:02:19.569 Greg Stoutenburg: Okay, set a tackle something. Yeah, so…
10 00:02:19.730 ⇒ 00:02:26.239 Greg Stoutenburg: Yeah, hope your week’s off to a good start. This is our final round interview, so,
11 00:02:26.240 ⇒ 00:02:40.680 Greg Stoutenburg: I think Amber’s probably just wrapping something up, so she can just get started. Robert got called to an on-site thing, so, it’ll be… it’ll be me, you, and Amber, and then, so we’ll sort of, you know, give Robert the recording and report back.
12 00:02:40.870 ⇒ 00:02:44.090 Fanu Sisay: Yeah, sweet. I saw the interview was recording, so…
13 00:02:44.300 ⇒ 00:02:48.720 Greg Stoutenburg: Okay, yeah, yep, that’s right. We do a lot of recording around here, so… Yep, awesome.
14 00:02:49.350 ⇒ 00:02:55.110 Greg Stoutenburg: Yeah, so yeah, if you could… I mean, basically, we’re gonna work through the case study that you did.
15 00:02:55.110 ⇒ 00:02:55.540 Fanu Sisay: Yep.
16 00:02:55.540 ⇒ 00:03:12.920 Greg Stoutenburg: And that’s our goal, and so what I’d like for you to do is just take, like, you know, take about 10 minutes, and just give the presentation, and, we’ll ask some questions sort of toward the end, but we’ll just… we’ll just go quiet now, and let you do the presentation, and then we’ll check in in a bit.
17 00:03:13.280 ⇒ 00:03:21.579 Fanu Sisay: Lovely. Yeah, sounds good. Just giving access to Zoom, to share my screen.
18 00:03:21.580 ⇒ 00:03:26.759 Greg Stoutenburg: Yeah, I understand. If you’re on a Mac, seems like you have to give permissions again every couple of hours.
19 00:03:27.000 ⇒ 00:03:27.810 Fanu Sisay: Yeah.
20 00:03:27.810 ⇒ 00:03:28.880 Greg Stoutenburg: Nice deal.
21 00:03:29.140 ⇒ 00:03:34.040 Fanu Sisay: I apologize, it’s asking me to leave the meeting to refresh. I’ll be back in less than a minute.
22 00:03:34.040 ⇒ 00:03:35.969 Greg Stoutenburg: Sure. Yeah, go ahead. No problem.
23 00:04:13.910 ⇒ 00:04:15.839 Fanu Sisay: Awesome. You guys able to see?
24 00:04:16.360 ⇒ 00:04:16.760 Greg Stoutenburg: Yep.
25 00:04:17.450 ⇒ 00:04:18.290 Fanu Sisay: Lovely.
26 00:04:22.430 ⇒ 00:04:38.200 Fanu Sisay: Okay, yeah, just want to start off by saying thank you guys for, putting me through the process. I’ve really enjoyed, this exercise, and yeah, excited to go over this case study. Feel free to interrupt if need be, but yeah, I’ll run through quite smoothly.
27 00:04:38.330 ⇒ 00:04:40.440 Fanu Sisay: So yeah, just…
28 00:04:40.570 ⇒ 00:04:53.709 Fanu Sisay: looking through the data, I think it was quite clear to me that this was DoorDash, DoorDash exercise, seeing words like Dash Mart, and being quite familiar with the space, yeah, I was able to recognize that.
29 00:04:54.230 ⇒ 00:05:02.670 Fanu Sisay: And so yeah, went through the objective. Here are my strategic recommendations. I’ll go through more of that as we go through this deck.
30 00:05:02.790 ⇒ 00:05:08.519 Fanu Sisay: I’ll start off with some, assumptions that I made, and then go through key findings, and then, yeah.
31 00:05:08.680 ⇒ 00:05:23.649 Fanu Sisay: these recommendations, TN. So yeah, I noticed that, this was Cincinnati data only. I thought this was something good to point out. You know, Cincinnati is, just one city, so
32 00:05:24.000 ⇒ 00:05:42.940 Fanu Sisay: I want to keep this quite directional. I don’t want to put any concrete recommendations in due to it being only one city. I would love to have more data and, you know, more cities to look at, but this was just Cincinnati. Also want to note that this was back in 2022, one month of data back then, so not necessarily recent.
33 00:05:42.990 ⇒ 00:05:48.980 Fanu Sisay: So yeah, would love more up-to-date data to make more concrete recommendations, but yeah.
34 00:05:50.080 ⇒ 00:06:10.859 Fanu Sisay: Another thing I noticed was that there was no convenience or alcohol data. I noticed that there were some alcohol products a part of grocery orders, but I chose not to assume, or not to make an alcohol vertical assumption there. I’m not sure if that was something I was supposed to do, but just wanted to make that clear in the beginning.
35 00:06:10.860 ⇒ 00:06:19.220 Fanu Sisay: And then also wanted to clarify that, you know, I considered all three parts of the marketplace, with this exercise. The consumers, merchants, and dashers.
36 00:06:19.540 ⇒ 00:06:36.460 Fanu Sisay: So yeah, going through my key findings, I think the first one, I saw was that the… there was a lot of value in grocery orders and deliveries. They were about 2X, the value that we saw in the Dashmart orders, so not to say that, you know, it…
37 00:06:36.490 ⇒ 00:06:43.469 Fanu Sisay: the Dash Mart isn’t a place we should focus, but I saw that, grocery orders do quite well. Another issue, or…
38 00:06:43.470 ⇒ 00:06:59.140 Fanu Sisay: something I would call an issue, was that the fulfillment rate saw a drop-off when considering grocery orders. They were about in the 84% to 87% range, whereas Dashmart orders, were, I think, high 99% range.
39 00:06:59.140 ⇒ 00:07:00.209 Fanu Sisay: And then…
40 00:07:00.210 ⇒ 00:07:08.959 Fanu Sisay: Another, another issue I found was that the dashers were quite siloed in the verticals that they worked in, so only…
41 00:07:09.330 ⇒ 00:07:19.790 Fanu Sisay: looking through, I only saw 6 Dashers that had experience with Dash Mart and grocery, orders. So I saw this as a potential vulnerability, but yeah.
42 00:07:19.790 ⇒ 00:07:35.020 Fanu Sisay: to look more into that, here I have a breakout of all the deliveries on the left. It shows that 69% of the orders were Dash Mart, which, you know, is great. It is a DoorDash product. You know, it’s great to see that it’s doing well.
43 00:07:35.020 ⇒ 00:07:41.940 Fanu Sisay: But, when looking at the average, you know, value to each of the carts,
44 00:07:41.960 ⇒ 00:07:55.639 Fanu Sisay: I saw that grocery orders were much more, valuable. So, up in the 18. And, you know, I saw this as a potential opportunity to grow, to get into that grocery space.
45 00:07:57.860 ⇒ 00:08:07.599 Fanu Sisay: Okay, and then the fulfillment issue. I saw that, you know, 1 out of 6, items in a grocery cart were found missing.
46 00:08:07.600 ⇒ 00:08:21.779 Fanu Sisay: And obviously, they have the ability to substitute these items, but even then, there were specific cases where those weren’t found. So yeah, I would like to assume this is an issue with the inventory being out of sync.
47 00:08:22.250 ⇒ 00:08:26.229 Fanu Sisay: customers were going on the DoorDash app and seeing items listed there.
48 00:08:26.450 ⇒ 00:08:38.979 Fanu Sisay: And those items were not in our, or in the grocery partners, which, you know, led to missing items, it led to substitutions when, applicable, and, you know.
49 00:08:39.070 ⇒ 00:08:46.880 Fanu Sisay: this frustrates customers, led to cancellations, led to MIRs, missing item reports,
50 00:08:46.970 ⇒ 00:09:10.110 Fanu Sisay: And, yeah, leaves our customers frustrated. And honestly, all three, segments of the marketplace frustrated. Dashers wasting time looking for substitutions in stores for items that aren’t there, or, you know, are in contact with customers asking, you know, hey, what would you like to replace this with? Customers being frustrated that they saw an item on the app, and it was not there.
51 00:09:10.110 ⇒ 00:09:19.270 Fanu Sisay: or Dashers went to the store and it wasn’t there. And then merchants being left with the blame of this, mishap. So yeah, saw that issue there.
52 00:09:19.660 ⇒ 00:09:32.899 Fanu Sisay: And then our siloed dashers problem. Here on the left, you see that there was about 62% of dashers that were dash smart only, or at least our data told us that they only worked in the dash smart space. And then,
53 00:09:33.260 ⇒ 00:09:53.250 Fanu Sisay: 38% only working in the grocery space. I only saw 6, dashers that had experience with both Dash Mart and grocery, verticals. This, I think, is a vulnerability for, all 3 cases. So, say there’s some kind of surge, pre, you know, a big storm coming to town,
54 00:09:53.660 ⇒ 00:10:14.150 Fanu Sisay: Dashers are, you know, might get busy with just grocery orders. And with only 38% of the dashers being, you know, experienced in that, that leaves 62% of Dashers, you know, sitting idle, not working, as, you know, they may not prefer to do grocery orders. This leaves consumers with late orders, coming in, maybe
55 00:10:14.150 ⇒ 00:10:23.190 Fanu Sisay: something they wouldn’t even consider, like, a 2-hour wait time, and maybe going to another, competitor. Merchants being left with the blame that, hey, you know.
56 00:10:23.190 ⇒ 00:10:29.259 Fanu Sisay: Costco’s orders take 2 hours late, I’m not gonna shop at Costco. And then Dashers, you know.
57 00:10:29.670 ⇒ 00:10:34.479 Fanu Sisay: Those who aren’t, you know, familiar with that vertical sitting idle and wasting time.
58 00:10:35.720 ⇒ 00:10:45.829 Fanu Sisay: So yeah, those are 3 key findings. I went through the data and found a lot of things, but these were things I thought were key to my recommendations. So I,
59 00:10:45.830 ⇒ 00:11:02.199 Fanu Sisay: have, one that’s broken out into 1A, 1B. I think 1A is much more immediate, fix to what can happen, and then 1B is more of a strategic long-term, recommendation, and then number 2 has to do with that, siloed dashers.
60 00:11:02.200 ⇒ 00:11:03.829 Fanu Sisay: problem. So yeah.
61 00:11:03.830 ⇒ 00:11:10.500 Fanu Sisay: the immediate solution. I think having, you know, DoorDash,
62 00:11:11.240 ⇒ 00:11:18.040 Fanu Sisay: Having access to real-time data from our grocery partner… er, from the grocery partners,
63 00:11:18.280 ⇒ 00:11:22.600 Fanu Sisay: allows for a huge fix in this, issue. So…
64 00:11:22.680 ⇒ 00:11:39.770 Fanu Sisay: when a customer is able to see on their DoorDash app that these items are actually, you know, at their, at the grocery store that they want to shop at, and maybe even some additional information there. So, you know, low in stock, or fully stocked for, you know.
65 00:11:39.930 ⇒ 00:11:50.629 Fanu Sisay: customers to have all the information necessary for them to make their grocery order, I think that would be super helpful. You know, there are some questions to this.
66 00:11:50.890 ⇒ 00:11:59.580 Fanu Sisay: you know, how well are groceries, keeping their inventory? I know it’s a bit more of a traditional business, and maybe not as,
67 00:11:59.810 ⇒ 00:12:00.599 Fanu Sisay: you know.
68 00:12:01.270 ⇒ 00:12:19.659 Fanu Sisay: kept up in the right way, and are they willing to sync their data with DoorDash? You know, specifically here, I think having partnerships with, you know, different grocery chains, being able to, you know, have that data in and out in real time would be great.
69 00:12:19.890 ⇒ 00:12:24.659 Fanu Sisay: And then long-term, the grocery space. I…
70 00:12:24.800 ⇒ 00:12:27.300 Fanu Sisay: You know, did some market research,
71 00:12:27.480 ⇒ 00:12:50.900 Fanu Sisay: I went with data that… based back in 2023 to stay similar to the time that this data was pulled. DoorDash had a 5% grocery market share, whereas, you know, big-time competitors like Walmart and Instacart were quite successful in this space. We know that, you know, when DoorDash was making grocery orders, those were almost 2x what they were seeing at that
72 00:12:50.900 ⇒ 00:12:56.669 Fanu Sisay: the Dash Mart, level. So we know that there’s value there, and there’s space for DoorDash to grow.
73 00:12:56.720 ⇒ 00:13:01.169 Fanu Sisay: So yeah, adding different kinds of features that are, you know.
74 00:13:01.180 ⇒ 00:13:09.929 Fanu Sisay: consumer-facing and friendly to the grocery space, I think would be a great strategy in, you know, growing that market share.
75 00:13:09.930 ⇒ 00:13:21.719 Fanu Sisay: having a scheduled recurring grocery delivery option. So, you know, most people want to get the same things, maybe bi-weekly or weekly, from the grocery store. Having those listed out in a, you know, easy go…
76 00:13:21.760 ⇒ 00:13:27.119 Fanu Sisay: You know, recurring state, hands-off, and allowing for customers to, you know.
77 00:13:27.240 ⇒ 00:13:42.580 Fanu Sisay: be a bit more, you know, they can expect that DoorDash is delivering their groceries bi-weekly, or however often they would like. Preferred substitutions. We know that a pain point was missing items. Having, you know.
78 00:13:43.130 ⇒ 00:13:57.810 Fanu Sisay: the next best item that a customer would want, right there, you know, alleviates that pain point, that issue that, you know, was leaving a lot of customers frustrated. And then DashPass, DoorDash’s,
79 00:13:57.940 ⇒ 00:14:04.790 Fanu Sisay: You know, loyalty program, having some perks within that, program, allowing for the grocery space to grow.
80 00:14:04.790 ⇒ 00:14:24.730 Fanu Sisay: And, you know, the questions here being, how open is the customer base to, you know, testing new verticals or features? You know, maybe, you know, humans are creatures of habit, maybe they’re more likely to go to another provider. How willingly are they to use DoorDash? That was one question I had.
81 00:14:26.400 ⇒ 00:14:40.220 Fanu Sisay: Okay, and then breaking down our silos. We know that right now, only about 0.3%, 6 dashes were, you know, familiar with both, spaces, and that’s only 40% in the grocery space, you know, a place we want to grow.
82 00:14:40.370 ⇒ 00:14:58.930 Fanu Sisay: and there’s a lot of potential vulnerabilities there, as I mentioned earlier. I think, you know, introducing a bonus pay feature for dashers who, in one singular session, you know, work, under both verticals, confirm orders under both verticals.
83 00:14:59.160 ⇒ 00:15:09.020 Fanu Sisay: I was kind of vague here, bonus vague, because I’m not 100% sure how the payment structure is, but, being able to, you know, reward dashers who
84 00:15:09.120 ⇒ 00:15:26.570 Fanu Sisay: confirm orders in both, spaces in one session, one week, whatever it may be, but, you know, incentivizing, dashers to work in both avenues. I think this helps consumers during those rush periods, confirming that they will get their orders, regardless of, you know.
85 00:15:26.690 ⇒ 00:15:37.930 Fanu Sisay: how… how many people are ordering, and then, more experienced dashers on the job allows for the merchant’s job to be easier. You know, they’re not guiding, new, new time,
86 00:15:38.070 ⇒ 00:15:43.940 Fanu Sisay: You know, dashers, or just, you know, not dealing with the stress that comes with those surges.
87 00:15:44.460 ⇒ 00:15:51.189 Fanu Sisay: So yeah, those were my three recommendations. I have an appendix in the back here with some of the data I pulled.
88 00:15:51.300 ⇒ 00:15:53.340 Fanu Sisay: But yeah, open to any questions.
89 00:15:55.450 ⇒ 00:16:06.410 Greg Stoutenburg: Yeah, cool! Thanks for walking us through that. Yeah, that, that’s really helpful. So, I have a couple questions, maybe you could just, just sort of, like, things to expand upon.
90 00:16:06.840 ⇒ 00:16:20.829 Greg Stoutenburg: One is, could you just say a little bit more about why dashers being siloed, as you put it, is a vulnerability? And maybe some alternative remedies? You know, so granting that it’s a vulnerability, then, what some alternative remedies might be?
91 00:16:21.510 ⇒ 00:16:28.460 Fanu Sisay: Yeah, so… you know, I think of, you know, where I am now, currently in New York,
92 00:16:28.570 ⇒ 00:16:39.050 Fanu Sisay: different kinds of snowstorms that we’ve experienced in the last couple months, people are, you know, ordering groceries at mass. And with DoorDash only having,
93 00:16:40.070 ⇒ 00:16:44.999 Fanu Sisay: Yeah, 38% of their dashers in that, specific vertical.
94 00:16:45.380 ⇒ 00:16:46.880 Fanu Sisay: you know, I’d assume that, okay.
95 00:16:47.100 ⇒ 00:16:55.110 Fanu Sisay: the first group of people get their orders taken care of. But you know, when that is starting to overflow.
96 00:16:55.620 ⇒ 00:17:05.559 Fanu Sisay: you’re expecting a dasher to, you know, take care of one order, order, deliver that order, and then come back, and take, you know, more orders. I think
97 00:17:05.950 ⇒ 00:17:14.489 Fanu Sisay: You know, there’s an issue there with, you know, repeated, or, you know, a mass of people ordering, and a minimal amount of staff
98 00:17:15.859 ⇒ 00:17:18.919 Fanu Sisay: Able to handle that, specific, issue.
99 00:17:19.800 ⇒ 00:17:28.859 Greg Stoutenburg: Okay, so if you could get… so then the idea is that if you can get drivers to take both types of orders, then the store is more satisfied?
100 00:17:28.860 ⇒ 00:17:34.909 Fanu Sisay: Yeah, so introducing different kinds of incentives. So, you know.
101 00:17:34.910 ⇒ 00:17:50.389 Fanu Sisay: When… and this doesn’t have to be necessarily in that surge period, but having, you know, a new kind of, bonus pay that, hey, if you complete one, and this doesn’t necessarily have to be,
102 00:17:51.040 ⇒ 00:17:55.319 Fanu Sisay: Dash Mart and Grocery. You know, if you…
103 00:17:55.950 ⇒ 00:18:02.380 Fanu Sisay: Confirm one convenience order, and then you, confirm one.
104 00:18:03.480 ⇒ 00:18:20.300 Fanu Sisay: I don’t know why, grocery order, you get a specific bonus to that specific session. And that, you know, allows for… when that surge period comes in the future, you feel more comfortable to, you know.
105 00:18:20.650 ⇒ 00:18:37.880 Fanu Sisay: oh, I really only work in Dash Mart, but because of the bonus pay features the last couple months, I have worked in groceries. I see a ton of grocery orders coming in that I used to deny, and now, I’m happy to accept them because I know, one, how it works, and two, I get a bonus pay feature with that.
106 00:18:38.480 ⇒ 00:18:42.150 Greg Stoutenburg: Yeah, yeah, yeah. Okay, alright, fair enough.
107 00:18:42.940 ⇒ 00:18:44.540 Greg Stoutenburg: Where do I put my other comment.
108 00:18:44.930 ⇒ 00:18:45.940 Greg Stoutenburg: One moment.
109 00:18:48.050 ⇒ 00:19:12.870 Greg Stoutenburg: Cool. So, one of the things that you said is you… so you said you’d assume that the inventory shown in the customer’s app is out of sync with the store. And that seems… yeah, that does seem reasonable, right? That’s a… that’s a plausible reason why there’d be missed orders. Could you walk me through some of your reasoning toward that conclusion? And then what are your hypotheses about where the data issues
110 00:19:12.910 ⇒ 00:19:15.399 Greg Stoutenburg: Might exist, and, like, where would you look first?
111 00:19:16.110 ⇒ 00:19:21.040 Fanu Sisay: Yeah, so I think of the flow of… one,
112 00:19:22.050 ⇒ 00:19:27.100 Fanu Sisay: a customer opens their app and begins their order. And I think…
113 00:19:27.520 ⇒ 00:19:35.819 Fanu Sisay: Yeah, this table in the middle, is great. So, a customer opens their app and, confirms an order.
114 00:19:36.470 ⇒ 00:19:49.009 Fanu Sisay: I’m not 100% sure what the process is for a grocery store to send their data to Dash Martin and say, hey, we have these products available, we have, you know, X products not available, but
115 00:19:49.330 ⇒ 00:19:55.089 Fanu Sisay: When the customer opens their phone, and that item is there.
116 00:19:55.690 ⇒ 00:19:57.900 Fanu Sisay: By the time that,
117 00:19:58.350 ⇒ 00:20:11.650 Fanu Sisay: the dasher accepts the order and gets to the store, we know that, you know, 84%… 84.5% of the time for grocery number one, that those items aren’t there. And, you know, I think…
118 00:20:11.860 ⇒ 00:20:16.259 Fanu Sisay: To say that it’s an inventory-out-of-sync problem is…
119 00:20:16.810 ⇒ 00:20:21.720 Fanu Sisay: probably the only reason. I think… you know.
120 00:20:21.870 ⇒ 00:20:27.279 Fanu Sisay: It’s likely that at the beginning of every day, or at the beginning of every week,
121 00:20:27.520 ⇒ 00:20:32.780 Fanu Sisay: groceries inform DoorDash of what is in, inventory, and…
122 00:20:33.060 ⇒ 00:20:40.269 Fanu Sisay: it’s not as recurring as it needs to be in order for DoorDash to run correctly.
123 00:20:41.350 ⇒ 00:20:46.830 Fanu Sisay: I struggle to consider what other cases, you know, would cause
124 00:20:47.000 ⇒ 00:20:52.910 Fanu Sisay: for an item to be placed on the app when it’s not in store. Maybe it is,
125 00:20:53.240 ⇒ 00:20:57.910 Fanu Sisay: the Dasher’s struggling to, you know, find it in store. I think…
126 00:20:58.550 ⇒ 00:21:00.940 Fanu Sisay: you know, maybe… in that sense, I…
127 00:21:01.160 ⇒ 00:21:11.849 Fanu Sisay: the instructions are clear, you know, ask a, someone who works at the grocery store, in my opinion. But, you know, that is also slowing down these grocery orders, as well.
128 00:21:12.160 ⇒ 00:21:19.310 Greg Stoutenburg: So that’s another possibility, is that… is that, the dasher simply being unable to find something contributes to missed orders.
129 00:21:19.310 ⇒ 00:21:24.820 Fanu Sisay: Yeah, yeah, that is definitely another possibility for… Items not being found.
130 00:21:24.820 ⇒ 00:21:29.130 Greg Stoutenburg: You don’t think that’s as plausible, though, as the… as, like, a data sync issue?
131 00:21:30.680 ⇒ 00:21:31.930 Fanu Sisay: No, because…
132 00:21:31.930 ⇒ 00:21:34.730 Greg Stoutenburg: I’m suggesting that you should say that I’m not trying to lead you. I’m asking.
133 00:21:34.730 ⇒ 00:21:35.839 Fanu Sisay: Just conversation, yeah.
134 00:21:35.840 ⇒ 00:21:36.390 Greg Stoutenburg: Yep.
135 00:21:36.390 ⇒ 00:21:37.100 Fanu Sisay: I…
136 00:21:38.020 ⇒ 00:21:45.929 Fanu Sisay: I assume no, because there is staff at grocery stores, or at least, you know, in 2022, there was.
137 00:21:45.930 ⇒ 00:21:49.129 Greg Stoutenburg: Yeah, yeah, yeah, that wouldn’t be the explanation then, right?
138 00:21:49.130 ⇒ 00:21:55.129 Fanu Sisay: Yeah, and, you know, Though it’s still a reason for why
139 00:21:55.250 ⇒ 00:22:09.469 Fanu Sisay: grocery store, or these grocery orders aren’t running as smoothly, you know, you’re able to ask a staff member and say, like, hey, I can’t find this item. You know, it slows the order down, and it’s not running as smoothly, but
140 00:22:09.990 ⇒ 00:22:14.200 Fanu Sisay: I think that’s a less plausible reason for items not being found.
141 00:22:14.920 ⇒ 00:22:20.200 Greg Stoutenburg: Yeah. Okay. Now, as far as, as far as, like, data issues.
142 00:22:20.380 ⇒ 00:22:38.610 Greg Stoutenburg: being the cause of a customer seeing something in inventory in the app and saying, you know, I want these granola bars and not some other ones, and then, you know, then they’re not there. Where do you think those issues might arise, and where would you look first? So, say… say that you get to the point where you’ve pitched
143 00:22:38.740 ⇒ 00:22:52.690 Greg Stoutenburg: a leader who’s responsible for this, who’s responsible for this, and they’re like, I like what you’re thinking about, the idea that it’s an out of… it’s an inventory issue. Where should we begin
144 00:22:52.920 ⇒ 00:22:56.270 Greg Stoutenburg: To diagnose and then solve those problems.
145 00:22:57.860 ⇒ 00:23:00.420 Fanu Sisay: And, and that’s with speak… er…
146 00:23:01.230 ⇒ 00:23:03.280 Fanu Sisay: Yeah, so I think I would approach.
147 00:23:03.280 ⇒ 00:23:17.529 Greg Stoutenburg: I’m saying, let’s say they heard your recommendations and went, okay, this first one that you pointed to that you say you think is the biggest one that’s contributing to cancellation rates being unacceptable, where should we get started doing the work to fix this?
148 00:23:17.910 ⇒ 00:23:36.470 Fanu Sisay: I think a exploration of how these grocery stores are tracking their items. And, you know, that starts with, you know, what’s incoming and what’s outcoming, you know, the shipments that they get, and how they, the system of placing them out to show,
149 00:23:36.760 ⇒ 00:23:40.779 Fanu Sisay: you know, that’s where I ponder that
150 00:23:41.380 ⇒ 00:23:43.959 Fanu Sisay: You know, there’s probably much more traditional…
151 00:23:44.460 ⇒ 00:23:49.559 Fanu Sisay: hand-to-paper tracking of these items, for at least, like, you know.
152 00:23:49.790 ⇒ 00:24:06.739 Fanu Sisay: not the larger chain restaurants. And maybe that’s why we see Walmart… Instacart was one I made present on that slide, but Amazon was another big player in the space. It’s probably why they have success, is because they’ve, you know, automated these processes.
153 00:24:06.890 ⇒ 00:24:14.099 Fanu Sisay: you know, you’d hope that there’s automation behind those processes, but I think that’s another opportunity to introduce,
154 00:24:14.250 ⇒ 00:24:19.400 Fanu Sisay: you know, data keeping and AI, or whatever it may be, but,
155 00:24:20.000 ⇒ 00:24:25.179 Fanu Sisay: You know, a much better tracking system of how items are being, placed.
156 00:24:26.330 ⇒ 00:24:28.789 Greg Stoutenburg: Okay, yeah, fair enough.
157 00:24:29.130 ⇒ 00:24:43.070 Greg Stoutenburg: Cool, alright, one… Oh, yeah, here’s another one. Why do you think that the grocery… and maybe, maybe you said this and went over it just sort of quickly, and I just didn’t quite grasp it. Why do you think that the grocery vertical isn’t already stronger than it is now?
158 00:24:43.850 ⇒ 00:24:45.919 Fanu Sisay: For Jordath, or.
159 00:24:46.450 ⇒ 00:24:59.000 Greg Stoutenburg: Yeah, on here, when you’re comparing grocery to, to Dash Mart, and one of your recommendations was, here’s how we improve the performance of grocery, my question is just, you know, why do you think it isn’t already stronger?
160 00:25:03.610 ⇒ 00:25:10.710 Fanu Sisay: I think there’s… there’s bigger players in the space, so I…
161 00:25:10.990 ⇒ 00:25:21.930 Fanu Sisay: highlighted Walmart and Instacart here, and I, you know, think specifically about Walmart, you know, as much as it’s a, you know, superstore or whatnot.
162 00:25:21.930 ⇒ 00:25:34.410 Fanu Sisay: it’s a tech company as well, and they’re tracking, you know, their products much better. It’s also the fact that, you know, DoorDash is marketed as a, you know, to-go food section, and, you know.
163 00:25:34.410 ⇒ 00:25:42.509 Fanu Sisay: Dash Mart and Convenience Alcohol, they’re introducing new verticals, but, the grocery space, I don’t know if that overlaps
164 00:25:42.540 ⇒ 00:25:57.279 Fanu Sisay: perfectly with, people who are ordering food to go. And I think that that may be an issue. So, maybe these customers aren’t neces… or the potential customers in the grocery space aren’t necessarily using DoorDash.
165 00:25:57.280 ⇒ 00:26:08.569 Fanu Sisay: So I think those are all things to consider. Obviously, we need more information, data, research to, like, fully put a period on that, but those are reasons that I think of immediately.
166 00:26:08.960 ⇒ 00:26:12.640 Greg Stoutenburg: Yeah, okay, alright, very good. And then…
167 00:26:12.930 ⇒ 00:26:15.439 Greg Stoutenburg: I think my last question is,
168 00:26:15.870 ⇒ 00:26:30.189 Greg Stoutenburg: So, you’ve identified where we could get started doing the work and prioritize these interventions. What… have you given any thought to what the expected outcome would be if we did these things? Like, how much growth we might be expected to see? What the impact would be?
169 00:26:30.620 ⇒ 00:26:40.310 Fanu Sisay: I haven’t done much work around that, more so, or besides the fact that, you know, like, we’d like to see this num… this 5% grow,
170 00:26:40.520 ⇒ 00:26:46.110 Fanu Sisay: I think, you know, you can track that with dashboards, but specific metrics to,
171 00:26:46.170 ⇒ 00:27:04.129 Fanu Sisay: to track is, you know, amount of deliveries, here. And I think I’ve focused a lot on, this, like, percentage number, but I think specifically this, amount of deliveries, completed is what I…
172 00:27:04.320 ⇒ 00:27:20.859 Fanu Sisay: would care mostly about, because I don’t think it’s bad that Dash Mart is doing well, or, you know, has a high share. So I, you know, I think, you know, pushing for a higher share of deliveries isn’t necessarily the right thing to say, but pushing for more deliveries per month.
173 00:27:20.960 ⇒ 00:27:24.610 Fanu Sisay: And we know that, you know, this number…
174 00:27:24.730 ⇒ 00:27:29.509 Fanu Sisay: Is, you know, a big reason why we should do that, the average basket value there.
175 00:27:31.700 ⇒ 00:27:33.800 Greg Stoutenburg: Okay, very good.
176 00:27:34.120 ⇒ 00:27:40.300 Greg Stoutenburg: Cool, yeah, thanks, thanks for this. Amber, did you have any questions you wanted to… Put out here?
177 00:27:41.070 ⇒ 00:27:42.610 Amber Lin: Not really.
178 00:27:43.820 ⇒ 00:27:44.550 Greg Stoutenburg: Okay.
179 00:27:44.780 ⇒ 00:27:51.780 Greg Stoutenburg: Cool, fair enough. Well, I guess I’ll… I’ll turn it to you then, Family, if you want to… if you have any questions or any other thoughts.
180 00:27:52.330 ⇒ 00:28:03.000 Greg Stoutenburg: I think I’m pretty satisfied on our end, you know, we got the presentation, we were able to hear a little bit about your reasoning and what you would prioritize. So yeah, if there are other questions that you have, we could talk about them.
181 00:28:03.580 ⇒ 00:28:05.140 Fanu Sisay: Yeah, so, I guess…
182 00:28:05.560 ⇒ 00:28:15.859 Fanu Sisay: it’s kind of my fault for not asking this until the final round, but I was curious about the benefits that come with this role, specifically healthcare,
183 00:28:16.160 ⇒ 00:28:19.570 Fanu Sisay: Amongst other things. I… maybe you guys aren’t the best people to ask.
184 00:28:19.570 ⇒ 00:28:34.609 Greg Stoutenburg: Nope. Yeah, unfortunately, I don’t know what, what package may be offered, so I can’t really speak to that, but that’s, you know, depending on how things go, that might be something you could take up in a subsequent step.
185 00:28:34.990 ⇒ 00:28:37.769 Greg Stoutenburg: If you’ve been working with Kayla, you could maybe just email her instead.
186 00:28:37.890 ⇒ 00:28:40.789 Fanu Sisay: Yeah, completely understand. And…
187 00:28:41.740 ⇒ 00:28:53.669 Fanu Sisay: Sorry, I blanked for a second. Oh, yeah, another question I probably should have asked, how often are you guys working per week? Do you find yourself working on the weekends?
188 00:28:54.190 ⇒ 00:28:56.990 Fanu Sisay: Like, an hour total, but also, like, the days that you guys work.
189 00:28:57.440 ⇒ 00:29:10.770 Greg Stoutenburg: Yeah, reasonable question. I care about work-life balance as well. I… I have only… I mean, I’ve just been with Brainforge since January. I’ve only done anything on a weekend a few times.
190 00:29:10.960 ⇒ 00:29:30.399 Greg Stoutenburg: the… I mean, for the most part, it seems that people work overlapping hours between Eastern Time, roughly 8 to 6. And yeah, and I’ve never… I’ve never had anyone, like, ping me on a Sunday or something like that, and be like, this is urgent. But I also don’t Slack notifications on my phone, so…
191 00:29:30.400 ⇒ 00:29:31.270 Fanu Sisay: What?
192 00:29:31.270 ⇒ 00:29:39.060 Greg Stoutenburg: where I haven’t tried. So yeah, I haven’t had, I haven’t had issues or anything like that. I mean, I guess as far as just, like, you know, if we’re talking about, like.
193 00:29:39.460 ⇒ 00:29:46.280 Greg Stoutenburg: work, sort of, like, pace overall and cadence. Things do move pretty quickly during the day.
194 00:29:46.280 ⇒ 00:30:03.650 Greg Stoutenburg: But they’re also, like, resources, so… I mean, I’ll just give a story from, like, a week ago. I was… I had a few things that I needed to get out, and I had, like, a wall of meetings, and so, you know, I… I raised this to the CEO, and he just started getting stuff off my calendar, and then I was like, alright, cool, everything’s done by 5.
195 00:30:03.650 ⇒ 00:30:16.130 Greg Stoutenburg: So, you know, so that to say, you know, there’s the… like, expectations around speed are high, but also you can get support to make sure that, like, your workload is manageable. And,
196 00:30:16.130 ⇒ 00:30:35.880 Greg Stoutenburg: again, only been here since January, but anytime I’ve had someone say, like, hey, you know, I’m, like, at capacity on this thing, then it’s been, like, okay, I’ll help you prioritize, or, alright, let’s give this to someone else. I’ve never heard something like, well, then you need more capacity. So, yeah. Anyway, I’m just trying to re-emphasize, like.
197 00:30:35.950 ⇒ 00:30:40.519 Greg Stoutenburg: Lots of, you know, demand is high, but support is high as well, has been my experience.
198 00:30:40.960 ⇒ 00:30:44.950 Fanu Sisay: Sweet. And yeah, something I just noticed,
199 00:30:45.340 ⇒ 00:31:01.210 Fanu Sisay: you know, through my interview process. When I met with Kayla, she seemed like she was with a couple other Brainforge employees out in LA. Robert today is on-site. Are you guys traveling a lot, or is that an option?
200 00:31:01.510 ⇒ 00:31:02.090 Greg Stoutenburg: Yeah.
201 00:31:02.090 ⇒ 00:31:02.770 Fanu Sisay: Yeah, just curious.
202 00:31:02.770 ⇒ 00:31:16.459 Greg Stoutenburg: I mean, some folks travel for some things, I generally don’t know the specifics behind it. Like, I’m in Pennsylvania, Robert lives in New York, Utam lives in Austin, I forget where Amber lives, maybe she can tell us.
203 00:31:16.460 ⇒ 00:31:17.900 Amber Lin: I’m in LA with Kayla.
204 00:31:17.900 ⇒ 00:31:21.550 Greg Stoutenburg: That’s right, that’s right, you’re in LA. You were part of the LA meetup, that’s right.
205 00:31:21.620 ⇒ 00:31:44.499 Greg Stoutenburg: so there are some folks that live, like, relatively close to each other, and have gotten together for meetups and things like that. I could have, if my schedule had been more free, I could have gone to an event in New York City last week. So yeah. So some people have met up in person. I think it’s mostly like that. It’s less that we’ve got, like, you know, an annual trip or something like that, and more like…
206 00:31:44.520 ⇒ 00:31:48.549 Greg Stoutenburg: Oh, I’m gonna be out here for this reason already, some of you live in the area, let’s meet up.
207 00:31:48.830 ⇒ 00:31:52.609 Fanu Sisay: Sweet. Yeah. No, that sounds great. Much more casual.
208 00:31:53.170 ⇒ 00:31:59.749 Greg Stoutenburg: Yeah, yeah, yeah, no one’s, like, no one’s called into the office. There’s no office. Yeah. This is the office. Yeah.
209 00:31:59.750 ⇒ 00:32:00.930 Fanu Sisay: Sweet,
210 00:32:01.960 ⇒ 00:32:13.679 Fanu Sisay: Yeah, so I noticed with this role that there were a couple other roles, you guys were hiring for. Are you guys expecting to have, like, a cohort coming in? Yeah, I was just curious about that.
211 00:32:13.860 ⇒ 00:32:32.179 Greg Stoutenburg: I mean, so we’re just trying to, like, maintain… like, grow the team actively, but also maintain high standards, so, like, the hiring push is real right now. There’s not something like a structured program where, you know, we’re like, alright, we’re gonna hire 5 people, and they’re all gonna start May 1st, or something like that.
212 00:32:33.550 ⇒ 00:32:34.999 Greg Stoutenburg: Does that answer the question?
213 00:32:35.000 ⇒ 00:32:40.959 Fanu Sisay: Yeah, no, specifically that. I was just wondering if, like, there was a mandatory date that you guys were looking to have.
214 00:32:40.960 ⇒ 00:32:55.229 Greg Stoutenburg: Oh, oh, got it. Yeah, no, I, I mean, Brainforge speed is typically, like, what can we do right now? But I don’t, like… if there’s an underlying question around an ideal start date or something like that, I think that would just have to go to Kayla.
215 00:32:55.470 ⇒ 00:33:08.440 Fanu Sisay: Yeah, okay, sweet. But yeah, that was about it for me. Just want to reiterate how thankful I am speaking with y’all. It’s been great, and yeah, really appreciate all the consideration.
216 00:33:08.710 ⇒ 00:33:20.950 Greg Stoutenburg: Yeah, yeah, yeah, it’s been great talking with you. Cool, we’ll just… we’ll share the recording and comments with, with Robert, with Kayla, and then, yeah, I mean, you’ll hear something from Kayla, I guess.
217 00:33:21.300 ⇒ 00:33:23.120 Greg Stoutenburg: As soon as Robert has a chance to take a look.
218 00:33:23.120 ⇒ 00:33:27.799 Fanu Sisay: Yeah, and I’ll send this out in a PDF to the team, yeah.
219 00:33:27.800 ⇒ 00:33:34.150 Greg Stoutenburg: Very appreciated. Yeah, thanks. Awesome. Awesome. Alright. Good talking to you again. Alright, see ya.
220 00:33:34.280 ⇒ 00:33:35.110 Greg Stoutenburg: Bye.