Meeting Title: ABC | inspector sheet - ticketing system Date: 2025-08-08 Meeting participants: Casie Aviles, Uttam Kumaran, Amber Lin
WEBVTT
1 00:01:12.100 ⇒ 00:01:13.460 Uttam Kumaran: Hello!
2 00:01:14.360 ⇒ 00:01:15.170 Casie Aviles: Hey? Don!
3 00:01:15.690 ⇒ 00:01:20.260 Uttam Kumaran: Okay. So I just did not. Since you sent your message like.
4 00:01:20.880 ⇒ 00:01:23.897 Uttam Kumaran: whenever that was, I have not
5 00:01:25.160 ⇒ 00:01:31.180 Uttam Kumaran: taking a look. So let me just walk through your notes. So yeah, no problem.
6 00:01:32.820 ⇒ 00:01:40.190 Uttam Kumaran: Okay. So I’m just gonna pull B notion, Doc up.
7 00:01:55.630 ⇒ 00:01:57.809 Casie Aviles: I can also share my screen.
8 00:01:59.320 ⇒ 00:02:05.410 Uttam Kumaran: I think that’s okay. I have this dock up. So I saw we have these short term fixes here
9 00:02:05.930 ⇒ 00:02:11.380 Uttam Kumaran: so preventative action. So how many of the short term problems still remain.
10 00:02:14.118 ⇒ 00:02:16.769 Casie Aviles: Well, for now, like what I’ve done
11 00:02:16.990 ⇒ 00:02:21.940 Casie Aviles: for the sheet is I’ve implemented all of these this updated.
12 00:02:22.480 ⇒ 00:02:24.140 Casie Aviles: what do you call this formula.
13 00:02:24.470 ⇒ 00:02:25.080 Casie Aviles: Yeah, yeah, yeah.
14 00:02:25.670 ⇒ 00:02:29.819 Casie Aviles: So I’ve applied them and they should be good. Now.
15 00:02:30.645 ⇒ 00:02:36.170 Casie Aviles: just, you know, the things that I I just worry about are like, for example, here.
16 00:02:37.060 ⇒ 00:02:41.080 Casie Aviles: If you can, you’re are you currently looking at the screen by.
17 00:02:41.080 ⇒ 00:02:41.800 Uttam Kumaran: Yes.
18 00:02:42.030 ⇒ 00:02:45.780 Casie Aviles: So, for example, here, this particular zip code, right like
19 00:02:46.010 ⇒ 00:02:51.490 Casie Aviles: all here are from the satellite stable they’re getting from this table.
20 00:02:53.014 ⇒ 00:03:01.549 Casie Aviles: So same here. But then there’s like this is like a weird one, and then it it has to get from the pest table. So I had to change that.
21 00:03:02.210 ⇒ 00:03:08.755 Casie Aviles: And that’s like kind of the the issue with the setup of their
22 00:03:09.780 ⇒ 00:03:14.129 Casie Aviles: what they call this, of this of their format like for their sheets.
23 00:03:14.410 ⇒ 00:03:17.980 Casie Aviles: So there are sometimes things like this would happen where
24 00:03:19.229 ⇒ 00:03:27.620 Casie Aviles: when supposed to be like from just the satellite stable, and then out of the blue there will be one that needs to be from the pest table.
25 00:03:29.870 ⇒ 00:03:31.640 Uttam Kumaran: Hmm.
26 00:03:31.640 ⇒ 00:03:32.999 Casie Aviles: So I think those might.
27 00:03:33.000 ⇒ 00:03:38.340 Uttam Kumaran: But like, how do you like? My question is like the
28 00:03:38.570 ⇒ 00:03:43.059 Uttam Kumaran: like, we have the source sheet. Right? So you’re saying some of them the source sheet doesn’t have it.
29 00:03:45.280 ⇒ 00:03:46.049 Casie Aviles: Oh, you’re saying.
30 00:03:46.050 ⇒ 00:03:50.760 Uttam Kumaran: I think, for some of them. It’s not clear whether to go from the source sheet or the branch sheet.
31 00:03:51.990 ⇒ 00:03:53.196 Casie Aviles: Yes, yes.
32 00:03:54.260 ⇒ 00:04:01.699 Casie Aviles: let’s see. Yeah. So as you can see here, like with with Georgetown like it should, it should be like from the satellites.
33 00:04:03.097 ⇒ 00:04:07.359 Casie Aviles: Where’s the satellite stable? This is their table, by the way.
34 00:04:07.740 ⇒ 00:04:11.999 Casie Aviles: so as you can see it, it’s not here like 7, 8, 6, 3, 4
35 00:04:13.753 ⇒ 00:04:18.720 Casie Aviles: and then when you go to Atx, it’s going to be there.
36 00:04:21.620 ⇒ 00:04:23.130 Uttam Kumaran: Hmm.
37 00:04:23.130 ⇒ 00:04:27.869 Casie Aviles: So that can introduce some confusion like I had to spot that.
38 00:04:29.050 ⇒ 00:04:32.159 Uttam Kumaran: Okay, okay, makes sense. That’s 1 thing.
39 00:04:35.370 ⇒ 00:04:38.939 Casie Aviles: But yeah, I tried to sync as much as I can. So I went. I just
40 00:04:39.210 ⇒ 00:04:44.279 Casie Aviles: tested a lot. And based on, like, you know the the feedback that they gave
41 00:04:45.728 ⇒ 00:04:47.621 Casie Aviles: another thing, I guess that
42 00:04:48.680 ⇒ 00:04:55.190 Casie Aviles: it’s like for the syncing right? Like we mentioned that we could use import range
43 00:04:57.510 ⇒ 00:05:04.949 Casie Aviles: although right now I think one of the problems I have encountered there is I can’t
44 00:05:05.520 ⇒ 00:05:10.949 Casie Aviles: exactly import from this Inspector Zip code sheet
45 00:05:11.455 ⇒ 00:05:18.299 Casie Aviles: and I think that’s because it’s it’s in this format that they have. This is their sheet, the the one they use live
46 00:05:20.280 ⇒ 00:05:24.539 Casie Aviles: to compare that with another sheet that they have. This is also theirs.
47 00:05:24.650 ⇒ 00:05:30.560 Casie Aviles: This one is not an Xlsx format, and I was able to pull it this one.
48 00:05:31.930 ⇒ 00:05:37.959 Casie Aviles: and so I don’t think it’s also just a permission issue, because I already have like access here.
49 00:05:38.870 ⇒ 00:05:40.869 Casie Aviles: So I think it’s really their
50 00:05:41.730 ⇒ 00:05:44.140 Casie Aviles: it because of this format. I couldn’t, you know.
51 00:05:44.140 ⇒ 00:05:49.210 Uttam Kumaran: Oh, yeah, so it cannot be in that. Xlsx format.
52 00:05:49.710 ⇒ 00:05:56.309 Casie Aviles: Yeah. And this is their source. This is the one they use. So that, yeah, that that’s like a wall there for me.
53 00:05:57.170 ⇒ 00:05:59.590 Uttam Kumaran: Okay, I can ask them about that.
54 00:06:01.230 ⇒ 00:06:04.199 Casie Aviles: But yeah, I think so far, that’s pretty much
55 00:06:05.490 ⇒ 00:06:07.481 Casie Aviles: all I have for this.
56 00:06:08.330 ⇒ 00:06:13.480 Casie Aviles: yeah, most of it is just manual checking, verifying. So
57 00:06:13.650 ⇒ 00:06:17.200 Casie Aviles: like, I’m just thinking, like, maybe.
58 00:06:17.970 ⇒ 00:06:22.279 Casie Aviles: as part of like a broader or long term fix. Maybe we there should be like
59 00:06:22.550 ⇒ 00:06:30.239 Casie Aviles: a reevaluation of how we get the data from here, or make it easier so and less error prone.
60 00:06:32.410 ⇒ 00:06:33.719 Casie Aviles: If that makes sense.
61 00:06:34.290 ⇒ 00:06:41.023 Amber Lin: That that makes sense to me. Do you think if there’s a way, we can directly get the data from
62 00:06:41.820 ⇒ 00:06:44.880 Amber Lin: the team that handles these so maybe.
63 00:06:44.880 ⇒ 00:06:46.290 Uttam Kumaran: Yes, please.
64 00:06:46.290 ⇒ 00:06:47.220 Amber Lin: And not.
65 00:06:47.220 ⇒ 00:06:50.100 Uttam Kumaran: Where is this coming? Is this in a system somewhere.
66 00:06:50.440 ⇒ 00:07:10.220 Amber Lin: I don’t know. So like, I know that the team of. So the managers of these inspectors give updates of okay, this person had passed training they had. They handled this, and they send some zip codes in the email with this name. And then Janice and you said, updates this sheet.
67 00:07:10.640 ⇒ 00:07:20.280 Amber Lin: So I’m hoping that the service managers have it in the system, but they also might have it in excel. But I would love to get that
68 00:07:20.890 ⇒ 00:07:22.880 Amber Lin: if it’s cleaner than this.
69 00:07:23.340 ⇒ 00:07:32.830 Uttam Kumaran: Okay, that’s 1 good question. So we have both of those, I guess. Like, yeah, I want to figure out, I guess I’m I’m okay with both of those, Casey. And I’m I’m kind of okay with
70 00:07:32.940 ⇒ 00:07:34.999 Uttam Kumaran: where we are right now.
71 00:07:35.200 ⇒ 00:07:42.000 Uttam Kumaran: Okay, I think my question is about prevent prevention. So there’s kind of 2 levels of prevention. One is like
72 00:07:43.760 ⇒ 00:07:49.529 Uttam Kumaran: like logs are coming in right? So like today, there is
73 00:07:51.700 ⇒ 00:07:54.880 Uttam Kumaran: 7, 8, 0 6, 1 inspector commercial
74 00:07:55.000 ⇒ 00:08:02.340 Uttam Kumaran: for 7, 8, 0 6 1. There are no commercial pests, inspectors listed.
75 00:08:03.330 ⇒ 00:08:11.640 Uttam Kumaran: but then the feedback is service areas by branch. Zip Sheet says commercial pest is the only service, but no inspector is listed.
76 00:08:13.608 ⇒ 00:08:15.460 Casie Aviles: Yeah, this is on their side.
77 00:08:18.950 ⇒ 00:08:24.769 Casie Aviles: Yes, sir. I did check this so we could go right now. This is 7, 8 0 6 1.
78 00:08:25.090 ⇒ 00:08:25.890 Uttam Kumaran: Yeah.
79 00:08:31.200 ⇒ 00:08:34.890 Casie Aviles: Here. So 7, 8, 0 6 1.
80 00:08:35.380 ⇒ 00:08:41.289 Casie Aviles: So, yeah, there are. No, there’s nothing listed here, and then we can check the original one. This.
81 00:08:41.299 ⇒ 00:08:45.729 Uttam Kumaran: Yeah, let’s check the og, and you can. You can search across all sheets.
82 00:08:46.950 ⇒ 00:08:47.850 Casie Aviles: Oh!
83 00:08:48.260 ⇒ 00:08:48.770 Uttam Kumaran: But yeah.
84 00:08:48.770 ⇒ 00:08:53.023 Uttam Kumaran: control, do command F, and just search for it and then click on the dots and then do
85 00:08:53.980 ⇒ 00:08:56.350 Uttam Kumaran: search for it anywhere. Yeah.
86 00:08:57.230 ⇒ 00:09:00.310 Casie Aviles: Was that 7, 8, 0 6, 1.
87 00:09:00.310 ⇒ 00:09:01.190 Uttam Kumaran: Yeah.
88 00:09:03.440 ⇒ 00:09:04.690 Casie Aviles: Oh, sheets.
89 00:09:05.400 ⇒ 00:09:06.550 Uttam Kumaran: Yeah, okay.
90 00:09:08.100 ⇒ 00:09:13.380 Casie Aviles: Oh, see, yeah, that’s but this is for 3, though this is not for.
91 00:09:13.760 ⇒ 00:09:16.710 Uttam Kumaran: Yeah. So we’re we’re probably right. Right?
92 00:09:17.160 ⇒ 00:09:23.590 Uttam Kumaran: Oh, so the feedback is so literally, the feedback we got is that someone needs to be assigned.
93 00:09:23.760 ⇒ 00:09:24.550 Casie Aviles: Yes, someone.
94 00:09:24.550 ⇒ 00:09:26.200 Uttam Kumaran: Okay, so that’s a Denise.
95 00:09:26.680 ⇒ 00:09:27.510 Casie Aviles: Yeah.
96 00:09:28.280 ⇒ 00:09:29.330 Uttam Kumaran: Okay, great.
97 00:09:35.410 ⇒ 00:09:41.620 Uttam Kumaran: And then there’s so how about this? There’s like a question that’s like, Can Hile, can Hannah Wiley do a Wdi.
98 00:09:42.700 ⇒ 00:09:47.580 Casie Aviles: Okay? So that for that, the querying doesn’t work that way where we.
99 00:09:47.580 ⇒ 00:09:48.909 Uttam Kumaran: We look forward.
100 00:09:48.910 ⇒ 00:09:50.100 Casie Aviles: The name it clearly.
101 00:09:50.100 ⇒ 00:09:51.140 Uttam Kumaran: Well, yeah, yeah.
102 00:09:51.140 ⇒ 00:09:51.460 Casie Aviles: Thanks. Yeah.
103 00:09:51.460 ⇒ 00:09:53.620 Uttam Kumaran: Exactly. Name first.st
104 00:09:53.980 ⇒ 00:10:08.565 Amber Lin: I think that should be a let me check their other spreadsheets. There should be one pest directory. Let me check what they if they have okay, let me share this one. I’ll also share screen.
105 00:10:08.960 ⇒ 00:10:09.630 Casie Aviles: Okay.
106 00:10:09.840 ⇒ 00:10:12.100 Amber Lin: Check this one. So this
107 00:10:12.280 ⇒ 00:10:20.309 Amber Lin: I didn’t ask us to add this because they said this wasn’t the most updated but this is name
108 00:10:20.900 ⇒ 00:10:28.270 Amber Lin: what they are, and then the services they do. But I’ve heard that these are not that updated.
109 00:10:28.400 ⇒ 00:10:31.179 Amber Lin: So some of these are wrong and old.
110 00:10:31.530 ⇒ 00:10:41.160 Amber Lin: like ideally, we could maybe use this to assign assign zip codes, but this is by person.
111 00:10:42.730 ⇒ 00:10:49.449 Amber Lin: so that would be. Say, Oh, WDI
112 00:10:50.050 ⇒ 00:10:56.420 Amber Lin: gosh! I don’t know where the Wdi would be, but they will say.
113 00:10:57.450 ⇒ 00:11:00.660 Amber Lin: I think this is technicians. So sales.
114 00:11:01.540 ⇒ 00:11:09.710 Amber Lin: Yeah, okay, never mind. It doesn’t have the different items for sales, which is inspectors.
115 00:11:10.100 ⇒ 00:11:16.289 Amber Lin: But anyways, these are the names, and ideally we have names, and then the services they’re able to do.
116 00:11:17.800 ⇒ 00:11:19.900 Amber Lin: Anyways, that’s the other sheet.
117 00:11:31.280 ⇒ 00:11:31.980 Uttam Kumaran: Okay.
118 00:11:32.380 ⇒ 00:11:33.939 Uttam Kumaran: So I feel like,
119 00:11:41.830 ⇒ 00:11:45.560 Uttam Kumaran: I mean, I I feel kind of good. Otherwise with like the
120 00:11:48.370 ⇒ 00:11:52.309 Uttam Kumaran: with the changes. So it looks like we fixed all the problems. We haven’t gotten any feedback on it.
121 00:11:52.450 ⇒ 00:11:58.270 Uttam Kumaran: I do. I do think, overall amber. We should switch to using linear for triage.
122 00:11:58.430 ⇒ 00:11:59.720 Amber Lin: Yeah, I agree.
123 00:12:00.440 ⇒ 00:12:02.560 Uttam Kumaran: Do we want to try to set that up now.
124 00:12:03.620 ⇒ 00:12:12.130 Amber Lin: Yeah, I think for so for every message that comes into slack let me enable the triage status in ABC.
125 00:12:12.130 ⇒ 00:12:12.460 Uttam Kumaran: Like.
126 00:12:12.460 ⇒ 00:12:13.330 Amber Lin: Let’s
127 00:12:14.200 ⇒ 00:12:15.260 Uttam Kumaran: Let’s see if we can do that.
128 00:12:15.260 ⇒ 00:12:27.519 Amber Lin: Go into triage. Casey, I’ll need to help link the triage with with the slack ABC logs.
129 00:12:28.850 ⇒ 00:12:32.280 Uttam Kumaran: I think. Let’s see. Yeah, once you enable it. Let’s.
130 00:12:35.510 ⇒ 00:12:35.920 Amber Lin: Yeah.
131 00:12:35.920 ⇒ 00:12:37.590 Uttam Kumaran: Okay. Triage is enabled.
132 00:12:39.690 ⇒ 00:12:45.239 Uttam Kumaran: Enable triage for this team use rules to automatically process and route.
133 00:12:45.780 ⇒ 00:12:48.380 Amber Lin: That’s Enterprise Plan.
134 00:12:48.380 ⇒ 00:12:51.590 Uttam Kumaran: But what is what is audit? What does that even feature even mean.
135 00:12:53.920 ⇒ 00:12:55.240 Amber Lin: Don’t know.
136 00:13:02.940 ⇒ 00:13:13.039 Uttam Kumaran: Oh, so triage, configure, basics, create issues, take action, similar issues, triage routing
137 00:13:13.620 ⇒ 00:13:17.700 Uttam Kumaran: on enterprise plans, configure custom, rules.
138 00:13:22.610 ⇒ 00:13:23.620 Amber Lin: Hmm!
139 00:13:30.410 ⇒ 00:13:35.140 Amber Lin: Oh, can we set it in the triage status?
140 00:13:36.780 ⇒ 00:13:40.079 Amber Lin: Is that possible status? Name.
141 00:13:41.340 ⇒ 00:13:42.560 Casie Aviles: Outside of steam.
142 00:13:43.260 ⇒ 00:13:43.890 Amber Lin: Yeah.
143 00:13:44.510 ⇒ 00:13:46.860 Uttam Kumaran: Oh, I mean, we could probably just quickly.
144 00:13:46.860 ⇒ 00:13:47.900 Amber Lin: Oh, state name.
145 00:13:47.900 ⇒ 00:13:50.849 Uttam Kumaran: Happier, right or something, or you can do it here.
146 00:13:51.970 ⇒ 00:13:56.260 Casie Aviles: Yeah, this is the workflow that we have that again, that routes the.
147 00:13:56.260 ⇒ 00:13:57.390 Uttam Kumaran: Oh, 6!
148 00:13:57.390 ⇒ 00:13:58.350 Amber Lin: Oh no!
149 00:13:58.350 ⇒ 00:14:01.549 Uttam Kumaran: Really do this. But can you do a triage.
150 00:14:02.780 ⇒ 00:14:03.320 Amber Lin: There it is!
151 00:14:03.320 ⇒ 00:14:04.440 Uttam Kumaran: Don’t know, but it’s actually not.
152 00:14:04.880 ⇒ 00:14:06.199 Uttam Kumaran: Title triage. It’s
153 00:14:07.090 ⇒ 00:14:09.040 Uttam Kumaran: It’s status triage.
154 00:14:09.040 ⇒ 00:14:11.790 Casie Aviles: State name Jayaj. Here.
155 00:14:11.790 ⇒ 00:14:15.036 Uttam Kumaran: Oh, perfect, perfect! Yep, sorry you’re right.
156 00:14:15.830 ⇒ 00:14:16.890 Uttam Kumaran: Just catching up.
157 00:14:17.590 ⇒ 00:14:18.335 Casie Aviles: Okay.
158 00:14:25.290 ⇒ 00:14:28.020 Casie Aviles: I’ll just fill out the title.
159 00:14:31.800 ⇒ 00:14:36.909 Casie Aviles: but I’ll probably make a more dynamic one through the AI.
160 00:14:37.690 ⇒ 00:14:38.155 Amber Lin: Okay.
161 00:14:39.690 ⇒ 00:14:40.270 Amber Lin: Okay.
162 00:14:40.270 ⇒ 00:14:41.139 Casie Aviles: Can do something like that.
163 00:14:41.140 ⇒ 00:14:50.429 Amber Lin: The person that requested it, maybe the department in the title, and then that will make it nicer.
164 00:14:51.903 ⇒ 00:14:52.769 Casie Aviles: Yes. Okay.
165 00:15:04.810 ⇒ 00:15:05.510 Amber Lin: can we.
166 00:15:05.510 ⇒ 00:15:06.090 Casie Aviles: Later.
167 00:15:07.880 ⇒ 00:15:09.569 Casie Aviles: Sorry, like a date field.
168 00:15:09.720 ⇒ 00:15:13.499 Amber Lin: Yeah, I just want so that we don’t leave anything there for too long.
169 00:15:47.730 ⇒ 00:15:48.639 Casie Aviles: Yeah, okay.
170 00:15:57.270 ⇒ 00:15:59.929 Uttam Kumaran: Okay. So then, once it gets into triage.
171 00:16:00.270 ⇒ 00:16:07.220 Uttam Kumaran: like, basically, once a day, or once every other day, we can just triage assigned to Janice assigned to us, and then go from there.
172 00:16:07.756 ⇒ 00:16:10.439 Amber Lin: Okay, yeah, I like that.
173 00:16:28.330 ⇒ 00:16:34.769 Uttam Kumaran: And then eventually, Casey, I want to build an AI that, like kind of automatically suggests the fix.
174 00:16:36.880 ⇒ 00:16:37.610 Casie Aviles: Okay.
175 00:16:37.740 ⇒ 00:16:38.240 Uttam Kumaran: Right?
176 00:16:38.240 ⇒ 00:16:39.619 Uttam Kumaran: We can do that later.
177 00:16:40.800 ⇒ 00:16:41.810 Casie Aviles: Okay? Sure.
178 00:16:45.740 ⇒ 00:16:52.400 Casie Aviles: yeah. I think there was like a way there was like an AI step in the feedback. But yeah, I’ll have to revisit that
179 00:16:55.080 ⇒ 00:16:57.390 Casie Aviles: if we implemented something here.
180 00:16:58.520 ⇒ 00:16:59.160 Amber Lin: Okay.
181 00:16:59.890 ⇒ 00:17:02.729 Uttam Kumaran: So do is the is the triage thing hooked up.
182 00:17:05.520 ⇒ 00:17:11.670 Uttam Kumaran: So let’s just yeah, maybe we could just test this so that we can put that in email today that that’s working too.
183 00:17:12.920 ⇒ 00:17:13.560 Casie Aviles: All right
184 00:17:16.710 ⇒ 00:17:17.400 Casie Aviles: here.
185 00:17:28.349 ⇒ 00:17:37.469 Amber Lin: If I think our response times has gotten a little bit longer recently compared when we 1st implemented rag.
186 00:17:40.930 ⇒ 00:17:42.280 Casie Aviles: I’m about to check.
187 00:17:52.410 ⇒ 00:17:53.560 Amber Lin: Let’s see.
188 00:18:00.280 ⇒ 00:18:04.150 Amber Lin: Okay, we got the test feed back in slack.
189 00:18:04.910 ⇒ 00:18:06.729 Amber Lin: Let me see it right here.
190 00:18:20.210 ⇒ 00:18:27.050 Amber Lin: Oh, yay, yeah, we got it. It doesn’t show the time, but.
191 00:18:28.250 ⇒ 00:18:28.810 Casie Aviles: Oh, okay.
192 00:18:28.810 ⇒ 00:18:29.200 Amber Lin: Exciting.
193 00:18:29.200 ⇒ 00:18:29.910 Casie Aviles: The time.
194 00:18:30.350 ⇒ 00:18:32.370 Amber Lin: Yeah, it worked. That’s awesome.
195 00:18:38.070 ⇒ 00:18:38.700 Casie Aviles: Okay.
196 00:18:40.170 ⇒ 00:18:47.729 Amber Lin: Yeah, I have to hop soon. Which am I talking to, Emily in a bit? Do you have notes for her?
197 00:18:48.190 ⇒ 00:18:51.980 Uttam Kumaran: Yes, can I? You want me to just.
198 00:18:51.980 ⇒ 00:18:54.050 Amber Lin: You can just tell me, okay.
199 00:18:54.409 ⇒ 00:18:58.359 Uttam Kumaran: I’m gonna send. I don’t have the granola because I called.
200 00:18:59.585 ⇒ 00:19:01.910 Uttam Kumaran: I called her. But basically
201 00:19:02.260 ⇒ 00:19:21.439 Uttam Kumaran: she worked with David from superposition, worked for David. She worked at Ntt data and then a smaller healthcare, consulting firm, not exactly sure what she wants to fit into, although project management is probably the only actual like official title that we have. But she kind of has worked
202 00:19:22.385 ⇒ 00:19:33.410 Uttam Kumaran: on client. She’s managed clients. She’s also assisted in sort of general consulting operations, working really heavily with their boomer Ceos
203 00:19:33.830 ⇒ 00:19:39.969 Uttam Kumaran: consulting company. I think she’s seen like what a consult a company
204 00:19:40.424 ⇒ 00:19:46.039 Uttam Kumaran: like us can become like. She was kind of with them when they were pretty small, and then when they become really big
205 00:19:46.857 ⇒ 00:19:53.230 Uttam Kumaran: I think like Project Manager is really like the the main role we’re hiring for. But she could end up
206 00:19:53.610 ⇒ 00:20:11.080 Uttam Kumaran: going somewhere larger. She’s kind of a skeptical person, which I think was really good, like. She had a lot of questions for me about like how much money you guys making like, what’s the path like? What’s the goal? So I actually think she was curious. David really really recommended her
207 00:20:11.770 ⇒ 00:20:16.450 Uttam Kumaran: and she also comes from our field like, she works in data.
208 00:20:16.450 ⇒ 00:20:17.330 Uttam Kumaran: Yeah, updated.
209 00:20:17.330 ⇒ 00:20:21.500 Amber Lin: I think she should be someone that helps manage the company
210 00:20:22.760 ⇒ 00:20:29.890 Amber Lin: like there should be like, especially as Robert is. Gonna spend less time, or you have more stuff like
211 00:20:30.480 ⇒ 00:20:33.330 Amber Lin: maybe she can help you manage something.
212 00:20:34.510 ⇒ 00:20:38.709 Uttam Kumaran: I agree. I mean, I I think it’s I’d be curious to see like what
213 00:20:39.690 ⇒ 00:21:00.917 Uttam Kumaran: where she wants to fit in. I mean, we have this Pm. Role, but like she could come in and lead pro fleet delivery, she could do other stuff so but like, I think she’s earlier in her career where she wants to sort of still work with a lot of clients. But also she’s really she can clearly scrappy.
214 00:21:02.150 ⇒ 00:21:03.480 Uttam Kumaran: So.
215 00:21:04.110 ⇒ 00:21:07.630 Amber Lin: So would you consider her competition with Vinay?
216 00:21:09.376 ⇒ 00:21:10.429 Uttam Kumaran: Yeah, definitely.
217 00:21:10.660 ⇒ 00:21:12.760 Amber Lin: Okay, so that helps
218 00:21:15.150 ⇒ 00:21:23.999 Amber Lin: Agreement to her as established like this is our main like revenue driving function, and we want her to get get a set up and be scrappy and.
219 00:21:24.580 ⇒ 00:21:34.370 Uttam Kumaran: Yeah, I would just say that delivery is our number one priority. Now, you know. So like, whatever that means right now, that is like we have this sort of project management, but it’s also like
220 00:21:35.020 ⇒ 00:21:46.320 Uttam Kumaran: whatever that means. It is, however, also, I think she is still interested in like being involved in like recruiting in in marketing, but like
221 00:21:46.470 ⇒ 00:21:52.320 Uttam Kumaran: she probably just doesn’t want to be on the hook for that stuff like she was before, and that stuff is not like
222 00:21:52.760 ⇒ 00:21:56.629 Uttam Kumaran: like that stuff that over time should go to. Marketers shouldn’t be with people like our.
223 00:21:56.630 ⇒ 00:21:58.000 Amber Lin: Yeah, yeah. Tools.
224 00:21:58.000 ⇒ 00:22:13.906 Amber Lin: I think she knows better direction. Wise for our company. I think she’s a opposite of pros and cons for Vinay. I I think she’s very scrappy. She might not have that many processes, but she knows how it works for a company like us.
225 00:22:14.700 ⇒ 00:22:26.269 Amber Lin: like I for vine. I don’t know. I think she he will set up our Pm. Function as in how we do things, how we handle the different sops. But I don’t know if he’s gonna set
226 00:22:26.470 ⇒ 00:22:28.660 Amber Lin: goals for delivery.
227 00:22:28.890 ⇒ 00:22:29.460 Amber Lin: What
228 00:22:30.090 ⇒ 00:22:48.270 Amber Lin: thinking about goals for the company? Because that’s like setting goals for delivery needs one to think about what are goals for the company? What what do we want to achieve and like? It sounds like Emily knows better on that, and I don’t know how much Vinay has experience for that he seems very.
229 00:22:48.270 ⇒ 00:22:58.570 Uttam Kumaran: Yeah, I could see. I think I mean for me. I’m interested to hear about like what you find out about her goals like I sold her on the company. I think she’s I mean, I think she’s interested. I’m interested, like
230 00:22:59.540 ⇒ 00:23:03.909 Uttam Kumaran: she’s done all these random things like, what do you want to do. And also, yeah, I want her to be like.
231 00:23:04.160 ⇒ 00:23:16.249 Uttam Kumaran: not like, Oh, I’m going to be here so we can get our sprint rituals figured out. It’s like, no, the company wins when you join right like. So whatever figure out what part you can contribute to the company winning
232 00:23:16.560 ⇒ 00:23:44.179 Uttam Kumaran: whether that one day is delivery like Pm. Rituals. Then it’s more like portfolio understanding, say, like whatever it is, we should figure out like where she wants to fit the the blessing about a company like ours is like you can fit in multiple places like if she was. If she’s going to go to back to like an Ntt data or accenture. They’re going to put her in a role like with one title where you can’t do kind of shit outside of that.
233 00:23:45.580 ⇒ 00:23:46.779 Uttam Kumaran: So
234 00:23:47.160 ⇒ 00:23:50.669 Uttam Kumaran: that’s like what I’ve kind of pitched her on. But I also pitched her on the fact that
235 00:23:51.090 ⇒ 00:23:59.109 Uttam Kumaran: at her last company she someone had to take care of all that stuff, so she just did it, and was never really rewarded for it. And that company just got sold.
236 00:23:59.250 ⇒ 00:24:04.280 Uttam Kumaran: So she’s probably also probably pissed off that she didn’t make any money off, that I had to guess
237 00:24:04.470 ⇒ 00:24:11.780 Uttam Kumaran: I would be, especially if she was like a real big contributor. So those are kind of the things I learned.
238 00:24:13.380 ⇒ 00:24:14.350 Uttam Kumaran: Yeah.
239 00:24:15.290 ⇒ 00:24:17.430 Amber Lin: Okay, yeah, that’s good.
240 00:24:17.980 ⇒ 00:24:20.210 Amber Lin: That’s that’s what I need to know.
241 00:24:20.650 ⇒ 00:24:22.040 Uttam Kumaran: Okay, okay, perfect.
242 00:24:22.790 ⇒ 00:24:24.819 Uttam Kumaran: Alright. Let me know how it goes.
243 00:24:25.230 ⇒ 00:24:26.670 Amber Lin: Okay. Yeah.
244 00:24:27.570 ⇒ 00:24:27.910 Uttam Kumaran: You are.
245 00:24:27.910 ⇒ 00:24:29.569 Amber Lin: I’ll talk to you later today. Yeah.
246 00:24:29.570 ⇒ 00:24:36.360 Uttam Kumaran: Yeah, I’ll I’ll I’ll I can get an ABC note out. Once. This linear thing, if we can confirm. That’s all. Set up.
247 00:24:36.900 ⇒ 00:24:43.130 Amber Lin: Sure. Yeah, sure that that’ll be great. You can also send it to me, and I can send it in our in my like sprint update.
248 00:24:43.130 ⇒ 00:24:46.830 Uttam Kumaran: Oh, nice. Okay. I’ll just throw some. I’ll just throw something in the channel in.
249 00:24:46.830 ⇒ 00:24:48.239 Amber Lin: Yeah. Okay. Sounds, good.
250 00:24:48.240 ⇒ 00:24:49.969 Uttam Kumaran: Okay. Thank you. Bye.
251 00:24:49.970 ⇒ 00:24:50.780 Casie Aviles: Thank you.