Meeting Title: Weekly Managers Meeting Date: 2025-07-09 Meeting participants: robert, Hannah Wang, Amber Lin, Uttam Kumaran
WEBVTT
1 00:00:18.360 ⇒ 00:00:19.650 robert: Hello!
2 00:00:21.790 ⇒ 00:00:23.280 Hannah Wang: Hello!
3 00:00:24.650 ⇒ 00:00:25.660 robert: How are you feeling.
4 00:00:26.970 ⇒ 00:00:35.489 Hannah Wang: I feel better now. I just had a really bad headache this morning, and then I felt really nauseous because of that. But I feel better now.
5 00:00:36.180 ⇒ 00:00:36.730 robert: Wow!
6 00:00:38.130 ⇒ 00:00:45.139 Hannah Wang: I think it’s cause I well, I didn’t have time to eat dinner yesterday, and went to an escape room.
7 00:00:46.440 ⇒ 00:00:47.690 robert: Oh! What!
8 00:00:48.850 ⇒ 00:00:56.069 Hannah Wang: For a brother’s birthday party birthday, basically in Cape Town. It was really fun.
9 00:00:56.850 ⇒ 00:00:58.270 robert: And know they had one of the tape back.
10 00:00:58.620 ⇒ 00:01:05.480 Hannah Wang: Yeah, it’s like the it’s like the best in the state or something. It’s like, really fun.
11 00:01:05.489 ⇒ 00:01:06.139 robert: People.
12 00:01:06.720 ⇒ 00:01:10.250 Hannah Wang: I think there’s like 8 to 9 of us.
13 00:01:11.970 ⇒ 00:01:12.560 Hannah Wang: But
14 00:01:12.560 ⇒ 00:01:17.709 Hannah Wang: I’m thinking of activities that we could do next week as well. That aren’t just eating and hanging out it.
15 00:01:17.710 ⇒ 00:01:22.480 Hannah Wang: Oh, my gosh! We should go to an escape room. They’re so fun! I really like them.
16 00:01:22.480 ⇒ 00:01:24.090 robert: Okay, I’m down. Yeah.
17 00:01:24.240 ⇒ 00:01:33.282 Hannah Wang: Yeah, I think Eric should have a list, because he researched him for like a bachelor party or bachelor thing, so you can ask him,
18 00:01:34.950 ⇒ 00:01:45.127 Hannah Wang: But yeah. And then, like we got ice cream after. So I guess ice cream was my dinner, and then, like, I came home at midnight, and I’m like so dead I’m ready to go home.
19 00:01:45.410 ⇒ 00:01:46.040 robert: Ow.
20 00:01:46.500 ⇒ 00:01:47.010 Hannah Wang: Yeah.
21 00:01:47.190 ⇒ 00:01:50.299 robert: But you’re still in your loft.
22 00:01:50.300 ⇒ 00:01:56.329 Hannah Wang: I’m still dog sitting. Today’s my last day. I can’t wait to sleep on my own bed.
23 00:01:56.960 ⇒ 00:01:59.049 robert: Oh! And then we got a dog sit again.
24 00:01:59.750 ⇒ 00:02:00.649 Uttam Kumaran: Yeah, for birdie.
25 00:02:00.950 ⇒ 00:02:04.599 robert: Some person, and we have to sit me.
26 00:02:06.210 ⇒ 00:02:12.737 Hannah Wang: You’re easier to sit because you kind of do your own thing, you know. So not a problem.
27 00:02:15.490 ⇒ 00:02:16.300 Uttam Kumaran: Hey, guys.
28 00:02:17.190 ⇒ 00:02:17.640 Hannah Wang: Hello!
29 00:02:17.640 ⇒ 00:02:18.100 robert: Hey!
30 00:02:19.516 ⇒ 00:02:25.620 Uttam Kumaran: So I made a pretty fat dent into this financial model. So I basically built
31 00:02:26.484 ⇒ 00:02:34.549 Uttam Kumaran: what we needed in terms of this like project. Month hours costs average rate revenue margin
32 00:02:34.990 ⇒ 00:02:41.609 Uttam Kumaran: in one view. Which is good. I will just share this, and we can
33 00:02:42.190 ⇒ 00:02:45.639 Uttam Kumaran: sort of take a look. It’s a little scrappy. I need to clean it up. But
34 00:02:46.300 ⇒ 00:02:48.599 Uttam Kumaran: that’s why I was 3 min late.
35 00:02:50.890 ⇒ 00:02:58.268 Uttam Kumaran: Also, I just realized, like, I’m better at financial modeling than our fucking accounts. So it’s kind of ridiculous. But whatever
36 00:02:58.850 ⇒ 00:03:00.220 Uttam Kumaran: it’s so sad.
37 00:03:01.790 ⇒ 00:03:08.269 Uttam Kumaran: In fact, the way they’re trying to model this is like so ugly. And I’m like.
38 00:03:08.580 ⇒ 00:03:10.900 Uttam Kumaran: Who is this supposed to be the expert here.
39 00:03:11.340 ⇒ 00:03:11.980 Amber Lin: Hmm, bye.
40 00:03:13.380 ⇒ 00:03:24.489 Uttam Kumaran: But okay, so you all should be able to see this.
41 00:03:25.010 ⇒ 00:03:26.517 Uttam Kumaran: So let me
42 00:03:28.130 ⇒ 00:03:32.170 Uttam Kumaran: Let me just walk you through what is going on here.
43 00:03:33.390 ⇒ 00:03:38.770 Uttam Kumaran: And then you can kind of get a sense of what I need to do.
44 00:03:44.030 ⇒ 00:03:47.959 Uttam Kumaran: One second, let me just pull out here.
45 00:03:51.260 ⇒ 00:04:01.349 Uttam Kumaran: Okay. So that’s let me just get out like a a big jam
46 00:04:01.970 ⇒ 00:04:05.610 Uttam Kumaran: to kind of share sort of like what the core.
47 00:04:07.560 ⇒ 00:04:11.020 Uttam Kumaran: You see the cooler way. I I model this. So
48 00:04:16.320 ⇒ 00:04:21.410 Uttam Kumaran: so we have kind of a couple of key sources.
49 00:04:21.589 ⇒ 00:04:23.380 Uttam Kumaran: We have clockify.
50 00:04:24.790 ⇒ 00:04:37.970 Uttam Kumaran: We have quickbooks, invoices. This is a revenue. We also have basically, like our active contracts.
51 00:04:39.470 ⇒ 00:04:48.300 Uttam Kumaran: This is manual and that is roughly it.
52 00:04:48.680 ⇒ 00:04:54.409 Uttam Kumaran: So basically, what I do is from.
53 00:04:55.010 ⇒ 00:04:58.840 Uttam Kumaran: we basically have these, as these are all like core
54 00:04:58.960 ⇒ 00:05:02.911 Uttam Kumaran: sources. So I create a table called like
55 00:05:04.195 ⇒ 00:05:12.499 Uttam Kumaran: If you see in financial models, you’ll see it at the far right called talkify time entries and quickbooks, voice actuals.
56 00:05:12.690 ⇒ 00:05:17.950 Uttam Kumaran: So, yeah, clock of files, time entries.
57 00:05:20.066 ⇒ 00:05:27.950 Uttam Kumaran: You. Then have quick books invoice actuals.
58 00:05:29.720 ⇒ 00:05:38.550 Uttam Kumaran: You’ll see that I’m bringing in the columns of I’m bringing in these columns for quickbooks. I’ll just paste them in here somewhere.
59 00:05:39.920 ⇒ 00:05:40.800 Uttam Kumaran: Yeah.
60 00:05:41.130 ⇒ 00:05:42.220 Uttam Kumaran: And I’m not.
61 00:05:47.400 ⇒ 00:05:48.590 Uttam Kumaran: I still don’t know what it is.
62 00:05:48.710 ⇒ 00:05:50.969 Uttam Kumaran: Oh, I’m so glad, you know.
63 00:05:51.350 ⇒ 00:05:53.980 Uttam Kumaran: Oh, okay, okay.
64 00:05:55.060 ⇒ 00:06:01.099 Uttam Kumaran: Bye, bye, oh, did not want them.
65 00:06:01.829 ⇒ 00:06:08.060 Uttam Kumaran: I’m just gonna roughly put in the columns in here, which is
66 00:06:08.750 ⇒ 00:06:15.839 Uttam Kumaran: transaction dates. I’m bringing in the amounts I’m bringing in the the client.
67 00:06:18.280 ⇒ 00:06:22.559 Uttam Kumaran: And then for clockify time entries.
68 00:06:29.598 ⇒ 00:06:35.770 Uttam Kumaran: Let me just double check I’m bringing in.
69 00:06:36.770 ⇒ 00:06:44.370 Uttam Kumaran: Yeah. So the client, the date
70 00:06:45.220 ⇒ 00:06:49.850 Uttam Kumaran: actually, we’re doing. We’re basically timestamped bringing in the hours.
71 00:06:52.700 ⇒ 00:06:56.280 Uttam Kumaran: Right? So the product. And then the person right, the team member.
72 00:06:59.880 ⇒ 00:07:05.359 Uttam Kumaran: so these are all here. The additional thing that we also have is active contracts. We also have active.
73 00:07:06.128 ⇒ 00:07:09.760 Uttam Kumaran: Active. We just also have payroll history.
74 00:07:10.878 ⇒ 00:07:16.159 Uttam Kumaran: So this will come into really in handy here because
75 00:07:16.889 ⇒ 00:07:26.750 Uttam Kumaran: we need to understand at any moment when someone bills time to Brainforge. We need to know what that time cost.
76 00:07:26.920 ⇒ 00:07:33.249 Uttam Kumaran: And so payroll history. This is getting us. Basically a table.
77 00:07:35.090 ⇒ 00:07:48.600 Uttam Kumaran: That’s here and payroll history as the team member like start and end date the rates
78 00:07:49.830 ⇒ 00:07:51.260 Uttam Kumaran: and their hourly rate.
79 00:07:51.820 ⇒ 00:07:54.569 Uttam Kumaran: So, therefore, for any hour booked
80 00:07:54.880 ⇒ 00:07:58.310 Uttam Kumaran: at any time, I know how much an hour cost.
81 00:07:59.353 ⇒ 00:08:06.650 Uttam Kumaran: And so these are like sort of the core sources for information. So this is.
82 00:08:06.860 ⇒ 00:08:10.189 Uttam Kumaran: this is active contracts, and so active contracts.
83 00:08:11.020 ⇒ 00:08:20.226 Uttam Kumaran: This includes the client name starts and and includes the
84 00:08:22.070 ⇒ 00:08:26.849 Uttam Kumaran: and includes the rates, and it also includes the billable name
85 00:08:27.110 ⇒ 00:08:31.929 Uttam Kumaran: and aliases, which is what I just spent the last hour trying to figure out.
86 00:08:32.506 ⇒ 00:08:43.247 Uttam Kumaran: So I’m gonna just these, these are like, you consider, these are the table names. We were to do this all in sequel, which this will get basically moved there soon.
87 00:08:44.780 ⇒ 00:08:58.449 Uttam Kumaran: so this is basically what we end up having so what I do is I bring everything is raw data, right? So these are all of our invoices that we’ve ever sent. This is. This is coming in from quickbooks.
88 00:08:58.887 ⇒ 00:09:03.649 Uttam Kumaran: I also have all of the time entries. This is coming in from clockify daily.
89 00:09:04.144 ⇒ 00:09:23.519 Uttam Kumaran: This will end up coming in daily, or something as well, I think, create clean versions of these where I’m actually creating helpful columns like columns that we’ll need to pivot on date, year, month, number month dates right? So that we can look at for a given time entry. What month was it attributed to
90 00:09:23.630 ⇒ 00:09:39.849 Uttam Kumaran: availability? Not so relevant right now, but I probably won’t pull it from here. But the other thing is to do. I can for any, for any given for any given hourly like booking. I can see that person’s rate.
91 00:09:40.390 ⇒ 00:09:50.010 Uttam Kumaran: And then I can also then look at the cost. So, for example, for a cost, he billed an hour 8, and so this hour cost us 64 80
92 00:09:50.200 ⇒ 00:09:54.229 Uttam Kumaran: And then the last thing I’m doing so let me let me just
93 00:09:54.500 ⇒ 00:09:58.158 Uttam Kumaran: stop there, and then I’ll just share. Similarly, we’re doing this on the
94 00:09:58.590 ⇒ 00:10:14.730 Uttam Kumaran: quickbooks invoices side. So I’ve cleaned quickbooks, invoices. These are all the invoices coming in. You can see like more information about the invoice, although this is not so relevant. We’re we’re breaking down different service revenue for the income statement. But it’s not certain in here.
95 00:10:15.410 ⇒ 00:10:34.029 Uttam Kumaran: but basically, I’m doing another thing. So I have the year, month, quarter. I also have coverage months. For example, we have some invoices. No longer is this happening, but we were sort of billing. For example, ABC, we billed late, and it was for like 2 months before. So I’m not really looking at the transaction date. I need like another month.
96 00:10:34.160 ⇒ 00:10:40.319 Uttam Kumaran: So we have a clean. We have a coverage month, which is like, what month did this cover Aka like
97 00:10:40.470 ⇒ 00:10:53.130 Uttam Kumaran: when you do revenue recognition? You need to recognize the revenue in the month of services rendered. So this just says, like this revenue is actually attributed to that, not even though we build them in
98 00:10:55.839 ⇒ 00:11:04.330 Uttam Kumaran: and then the last thing I’m doing is I’m getting what’s called a contracted name, basically final table that I’m building is
99 00:11:05.490 ⇒ 00:11:11.079 Uttam Kumaran: is something here where I need the I need the name of the client, the month I need the hours.
100 00:11:11.250 ⇒ 00:11:17.570 Uttam Kumaran: the cost, like how much we spent on it. You need the average rate for the folks for those hours.
101 00:11:18.172 ⇒ 00:11:22.800 Uttam Kumaran: I need the revenue that came in for that month.
102 00:11:23.130 ⇒ 00:11:32.080 Uttam Kumaran: client combo, and then we can calculate gross margin. So what I did is this is sort of where like, it’s a little bit tedious to do this here.
103 00:11:32.280 ⇒ 00:11:35.859 Uttam Kumaran: although it’s worth doing here first, st and I can reduce all the sequel later.
104 00:11:36.313 ⇒ 00:11:41.170 Uttam Kumaran: But we actually have all of our clients here, but we we have aliases meaning
105 00:11:41.420 ⇒ 00:11:46.729 Uttam Kumaran: in clockify and quickbooks, and in this sheet things are named differently.
106 00:11:47.254 ⇒ 00:11:53.279 Uttam Kumaran: Like matter. More Inc. Is actually who we bill to. But matter more is the name in
107 00:11:53.400 ⇒ 00:12:01.250 Uttam Kumaran: spotify and so we need to build a little bit of like an alias program where, like.
108 00:12:01.680 ⇒ 00:12:05.702 Uttam Kumaran: I can just say, like cool ABC can go by ABC home and ABC.
109 00:12:06.330 ⇒ 00:12:11.929 Uttam Kumaran: Does it for me. I need to be able to join on any of these to any of those sources.
110 00:12:12.520 ⇒ 00:12:18.409 Uttam Kumaran: So what happens at this point is, we have our active contracts here.
111 00:12:19.160 ⇒ 00:12:21.009 Uttam Kumaran: We have payroll history.
112 00:12:21.240 ⇒ 00:12:26.939 Uttam Kumaran: So what we do is we create. As I mentioned, we create clean
113 00:12:28.140 ⇒ 00:12:33.780 Uttam Kumaran: clockify time entries right, which joins these 2 together
114 00:12:36.420 ⇒ 00:12:44.759 Uttam Kumaran: great. And then we create oh, we create this.
115 00:12:45.680 ⇒ 00:12:51.816 Uttam Kumaran: And then active contracts actually comes into play here as well, and it comes into this thing called clean.
116 00:12:52.560 ⇒ 00:12:59.580 Uttam Kumaran: plain quickbooks, invoices, and this flows into here as well.
117 00:13:01.990 ⇒ 00:13:04.379 Uttam Kumaran: everyone kind of following a little bit.
118 00:13:07.450 ⇒ 00:13:11.428 Uttam Kumaran: So then, lastly, what? Lastly, what happens here is
119 00:13:12.390 ⇒ 00:13:20.950 Uttam Kumaran: We then can create basically monthly project margin, summary.
120 00:13:22.190 ⇒ 00:13:22.980 Amber Lin: Okay.
121 00:13:23.660 ⇒ 00:13:25.770 Uttam Kumaran: We should include the clients.
122 00:13:25.770 ⇒ 00:13:32.160 Amber Lin: No, you overall summary. Oh, sorry. Yes. Month. Per team. Member.
123 00:13:34.910 ⇒ 00:13:37.210 Uttam Kumaran: Oh, I don’t know if I brought that in.
124 00:13:37.210 ⇒ 00:13:42.069 Amber Lin: There’s there’s revenue and cost. I don’t. There wasn’t a team member last.
125 00:13:42.250 ⇒ 00:13:49.959 Uttam Kumaran: Yeah, so this one. So this one I just bring in hours revenue cost. And then gross margin
126 00:13:51.110 ⇒ 00:13:58.620 Uttam Kumaran: number and percentage is basically a calc.
127 00:14:00.402 ⇒ 00:14:03.230 Uttam Kumaran: and so this is the current
128 00:14:03.420 ⇒ 00:14:15.086 Uttam Kumaran: sort of process. We can now basically add any more dimensionality to this. Like, if you guys want to see for a specific client for specific month by person. You can do that.
129 00:14:16.050 ⇒ 00:14:21.879 Uttam Kumaran: And this this updates like quite dynamically, meaning like
130 00:14:22.150 ⇒ 00:14:29.824 Uttam Kumaran: as new time entries come in and new invoices come in. Stuff will just refresh like you don’t have to drag stuff. These are all like
131 00:14:31.900 ⇒ 00:14:35.099 Uttam Kumaran: These are all like array formulas or queries.
132 00:14:35.620 ⇒ 00:14:40.149 Uttam Kumaran: So this is actually selecting from clean clockify time entries
133 00:14:40.420 ⇒ 00:14:45.179 Uttam Kumaran: so that anytime clean clockified time entries expands. It’ll automatically select that
134 00:14:45.420 ⇒ 00:15:02.234 Uttam Kumaran: similarly, if you looked at clean, quick books, invoices. You may want like, I kind of want this anytime a new invoice comes in. I need. I want the contracted name to update. These are all array formulas, so basically as new as new,
135 00:15:03.850 ⇒ 00:15:11.679 Uttam Kumaran: as new things coming in from clockify and come in from quickbooks. As long as there exists an active contract for that client.
136 00:15:13.530 ⇒ 00:15:18.819 Uttam Kumaran: This will update so these will start to update. Basically
137 00:15:18.950 ⇒ 00:15:27.919 Uttam Kumaran: like we should. I mean, we will basically be able to look at it on any given day, like what what we spent that day. I don’t think like we’re gonna be doing that
138 00:15:28.170 ⇒ 00:15:31.289 Uttam Kumaran: right now, but mainly on the week level. I want to know
139 00:15:31.560 ⇒ 00:15:37.189 Uttam Kumaran: how much we spent on every project on any given day.
140 00:15:37.580 ⇒ 00:15:46.459 Uttam Kumaran: And then this also you can do month, basically do month, weekday. You can add team member. So all the dimensionality and all the joins now work kind of between this
141 00:15:47.091 ⇒ 00:15:53.850 Uttam Kumaran: probably the only thing that we don’t have, if I was to add something here is like we don’t have operating
142 00:15:54.552 ⇒ 00:16:00.110 Uttam Kumaran: and what is operating include. So operating will include our plan hours.
143 00:16:00.770 ⇒ 00:16:03.889 Uttam Kumaran: Right? So one thing I want to get into here is like.
144 00:16:04.040 ⇒ 00:16:12.100 Uttam Kumaran: what what do we plan for hours, and then you can go look at what it was. What was the difference? Right like? Did we plan? And we over exceed?
145 00:16:12.240 ⇒ 00:16:14.490 Uttam Kumaran: Did we plan? And did we go under.
146 00:16:17.041 ⇒ 00:16:26.958 Uttam Kumaran: And then finally, the other thing that we don’t have here is like we don’t have. I don’t have a forecast for you like. I can’t tell you yet what
147 00:16:27.820 ⇒ 00:16:30.363 Uttam Kumaran: until I get operating
148 00:16:31.130 ⇒ 00:16:35.510 Uttam Kumaran: I’m not gonna be able to tell you what our projected like costs are. Gonna be for the next month.
149 00:16:35.650 ⇒ 00:16:39.170 Uttam Kumaran: and then also what our projected revenue is gonna be for the next month.
150 00:16:39.430 ⇒ 00:16:43.664 Uttam Kumaran: for which I can tell you what the gross margin is going to be in that 2 weeks.
151 00:16:44.350 ⇒ 00:16:48.559 Uttam Kumaran: so this is why I think it’s helpful to do it will
152 00:16:48.790 ⇒ 00:16:51.720 Uttam Kumaran: like I can build a forecast model on.
153 00:16:52.030 ⇒ 00:16:55.759 Uttam Kumaran: like, just like our existing costs. But ideally.
154 00:16:55.970 ⇒ 00:17:01.140 Uttam Kumaran: ideally operating is a source of truth for forward looking, planning.
155 00:17:01.300 ⇒ 00:17:08.260 Uttam Kumaran: and then I can bring those hours in, and then I can. Also, I’ll bring in contracts that haven’t cleared yet.
156 00:17:08.369 ⇒ 00:17:24.510 Uttam Kumaran: Like things we expect to close like. For example, I knew default was gonna close this month. I just didn’t know when, but I could have brought that in, and so sort of looked at July, I could have showed you cool. We expect a hundred K in, and we expect 70 K. And here’s like the breakdown
157 00:17:26.109 ⇒ 00:17:35.879 Uttam Kumaran: so ideally we could start looking at this on a weekly basis, but also start looking at concentrations of where is most of the revenue coming from? Where most of the costs going?
158 00:17:36.160 ⇒ 00:17:39.992 Uttam Kumaran: Who is most released, efficient with their time?
159 00:17:42.190 ⇒ 00:17:46.709 Uttam Kumaran: And then, you know, you could sort of rabbit hole from there as needed.
160 00:17:49.350 ⇒ 00:17:51.809 Uttam Kumaran: So I know it’s a little bit complicated.
161 00:17:51.960 ⇒ 00:17:59.219 Uttam Kumaran: but I will say like I will make it super easy for you to go into here, and you really won’t need to. Look at any of these
162 00:17:59.460 ⇒ 00:18:02.949 Uttam Kumaran: clean tables. You really can go straight to the summaries.
163 00:18:03.290 ⇒ 00:18:05.970 Uttam Kumaran: and the summaries are fairly easy to build.
164 00:18:06.260 ⇒ 00:18:09.100 Uttam Kumaran: You could just just running select queries.
165 00:18:10.440 ⇒ 00:18:13.179 Uttam Kumaran: And I’ll delete some of the stuff up top. But
166 00:18:13.550 ⇒ 00:18:24.069 Uttam Kumaran: yeah, ideally, we want to view like this, where for any given client in month, you can see like if we hit 1 50 billable, if we hit 2 50 billable, if it 40% margin, if we hit 50% margin.
167 00:18:24.280 ⇒ 00:18:27.360 Uttam Kumaran: And that’s what we’re gonna want to
168 00:18:27.580 ⇒ 00:18:33.290 Uttam Kumaran: sort of look at. And ideally, I think we can start looking at this other on a weekly basis.
169 00:18:33.831 ⇒ 00:18:37.700 Uttam Kumaran: And so at the end of the week. We can say like, Hey did, where we
170 00:18:37.880 ⇒ 00:18:40.029 Uttam Kumaran: do we? How do we do last week?
171 00:18:40.480 ⇒ 00:18:45.060 Uttam Kumaran: Do we make it need to make adjustments.
172 00:18:45.370 ⇒ 00:18:47.060 Uttam Kumaran: use a standard of trying to.
173 00:18:48.320 ⇒ 00:18:51.169 Amber Lin: Okay, this is this is really great.
174 00:18:51.490 ⇒ 00:18:52.960 Uttam Kumaran: That makes sense.
175 00:18:56.630 ⇒ 00:18:57.260 Amber Lin: But.
176 00:18:57.260 ⇒ 00:19:12.619 Uttam Kumaran: Yeah, and you can pivot. Of course you can pivot. This is. This will be easily pivotable. I didn’t want to build this as a pivot table, because it’ll be really ugly. But you can take this and pivot it will, however much you want. So I’ll give you. I’ll make 3 tables, one with project month.
177 00:19:13.000 ⇒ 00:19:18.590 Uttam Kumaran: These metrics project Month person, these metrics Project Week
178 00:19:18.730 ⇒ 00:19:26.080 Uttam Kumaran: person, these metrics project we these metrics. So you’ll have all 4 of those summaries, and then you can pivot those and get everything.
179 00:19:26.080 ⇒ 00:19:33.099 Amber Lin: Okay, that’s great. Is there a place where I can pivot per person?
180 00:19:33.430 ⇒ 00:19:37.220 Amber Lin: Say, for for those time grains.
181 00:19:38.538 ⇒ 00:19:44.010 Uttam Kumaran: Yeah. So once I give you the project month, person or project week person, you can then just pivot.
182 00:19:44.320 ⇒ 00:19:45.520 Uttam Kumaran: Okay? Awesome.
183 00:19:45.520 ⇒ 00:19:46.070 Uttam Kumaran: Yeah.
184 00:19:46.070 ⇒ 00:19:46.799 Amber Lin: That’s all I need.
185 00:19:47.170 ⇒ 00:19:49.769 Uttam Kumaran: Yeah, I would just suggest.
186 00:19:49.770 ⇒ 00:19:52.590 Amber Lin: This really feels like matter more.
187 00:19:54.170 ⇒ 00:19:57.770 Uttam Kumaran: Yeah, well, it’s basically doing what they’re trying to do for their clients.
188 00:19:59.040 ⇒ 00:20:03.589 Uttam Kumaran: Yeah, I mean, but they’re the problem is, they have no idea like what they’re doing. So it’s like.
189 00:20:04.650 ⇒ 00:20:13.900 Uttam Kumaran: this is a lot. This is this is tough to do. But like, we know our business really? Well. So it’s easy to like build. I mean, ideally, yeah, we’re gonna do what they we’re gonna start to layer in
190 00:20:14.020 ⇒ 00:20:21.920 Uttam Kumaran: like this is the this is the sort of advanced mode of this is like we’re gonna start to layer in. How many slacks were sent, how many linear tickets were created
191 00:20:22.370 ⇒ 00:20:28.519 Uttam Kumaran: like. And you’ll basically be able to look at like cost per ticket like stuff like that like that’s sort of the next level
192 00:20:28.920 ⇒ 00:20:32.560 Uttam Kumaran: sort of stuff, like number of hours spent in meetings.
193 00:20:32.900 ⇒ 00:20:35.490 Uttam Kumaran: and you can start to look at trends and stuff like that.
194 00:20:37.550 ⇒ 00:20:44.500 Uttam Kumaran: But I’ll I’ll sort of make these 4 available here, and then you can either create a playground sheet.
195 00:20:45.251 ⇒ 00:20:48.019 Uttam Kumaran: I would probably suggest that. And then you can just like
196 00:20:48.560 ⇒ 00:20:54.103 Uttam Kumaran: mess around, and then we can keep some fixed reports to look at and then ideally
197 00:20:54.920 ⇒ 00:20:59.310 Uttam Kumaran: I kinda wanna mess with this. Use this for about a month, and then.
198 00:20:59.670 ⇒ 00:21:02.739 Uttam Kumaran: We can. I can move this all the sequel and put this in real.
199 00:21:03.600 ⇒ 00:21:04.549 Amber Lin: Okay. I’m down.
200 00:21:05.720 ⇒ 00:21:07.720 Uttam Kumaran: So that is obviously
201 00:21:09.261 ⇒ 00:21:14.319 Amber Lin: Since we’re talking about this, I’m gonna go into the management part.
202 00:21:15.241 ⇒ 00:21:18.429 Amber Lin: or financial modeling. I’m just gonna
203 00:21:19.950 ⇒ 00:21:25.790 Amber Lin: add a ticket. So I know, like next time I don’t have to recall what we’re talking about.
204 00:21:25.910 ⇒ 00:21:29.100 Amber Lin: Financial modeling.
205 00:21:30.341 ⇒ 00:21:41.270 Amber Lin: I’ll add a test financial model in July. Slash August time. Allocations.
206 00:21:42.258 ⇒ 00:21:49.270 Amber Lin: Determine when to move to SQL. Or move to where would.
207 00:21:49.270 ⇒ 00:21:53.159 Uttam Kumaran: Yeah. Well, I’ll move this all to rail. It’ll live in the warehouse.
208 00:21:54.020 ⇒ 00:21:58.500 Amber Lin: Call to real, so.
209 00:21:58.500 ⇒ 00:21:58.920 Uttam Kumaran: I think.
210 00:21:58.920 ⇒ 00:22:11.579 Amber Lin: You need. My, you need a time allocations, teams, input on if there’s any adjustments. And then you need to have a handout process with the data platform team, which is probably the interns.
211 00:22:12.890 ⇒ 00:22:14.890 Uttam Kumaran: I don’t need. What are we handing off to them?
212 00:22:15.280 ⇒ 00:22:17.680 Amber Lin: Oh, are you gonna build the rail, or are they gonna.
213 00:22:17.680 ⇒ 00:22:22.720 Uttam Kumaran: Yeah, yeah, that’ll take me like 10 seconds. I don’t want that’ll. It’ll take them like a thousand years to do this.
214 00:22:23.070 ⇒ 00:22:28.680 Amber Lin: Yeah, I thought they were. That’s what I thought. That was their whole internship project.
215 00:22:28.680 ⇒ 00:22:31.733 Uttam Kumaran: They’re building. No, they’re building like
216 00:22:32.760 ⇒ 00:22:35.339 Uttam Kumaran: linear. I’m having them model linear tickets.
217 00:22:36.120 ⇒ 00:22:42.060 Amber Lin: Okay, okay, sounds good. I know they were getting some stuff with clockify starting stuff with linear. I was confused.
218 00:22:42.060 ⇒ 00:22:44.520 Uttam Kumaran: Yeah, they’re they’re gonna do hours and
219 00:22:44.650 ⇒ 00:22:47.290 Uttam Kumaran: tickets. But like the financial stuff, it’s
220 00:22:47.900 ⇒ 00:22:49.740 Uttam Kumaran: they’re just not gonna get it. So.
221 00:22:49.740 ⇒ 00:22:50.170 Amber Lin: Followers.
222 00:22:50.170 ⇒ 00:22:55.819 Uttam Kumaran: I, I’m gonna need that data anyways. But those are that’s kind of like bonus points. We’re able to see, like
223 00:22:56.140 ⇒ 00:22:58.920 Uttam Kumaran: how many tickets went to apply per month, and like.
224 00:22:59.100 ⇒ 00:22:59.560 Amber Lin: Okay.
225 00:22:59.560 ⇒ 00:23:03.690 Uttam Kumaran: How many people are getting tickets done. We’ll we’ll do that later, and.
226 00:23:03.690 ⇒ 00:23:04.139 Amber Lin: Go ahead!
227 00:23:04.140 ⇒ 00:23:10.529 Uttam Kumaran: I think another question for us is like, How do we want to? I think we should start looking at this
228 00:23:11.060 ⇒ 00:23:12.619 Uttam Kumaran: on a weekly basis?
229 00:23:14.060 ⇒ 00:23:14.600 Amber Lin: Go ahead!
230 00:23:14.820 ⇒ 00:23:18.790 Uttam Kumaran: Ideally for probably the the closed week.
231 00:23:20.460 ⇒ 00:23:20.720 Amber Lin: Bro.
232 00:23:20.720 ⇒ 00:23:29.740 Uttam Kumaran: Because I feel like clockify hours are gonna lag a bit so ideally. On on Friday or Wednesday
233 00:23:29.850 ⇒ 00:23:32.429 Uttam Kumaran: we look at the past week closed.
234 00:23:34.570 ⇒ 00:23:40.999 Amber Lin: Yes, main blocker, we all talked about this people not locking their hours.
235 00:23:41.000 ⇒ 00:23:43.470 Uttam Kumaran: So this is the main function for that. Yeah.
236 00:23:44.780 ⇒ 00:23:53.949 Uttam Kumaran: It’ll be out, you’ll it’ll be really clear which projects. The hours are not up to date, because the numbers will look like shit, basically, or they look really good.
237 00:23:55.106 ⇒ 00:23:59.260 Uttam Kumaran: So I will. So I can produce for Rico a report that just shows like.
238 00:23:59.640 ⇒ 00:24:04.509 Uttam Kumaran: here are all the people with less than something hours.
239 00:24:04.680 ⇒ 00:24:16.620 Uttam Kumaran: And he I’m I’m having him do an end of week close process that he can execute on Fridays and Mondays so like when the week closes. There’s a couple of things he needs to go. Make sure everybody has logged hours.
240 00:24:16.790 ⇒ 00:24:21.830 Uttam Kumaran: and that needs to sort of be like reported out to us, and there’s a couple of other tasks the end of the week to do
241 00:24:25.774 ⇒ 00:24:30.349 Uttam Kumaran: so I think we need something on a weekly basis, and then on a monthly basis as well.
242 00:24:30.610 ⇒ 00:24:32.610 Uttam Kumaran: I really think we should.
243 00:24:33.540 ⇒ 00:24:37.280 Uttam Kumaran: I mean I would. I would prefer to get like at least
244 00:24:37.870 ⇒ 00:24:43.509 Uttam Kumaran: 2 months ahead, I mean for many, for we have some clients now that are on 6 month contracts.
245 00:24:43.710 ⇒ 00:24:45.840 Uttam Kumaran: so I would love to have
246 00:24:46.690 ⇒ 00:24:50.189 Uttam Kumaran: at least a month ahead, so we can forecast hours.
247 00:24:50.410 ⇒ 00:24:54.460 Uttam Kumaran: But ideally, as far ahead as we can go would be great.
248 00:24:55.770 ⇒ 00:25:00.100 Uttam Kumaran: Okay? When’s the 1st time we can get that started.
249 00:25:01.440 ⇒ 00:25:09.880 Uttam Kumaran: So we’re kind of. We’re kind of delayed because I wanted to have this for last month. But I guess I’ll ask you guys if you’ve already planned out July and operating.
250 00:25:10.779 ⇒ 00:25:23.360 Amber Lin: We plan it out, I believe. I asked Rico to put it in operating. He was reconciling some differences between operating and clockify. But that should be done. But I think what I was.
251 00:25:23.630 ⇒ 00:25:37.709 Amber Lin: It’s more of you said that weekly cadence of checking whose hours are not longer we could cadence or looking at the financial models that we could start. We currently have the meetings on Tuesdays. I could move me and his meeting
252 00:25:37.960 ⇒ 00:25:49.909 Amber Lin: to Wednesdays like. I don’t think we need to do it in the management meeting, like I can check it with him and then take the results. And we talk about it in in this meeting.
253 00:25:49.910 ⇒ 00:25:50.630 Uttam Kumaran: Sure.
254 00:25:51.120 ⇒ 00:26:03.230 Amber Lin: Okay, so I’ll I’ll keep the weekly Tuesday meetings with him, and in those meetings we’ll check if everybody’s hours are logged and then do a quick check against our allocations.
255 00:26:03.920 ⇒ 00:26:10.719 Uttam Kumaran: Yeah. So the next job for me is to get the allocations in here so that we can look at what did we allocate versus
256 00:26:11.100 ⇒ 00:26:12.600 Uttam Kumaran: what ended up happening.
257 00:26:15.150 ⇒ 00:26:16.660 Uttam Kumaran: And then ideally.
258 00:26:16.840 ⇒ 00:26:22.069 Uttam Kumaran: we look at that for the for the month ahead, like for this month. I know how much money is gonna come in
259 00:26:24.154 ⇒ 00:26:29.849 Uttam Kumaran: and we should. We should know on a weekly basis how many, how many hours went into it? And then
260 00:26:30.210 ⇒ 00:26:32.650 Uttam Kumaran: do we need to increase or reduce, you know.
261 00:26:33.110 ⇒ 00:26:33.810 Amber Lin: Okay.
262 00:26:34.230 ⇒ 00:26:53.419 Amber Lin: yeah, for one thing, on the allocations. Currently, we set the allocations in Google sheets because we look at the previous actual hours on Google sheets. And then we like enter it into operating. Why don’t we? Just directly? If we’re going to enter it in Google sheets, why can’t we just.
263 00:26:54.240 ⇒ 00:27:01.470 Uttam Kumaran: Well, I guess, like my question is why we shouldn’t be going off clockify actuals right?
264 00:27:01.940 ⇒ 00:27:02.680 Amber Lin: Okay.
265 00:27:02.680 ⇒ 00:27:07.130 Uttam Kumaran: Like we should understand. If someone has 40 h of time.
266 00:27:07.440 ⇒ 00:27:11.239 Uttam Kumaran: then they have X time to dedicate here and here, right.
267 00:27:11.730 ⇒ 00:27:36.379 Amber Lin: Okay, I understand that approach. But won’t that be disconnected if we only look at, say desired profitability and desired people’s actual hours. I guess our we can always say like, Oh, we want to close that gap. We want to close that gap. But shouldn’t we have a more realistic goal and aim to gradually decrease the gap.
268 00:27:36.660 ⇒ 00:27:37.890 Amber Lin: I don’t know.
269 00:27:38.130 ⇒ 00:27:50.789 Uttam Kumaran: But plan. But no, no, but planning is not planning. We shouldn’t put what’s actually happening because we’ll the actuals are actuals. Otherwise the actuals are gonna match our planning. And then we’re gonna be like, well, we plan for
270 00:27:51.630 ⇒ 00:27:54.110 Uttam Kumaran: like we plan to not make money on this right? So you.
271 00:27:54.110 ⇒ 00:27:54.820 Amber Lin: That’s fabulous.
272 00:27:54.820 ⇒ 00:27:58.289 Uttam Kumaran: Yeah, everything we should plan towards the
273 00:27:58.870 ⇒ 00:28:03.899 Uttam Kumaran: hey, we? If this is budgeted for 5 K, and then we have Max 33 h.
274 00:28:04.450 ⇒ 00:28:05.130 Amber Lin: Okay.
275 00:28:05.940 ⇒ 00:28:08.359 Uttam Kumaran: So the 1st goal to hit is the 1 50,
276 00:28:08.640 ⇒ 00:28:18.789 Uttam Kumaran: and then the ideally. We should be planning towards hitting 200 as much as possible. So when you so the so the goal, when you do hours for a client, is to look at
277 00:28:19.547 ⇒ 00:28:25.199 Uttam Kumaran: when much money is coming in, and then you divide that by 200. And then you’re like, this is amount of hours I can allocate
278 00:28:27.070 ⇒ 00:28:29.240 Uttam Kumaran: right. And that’s the planned amount.
279 00:28:29.700 ⇒ 00:28:31.260 Uttam Kumaran: And that’s that’s what we do.
280 00:28:31.430 ⇒ 00:28:35.499 Amber Lin: I agree that that clarifies it for me. I understand that.
281 00:28:35.500 ⇒ 00:28:40.360 Uttam Kumaran: So what I can also do is I can. I can put that in somewhere here
282 00:28:40.490 ⇒ 00:28:42.030 Uttam Kumaran: where, like, for example.
283 00:28:43.110 ⇒ 00:28:53.640 Uttam Kumaran: in our contract, I can tell you like what our fixed rate is, or what our like estimated rate is, and then I can probably put in like what the
284 00:28:55.350 ⇒ 00:28:58.090 Uttam Kumaran: on a Max hours.
285 00:28:58.310 ⇒ 00:29:01.979 Uttam Kumaran: I can put the hours for 1 50. I could put the hours for 200.
286 00:29:01.980 ⇒ 00:29:09.010 Amber Lin: Yes, please I I would love that. That would be really, really helpful. That’s what we did for the last time. We allocations.
287 00:29:09.210 ⇒ 00:29:11.160 Uttam Kumaran: Okay. So I can put that in
288 00:29:14.280 ⇒ 00:29:19.760 Uttam Kumaran: and then I think it will still be up to you guys. But operating will help you do this, basically do like.
289 00:29:19.900 ⇒ 00:29:23.800 Uttam Kumaran: okay, 60% of this time, 40% of this time.
290 00:29:24.481 ⇒ 00:29:27.720 Uttam Kumaran: And then you’ll see the total number of hours that go into it right.
291 00:29:30.060 ⇒ 00:29:32.460 Uttam Kumaran: Okay, so blah, blah.
292 00:29:39.750 ⇒ 00:29:40.570 Uttam Kumaran: okay.
293 00:29:41.170 ⇒ 00:29:47.409 Amber Lin: Okay, anything else? We wanted to address.
294 00:29:49.860 ⇒ 00:29:52.210 Uttam Kumaran: Well, shit.
295 00:29:54.100 ⇒ 00:29:57.650 Uttam Kumaran: I feel like for me.
296 00:30:00.070 ⇒ 00:30:08.929 Uttam Kumaran: yeah, I think. It’s getting a little bit. We had a bunch of sort of intros come in. So I sort of have been sending out emails for those
297 00:30:09.732 ⇒ 00:30:11.690 Uttam Kumaran: think other updates.
298 00:30:12.544 ⇒ 00:30:14.909 Uttam Kumaran: Yeah, I’m sort of waiting for
299 00:30:17.400 ⇒ 00:30:23.635 Uttam Kumaran: I’m waiting for hash to come in to sort of make
300 00:30:24.050 ⇒ 00:30:29.054 Uttam Kumaran: payments. But that’s you’re like, okay, I think.
301 00:30:32.220 ⇒ 00:30:37.176 Uttam Kumaran: Henry just signed so excited to have him sort of come in.
302 00:30:38.010 ⇒ 00:30:39.260 robert: Nice.
303 00:30:39.260 ⇒ 00:30:46.060 Uttam Kumaran: Yeah, so that’s big. I also go back.
304 00:30:46.400 ⇒ 00:30:56.010 Uttam Kumaran: I I’m kind of like, I think we have the stuff. It’s really kind of project management is the gonna be the star of the show for about a month here. So
305 00:30:56.150 ⇒ 00:31:10.669 Uttam Kumaran: kind of relying on you, Amber and Alex the kind of figure out how we can get everything kind of on rails across default and even, and things like that. So we’ll kind of be looking for
306 00:31:10.800 ⇒ 00:31:12.300 Uttam Kumaran: assistance there.
307 00:31:12.846 ⇒ 00:31:24.610 Uttam Kumaran: Ideally, you know, we test out the process. And then also, Mcgah is asking about sort of our Poc process. So that’ll allow you guys to sort of document that as well, and then.
308 00:31:25.037 ⇒ 00:31:26.320 Amber Lin: The Poc process.
309 00:31:26.320 ⇒ 00:31:29.189 Uttam Kumaran: Like kind of how we do those 2 week trials for.
310 00:31:29.570 ⇒ 00:31:31.747 Amber Lin: 2 week or 2, 1 month. Trials for
311 00:31:32.050 ⇒ 00:31:37.120 Amber Lin: I see every time we say, Poc, I’m like, is it point of contact? Where is that proof?
312 00:31:37.120 ⇒ 00:31:41.540 Uttam Kumaran: Proof of concept. Sorry? Sorry. Yeah, just like their trial period or audits, or whatever.
313 00:31:42.330 ⇒ 00:31:43.280 Uttam Kumaran: Yeah.
314 00:31:45.210 ⇒ 00:31:47.210 robert: Yeah, I can help. I can help put that together.
315 00:31:47.210 ⇒ 00:31:51.039 Uttam Kumaran: Okay, yeah. I know Robert. Robert has a ton of stuff already written on this.
316 00:31:51.220 ⇒ 00:31:51.650 Amber Lin: Yeah.
317 00:31:51.650 ⇒ 00:31:56.440 Uttam Kumaran: So like, let’s say, notion, somewhere on, like the different types of of
318 00:31:56.680 ⇒ 00:32:02.639 Uttam Kumaran: proof of concept to do, Mcgow is gonna be particularly interested in the stuff that is related to data engineering, I think.
319 00:32:03.720 ⇒ 00:32:13.329 Uttam Kumaran: Which I think urban stems is probably the the only one where we did that. But we do have a sample. We have a sample data platform, Doc. Now that has
320 00:32:13.994 ⇒ 00:32:18.270 Uttam Kumaran: synthetic information is really full. So I can
321 00:32:20.140 ⇒ 00:32:43.450 Uttam Kumaran: send that over. But the the urban stems. The 1st month I spent on urban stems is probably the best representation of what this looks like. Where I went in. I understood every single data source that was coming in. We built them a great diagram. We built out the data platform documentation with costs around everything. And then we built them a 6 month analytics roadmap
322 00:32:45.260 ⇒ 00:32:57.459 Uttam Kumaran: and then we basically like, basically interviewed and understood all of the core data stakeholders, and kind of deliver them like a sort of like. Here’s the state of your system. Report
323 00:32:57.879 ⇒ 00:33:06.550 Uttam Kumaran: and that that crushed like. So I think that’s probably what the gone needs. And that took a month. We could definitely do that in 2 weeks.
324 00:33:06.980 ⇒ 00:33:13.599 Uttam Kumaran: But I but I pretty much, I think, like we have several types of audits. I think that’s probably more of the
325 00:33:15.100 ⇒ 00:33:25.830 Uttam Kumaran: It’s like the data architecture audit is probably what I would. Just what I would describe it as versus the product analytics audit that I think Robert typically does, which is, if the read me, Doc, is more of a product. Analytics audit.
326 00:33:28.430 ⇒ 00:33:31.600 Uttam Kumaran: So right now I think we have 2 kind of 2 flavors of audits. There.
327 00:33:33.293 ⇒ 00:33:35.399 Uttam Kumaran: To give you to give you another sense like
328 00:33:35.570 ⇒ 00:33:47.029 Uttam Kumaran: the Fan stake work is closer to the urban sense work where I’m mapping out all their sources, building them like a simple data model, making recommendation, giving them an architecture, diagram. Things like that.
329 00:33:48.750 ⇒ 00:33:51.080 Uttam Kumaran: Teams, and also.
330 00:33:51.080 ⇒ 00:33:53.399 robert: I think it’ll be important to like, yeah, I think.
331 00:33:53.400 ⇒ 00:33:53.960 Uttam Kumaran: Positive.
332 00:33:53.960 ⇒ 00:33:54.920 robert: That that’s what would be wrong.
333 00:33:55.410 ⇒ 00:34:01.250 robert: But then, also, I I think they they we need to basically tell them how to sell. Sell.
334 00:34:01.250 ⇒ 00:34:01.900 robert: It’s like.
335 00:34:01.900 ⇒ 00:34:22.629 robert: what are they’re in these conversations, you know. They’re amber. You got a you got a taste of this today like they do the Cdp work that I kind of walk walked through today. So it’s kind of like, when how do they know when their clients are ready to move into data warehousing? Then I think we’re gonna have to just be able to communicate that to them.
336 00:34:22.639 ⇒ 00:34:23.499 Uttam Kumaran: City, one.
337 00:34:23.820 ⇒ 00:34:29.810 robert: Yeah, because most of their clients, they they don’t really work with the same type of tech stack that we do.
338 00:34:31.520 ⇒ 00:34:37.959 robert: Yeah, I think it’s just I. I think that’s that’s where we’ll have to collaborate with them.
339 00:34:42.670 ⇒ 00:34:43.449 Amber Lin: Okay?
340 00:34:45.130 ⇒ 00:34:51.289 Amber Lin: you specify what is asked of me, so I can make a ticket for that. So I remember.
341 00:34:52.190 ⇒ 00:34:58.550 robert: Yeah, no, I’m I’m I’m gonna that’s why I said, I wanna be involved in the kind of
342 00:34:59.150 ⇒ 00:35:13.530 robert: assembling what the Pocs look like and how we present it to the golf. I’ve been thinking about it this afternoon, so I think probably no action from you, for now I think I’m just trying to put something together and then send it to this group.
343 00:35:14.630 ⇒ 00:35:21.379 Amber Lin: Okay, do you still want to do that meeting this afternoon? Then.
344 00:35:22.509 ⇒ 00:35:27.025 Uttam Kumaran: I’m happy to keep the meeting this afternoon.
345 00:35:27.590 ⇒ 00:35:27.980 Amber Lin: Okay.
346 00:35:27.980 ⇒ 00:35:30.880 Uttam Kumaran: But but also we can push it if you want to.
347 00:35:32.410 ⇒ 00:35:33.420 robert: I’m I’m.
348 00:35:33.420 ⇒ 00:35:35.399 Amber Lin: What were you gonna meet on about this?
349 00:35:36.290 ⇒ 00:35:37.200 Amber Lin: Around that? Yeah.
350 00:35:37.200 ⇒ 00:35:38.080 Uttam Kumaran: Yeah.
351 00:35:38.080 ⇒ 00:35:38.860 robert: Okay.
352 00:35:40.180 ⇒ 00:35:43.979 Amber Lin: Robert, do you want to join? It might be a late bit late for both of you.
353 00:35:44.170 ⇒ 00:35:48.222 robert: Yeah, no, I’m I’m good. I don’t. I don’t. Wanna take meetings.
354 00:35:49.160 ⇒ 00:35:52.349 robert: have some stuff that I want to just think about.
355 00:35:53.640 ⇒ 00:35:54.015 Amber Lin: Okay.
356 00:35:56.440 ⇒ 00:36:03.610 Uttam Kumaran: Yeah, I’ll knock that out. And I think it’s it’ll mainly be just explaining kind of like some of some of the things that give me all the assets. I don’t think it’ll take too long.
357 00:36:03.790 ⇒ 00:36:09.659 robert: Yeah, I mean, I’ll please. I mean, I’m sure it’ll I’ll I’ll probably review those notes, too. But yeah.
358 00:36:12.440 ⇒ 00:36:13.160 Uttam Kumaran: Yeah.
359 00:36:14.360 ⇒ 00:36:28.449 Amber Lin: Okay. And, Robert, if you want my help on it, just feel free to just dump all the documents to me, or I can try to find them. I can help try and consolidate them, and you can review whichever way is faster and easier for you.
360 00:36:28.580 ⇒ 00:36:34.350 Amber Lin: unless this is a lot of thinking, and you just want to do it yourself, like I can help if it’s otherwise.
361 00:36:34.700 ⇒ 00:36:40.280 robert: Yeah, I mean, feel free to whatever you guys discuss. I’m sure it’ll be helpful for me. But I’ve already kind of been
362 00:36:41.240 ⇒ 00:36:43.352 robert: like outlining like I’m
363 00:36:44.660 ⇒ 00:36:50.659 robert: there’s like 2 things that I’m I’m working through today. One is one is that trying to get
364 00:36:50.925 ⇒ 00:36:53.729 robert: Hi, wrap my head around the poc stuff like and
365 00:36:55.900 ⇒ 00:37:00.169 robert: the other thing I mean. I already, I think the handoff to to Henry
366 00:37:00.510 ⇒ 00:37:05.194 robert: at least, the kickoff seemed to go well today. So I’m not really thinking about that anymore.
367 00:37:06.920 ⇒ 00:37:16.009 robert: yeah, I’m I’m also just think planning, planning out like, how how insomnia is gonna gonna go next week. So it’s also related to Poc. But it’s more of like.
368 00:37:16.730 ⇒ 00:37:20.559 Uttam Kumaran: Okay, what is this playbook for? Like to like the first.st
369 00:37:20.770 ⇒ 00:37:33.279 robert: 1st month of a of a contract that’s not like pro. It’s not product analytics. So I think the product analytics stuff the roadmaps very clear. The Pocs, like, you know, I’m reading spark. Plug ran the same thing.
370 00:37:33.672 ⇒ 00:37:38.029 robert: But yeah, I’m just like trying to think through like the other. The other range of
371 00:37:38.500 ⇒ 00:37:39.610 robert: of things that we’re starting.
372 00:37:43.600 ⇒ 00:37:55.740 Amber Lin: Yeah, on, on that, I think after we discuss what my involvement will be on Eden, I do think I will have space to take on analysis for insomnia. I do need to know how big
373 00:37:57.100 ⇒ 00:38:01.850 Amber Lin: default will be cause Robert, you told me a song that’s gonna be around 10 h, which I think.
374 00:38:02.550 ⇒ 00:38:06.999 Amber Lin: even at this rate, probably will take me like 5 h.
375 00:38:07.000 ⇒ 00:38:07.430 Uttam Kumaran: Settings.
376 00:38:07.860 ⇒ 00:38:15.269 Amber Lin: Max and so I’ll have space for insomnia. I don’t know for default, so we’ll look at my hours and we can see where we’re
377 00:38:15.900 ⇒ 00:38:16.570 Amber Lin: intake.
378 00:38:16.885 ⇒ 00:38:17.200 robert: Yeah.
379 00:38:17.200 ⇒ 00:38:22.629 robert: I think that seems right. I think I expect maybe 5 h. This is, we’re just gonna limit you to.
380 00:38:22.630 ⇒ 00:38:25.619 robert: It’s interesting, internal, like epm on Eden, and then.
381 00:38:25.620 ⇒ 00:38:26.030 Uttam Kumaran: That’s in the.
382 00:38:26.030 ⇒ 00:38:31.199 robert: For insomnia. We’ll probably run it closer to what we were doing with pool parts between me and you.
383 00:38:32.540 ⇒ 00:38:34.849 robert: I think just showing them a couple.
384 00:38:35.490 ⇒ 00:38:39.399 robert: you know, if we can get them inside a week, like I’m sure they’ll be happy with that. So.
385 00:38:40.140 ⇒ 00:38:42.020 Amber Lin: Okay. Good.
386 00:38:50.319 ⇒ 00:38:50.910 Uttam Kumaran: Awesome.
387 00:38:50.910 ⇒ 00:38:52.400 Amber Lin: Any other agendas
388 00:38:54.610 ⇒ 00:39:00.109 Amber Lin: I’ll run through. I’ll run through my 3 projects. If if that’s helpful, I can do a quick update.
389 00:39:01.673 ⇒ 00:39:02.700 Uttam Kumaran: Yeah, perfect.
390 00:39:02.960 ⇒ 00:39:06.919 Amber Lin: Okay. So general pm, side.
391 00:39:06.920 ⇒ 00:39:07.530 Amber Lin: So
392 00:39:07.947 ⇒ 00:39:26.329 Amber Lin: been helping marketing groom the board, which I think will be really helpful. Onboarding onboarding Rico to Pm. Processes and looking at time allocations with him. I I do like working with him like he. He is very proactive, and he thinks
393 00:39:26.340 ⇒ 00:39:42.385 Amber Lin: pretty fast. So I I do like working with him, and I do think like with project management. I started not knowing anything, so I think he can also get started. Not knowing anything. I I think he is able to do it. We’ll see how it goes.
394 00:39:43.470 ⇒ 00:39:46.810 Amber Lin: And then, in terms of
395 00:39:47.190 ⇒ 00:40:01.190 Amber Lin: so Madam Moore is closing out. I’ve had the meeting with their in-house team, in-house and analysts handed off docs that he needs. And so right now is
396 00:40:01.400 ⇒ 00:40:24.590 Amber Lin: all the client related. Closing is complete. What’s left is to do a project retro. So for the team to say, Okay, overall, how did this project go? I think it’ll be also helpful to look at. Okay, overall as a team. What did we do overall? Are we margin margin wise? Maybe that’s something we look at in as a management team. Okay.
397 00:40:24.590 ⇒ 00:40:45.370 Amber Lin: was this engagement profitable? Do we allocate the right resources? Do we have the right rituals or manage project management in place? So we can have some learnings we take from that as as a closed off project. To look at it from end to end. Other parts relate more related to sales is that
398 00:40:45.390 ⇒ 00:41:00.110 Amber Lin: sending out testimonial request, I would prefer that it gets sent out from a sales account also because Matthew doesn’t really respond to me. He prefers to communicate with Utam.
399 00:41:00.330 ⇒ 00:41:14.069 Amber Lin: That’s how it is. It doesn’t really most of the time ignores me, and then also to to internally write up the case studies with anonymization that’s needed
400 00:41:15.090 ⇒ 00:41:25.569 Amber Lin: and then send it to them to review. I don’t know if they’re okay with adding their name on it. But well, I think as long as we don’t include the type of data where
401 00:41:26.308 ⇒ 00:41:34.419 Amber Lin: we’re including, it should be fine. I need to double check on that. So that’s where matter more, I’ll pause for inputs.
402 00:41:38.420 ⇒ 00:41:40.220 Uttam Kumaran: Yeah, I mean, I think,
403 00:41:40.770 ⇒ 00:41:49.009 Uttam Kumaran: probably Hannah, on marketing team can reach out to Matthew for testimonial. I think we we did this previously
404 00:41:49.689 ⇒ 00:41:53.709 Uttam Kumaran: with Vishnu, or actually Matthew’s in slack, you can also reach out slack.
405 00:41:53.840 ⇒ 00:41:59.419 Uttam Kumaran: We did this previously with Vishnu and other folks, so don’t think it should be too much different.
406 00:42:01.200 ⇒ 00:42:02.700 Uttam Kumaran: Yes, so.
407 00:42:03.840 ⇒ 00:42:10.699 Hannah Wang: I can just like well, we’ll see if he responds to me so you could just intro me, and then I’ll ask.
408 00:42:11.130 ⇒ 00:42:11.560 Amber Lin: Okay.
409 00:42:11.560 ⇒ 00:42:19.370 Amber Lin: I’ll try to send it first.st I think it’s it’ll be easier. I’ll send it first.st If he doesn’t respond like we’ll reach out as a company more officially.
410 00:42:19.850 ⇒ 00:42:20.480 Uttam Kumaran: Okay.
411 00:42:20.780 ⇒ 00:42:21.370 Amber Lin: Bye
412 00:42:21.774 ⇒ 00:42:48.060 Amber Lin: for urban stems. I think it’s getting so on the good side, we’re engaging the stakeholders a lot more. We had a working session with Felipe into the inventory stakeholders. So we got their pain points and got what they’re what they need. So on that side, it’s going well. Second project management wise. This is getting standardized. We’re having better grooming sessions.
413 00:42:48.518 ⇒ 00:43:00.630 Amber Lin: And that then that leads to planning as well. So things are a bit more standardized. People have better understanding of what the project is about. So
414 00:43:01.371 ⇒ 00:43:05.430 Amber Lin: immediate result is that I don’t have to explain
415 00:43:05.580 ⇒ 00:43:14.359 Amber Lin: all the time what this means. It’s great, because I don’t really know what it means sometimes. So we discuss internally in grooming whatever
416 00:43:14.820 ⇒ 00:43:22.180 Amber Lin: about if this ticket makes sense, if we still need it. So that’s great. In terms of risk. I think that
417 00:43:22.670 ⇒ 00:43:32.959 Amber Lin: I would so like to involve Zach more. He did not show up at our grooming. So I’m trying to get him to show up tomorrow at our State meeting with all the stakeholders
418 00:43:33.020 ⇒ 00:43:33.750 Amber Lin: that would be.
419 00:43:33.750 ⇒ 00:43:47.459 Amber Lin: Prepare this slide to show them what we have done in inventory and then I would like Zack to be there. So he knows that we’re actually doing stuff one other risk is that
420 00:43:48.620 ⇒ 00:43:59.890 Amber Lin: this project is really bigger than what we expected when we signed the 6 month contract. The timeline we initially agreed on is too tight.
421 00:44:01.250 ⇒ 00:44:01.860 Amber Lin: It doesn’t
422 00:44:02.870 ⇒ 00:44:11.820 Amber Lin: expect the whole size of these March rebuilds and isn’t take into like. It’s just smaller than what we need.
423 00:44:11.820 ⇒ 00:44:13.469 Uttam Kumaran: And I think.
424 00:44:13.470 ⇒ 00:44:19.770 Amber Lin: Instead of trying to fit, scramble, and fit it into that tight timeline.
425 00:44:19.770 ⇒ 00:44:20.200 Uttam Kumaran: Okay.
426 00:44:20.200 ⇒ 00:44:40.709 Amber Lin: Better decision would just be communicate with Zack, confirm, get their confirmation that okay, things might be larger than what we planned, and for this, because right now we’re in Cycle 4. So that means we’re in the second month, and in 6 months time
427 00:44:40.850 ⇒ 00:44:44.009 Amber Lin: I think it’s Max 3 marts.
428 00:44:44.630 ⇒ 00:45:02.990 Amber Lin: I don’t. I don’t, I think, like, for Mars is very ambitious, and I want to confirm with them that it’s okay like that. We finish inventory finish revenue, and we might have space for one other mart. I just want to get his okay on that.
429 00:45:05.460 ⇒ 00:45:18.570 Uttam Kumaran: Okay, yeah, I don’t mind. I feel like I can be part of that meeting this is like the work we were. Gonna we’re gonna be with them for quite a while to do this work. So our best, the best way to explain this is that
430 00:45:18.680 ⇒ 00:45:23.240 Uttam Kumaran: look, we’re meeting with Felipe, and we’re constantly digging up way. More stuff like
431 00:45:23.450 ⇒ 00:45:30.565 Uttam Kumaran: they also didn’t want us to go spend time with them during the mother’s day thing. So I be. We built a roadmap based on what I knew.
432 00:45:31.455 ⇒ 00:45:32.090 Amber Lin: Totally.
433 00:45:32.090 ⇒ 00:45:38.389 Uttam Kumaran: So I don’t mind, and that’s good for us. I mean, we have a lot of work to do, so if anything.
434 00:45:38.390 ⇒ 00:45:38.980 Amber Lin: I am.
435 00:45:38.980 ⇒ 00:45:39.630 Uttam Kumaran: You’ve been.
436 00:45:39.830 ⇒ 00:45:44.520 Uttam Kumaran: Yeah, if anything you can say, look, are there are there? Other option is to expand
437 00:45:44.850 ⇒ 00:45:48.279 Uttam Kumaran: like our hours. But if we’re not gonna expand hours. Then
438 00:45:48.660 ⇒ 00:45:52.949 Uttam Kumaran: we’re most likely gonna just aim to like, do these 2
439 00:45:53.070 ⇒ 00:45:57.250 Uttam Kumaran: 2 or 3 marts by the end, or or whatever we decide.
440 00:45:57.250 ⇒ 00:46:16.530 Amber Lin: Yeah, yeah, that will give me a lot more space to do allocations and get better margins. I feel like every time I’m planning. I’m feeling like, Oh, gosh! We’re so behind. But that if we change that one simple thing like our margins will be a lot better.
441 00:46:17.570 ⇒ 00:46:35.860 Uttam Kumaran: Okay, yeah. And I just, I just know, I just know that, like, I think Kyle book like 90 h last month to this. And like, I don’t know. I think this weekly process is gonna get a little bit better. But people cannot be just willy-nilly booking hours to stuff and then be like, oh, I spent so much time on it like
442 00:46:36.180 ⇒ 00:46:37.310 Uttam Kumaran: they need to know.
443 00:46:37.310 ⇒ 00:46:38.030 Amber Lin: Yes.
444 00:46:38.030 ⇒ 00:46:45.770 Uttam Kumaran: What their cap is. And like he, he in particular is, he’s he just takes his time with stuff. And
445 00:46:45.890 ⇒ 00:46:47.220 Uttam Kumaran: like, Yeah.
446 00:46:47.720 ⇒ 00:46:49.580 Uttam Kumaran: I don’t know. It’s it. We’re sort of like when I hear
447 00:46:49.580 ⇒ 00:46:53.490 Uttam Kumaran: people being like, Oh, I ended up taking way longer. I’m basically.
448 00:46:53.490 ⇒ 00:46:54.129 Amber Lin: He’s like, I gotta.
449 00:46:54.130 ⇒ 00:46:57.510 Uttam Kumaran: Paper cut, and and my arteries bleed out, is how I feel.
450 00:46:58.710 ⇒ 00:46:59.029 Amber Lin: I know.
451 00:46:59.030 ⇒ 00:47:04.580 Uttam Kumaran: So if we keep doing this, it’s death by a thousand paper cuts like we will just continue.
452 00:47:04.580 ⇒ 00:47:05.020 Amber Lin: Yeah.
453 00:47:06.320 ⇒ 00:47:09.089 Uttam Kumaran: So like when I see you spend 90 h.
454 00:47:09.230 ⇒ 00:47:15.689 Uttam Kumaran: I don’t care if, like those 90 h he was, he felt really good about words, but we didn’t get paid.
455 00:47:15.800 ⇒ 00:47:18.280 Uttam Kumaran: Ryan have paid so.
456 00:47:18.280 ⇒ 00:47:19.190 Amber Lin: Yeah, yeah.
457 00:47:19.190 ⇒ 00:47:22.020 Uttam Kumaran: There has to be some correction here.
458 00:47:22.570 ⇒ 00:47:24.539 Amber Lin: Yeah, I think
459 00:47:24.940 ⇒ 00:47:35.410 Amber Lin: I talked to them a lot on this, like, when I was planning this side this current sprint. I got his time. We talked individually afterwards, and like I’m concerned
460 00:47:36.455 ⇒ 00:47:37.319 Amber Lin: about
461 00:47:37.530 ⇒ 00:47:59.249 Amber Lin: because we’re in the audit phase for the revenue mart. I was like, I’m I’m very concerned that Kyle is gonna take a lot of time on this and what me and Dom a lot of agreed on. So a lot is gonna meet with Kyle 10 min each day, just to get Kyle’s process unblock him, and so sort of make sure that he’s on track
462 00:48:00.100 ⇒ 00:48:06.999 Amber Lin: of his hours so hopefully. That will help, because it’s hard for me to gauge how much hours he spent
463 00:48:07.770 ⇒ 00:48:08.860 Amber Lin: cause I
464 00:48:09.030 ⇒ 00:48:17.609 Amber Lin: like. I can only determine if a ticket is done on a day basis. I don’t know how much hours he spent in that day.
465 00:48:18.790 ⇒ 00:48:29.089 Uttam Kumaran: Yeah, I mean, but we’re gonna start looking at this hourly weekly. So at least you’ll be able to look at like, what was our goal hours like weekly. And what are we at?
466 00:48:29.380 ⇒ 00:48:31.322 Uttam Kumaran: Per person? Yeah,
467 00:48:32.290 ⇒ 00:48:54.210 Amber Lin: Sorry. One thing that was really helpful when I was working on ABC tickets. And this is thanks to Mustafa. He asked me, what’s my cab this week, and I told him the cab, and then he was able to tell me per ticket. Okay, yeah. I spent so many hours on this. So far, I really like that. And I think I want to implement that for all of these tickets, it’s just so simple.
468 00:48:54.750 ⇒ 00:49:00.830 Uttam Kumaran: But the equivalent of that is like you need to. You need to take your hours and turn that into that points. Estimation.
469 00:49:01.940 ⇒ 00:49:03.970 Amber Lin: It is like for, for.
470 00:49:05.390 ⇒ 00:49:08.620 Uttam Kumaran: But if Kyle’s is, is consistently taking
471 00:49:08.950 ⇒ 00:49:13.030 Uttam Kumaran: longer than his estimation, then that needs to be brought up to a wish.
472 00:49:13.660 ⇒ 00:49:18.949 Uttam Kumaran: Either he’s underestimating or he’s not able to perform right. There’s only 2 options.
473 00:49:18.950 ⇒ 00:49:19.550 Amber Lin: Okay. Great.
474 00:49:19.550 ⇒ 00:49:25.210 Uttam Kumaran: So like that’s not a don’t throw your hands up in the air and be like, Oh, engineers, just underestimate like
475 00:49:25.740 ⇒ 00:49:33.160 Uttam Kumaran: they they shouldn’t be. We’re we shouldn’t be underestimating. It’s under right. It’s not accurate. So one thing I would tell them is like
476 00:49:33.410 ⇒ 00:49:35.779 Uttam Kumaran: if they’re putting in 2 points.
477 00:49:36.060 ⇒ 00:49:38.640 Uttam Kumaran: and then it doesn’t get done until Friday.
478 00:49:39.370 ⇒ 00:49:41.589 Uttam Kumaran: Then that’s not a 2 pointer. Right?
479 00:49:42.084 ⇒ 00:49:50.269 Uttam Kumaran: So then, what you what you need to do is points for different people like. For example, it may be a 5 point for Kyle and a 2 point for demalade.
480 00:49:50.950 ⇒ 00:49:58.380 Uttam Kumaran: Right. But then this is where you have. We have to sort of then it then the question for I wish is a little bit like, okay, what do we do?
481 00:49:59.250 ⇒ 00:50:01.320 Amber Lin: Right and so.
482 00:50:01.870 ⇒ 00:50:16.910 Uttam Kumaran: It’s i i don’t like. The the engineers will jam you like this because they’ll just take way too long on stuff, and there’s no repercussions unless there is like a hey during retro. You’re like, why did this take? Why did you underestimate this
483 00:50:17.010 ⇒ 00:50:21.110 Uttam Kumaran: like? Because we’ve totally backed up half of our other stuff. Right?
484 00:50:26.880 ⇒ 00:50:27.670 Uttam Kumaran: Yeah.
485 00:50:28.180 ⇒ 00:50:29.050 Amber Lin: Okay.
486 00:50:29.260 ⇒ 00:50:33.170 Amber Lin: Great the the.
487 00:50:33.850 ⇒ 00:50:45.429 Amber Lin: Yes. Okay, I’m taking notes. That’s oh, sorry. ABC, boy, so for ABC.
488 00:50:45.530 ⇒ 00:50:48.450 Amber Lin: After this sprint.
489 00:50:49.808 ⇒ 00:50:52.949 Amber Lin: The documentation is pretty much
490 00:50:53.130 ⇒ 00:50:57.429 Amber Lin: good. Next step I want to enforce. So
491 00:50:58.180 ⇒ 00:51:02.220 Amber Lin: oh, okay, before I get into that, there was some stuff with Snowflake
492 00:51:02.460 ⇒ 00:51:16.323 Amber Lin: blocking the dashboards, blocking the feedback loops. It’s getting fixed now. But that’s something that was a blocker. And Yvette, email me about it. So it’s good. But it’s getting fixed. That’s 1 thing to
493 00:51:17.210 ⇒ 00:51:20.470 Amber Lin: the also on the data dashboard side.
494 00:51:20.650 ⇒ 00:51:27.190 Amber Lin: Luke was taking a while also, probably because he was confused and because there was this, these issues going on
495 00:51:27.580 ⇒ 00:51:29.670 Amber Lin: so that took longer than it should, and.
496 00:51:29.670 ⇒ 00:51:35.760 Uttam Kumaran: Yeah, I mean, I. So so on that point I gave. I sent a direct message to awash, and Luke basically saying.
497 00:51:36.353 ⇒ 00:51:44.189 Uttam Kumaran: All your tickets are taking way longer than expected, and I’m not able to plan. And this is for my team. For AI, I said.
498 00:51:44.510 ⇒ 00:51:50.019 Uttam Kumaran: I assigned you 5 tickets. Each of these should take 2 h. It’s been a week and a half. What’s going on?
499 00:51:50.270 ⇒ 00:51:50.720 Amber Lin: Yeah.
500 00:51:50.720 ⇒ 00:51:58.550 Uttam Kumaran: So I sort of like lit a little bit of a fire. I really need to see him improve.
501 00:51:58.700 ⇒ 00:52:06.620 Uttam Kumaran: or it’s like, gonna be a real issue, because he’s he’s like pretty unreliable, like. I either don’t hear back that he’s stuck.
502 00:52:06.750 ⇒ 00:52:10.349 Uttam Kumaran: or all I hear in stand up is that I’m still working on it
503 00:52:10.560 ⇒ 00:52:19.600 Uttam Kumaran: with some jargon, and I don’t like that because there’s no jargon. I don’t know what the jargon is, because I’m like, oh, you’re blocked by being locked out of Snowflake. Well, unlock it.
504 00:52:20.820 ⇒ 00:52:25.210 Uttam Kumaran: What the fuck are we talking? Telling me it’s on. It’s locked for? Just go unlock it
505 00:52:25.420 ⇒ 00:52:40.470 Uttam Kumaran: like Google had to do that call a waste call, Mustafa. Call anybody on Planet Earth to unlock it? Right? So I can’t like. And that’s happened. That’s happened so often this week that I got very frustrated, because all those pro, like all those tickets.
506 00:52:40.580 ⇒ 00:52:52.557 Uttam Kumaran: a wish or myself, can do in like 20 min. So for those to take 4 or 5 days each. It’s incredibly frustrating. So I sort of. I gave kind of a strike one
507 00:52:53.110 ⇒ 00:52:57.480 Uttam Kumaran: So I want to see sort of when I wish is back. I kind of want to see how.
508 00:52:57.906 ⇒ 00:53:04.529 Uttam Kumaran: I he! He! He’s handling it, and he’s he knows it’s a problem, but like it’s a little bit even frustrating for me, because
509 00:53:04.770 ⇒ 00:53:11.389 Uttam Kumaran: I can’t get any of my stuff reliably done, and the stuff I’m asking him to do is very, very simple.
510 00:53:12.230 ⇒ 00:53:20.960 Amber Lin: Yeah, I feel I feel the same. I I like him as a person. If Annie’s work has been blocked.
511 00:53:21.450 ⇒ 00:53:21.860 Uttam Kumaran: Yeah.
512 00:53:21.860 ⇒ 00:53:23.010 Amber Lin: Dashboard!
513 00:53:23.360 ⇒ 00:53:30.240 Uttam Kumaran: Yeah. So I said, look like, like, yeah, days can’t go by with stuff blocked like that.
514 00:53:30.240 ⇒ 00:53:30.740 Amber Lin: I understand.
515 00:53:31.950 ⇒ 00:53:35.870 Uttam Kumaran: Yeah. So I sent a note. Let’s see if things change.
516 00:53:37.130 ⇒ 00:53:46.490 Amber Lin: Yeah, yeah, sounds good and I know we have backup plans. If this doesn’t work. So it’s just like it’s just an issue that will.
517 00:53:46.490 ⇒ 00:54:06.480 Uttam Kumaran: Yeah, overall. I mean, look, we’re we’re starting to get better. We’re starting to get better talent on the team. And so the bar is gonna continue to rise like the bar is like a swimming pool that’s like slowly filling up. So the people like the more money we get and the bigger we get and the better clients we get the better people we can afford.
518 00:54:06.630 ⇒ 00:54:19.359 Uttam Kumaran: and the more talented people are going to join the team. But it’s sort of the problem. If you have a team of a players and one person that’s a c players, it brings everybody down. And so our job as leadership is a sort of
519 00:54:19.620 ⇒ 00:54:26.580 Uttam Kumaran: like, the floor has to come up higher. And so that’s gonna be on engineering management to sort of make that happen.
520 00:54:26.710 ⇒ 00:54:36.510 Uttam Kumaran: So we gave. Everybody’s been here for quite a while now understands how this stuff works. So I’m gonna continue to put pressure on to make sure that people are able to succeed because.
521 00:54:36.780 ⇒ 00:54:41.359 Uttam Kumaran: like this, the quality of our client work. That’s kind of getting impacted, you know.
522 00:54:41.360 ⇒ 00:54:48.342 Amber Lin: Yeah, I mean, how is the in? How is the new intern? How’s Vishnu? If he’s doing really well? And he’s like,
523 00:54:48.980 ⇒ 00:54:58.750 Amber Lin: he’s a good person to have like we can consider, level him, leveling him up. We don’t have to wait until the internship ends.
524 00:54:59.700 ⇒ 00:55:02.809 Uttam Kumaran: Yeah, I don’t know. It’s completely on a wish. I’m not really too involved. There.
525 00:55:02.810 ⇒ 00:55:04.909 Amber Lin: Talk. Talk about it later. Guys.
526 00:55:06.140 ⇒ 00:55:11.321 Amber Lin: Yeah. Last days on ABC, we’re finishing up the documentation.
527 00:55:12.310 ⇒ 00:55:38.230 Amber Lin: is looking good shape. The Csrs are now got them on the central dock finally, and then next thing I’m going to do is say, like following my roadmap, I want to install trust for the Csr. So I’m going to make a tracker that helps give trusted answers. And now it’s some final testing on the inspector sheet. So, having that will have
528 00:55:38.390 ⇒ 00:55:46.830 Amber Lin: a lot more usage. Just by that. So that’s something important. I tested it today. There were some issues. So
529 00:55:47.020 ⇒ 00:56:01.159 Amber Lin: putting it back. And now we’re editing it again. But hopefully, I think these few actions are just. It will just increase usage, because those are things that people people need. So that’s my plan.
530 00:56:02.370 ⇒ 00:56:07.899 Uttam Kumaran: Okay, heard someone tomorrow, like, Are we gonna be like, are you seeing increases in adoption in the dashboard?
531 00:56:09.020 ⇒ 00:56:10.550 Amber Lin: I need the dashboard.
532 00:56:12.130 ⇒ 00:56:13.540 Uttam Kumaran: Is it still? Not there?
533 00:56:14.320 ⇒ 00:56:17.030 Amber Lin: I need a doubt. I pinged. Today
534 00:56:17.330 ⇒ 00:56:23.658 Amber Lin: I can check. I last time I checked 2 h ago it was still down.
535 00:56:25.840 ⇒ 00:56:26.719 Amber Lin: I mean, that’s dude.
536 00:56:26.720 ⇒ 00:56:28.250 Uttam Kumaran: What is going on like.
537 00:56:29.300 ⇒ 00:56:29.985 Amber Lin: Yeah.
538 00:56:31.260 ⇒ 00:56:33.370 Uttam Kumaran: Can you just check right? It’s not there.
539 00:56:34.090 ⇒ 00:56:36.209 Amber Lin: Not there. Just checked.
540 00:56:40.290 ⇒ 00:56:41.060 Amber Lin: Yeah.
541 00:56:42.450 ⇒ 00:56:47.810 Uttam Kumaran: Okay. Alright. Well, I’m gonna I’ll I’ll make a big scene about that. This is like ridiculous, like
542 00:56:48.040 ⇒ 00:56:51.429 Uttam Kumaran: no one on the team is capable of figuring this out like.
543 00:56:53.150 ⇒ 00:57:02.819 Amber Lin: Yeah, I attacked Luke and Casey. I think I guess both of them are looking at it. I I’m gonna ping again. And on. Pm. Case pm, Casey.
544 00:57:03.110 ⇒ 00:57:08.740 Amber Lin: I trust him more to go. Figure it out. As long as he’s awake he’ll go figure it out.
545 00:57:09.646 ⇒ 00:57:12.233 Amber Lin: Let me check again.
546 00:57:27.710 ⇒ 00:57:30.320 Amber Lin: Okay, okay.
547 00:57:30.320 ⇒ 00:57:31.900 Uttam Kumaran: I think Hannah and I have to hop.
548 00:57:32.160 ⇒ 00:57:33.690 Amber Lin: Okay, go ahead.
549 00:57:35.803 ⇒ 00:57:37.609 Amber Lin: One. Last.
550 00:57:37.610 ⇒ 00:57:44.880 Uttam Kumaran: Just ping me about the just ping me about the dashboard thing. I’ll be back on my laptop in like right 30 min or so so I can figure it out.
551 00:57:45.600 ⇒ 00:57:48.759 Amber Lin: Sounds good alright.
552 00:57:48.760 ⇒ 00:57:49.280 Uttam Kumaran: Okay.
553 00:57:49.730 ⇒ 00:57:53.970 Amber Lin: I put a placeholder for default. Put a placeholder for the
554 00:57:54.140 ⇒ 00:57:58.000 Amber Lin: but gossing, let me know if you remove them.
555 00:57:58.000 ⇒ 00:57:58.790 Uttam Kumaran: Okay. Okay.
556 00:58:00.820 ⇒ 00:58:01.910 Amber Lin: All right.
557 00:58:02.010 ⇒ 00:58:03.200 Uttam Kumaran: Thank you.
558 00:58:03.510 ⇒ 00:58:04.430 Uttam Kumaran: I.