Meeting Title: Zoom Meeting Date: 2025-05-05 Meeting participants: Robert Tseng, Amber Lin
WEBVTT
1 00:00:20.150 ⇒ 00:00:21.320 Amber Lin: Hello!
2 00:00:22.350 ⇒ 00:00:23.280 Robert Tseng: Amber.
3 00:00:28.090 ⇒ 00:00:30.930 Amber Lin: Alright, let’s get started.
4 00:00:31.590 ⇒ 00:00:35.820 Amber Lin: I saw the Google Doc. You said it’s so good.
5 00:00:37.940 ⇒ 00:00:39.690 Robert Tseng: Oh, thanks!
6 00:00:43.850 ⇒ 00:00:46.290 Robert Tseng: So I guess what would be helpful for this call.
7 00:00:50.500 ⇒ 00:00:53.509 Amber Lin: Here, let me pull both of them up.
8 00:00:53.820 ⇒ 00:00:54.939 Robert Tseng: I have it all. Yes.
9 00:00:56.020 ⇒ 00:00:56.560 Amber Lin: Hmm.
10 00:00:57.510 ⇒ 00:00:59.130 Robert Tseng: I have it on my screen as well.
11 00:00:59.430 ⇒ 00:01:00.270 Robert Tseng: Awesome.
12 00:01:04.160 ⇒ 00:01:07.249 Amber Lin: Are you gonna be on the call with boulevards tomorrow?
13 00:01:07.740 ⇒ 00:01:13.280 Robert Tseng: I can be. I I guess I don’t think it was very clear like, what
14 00:01:13.560 ⇒ 00:01:15.200 Robert Tseng: who is gonna drive that call.
15 00:01:20.160 ⇒ 00:01:23.810 Robert Tseng: I said it wasn’t clear to me who was gonna drive that call.
16 00:01:24.370 ⇒ 00:01:45.430 Amber Lin: Yeah, I I don’t know either. It’s probably going to either Betam, or if you join, maybe you as well, especially if you found all these insights so it’d be pretty helpful to drive that I know. They also wanted to talk about some AI capabilities. And
17 00:01:45.850 ⇒ 00:01:53.719 Amber Lin: last, like last time we talked there was also interest in, say, forecasting, etc, but
18 00:01:54.020 ⇒ 00:01:55.919 Amber Lin: that was a while ago.
19 00:01:56.040 ⇒ 00:02:02.720 Amber Lin: so it will be great if you have time to just join and walk them through some of this stuff.
20 00:02:03.770 ⇒ 00:02:08.340 Amber Lin: But I guess for me, like
21 00:02:08.530 ⇒ 00:02:19.009 Amber Lin: I can go through all of this documentation, but more so, I guess, as a Hmm.
22 00:02:20.150 ⇒ 00:02:25.119 Amber Lin: How do I? How do I take this and say, do it for more clients, I guess, is
23 00:02:25.310 ⇒ 00:02:30.600 Amber Lin: is what I’m interested in for this call, because I can go through all of the contents.
24 00:02:31.917 ⇒ 00:02:42.519 Amber Lin: For those documents. And maybe how did you approach doing this? Or if I were to do it for another client. How should I approach it?
25 00:02:43.830 ⇒ 00:02:44.580 Robert Tseng: Oh, gosh!
26 00:02:50.040 ⇒ 00:02:51.579 Robert Tseng: I’ll share my screens.
27 00:02:51.885 ⇒ 00:02:52.190 Amber Lin: Okay.
28 00:02:52.930 ⇒ 00:02:54.160 Robert Tseng: So
29 00:02:58.330 ⇒ 00:03:01.855 Robert Tseng: I guess I’ll just start on the side. So I mean, I did start with,
30 00:03:02.390 ⇒ 00:03:06.480 Robert Tseng: yeah, this outline that you had put together. I think I think it makes sense kind of like
31 00:03:09.440 ⇒ 00:03:13.820 Robert Tseng: I guess I kind of just added like sub bullets just kind of expand on.
32 00:03:13.820 ⇒ 00:03:14.440 Amber Lin: Hmm.
33 00:03:14.440 ⇒ 00:03:21.070 Robert Tseng: Some of these things that you had written. So yeah, I think like
34 00:03:21.410 ⇒ 00:03:29.740 Robert Tseng: starting like we have building up, having a process where we’re we’re coming
35 00:03:29.850 ⇒ 00:03:40.049 Robert Tseng: up with business questions. We’re able to quantify it for for them to kind of just get their sign off on like. Whether or not these are the are the the questions
36 00:03:41.050 ⇒ 00:03:49.820 Robert Tseng: to what? Which questions they’re they’re interested in answering and then, you know, structuring some analysis around how we go about that. So
37 00:03:50.238 ⇒ 00:03:54.979 Robert Tseng: yeah, I think like the before to now, like, I think you were right
38 00:03:55.010 ⇒ 00:04:17.440 Robert Tseng: before, we were just focused on establishing trustworthy data across all the business. I kind of added this up point like along the way, as you’re cleaning the data, you find some quick wins because you notice like really big discrepancies and data, so, you know, got some wins on shipping negotiations, saw that they were severely overpaying for
39 00:04:17.751 ⇒ 00:04:29.199 Robert Tseng: shipping in a couple of zones. And then some other like supply chain, like cogs. Optimizations. So yeah, that was like, that was kind of what I my understanding of the work that he had done.
40 00:04:31.400 ⇒ 00:04:53.139 Robert Tseng: and then, yeah, in order, like, now, I think the opportunity is kind of like as I’ve broken it down. So we’re want to get the and the have like. Do these exercises of assigning opportunity size to the questions that we bring to them? So it isn’t just coming to them with like, is this the right question? Is this an important question? It’s like
41 00:04:53.930 ⇒ 00:05:06.470 Robert Tseng: here we’ve already thought about the questions that I think are important. This is the size of the opportunity for answering this question like, what do you think? And it’s like? And we also not only do what you think, but we know
42 00:05:06.700 ⇒ 00:05:12.839 Robert Tseng: we think these are the levers that you can do to actually like influence, that like to answer that question
43 00:05:13.280 ⇒ 00:05:21.829 Robert Tseng: so as far as like order. For why? It needs to happen this way. I think market research is like necessary. Because that’s.
44 00:05:22.870 ⇒ 00:05:23.449 Robert Tseng: You know
45 00:05:25.320 ⇒ 00:05:36.830 Robert Tseng: whether or not you are accurate or not is, you know, I really, you know, some people, some some companies are doing market research, like at the Enterprise level. They’re doing this every
46 00:05:37.000 ⇒ 00:05:51.860 Robert Tseng: every 2 years, probably, like every every year or 2 years, that it takes like 4, 6 months like a really long drawn out process. You know, you could buy really expensive reports. You can engage consulting firms, or whatever to do this like full blown exercise for you.
47 00:05:52.130 ⇒ 00:06:02.089 Robert Tseng: I don’t personally think that the market here is that big. It’s I mean, it’s still maybe a possibly 1 billion dollar market. But I think it’s really just to get.
48 00:06:02.090 ⇒ 00:06:02.450 Amber Lin: I love.
49 00:06:03.570 ⇒ 00:06:05.869 Robert Tseng: With them on, like what
50 00:06:06.070 ⇒ 00:06:17.460 Robert Tseng: what they think the size of the market is, because then, if we can agree on the size of the total market. Then we can start to assign dollar amounts to the to the opportunities that we find.
51 00:06:18.043 ⇒ 00:06:29.059 Robert Tseng: And so I think, yeah, your framework made sense to me like, that’s how I’ve approached it before you. You get the tam, and then you get the I mean to me like
52 00:06:29.710 ⇒ 00:06:59.580 Robert Tseng: yeah, this the Tam Sam, and then I don’t, I guess for me this is just penetration. So it’s like, yeah, this is the total market. Given our current capabilities. This is the amount. This is the market that we could actually go after and so I’ve kind of like pre thought, like some of the limitations. For like, why are the Sam is is smaller than the tam and then, like, there’s an estimation exercise here of like this is how much we think we’ve really penetrated so far in this market, right?
53 00:06:59.580 ⇒ 00:07:00.350 Amber Lin: Yes.
54 00:07:01.320 ⇒ 00:07:25.119 Robert Tseng: And so being able to get that level of like alignments at like the channel level and at the regional level. I think is super important. For any like Cpg company. Because then, you know, like, if you’re early in the market, and there’s more growth, maturity to to when there’s more growth to be had there. If you’re not
55 00:07:25.300 ⇒ 00:07:29.800 Robert Tseng: touching on the right like, if there are other untouched markets.
56 00:07:30.308 ⇒ 00:07:38.459 Robert Tseng: new like new channels or new regions that are really sizable like that makes it an easy conversation to be like.
57 00:07:38.970 ⇒ 00:07:58.040 Robert Tseng: okay, so you’re focused on the Sun Belt states. Obviously. But like, what about maybe like the largest market outside of the Sun Belt states, for example? So anyway, I think that’s they may have already done a lot of this work already, because if they’re exploring an M. And A. I kind of imagine that they have to have some have done this.
58 00:07:58.040 ⇒ 00:07:58.400 Amber Lin: Actually.
59 00:07:58.400 ⇒ 00:07:59.660 Robert Tseng: To some extent.
60 00:08:00.267 ⇒ 00:08:05.920 Robert Tseng: So I mean, I don’t think these are necessarily the right numbers. Kind of like what you said the
61 00:08:08.350 ⇒ 00:08:11.590 Robert Tseng: I think these are I
62 00:08:12.730 ⇒ 00:08:26.149 Robert Tseng: typical insights that I would expect I would expect us to have an estimated Tam Sam, and then our current share. So that’s like the obvious one I would expect us to have, like a sense of our current product portfolio
63 00:08:26.440 ⇒ 00:08:28.847 Robert Tseng: within our product portfolio.
64 00:08:34.330 ⇒ 00:08:41.070 Amber Lin: Did you write all of this, or did you give, like Chatgp, the framework for it to come up with all of this.
65 00:08:41.544 ⇒ 00:08:52.119 Robert Tseng: I think I kind of went back and forth a lot, I mean, I think, I I mean, a lot of this was kind of like, Ppt, help me package things. But like, I kind of thought through like
66 00:08:52.720 ⇒ 00:08:55.120 Robert Tseng: the structure, I suppose.
67 00:09:05.190 ⇒ 00:09:09.314 Robert Tseng: yeah. So this is just kind of like, you know, doing
68 00:09:11.470 ⇒ 00:09:17.264 Robert Tseng: I mean this, this is stuff I just notes that I found from looking at their data. And then
69 00:09:19.110 ⇒ 00:09:25.428 Robert Tseng: yes, like within their portfolio. What are like? What does the distribution of their skews look like?
70 00:09:26.400 ⇒ 00:09:34.149 Robert Tseng: where are they performing? Well, okay. Or they’re over like, for example, they’re over indexed in pops. They have
71 00:09:34.410 ⇒ 00:09:40.187 Robert Tseng: a higher concentration of skews in like the pump category than other pool pool.
72 00:09:41.230 ⇒ 00:09:54.949 Robert Tseng: that other pool equipment, and maybe they’re under index in like, I mean, they don’t have any chemicals. They don’t do cleaning supplies. Yeah, I I’ve like looked at some of the other competitor sites and seen that.
73 00:09:57.470 ⇒ 00:10:04.579 Robert Tseng: I mean, yeah, they they really don’t offer that many skews. It’s clear it’s very clear to me that they started off really, just as pool pumps
74 00:10:05.230 ⇒ 00:10:11.480 Robert Tseng: and then, like, they’ve recently expanded into brushes. But anyway, so that’s
75 00:10:12.060 ⇒ 00:10:14.640 Robert Tseng: that’s kind of where the niche that they’re playing in.
76 00:10:14.980 ⇒ 00:10:15.430 Amber Lin: Hmm.
77 00:10:15.430 ⇒ 00:10:20.393 Robert Tseng: And then it’s also clear to me as far as like Channel dynamics.
78 00:10:21.010 ⇒ 00:10:25.639 Robert Tseng: okay, I mean, I don’t necessarily agree with this. This is just gpt stuff, but like
79 00:10:25.870 ⇒ 00:10:29.879 Robert Tseng: is it? Is shopify really strong conversion, like I don’t think so.
80 00:10:31.760 ⇒ 00:10:35.530 Robert Tseng: Well, it’s kind of like shopify owned channels
81 00:10:40.070 ⇒ 00:10:43.209 Robert Tseng: tends to drive higher.
82 00:10:45.120 ⇒ 00:10:46.420 Robert Tseng: Conversions.
83 00:10:51.420 ⇒ 00:10:52.790 Robert Tseng: But lower margin.
84 00:10:58.410 ⇒ 00:11:00.292 Robert Tseng: and that’s because
85 00:11:01.380 ⇒ 00:11:05.109 Robert Tseng: I mean, this is just kind of the case for any any type of business. But
86 00:11:05.979 ⇒ 00:11:12.810 Robert Tseng: when you’re on the marketplace, Amazon will promote promote you. You don’t have to go and get
87 00:11:12.950 ⇒ 00:11:18.689 Robert Tseng: like people searching to come into your site. There’s just a bunch of potential buyers in the marketplace already.
88 00:11:20.010 ⇒ 00:11:20.710 Robert Tseng: Yeah.
89 00:11:21.140 ⇒ 00:11:26.010 Robert Tseng: And then managed marketplaces, Amazon.
90 00:11:29.520 ⇒ 00:11:36.310 Robert Tseng: And to have more, you thanks.
91 00:11:37.140 ⇒ 00:11:49.562 Robert Tseng: View level parity performance barely due to like, you know, just really just like
92 00:11:53.540 ⇒ 00:11:58.260 Robert Tseng: I’m quite confident it is like
93 00:12:00.740 ⇒ 00:12:14.174 Robert Tseng: not being Fba or not being prime, like, I know, you know, Amazon docs you a lot if you don’t have. If you’re not like fulfilled by Amazon, and you don’t have time, you’ll you’ll never really get featured in the top listings. So
94 00:12:14.882 ⇒ 00:12:20.920 Amber Lin: One of their costs as well, so that contributes to their cost of having Fba.
95 00:12:20.920 ⇒ 00:12:24.880 Robert Tseng: Yeah, I mean, if they take a lot more, they take a lot more money that way.
96 00:12:27.330 ⇒ 00:12:28.080 Robert Tseng: Yeah.
97 00:12:28.910 ⇒ 00:12:32.849 Robert Tseng: But it’s kind of like Amazon forces you to behave like their best.
98 00:12:32.980 ⇒ 00:12:43.649 Robert Tseng: basically to behave like their best partner in order to like be featured, hired wholesale growth. I don’t know if they’re really doing wholesale.
99 00:12:43.880 ⇒ 00:12:47.220 Robert Tseng: so I won’t necessarily talk about that. Well.
100 00:12:47.220 ⇒ 00:12:47.800 Amber Lin: Hey!
101 00:12:59.070 ⇒ 00:13:00.310 Robert Tseng: Yeah,
102 00:13:06.040 ⇒ 00:13:17.920 Robert Tseng: And then, like another set of insights, could be something around the competitive landscape like you kind of under you. We would maybe see like I know, like the range, for, like the pricing range for pumps is quite
103 00:13:18.250 ⇒ 00:13:21.629 Robert Tseng: why, I mean they they positioned themselves as like a lower
104 00:13:22.467 ⇒ 00:13:25.149 Robert Tseng: lower price bump in the market.
105 00:13:25.770 ⇒ 00:13:26.690 Amber Lin: We’re in original.
106 00:13:26.690 ⇒ 00:13:35.199 Amber Lin: I don’t think they compete against the major players that target more like industrial buyers.
107 00:13:35.770 ⇒ 00:13:42.539 Amber Lin: I think they’re much more B to C, from what I understand. Yeah.
108 00:13:42.840 ⇒ 00:13:53.910 Amber Lin: So they’re going after the individual customers. That kind of want to get it for a little bit of a lower price, because they get their stuff from Asia, or they manufacture it themselves.
109 00:13:55.620 ⇒ 00:14:00.081 Robert Tseng: Yeah. Well, I guess what I learned was that this company based. They’re they’re
110 00:14:00.530 ⇒ 00:14:16.399 Robert Tseng: Their E-com site was pretty much just like a discounting platform. They would basically go and sell unused inventory for retail sites. And then eventually they went, and they built like their own pump, and they have a black and Decker
111 00:14:16.510 ⇒ 00:14:17.510 Robert Tseng: partnership.
112 00:14:17.700 ⇒ 00:14:23.621 Robert Tseng: which I mean, it’s clear that, like that, the value of the Black and Decker partnership has not
113 00:14:25.750 ⇒ 00:14:29.250 Robert Tseng: hell of its value over time, like you can see like
114 00:14:29.440 ⇒ 00:14:32.750 Robert Tseng: over time, like maybe search trends when black and Decker was added
115 00:14:33.790 ⇒ 00:14:40.549 Robert Tseng: much more pressure than the beginning. And then there’s like this drop off over the years. So which which makes sense. I don’t think any like
116 00:14:40.820 ⇒ 00:14:45.069 Robert Tseng: branded partnership like lasts forever in terms of like its value.
117 00:14:47.080 ⇒ 00:15:02.159 Robert Tseng: you know other entrants come into the market, you know. Black and Decker is not the only household name that said for the market, you know. Maybe their their pace of innovation has slowed down. So there’s a lot of different factors, for like, why, overall like interest in
118 00:15:02.700 ⇒ 00:15:05.674 Robert Tseng: in their product has has dropped.
119 00:15:06.600 ⇒ 00:15:08.940 Robert Tseng: yeah. So I think there’s a lot to be said there.
120 00:15:10.000 ⇒ 00:15:17.069 Robert Tseng: anyway. So like, I think, like, that’s, I mean, I’m just like walking through kind of the each of these exercises, but, like.
121 00:15:17.070 ⇒ 00:15:18.539 Amber Lin: Yeah, it’s really helpful.
122 00:15:19.030 ⇒ 00:15:19.649 Robert Tseng: Yeah. So
123 00:15:19.650 ⇒ 00:15:25.940 Robert Tseng: some of the recommendation, I mean, yeah, I mean, if you have any questions, you you let me know I have to walk through this whole sheet like, I kind of
124 00:15:26.400 ⇒ 00:15:27.959 Robert Tseng: everything in mind.
125 00:15:28.280 ⇒ 00:15:30.050 Robert Tseng: Yeah. Oh, yeah.
126 00:15:31.618 ⇒ 00:15:38.261 Amber Lin: We don’t have to go through the whole thing. I think it takes a while it it just of certain things. I guess.
127 00:15:38.840 ⇒ 00:15:51.359 Amber Lin: I have to also think about. Is this chat Gpt, or is this actually true? So I guess that’s the only thing I wanna make sure before I’ll make sure before we present to them tomorrow.
128 00:15:55.020 ⇒ 00:16:00.180 Robert Tseng: Yeah, okay, I mean, we can go. And I mean this, whenever you see numbers like, I wouldn’t really necessarily.
129 00:16:00.940 ⇒ 00:16:06.659 Robert Tseng: I mean, I I don’t know for sure. I would say it’s maybe like 6, 75% driven by like less than
130 00:16:06.800 ⇒ 00:16:08.700 Robert Tseng: just like 10 skis.
131 00:16:10.960 ⇒ 00:16:14.019 Amber Lin: Framework. Did you use to approach this?
132 00:16:14.560 ⇒ 00:16:20.809 Amber Lin: Because it helps us? It helps me know how I should approach other other clients as well.
133 00:16:21.380 ⇒ 00:16:27.609 Amber Lin: you know, for the market research we’re mostly in Tamsom, Tom, and then I guess a bit of
134 00:16:28.250 ⇒ 00:16:30.879 Amber Lin: bit of 5, 4 cents, maybe.
135 00:16:32.792 ⇒ 00:16:34.980 Robert Tseng: Maybe a little bit of 5 horses.
136 00:16:35.770 ⇒ 00:16:40.969 Robert Tseng: Yeah, I mean, I don’t. I don’t think I’m following anything like textbook. Necessarily anything. The slight.
137 00:16:44.850 ⇒ 00:16:51.719 Amber Lin: Things just pop up when you know when you know the that type of business, all things that would just pop up for you.
138 00:16:52.170 ⇒ 00:16:57.748 Robert Tseng: But just thinking about like what I had to do.
139 00:16:58.630 ⇒ 00:17:07.570 Robert Tseng: in pre in previous jobs. And yeah, so I kinda just piece that together.
140 00:17:09.540 ⇒ 00:17:10.540 Amber Lin: I, see.
141 00:17:15.619 ⇒ 00:17:23.459 Robert Tseng: I think it’s more important to ask these questions rather than show them that we have like this like well thought out plan, like, I only spent a couple of hours on this, but, like.
142 00:17:23.909 ⇒ 00:17:24.759 Amber Lin: I.
143 00:17:26.049 ⇒ 00:17:33.499 Robert Tseng: If I put this in front of him, and he has any questions about things like, I can speak to examples of work, of of analyses, or like
144 00:17:33.679 ⇒ 00:17:36.449 Robert Tseng: that that are in any of these categories.
145 00:17:37.230 ⇒ 00:17:49.220 Amber Lin: So we should prioritize the the questions also to get them thinking about it. I know that, but they depend on us a lot to do the thinking, but probably should start stimulating their brain as well.
146 00:17:50.520 ⇒ 00:18:02.419 Robert Tseng: Yeah, well, it’s kind of just getting a better sense of like, what? How much of this have they actually already? Have? They actually done. If not, we’re starting from scratch like it’s fine. But like I could speak to like.
147 00:18:03.050 ⇒ 00:18:13.429 Robert Tseng: you know, this one is really just being able to size opportunities. You know, the second one second group with maturity is like, okay, then we have to actually see, like, how much.
148 00:18:13.770 ⇒ 00:18:17.760 Robert Tseng: how much of each opportunity have we actually squeezed out?
149 00:18:18.510 ⇒ 00:18:19.580 Robert Tseng: And so.
150 00:18:19.800 ⇒ 00:18:27.499 Robert Tseng: yeah, I think this is really like, you know, skew level like, like benchmarking. Pretty much so.
151 00:18:28.052 ⇒ 00:18:37.369 Robert Tseng: There’s like growth benchmarks, maturity benchmarks, you know, there’s a concept of like velocity to to margin. That’s like something that’s important to CPU companies.
152 00:18:37.844 ⇒ 00:18:42.000 Robert Tseng: So those are kind of that. That was my starting point. And then I had gpt kinda
153 00:18:42.620 ⇒ 00:18:45.690 Robert Tseng: like I work with it to get to the rest of this.
154 00:18:47.870 ⇒ 00:18:53.309 Robert Tseng: yeah, I mean, these are just my kind of initial insights. They are not necessarily data back. These are just what
155 00:18:53.510 ⇒ 00:19:04.910 Robert Tseng: I think. The way that I was taught to do this stuff is like you do this outline, you kind of project what you think the recommendations are. You kind of fill it out as much to your best of the bill, your best of your ability.
156 00:19:05.641 ⇒ 00:19:12.500 Robert Tseng: Like. Yeah, I would align. I’m sure you’ve done this like. Then we would align on the app.
157 00:19:12.500 ⇒ 00:19:12.820 Amber Lin: Oh!
158 00:19:12.820 ⇒ 00:19:13.350 Robert Tseng: This.
159 00:19:13.690 ⇒ 00:19:22.270 Amber Lin: Hypothesis, and then try to prove it or to prove it wrong. But at least to start from a statement rather than Oh, this is possible. Everything is not possible.
160 00:19:22.600 ⇒ 00:19:29.740 Robert Tseng: Yeah. Yeah. And you, if you want, you want to be able to like, have a sense of like, what are the possible levers that you’re gonna be able to pull?
161 00:19:30.293 ⇒ 00:19:34.239 Robert Tseng: What are the insights that are gonna influence like, what decisions you make?
162 00:19:35.126 ⇒ 00:19:37.620 Robert Tseng: How do you get to those insights.
163 00:19:37.800 ⇒ 00:19:39.789 Robert Tseng: and then, like, you know what are like
164 00:19:40.100 ⇒ 00:19:42.579 Robert Tseng: at the very, at the highest level.
165 00:19:44.220 ⇒ 00:19:50.489 Robert Tseng: You know the the driving questions that will like kind of get, push, push you in that direction right.
166 00:19:50.640 ⇒ 00:19:51.500 Amber Lin: So actually.
167 00:19:51.500 ⇒ 00:19:57.900 Amber Lin: you start from actually the reverse of this document, and you start from the recommendations kind of work back.
168 00:19:58.830 ⇒ 00:20:09.609 Robert Tseng: I I think it kind of depends, like, sometimes, like, I don’t know what the right question is, and honestly like, whenever I’ve done these types of analysis, the question continues to change until, like the last week, I feel like.
169 00:20:10.124 ⇒ 00:20:17.919 Robert Tseng: sometimes you think you’re answering a question, and then along the way you realize you answered like a slightly different question of
170 00:20:18.370 ⇒ 00:20:25.709 Robert Tseng: Yeah, we’re not. So. I don’t always like start with the question first, st because I don’t think it’s always that obvious like, what the best question to ask is.
171 00:20:25.970 ⇒ 00:20:26.720 Amber Lin: Okay.
172 00:20:27.020 ⇒ 00:20:27.580 Robert Tseng: Yeah.
173 00:20:29.520 ⇒ 00:20:30.940 Amber Lin: Oh!
174 00:20:33.720 ⇒ 00:20:41.259 Robert Tseng: Yeah, I’ll just say a couple more things on the so diversification. This is just like, this is more like a portfolio analysis. So if you’ve heard.
175 00:20:41.570 ⇒ 00:20:45.470 Robert Tseng: had done something like that, then, yeah, that’s kind of
176 00:20:45.620 ⇒ 00:20:55.307 Robert Tseng: but this really is and then time to listening, I think, is important, too. This is just like giving them a sense of like, how fast is their product development cycle?
177 00:20:55.610 ⇒ 00:20:56.190 Amber Lin: Hmm.
178 00:20:56.360 ⇒ 00:21:01.131 Robert Tseng: Yeah, like, are they even measuring that at all is kind of like the point that
179 00:21:03.180 ⇒ 00:21:18.279 Robert Tseng: yeah. And you know, because if you know how long it takes for you to develop a skew to put it to market. Then you can have like a clear that you can set kpis on like launch X number of skews in these verticals or categories like quarter
180 00:21:19.580 ⇒ 00:21:30.537 Robert Tseng: then you’ll be able to forecast out every for every every launch of the skew. You kind of have a estimate on how that’s going to impact your your growth right? And
181 00:21:31.660 ⇒ 00:21:39.420 Robert Tseng: yeah, like. And it’s just gotta be like a continuous, like cycle of like launching, launching things in order to like sustain your growth over the long term.
182 00:21:40.110 ⇒ 00:21:45.110 Robert Tseng: It looks like the velocity is very slow, like as far as like. How.
183 00:21:45.740 ⇒ 00:21:52.610 Robert Tseng: Us. They put they put skews out. But yeah, I think this is probably where I I would.
184 00:21:52.860 ⇒ 00:21:56.900 Amber Lin: Where did you? How fast it was skews out? Do we have data on that.
185 00:21:58.284 ⇒ 00:22:08.880 Robert Tseng: I think it’s not really so. I mean, it’s not in our existing data. All we have is order level data. I don’t think we really have been measuring the development cycle of life, the product.
186 00:22:08.880 ⇒ 00:22:10.350 Amber Lin: Oh, okay.
187 00:22:10.710 ⇒ 00:22:12.210 Robert Tseng: Yeah, so
188 00:22:12.360 ⇒ 00:22:21.299 Robert Tseng: yeah, it’s really taking. Like, I like like idea to, you know, listing on the site, like, what are all the different phases there?
189 00:22:21.992 ⇒ 00:22:29.809 Robert Tseng: Like, how how fast does it take for us to go from the transition between those different phases? What are where the bottlenecks, you know?
190 00:22:30.290 ⇒ 00:22:34.619 Robert Tseng: Yeah, I have, like some questions, that kind of around around that.
191 00:22:38.120 ⇒ 00:22:45.939 Robert Tseng: yeah. And then the last one is really just more of like a distribution question, or this is more than one analysis. But, like.
192 00:22:46.300 ⇒ 00:23:02.390 Robert Tseng: okay, well, we have, you know, the B to C, we have some wholesale or retail partnerships. What are these other channels that we could explore, you know? Ha! What have we actually tried like? What’s what? What do we think? Besides, with each of these channels is
193 00:23:02.530 ⇒ 00:23:04.990 Robert Tseng: some recommendations around that.
194 00:23:05.430 ⇒ 00:23:15.340 Robert Tseng: But yeah, so I would really say, like, the goal of sharing this with him is to me like just to be able to ask these types of questions. Get him thinking about
195 00:23:17.300 ⇒ 00:23:23.860 Robert Tseng: Well, wanting to understand like what he’s what he’s done already. And
196 00:23:24.960 ⇒ 00:23:29.500 Robert Tseng: yeah, I mean, I, and then give examples of like, what does
197 00:23:29.670 ⇒ 00:23:36.470 Robert Tseng: strategic work in each of these different areas? Like, look look like, yeah.
198 00:23:37.260 ⇒ 00:23:37.990 Amber Lin: Cool
199 00:23:38.720 ⇒ 00:23:50.020 Amber Lin: sounds good, I mean, that’s all I that’s essentially all I need, because this is a pretty well fleshed out document, and we don’t need to be that detailed in this yet.
200 00:23:50.020 ⇒ 00:23:50.620 Robert Tseng: Yeah.
201 00:23:50.620 ⇒ 00:24:06.700 Amber Lin: Need to think. Learn how you think about these things, especially of, like my biggest takeaway to start from the like, what action, recommendation and work from okay, what insights do we need, and what analysis will contribute to that insight?
202 00:24:07.070 ⇒ 00:24:12.500 Amber Lin: And then, like along the way, work on the questions that will come up like that would be my biggest takeaway.
203 00:24:14.090 ⇒ 00:24:17.220 Robert Tseng: Okay. Yeah, no. I think that’s that’s a good. That’s a good takeaway.
204 00:24:17.430 ⇒ 00:24:24.060 Amber Lin: Yeah, cool. I’ll try to figure like along the way as I do these things, I’ll try to.
205 00:24:24.920 ⇒ 00:24:29.079 Amber Lin: What’s a like replicable document
206 00:24:29.400 ⇒ 00:24:36.519 Amber Lin: that I can produce, because ultimately I don’t want you to have to be this singular person that has to do this
207 00:24:37.210 ⇒ 00:24:39.449 Amber Lin: because this does take a lot of time.
208 00:24:42.860 ⇒ 00:24:44.497 Robert Tseng: Yeah, I mean, I I think,
209 00:24:46.840 ⇒ 00:24:57.707 Robert Tseng: we yeah. There’s probably, you know, a lot of more tweaking that we need to do to this in order to make sense of like how we reproduce it. But
210 00:24:58.840 ⇒ 00:25:07.750 Robert Tseng: But yeah, I mean, i i i want I want their feedback as well like, I know I haven’t. I’ve never talked to Dan myself. So I think, just be able to
211 00:25:07.920 ⇒ 00:25:11.430 Robert Tseng: get in front of him and give him a different yeah, like
212 00:25:11.700 ⇒ 00:25:19.379 Robert Tseng: a different view of like, what we think is like, how we can help moving forward. Like, I, just, I want to test test this out.
213 00:25:20.165 ⇒ 00:25:25.890 Robert Tseng: With him, and I don’t know like I don’t. I don’t know how he’ll how he’ll take it. But this is
214 00:25:26.550 ⇒ 00:25:30.429 Robert Tseng: at Ruggle Bowl. Like all my everybody there was like.
215 00:25:30.890 ⇒ 00:25:37.970 Robert Tseng: bane like this is straight out. This is probably just a bane framework, honestly, that, like where we had to start every analysis this way, so.
216 00:25:39.300 ⇒ 00:25:40.580 Robert Tseng: Yeah, wow.
217 00:25:41.680 ⇒ 00:25:44.010 Amber Lin: Wait is ruggable, like a consultancy.
218 00:25:45.174 ⇒ 00:25:50.690 Robert Tseng: It’s not. It’s it was like it was an E-com company spun out of bane ventures.
219 00:25:53.040 ⇒ 00:25:54.749 Amber Lin: Yeah. Awesome. Okay?
220 00:25:55.460 ⇒ 00:25:56.740 Amber Lin: Interesting.
221 00:25:57.050 ⇒ 00:26:01.029 Robert Tseng: Yeah. So everybody. Like most people, there were
222 00:26:01.970 ⇒ 00:26:05.999 Robert Tseng: mostly vain. And then No. 0 Mckinsey people like.
223 00:26:06.550 ⇒ 00:26:07.529 Robert Tseng: And then a few.
224 00:26:07.590 ⇒ 00:26:09.090 Amber Lin: What’s the difference?
225 00:26:09.090 ⇒ 00:26:12.109 Robert Tseng: A few. They’re like rivals, you know. They don’t hire each other.
226 00:26:12.110 ⇒ 00:26:13.729 Amber Lin: So if it’s like.
227 00:26:13.730 ⇒ 00:26:16.570 Robert Tseng: If it’s a Mckinsey ventures, they’ll never hire vain people, and then.
228 00:26:16.570 ⇒ 00:26:18.070 Amber Lin: Whoa!
229 00:26:18.070 ⇒ 00:26:20.150 Robert Tseng: Yeah, it’s just just like that.
230 00:26:20.540 ⇒ 00:26:21.730 Amber Lin: Ew, okay.
231 00:26:21.730 ⇒ 00:26:25.349 Robert Tseng: But Vcg is pretty neutral. Seems like everyone’s okay with Vcg.
232 00:26:27.130 ⇒ 00:26:30.420 Amber Lin: Maybe because they don’t take on Ops.
233 00:26:30.890 ⇒ 00:26:32.099 Robert Tseng: Yeah, that’s true.
234 00:26:32.660 ⇒ 00:26:43.179 Robert Tseng: But vcg, ventures launches a lot of digital businesses. I think they do better than I don’t think bane launches any digital ventures. They do stuff like this. Let’s just like
235 00:26:44.110 ⇒ 00:26:49.020 Robert Tseng: high margin consumer product or whatever. And.
236 00:26:51.880 ⇒ 00:27:02.179 Amber Lin: Cool. Okay, hopefully, you can join tomorrow. I I realize Otam already, added you, I was gonna ask you if you weren’t there. I mean if you have time, that would be great.
237 00:27:02.330 ⇒ 00:27:04.701 Robert Tseng: Yeah, no, I I’ll I’ll be there.
238 00:27:05.170 ⇒ 00:27:13.260 Robert Tseng: yeah, no, I I’m I’m excited. I would like to. I would like to do some of this work again like this is this gives me energy. Yes.
239 00:27:13.260 ⇒ 00:27:17.050 Amber Lin: Oh, really well, I mean, what type of work gives you energy?
240 00:27:19.920 ⇒ 00:27:22.780 Robert Tseng: I think I think strategy work.
241 00:27:22.960 ⇒ 00:27:23.720 Robert Tseng: I don’t ring.
242 00:27:24.510 ⇒ 00:27:28.049 Robert Tseng: Yeah, I’m I’m not an engineer. I don’t like data.
243 00:27:28.050 ⇒ 00:27:31.390 Amber Lin: End up doing sales if you like. Strategy.
244 00:27:32.588 ⇒ 00:27:40.219 Robert Tseng: I think I do sales because I like I I kinda I ha kinda have to. So.
245 00:27:41.850 ⇒ 00:27:53.515 Amber Lin: I feel so bad because I feel the same way. I just like strategy. I don’t like sales, but I was like I would do it, because that’s the only way I think we can survive.
246 00:27:54.230 ⇒ 00:27:59.139 Amber Lin: damn, you’re making a lot of sacrifices, Robert, because you do this really well.
247 00:28:01.030 ⇒ 00:28:03.480 Robert Tseng: Oh, well, I mean, it’s it’s just a
248 00:28:03.630 ⇒ 00:28:09.767 Robert Tseng: it’s just 1 1 muscle, like, I don’t think I want to be doing this all day. Like I, yeah. But
249 00:28:10.410 ⇒ 00:28:16.049 Robert Tseng: I think being able to have a to do varied things throughout my day is
250 00:28:16.230 ⇒ 00:28:18.130 Robert Tseng: more interesting to me. Yeah.
251 00:28:18.130 ⇒ 00:28:22.730 Amber Lin: Yes, okay, that’s that’s also good to know. Cause.
252 00:28:22.730 ⇒ 00:28:23.050 Robert Tseng: Yeah.
253 00:28:23.050 ⇒ 00:28:43.930 Amber Lin: Ultimately, if I if I start, if I I’m sort of planning out my cheapest at work and figuring out how I can help both of you. I’ve been mostly with talking, Tom, so I know what his day looks like. I have no clue what your day looks like other than I know that you do sales. So this is also really helpful.
254 00:28:44.670 ⇒ 00:28:48.952 Robert Tseng: Oh, I definitely a lot more hands on the client works than he than he is.
255 00:28:49.220 ⇒ 00:28:54.339 Amber Lin: Well, he hired me so he can escape. So now he doesn’t have to do client work.
256 00:28:55.250 ⇒ 00:28:59.990 Amber Lin: Maybe Jacob will join soon, and then you’ll be freed from client work as well.
257 00:28:59.990 ⇒ 00:29:00.550 Robert Tseng: Yeah.
258 00:29:00.900 ⇒ 00:29:10.390 Robert Tseng: no, I mean, I I’m not itching to be free from it like he is like, I I think it’s necessary, like we need to have. We need to push
259 00:29:12.540 ⇒ 00:29:15.880 Robert Tseng: like, yeah, if you want to talk about roles and stuff like
260 00:29:16.290 ⇒ 00:29:23.880 Robert Tseng: he likes to be the public base of the company and go and like talk to anybody and everybody about the business. That’s like what gives him energy.
261 00:29:24.475 ⇒ 00:29:28.160 Robert Tseng: For me, like I’m definitely a lot more process driven. So
262 00:29:28.660 ⇒ 00:29:36.450 Robert Tseng: when leads come in, like, I figure out how to close them and like so pricing strategy and then go to market operations. Stuff like that like that’s
263 00:29:36.730 ⇒ 00:29:44.690 Robert Tseng: to me. That’s just like one part of strategy. And like I, I enjoy the strategy for execution feedback loop like I like to do that
264 00:29:45.204 ⇒ 00:29:50.160 Robert Tseng: but it’s not like, I love cold emailing and whatever like, you know. So
265 00:29:50.590 ⇒ 00:30:03.759 Robert Tseng: and then, like with clients like, yeah, he likes. He likes to like talk, really technical systems design. And you know, he’s he’s a he’s. He’s a pretty senior engineering person like
266 00:30:04.633 ⇒ 00:30:12.059 Robert Tseng: but like I care a lot more about the account management? And like, how do we
267 00:30:14.040 ⇒ 00:30:18.252 Robert Tseng: yeah, like, how do we work with different stakeholders?
268 00:30:19.890 ⇒ 00:30:29.630 Robert Tseng: like, who do? We need to be on our on our side like, how do we grow? Accounts? Like, you know, stuff like that? Maybe he thinks about it more in terms of like tickets and like
269 00:30:31.530 ⇒ 00:30:41.109 Robert Tseng: engineering engineering points. But I I don’t think about it that way. So I’m just
270 00:30:41.660 ⇒ 00:30:46.053 Robert Tseng: I’m just interested in solving solves problems.
271 00:30:46.940 ⇒ 00:31:00.609 Amber Lin: How do you think I should approach less like what piece? Because you guys complement each other pretty well like, where do you think I should fit in, or I mean, there’s definitely influences of what do I like more? But
272 00:31:00.790 ⇒ 00:31:10.829 Amber Lin: like, I think at this stage, it’s like, what’s the biggest need like, what would you like? A constant reminder on? Or what do you function? What like you want me to fill.
273 00:31:12.260 ⇒ 00:31:18.089 Robert Tseng: Yeah, I mean, I I don’t think I have that answer for you. I think.
274 00:31:18.410 ⇒ 00:31:18.950 Amber Lin: That’s okay.
275 00:31:18.950 ⇒ 00:31:32.241 Robert Tseng: But I do know that you you spend a lot more. That’s why I was like willing to. We can spend some time, you know every every week like I want to. I don’t only want you to get perspective. I think it’s my point, because
276 00:31:33.950 ⇒ 00:31:42.455 Robert Tseng: Yeah, like, he obviously has a way of doing things that may or may not, you know, be helpful for you all the time in every situation.
277 00:31:45.500 ⇒ 00:31:58.585 Robert Tseng: I mean, if I were, you know I I kind of describe your role as like kind of chief of staff, or like kind of what what you would like to see you grow to and for me, like what a chief of staff does is
278 00:31:59.910 ⇒ 00:32:03.529 Robert Tseng: like, yeah, you start to think, like both.
279 00:32:04.490 ⇒ 00:32:07.429 Robert Tseng: I guess. Usually chief of staff at like a
280 00:32:08.140 ⇒ 00:32:11.379 Robert Tseng: organization, is is usually assigned to.
281 00:32:11.880 ⇒ 00:32:13.590 Robert Tseng: Actually, it’s like the.
282 00:32:13.590 ⇒ 00:32:14.720 Amber Lin: Person, right.
283 00:32:15.060 ⇒ 00:32:22.800 Robert Tseng: It’s usually one person, yeah, usually like a chief of staff to the Cmo or to the CEO or to the CEO. And there’s like more of like a discipline.
284 00:32:22.800 ⇒ 00:32:31.228 Amber Lin: I was asking about his schedule, and then he was like, Oh, this person is gonna answer. It was like Whoa.
285 00:32:32.530 ⇒ 00:32:33.430 Robert Tseng: Yeah.
286 00:32:34.100 ⇒ 00:32:42.080 Robert Tseng: So I I mean, that’s different. I feel like his chief of staff is.
287 00:32:42.080 ⇒ 00:32:43.739 Amber Lin: Like a assistant.
288 00:32:43.740 ⇒ 00:32:47.179 Robert Tseng: Yeah, it’s just an executive assistant. Totally not the same skill set.
289 00:32:47.520 ⇒ 00:32:51.149 Robert Tseng: I think it’s yeah cheapest that you kind of have to know, like which
290 00:32:52.540 ⇒ 00:33:10.130 Robert Tseng: I mean, I know you’re open to like learning a lot a lot of different things. So you just kind of figure out like what you feel like you want to grow in and like you kind of can learn the thinking in in that area. More so, I personally think, like, you know, obviously you have a Wb. Background, like
291 00:33:11.030 ⇒ 00:33:21.269 Robert Tseng: the strategy stuff is is valuable. You’ll take it with you wherever you are and you know you have your ui background as well. And so I mean I I would.
292 00:33:21.400 ⇒ 00:33:27.270 Robert Tseng: I think you should. You know it. It’d be great for you to be able to do that kind of like
293 00:33:27.540 ⇒ 00:33:34.989 Robert Tseng: account management stuff for for clients, if that’s what you prefer. But if you prefer to do more like
294 00:33:35.590 ⇒ 00:33:41.020 Robert Tseng: sales, focus, like doing Demos, getting technical proficiency, being able to
295 00:33:41.540 ⇒ 00:33:56.086 Robert Tseng: like, kind of do more of like the solution design the beginning, then that’s probably more with with Utah. So you kind of have to, I mean, I don’t know like I I think you have you. You can. You can obviously do both. But
296 00:33:58.099 ⇒ 00:34:08.219 Amber Lin: If I completely do one, it kind of limits my ability to think, to think in the other way. It’s just a matter of where I put my mindset.
297 00:34:08.389 ⇒ 00:34:32.389 Amber Lin: and so probably experiment and learn what I like. I think at this point, even for the solution design. There’s so much about it. I don’t know yet that I can’t say if I if I would like or don’t like, because my only objection to it now is that oh, I have no clue. What would go into that? It seems very technical.
298 00:34:32.750 ⇒ 00:34:38.879 Robert Tseng: Yeah. And I didn’t have that background at all, like I totally had to like, learn that stuff on the fly. I don’t think I’m good at.
299 00:34:38.880 ⇒ 00:34:39.230 Amber Lin: I did.
300 00:34:39.239 ⇒ 00:34:40.114 Robert Tseng: So.
301 00:34:41.689 ⇒ 00:34:48.139 Robert Tseng: But yeah, I I totally hear you. So I’m definitely a lot more comfortable doing this kind of work.
302 00:34:49.349 ⇒ 00:34:55.070 Amber Lin: Cool. Would you be open to say like a 1 on one each week? I call yeah
303 00:34:55.340 ⇒ 00:34:56.119 Amber Lin: week as well.
304 00:34:56.120 ⇒ 00:34:56.820 Robert Tseng: Of course.
305 00:34:57.517 ⇒ 00:35:01.720 Amber Lin: I’m looking at your calendar. Everything until Thursday is
306 00:35:01.950 ⇒ 00:35:09.300 Amber Lin: very busy. Are you more open on a Friday? Or do you want to keep that more free like. How do you want.
307 00:35:09.300 ⇒ 00:35:17.090 Robert Tseng: Oh, yeah, so I try not to do meetings on Wednesday afternoons. So that’s probably why you see a giant block there. But then.
308 00:35:17.539 ⇒ 00:35:22.490 Robert Tseng: yeah. Monday, Tuesday is pretty back yeah. Thursday or Friday would probably be better.
309 00:35:22.490 ⇒ 00:35:22.990 Amber Lin: Okay.
310 00:35:22.990 ⇒ 00:35:24.929 Robert Tseng: I would honestly say, Yeah, okay.
311 00:35:25.230 ⇒ 00:35:29.292 Amber Lin: Yeah, cause my Monday through Thursday is packed.
312 00:35:30.700 ⇒ 00:35:39.469 Amber Lin: Yeah. And usually I get some time to think about how I’m like how I’m doing this week, only on Friday, so
313 00:35:39.810 ⇒ 00:35:45.380 Amber Lin: I’ll say, either like my 11, or
314 00:35:46.020 ⇒ 00:35:51.530 Amber Lin: like around around that time, like my 11 o’clock should be, or 2 pm. I don’t.
315 00:35:51.530 ⇒ 00:35:52.400 Robert Tseng: Yeah, yeah.
316 00:35:52.400 ⇒ 00:35:55.956 Amber Lin: Be too late for you, so we can end Friday, like maybe early.
317 00:35:56.230 ⇒ 00:36:01.260 Robert Tseng: Yeah, that that I think that works that works for me. I think last thing I’ll say is like
318 00:36:02.720 ⇒ 00:36:08.289 Robert Tseng: So like Utah’s always kind of pushing the team to like. Think about, like how to scale things. I guess.
319 00:36:08.440 ⇒ 00:36:08.725 Amber Lin: Hmm.
320 00:36:09.010 ⇒ 00:36:14.870 Robert Tseng: I honestly think it’s I mean, I’m the other side. I do things that don’t scale like, which is.
321 00:36:15.450 ⇒ 00:36:20.979 Robert Tseng: that’s just kind of how I push it like, I’d rather us like, really understand? Like what we’re doing before we try to just like
322 00:36:21.110 ⇒ 00:36:42.099 Robert Tseng: build a system for whatever. So yeah, I think like that’s probably the perspective that I’d like to. Maybe coach you from more like as you’re as you’re like doing things like really wanting to go deeper into like, why, you’re doing what you’re doing. You know, like, I know, like the AI tools and everything kind of helps. But like.
323 00:36:42.662 ⇒ 00:36:48.090 Robert Tseng: yeah, I like, I think you’ve you’ve
324 00:36:48.670 ⇒ 00:36:52.490 Robert Tseng: like, I think ownership is kind of if you really
325 00:36:53.300 ⇒ 00:36:59.920 Robert Tseng: is. Is it just like in the like, do it for
326 00:37:00.740 ⇒ 00:37:06.599 Robert Tseng: is isn’t just about repeating, like, I think repetition is like one part of
327 00:37:06.750 ⇒ 00:37:10.560 Robert Tseng: of like understanding being able to like copy it to something else. But
328 00:37:12.120 ⇒ 00:37:14.689 Robert Tseng: yeah, I don’t know. I I think that
329 00:37:15.030 ⇒ 00:37:22.310 Robert Tseng: like really understanding a a problem and figuring out like
330 00:37:23.470 ⇒ 00:37:31.115 Robert Tseng: your way of approaching it and be able to system like, systematize your. The way that you think
331 00:37:31.730 ⇒ 00:37:37.850 Robert Tseng: is is important, right? Because then you’ll be able to build frameworks like stuff like this. Right? That’s not like
332 00:37:39.420 ⇒ 00:37:41.629 Robert Tseng: Oh, too reliant on
333 00:37:42.910 ⇒ 00:37:53.969 Robert Tseng: on AI tools, or like, you’re not worried so much about like whether or not it will, it will. It will scale. Like I I think there, it’s 2 different sides sides of the brain that I I think you kind of
334 00:37:54.380 ⇒ 00:37:55.720 Robert Tseng: need to work. Yeah.
335 00:37:56.720 ⇒ 00:38:04.909 Amber Lin: Totally. Because if I think about scaling, it’s not tailored to any problem, it’s more of, Hey, this is the way that
336 00:38:05.310 ⇒ 00:38:06.730 Amber Lin: probably will work.
337 00:38:07.080 ⇒ 00:38:07.420 Amber Lin: Yeah.
338 00:38:07.420 ⇒ 00:38:09.300 Robert Tseng: And you tend to take shortcuts.
339 00:38:09.580 ⇒ 00:38:10.230 Amber Lin: Yeah.
340 00:38:10.380 ⇒ 00:38:10.930 Robert Tseng: Yeah.
341 00:38:12.360 ⇒ 00:38:20.649 Robert Tseng: The the acceptance criteria for doing something repeatedly is is lower than if you like. Actually do do something. Yeah.
342 00:38:20.840 ⇒ 00:38:21.460 Amber Lin: Yeah.
343 00:38:21.460 ⇒ 00:38:22.000 Robert Tseng: Yeah.
344 00:38:23.470 ⇒ 00:38:28.990 Amber Lin: I like that quote, oh, okay.
345 00:38:34.270 ⇒ 00:38:41.277 Amber Lin: totally. I mean, that’s why mass production yields lower results. But do you? That’s something that we
346 00:38:42.200 ⇒ 00:38:45.779 Amber Lin: what? Where does it fit in for our business?
347 00:38:45.970 ⇒ 00:38:57.339 Amber Lin: So does it become. I’m thinking about scaling again. But because I’ve been only talking to Utop, does it? Does it mean like we train
348 00:38:57.530 ⇒ 00:39:08.109 Amber Lin: people to also do this thinking? Once you say, if you train me, I can go train other people on doing this as a really good individual contributor.
349 00:39:08.320 ⇒ 00:39:15.129 Amber Lin: or like, How how does this fit in? Because, ideally, as this business.
350 00:39:15.310 ⇒ 00:39:18.240 Amber Lin: it wouldn’t just be you or just me, me
351 00:39:18.580 ⇒ 00:39:20.940 Amber Lin: that’s able to do this right.
352 00:39:22.630 ⇒ 00:39:24.013 Robert Tseng: Yeah, I mean, I think
353 00:39:25.370 ⇒ 00:39:33.076 Robert Tseng: execution scales. Well, thinking doesn’t necessarily doesn’t scale. Well, that’s what I kind of. That’s my opinion.
354 00:39:33.530 ⇒ 00:39:34.340 Amber Lin: Yeah.
355 00:39:34.340 ⇒ 00:39:35.010 Robert Tseng: And
356 00:39:36.060 ⇒ 00:39:44.559 Robert Tseng: I think that’s okay, like I don’t. I don’t think which I was always talking about like raising the bar like teaching the team teaching the other people is
357 00:39:45.160 ⇒ 00:39:53.289 Robert Tseng: like I I maybe I have more of a pessimistic view of people’s aptitude. But, like I think, depending, I I think it’s clear to me, like
358 00:39:54.660 ⇒ 00:39:56.700 Robert Tseng: certain people have like
359 00:39:57.870 ⇒ 00:40:02.619 Robert Tseng: there’s just more elasticity like they can. They can. They can learn and absorb a lot more.
360 00:40:02.940 ⇒ 00:40:03.530 Amber Lin: Hmm.
361 00:40:04.060 ⇒ 00:40:16.349 Robert Tseng: Across disciplines. They they actually want to learn thinking. But I think you’ll maybe the longer you stay in the workforce you’ll realize that most people don’t want to actually think they just want to like do stuff they just want to like.
362 00:40:16.760 ⇒ 00:40:24.019 Robert Tseng: do a job. And just like do this same thing like they. They kind of just want to switch their brain off. And it’s like and do it. So
363 00:40:24.900 ⇒ 00:40:26.040 Robert Tseng: I think it’s
364 00:40:26.830 ⇒ 00:40:38.999 Robert Tseng: when when we think about scaling. We’re catering to those people. We’re trying to make something a task as thoughtless as possible so that somebody else could do it. You’re like lowering the barrier to entry to do it, which is.
365 00:40:39.000 ⇒ 00:40:42.982 Amber Lin: Oh, my God! That is a crazy insight!
366 00:40:45.810 ⇒ 00:40:55.199 Robert Tseng: Which I think is helpful, because it does mean that, like, you’re enabling people to do work higher than what they would have like come to on their own. But like.
367 00:40:55.580 ⇒ 00:40:58.069 Robert Tseng: yeah, like, we have to.
368 00:40:58.680 ⇒ 00:41:02.439 Robert Tseng: Yeah, like, don’t do it at the cost of your own thinking, you know. Like, if if you.
369 00:41:02.960 ⇒ 00:41:08.534 Robert Tseng: I think that’s that’s just like a that’s just like a constant tension or trade off that we have to make
370 00:41:09.390 ⇒ 00:41:10.620 Amber Lin: Wow, yeah.
371 00:41:10.840 ⇒ 00:41:20.029 Amber Lin: yeah, I was, I was just like, recently, I’ve been asking people around me. I asked Utam last week of the this exact problem.
372 00:41:20.470 ⇒ 00:41:22.849 Amber Lin: I was encountering cases where, like
373 00:41:23.850 ⇒ 00:41:27.929 Amber Lin: I was encountering that type of people I was like, why is this
374 00:41:28.090 ⇒ 00:41:35.900 Amber Lin: not like? Why can’t you think, or how do you not get this of? I’m encountering that problem of?
375 00:41:36.020 ⇒ 00:41:50.360 Amber Lin: They’re very fundamentally different in the way that they operate. And even as I interviewed everybody for the AI thing when I asked them about Okay, what do you think can be a way that you can like?
376 00:41:50.480 ⇒ 00:41:55.689 Amber Lin: Where do you think can be like even faster. Or is there something that you wanna
377 00:41:55.810 ⇒ 00:42:02.567 Amber Lin: accomplish this this quarter? And oh, gosh! Some of them are just so hard.
378 00:42:03.560 ⇒ 00:42:04.200 Robert Tseng: Yeah.
379 00:42:04.900 ⇒ 00:42:05.330 Amber Lin: Is.
380 00:42:05.330 ⇒ 00:42:07.220 Robert Tseng: It’s hard to teach thinking. Yeah.
381 00:42:07.220 ⇒ 00:42:12.050 Amber Lin: Yeah, like, I feel like I have to think for them. I was like, that doesn’t make sense.
382 00:42:12.950 ⇒ 00:42:13.560 Robert Tseng: Yeah.
383 00:42:15.410 ⇒ 00:42:29.349 Amber Lin: So how do you deal with that like when you encounter people like that? How do you communicate, if you like? If you kind of need them to do something where you feel like they just don’t get it. How do you deal with that emotion, or like, how do you solve that problem?
384 00:42:31.330 ⇒ 00:42:37.080 Robert Tseng: I think for me, it’s not. It’s not giving. It’s not always giving people the answer.
385 00:42:38.740 ⇒ 00:42:44.339 Robert Tseng: Yeah, I think that’s just letting people kind of like struggle through it a bit more.
386 00:42:46.430 ⇒ 00:42:53.930 Robert Tseng: Yeah, like, I think we become a crutch. If people just like escalate whatever they don’t know to to us, and they they never really think about it. So
387 00:42:54.370 ⇒ 00:43:03.609 Robert Tseng: I feel like, at least with the teams, that I work with more closely on clients. If there’s the same problem that’s come up multiple times. And the same person has asked me something similar before.
388 00:43:03.750 ⇒ 00:43:12.470 Robert Tseng: I won’t answer them directly. The the next time, like, I’ll probably take a bit longer so that they can try to.
389 00:43:13.320 ⇒ 00:43:15.379 Robert Tseng: I try to like, facilitate.
390 00:43:16.010 ⇒ 00:43:25.069 Robert Tseng: like I just ask questions back, really. And I think that’s a good way for me to like unpack, like where they’re blocked. And then.
391 00:43:26.260 ⇒ 00:43:27.399 Robert Tseng: yeah, just
392 00:43:28.080 ⇒ 00:43:51.839 Robert Tseng: let them kind of take their take their time to get to the conclusion. Obviously there are certain urgent, urgent things that just like need to be handled, and if I just have to handle them that I have to. But I would say more often than not, the urgency really is just my own insecurity or my own pride, that, like I need, I feel like it needs to be done. But it doesn’t actually have to be. I have to just trust, because that people will get it if we, if we
393 00:43:52.330 ⇒ 00:43:54.740 Robert Tseng: and get them. Give them a chance. Yeah.
394 00:43:54.740 ⇒ 00:43:57.390 Amber Lin: I see. So do you.
395 00:43:57.870 ⇒ 00:44:02.730 Amber Lin: How do you deal with that frustration? But do you just like.
396 00:44:02.880 ⇒ 00:44:10.160 Amber Lin: because I don’t want to be aggressive or passive, aggressive in any way to my team, but sometimes it just gets so frustrating.
397 00:44:10.540 ⇒ 00:44:23.170 Robert Tseng: Yeah, I mean, tell. I mean, you can tell me who, Tom? Honestly, I got you need to have an outlet. I know that like you don’t really have a peer right now, which I you know I’ve I’ve told you, Tom, just partly why I want to hire like Jacob or someone else like that.
398 00:44:23.676 ⇒ 00:44:29.600 Robert Tseng: Like, I want you to be able to. It’s tough being a Pm. Like I I can understand like I
399 00:44:29.920 ⇒ 00:44:36.824 Robert Tseng: before I mean, I I complain to. We talk, you know. So we we have. We have our outlets. And,
400 00:44:38.030 ⇒ 00:44:40.580 Robert Tseng: yeah, it’s not like we’re we handle
401 00:44:41.355 ⇒ 00:44:50.860 Robert Tseng: these frustrations. Well, so anything like I want, like my time regularly with you to be a space where you feel comfortable. I don’t just like
402 00:44:53.720 ⇒ 00:44:57.765 Robert Tseng: yeah processing through the frustrations that you’re experiencing as well.
403 00:44:58.350 ⇒ 00:45:08.639 Amber Lin: Most of the times it doesn’t like. Take that long. It’s just in the moment it it takes a little bit. I’m very most of the time, very aware of my emotions.
404 00:45:08.850 ⇒ 00:45:10.599 Amber Lin: So I can spell it out.
405 00:45:10.980 ⇒ 00:45:12.550 Amber Lin: Okay, yeah.
406 00:45:12.680 ⇒ 00:45:23.200 Amber Lin: But it’s really it’s really helpful that I didn’t even realize there was a necessary thing to have like a specific outlet outlet at work. I didn’t know. That’s how things worked.
407 00:45:23.830 ⇒ 00:45:51.980 Robert Tseng: Yeah, yeah, no. I I think part of like being able to bring your full self to work. And I think you know, that’s kind of hard to think of what that’s like in a remote company as well. So yeah, I think, whatever you feel like, it’s helpful for you like. I know you have Hannah in la like do you want to do in person stuff for? Or you know, I mean who I don’t know who you feel it’s kind of up to you like who you feel comfortable talking to as well. I’m sure you maybe talk to your partner, or you know people outside of work as well.
408 00:45:51.980 ⇒ 00:45:52.420 Amber Lin: I’ll.
409 00:45:52.420 ⇒ 00:45:52.930 Robert Tseng: Oh!
410 00:45:52.930 ⇒ 00:46:01.319 Amber Lin: Share. So I’m comfortable talking about a lot of things it just. I’m not sure a lot of times if the person wants to hear it.
411 00:46:01.990 ⇒ 00:46:02.590 Robert Tseng: Oh!
412 00:46:02.800 ⇒ 00:46:10.890 Amber Lin: Yeah, I’m okay with talking about all these things. As long as they’re like they’re able to process it. Sometimes emotions are too much for people.
413 00:46:11.280 ⇒ 00:46:11.910 Robert Tseng: Yeah.
414 00:46:12.160 ⇒ 00:46:12.760 Amber Lin: Yeah.
415 00:46:12.760 ⇒ 00:46:15.890 Robert Tseng: Yeah, just definitely. Yeah. You know, there’s the
416 00:46:18.380 ⇒ 00:46:20.530 Robert Tseng: I’ve run into that, too. It’s not that I
417 00:46:21.230 ⇒ 00:46:27.550 Robert Tseng: feel like, I mean, I I kind of have to be cautious, because I’m I guess.
418 00:46:29.010 ⇒ 00:46:38.960 Robert Tseng: Like. I can’t talk bad about people at the company like that would be bad. I cannot talk bad about somebody to you like that would that would. That wouldn’t be good, you know. So.
419 00:46:38.960 ⇒ 00:46:40.960 Amber Lin: You’re at a different position. So.
420 00:46:40.960 ⇒ 00:46:41.340 Robert Tseng: Yeah.
421 00:46:41.420 ⇒ 00:46:42.440 Amber Lin: Different.
422 00:46:42.660 ⇒ 00:46:49.739 Robert Tseng: Yeah. So there’s I do have to like, be a bit careful. About it. I haven’t always done a good job about it, but I feel like I’m
423 00:46:50.050 ⇒ 00:46:51.860 Robert Tseng: hopefully learning better.
424 00:46:51.860 ⇒ 00:47:13.110 Amber Lin: To me like the company is so small that it just feels like a circle like it probably shouldn’t be a circle of friends, but it just feels very flat and tight knit, and you know the friends between each other. And then they’re okay again. Like to me, it’s venting I’ve I wrote to myself of like, Okay, if I feel really
425 00:47:13.570 ⇒ 00:47:21.170 Amber Lin: feel doubtful about a person, I probably should just book a 1 on one with them, because usually after I talk to them, I’m not pissed anymore. So.
426 00:47:21.170 ⇒ 00:47:21.790 Robert Tseng: Yeah.
427 00:47:21.790 ⇒ 00:47:32.449 Amber Lin: It’s it’s just venting like, if I talk about someone to you. I probably still think very good of them. It’s just a moment of frustration.
428 00:47:32.890 ⇒ 00:47:38.039 Robert Tseng: Yeah, no, I I get it. I I think that’s good that you have that agency to go. And
429 00:47:39.180 ⇒ 00:47:49.880 Robert Tseng: yeah, just reconcile with people directly. That’s definitely the best way to to do it, although not everybody is receptive, you know. So that’s also something you have to.
430 00:47:49.880 ⇒ 00:47:51.690 Amber Lin: That’s a fact as well.
431 00:47:51.900 ⇒ 00:48:01.451 Amber Lin: Yeah, biggest part right now, like throughout. I don’t want to take too much of your time, but overall up until now, like the biggest part I’ve learned is to have to
432 00:48:02.090 ⇒ 00:48:07.050 Amber Lin: drive shipping faster. So asking those
433 00:48:07.310 ⇒ 00:48:16.460 Amber Lin: questions and a lot of times they’re so like. They’re such awkward silence questions because you add, and people have just
434 00:48:17.020 ⇒ 00:48:28.960 Amber Lin: not done the work, or they know that they probably could have done more. So. It’s very, very awkward, but hopefully that doesn’t get personal.
435 00:48:29.720 ⇒ 00:48:37.039 Robert Tseng: Yeah, I would say, like on that. Ha! Kind of to lean into that more.
436 00:48:37.290 ⇒ 00:48:37.960 Amber Lin: Hey!
437 00:48:40.380 ⇒ 00:48:53.599 Robert Tseng: You know, I would see yourself as like the architect for the project, like, obviously, you’re not as I mean, you are writing a lot of the tickets, and you’re defining a lot of the requirements. You’re kind of like doing the work of the thinking and the vision of how it should be done. I guess.
438 00:48:54.363 ⇒ 00:49:00.609 Robert Tseng: Maybe your assumptions are wrong, but I think it’s good to come into like these meetings with a sense of like how
439 00:49:00.950 ⇒ 00:49:02.614 Robert Tseng: how it should go.
440 00:49:03.770 ⇒ 00:49:19.609 Robert Tseng: so obviously being like holding it loosely. Accepting that, you know, people work on different timelines. You may have make some incorrect assumptions. But if you come in with that mentality when people kind of give you silence, or they’re talking around trying to like skirt around like the questions that you’re asking.
441 00:49:21.880 ⇒ 00:49:25.810 Robert Tseng: Yeah, you’ll be able to like more confidently, be like.
442 00:49:26.150 ⇒ 00:49:35.769 Robert Tseng: okay, like, this is taking. This is taking a while. This is actually taking longer than I thought would be can can like. Do I? Do you give me permission to like
443 00:49:35.990 ⇒ 00:49:38.660 Robert Tseng: just name some of my assumptions?
444 00:49:38.850 ⇒ 00:49:41.310 Robert Tseng: I’m like what I think should have happened here.
445 00:49:41.430 ⇒ 00:49:52.869 Robert Tseng: and then you can talk to you, and you can spell it out. They may re react to that. Be like, Oh, it actually, wasn’t that smooth? This was like kind of the hang up. But I think people just have a hard time like articulating that
446 00:49:53.541 ⇒ 00:50:05.340 Robert Tseng: so sometimes like, that’s kind of how I do it. Like when I the tickets been stuck for a while like, I’ll just pull it up, and I’ll be like, okay. I thought it was just gonna go like this, this, that or whatever, and then build.
447 00:50:05.560 ⇒ 00:50:10.049 Robert Tseng: You know, you kind of play dumb in a bit kind of, in a sense, and if you have this.
448 00:50:10.210 ⇒ 00:50:20.160 Robert Tseng: if your ego can take it, or to just like, let let people be in a position where they’re correcting the assumptions that you’re making about what they’re about, what they’re doing.
449 00:50:21.190 ⇒ 00:50:36.389 Amber Lin: Yeah, I found honestly, that’s such a good point, because I found that the more I did that the things faster things have went with like, with matter more and with the sales go to market. I kinda just. I just made an assumption doesn’t really work.
450 00:50:36.520 ⇒ 00:50:44.660 Amber Lin: but then it sort of saved the engineers from the 0 to one thinking, which they usually
451 00:50:45.000 ⇒ 00:51:04.280 Amber Lin: take very, very long on, and then they just correct me, and then we just test it. So the so that goes faster. But then, AI, I’m like, I just don’t think I I feel that confident probably am already like competent enough. But I don’t just. I just don’t feel that competent in the room of
452 00:51:04.490 ⇒ 00:51:14.249 Amber Lin: professional AI engineers to say, Hey, this is this is how things should get done. And so they kind of like push me around here and there, based on how they feel.
453 00:51:14.420 ⇒ 00:51:15.380 Robert Tseng: Wait.
454 00:51:17.110 ⇒ 00:51:17.940 Robert Tseng: Yeah.
455 00:51:18.140 ⇒ 00:51:23.519 Amber Lin: Yeah. So I’ll do that more. I think that’s a really good. That’s a really good takeaway to do.
456 00:51:23.520 ⇒ 00:51:29.029 Robert Tseng: Yeah, you’ll you’ll train your thinking. Your intuition will be sharper. You’ll know how to make better assumptions
457 00:51:29.220 ⇒ 00:51:32.909 Robert Tseng: like, that’s that’s a valuable skill, you know.
458 00:51:33.490 ⇒ 00:51:34.250 Robert Tseng: Yeah.
459 00:51:35.930 ⇒ 00:51:51.510 Amber Lin: Awesome, very exciting. This weekend I was thinking about. I was thinking about this this weekend as well of okay, what does my next role look like. I was collecting different job descriptions to kind of consolidate it down, and I know oh.
460 00:51:51.890 ⇒ 00:52:00.780 Amber Lin: tomorrow as well. So I’ll I’ll see what we can get to for tomorrow. I know we still have some offsite stuff that we haven’t gone through yet.
461 00:52:01.500 ⇒ 00:52:03.580 Robert Tseng: Cool, excited to hear what you have to say.
462 00:52:03.580 ⇒ 00:52:04.220 Amber Lin: Yeah.
463 00:52:04.940 ⇒ 00:52:05.500 Robert Tseng: Yeah.
464 00:52:05.500 ⇒ 00:52:07.818 Amber Lin: Okay, thank you so much for your time. It’s almost.
465 00:52:08.050 ⇒ 00:52:12.859 Robert Tseng: Thank you. Amber, you’re doing a great job. Yeah, really appreciate having you on the team.
466 00:52:14.010 ⇒ 00:52:30.980 Amber Lin: Thank you for hiring me at this job like it. Nothing has been painful. I feel like at 1 point some stuff will start to be painful just because it’s necessary, but just because there’s so much available stuff I’ve never. I haven’t done anything that’s painful yet.
467 00:52:31.280 ⇒ 00:52:41.390 Robert Tseng: Yeah, I I can make. I think things get painful. I’m sure they will. But I think so. I’ve never. I’ve I’ve never been bored at doing.
468 00:52:41.750 ⇒ 00:52:47.390 Robert Tseng: Yeah, because there’s always something that you can stretch into. That’s different from your exactly.
469 00:52:47.860 ⇒ 00:52:48.840 Amber Lin: Awesome.
470 00:52:49.210 ⇒ 00:52:49.810 Robert Tseng: Oh!
471 00:52:51.390 ⇒ 00:52:52.260 Amber Lin: Bye.