Meeting Title: PharmOps Omni Reporting Date: 2026-03-19 Meeting participants: Mustafa Raja, Rebecca Emch, Greg Stoutenburg, Amber Lin
WEBVTT
1 00:00:20.760 ⇒ 00:00:21.940 Rebecca Emch: Hello!
2 00:00:22.810 ⇒ 00:00:24.100 Mustafa Raja: Hey, how are you?
3 00:00:24.610 ⇒ 00:00:25.870 Rebecca Emch: Good, how are you?
4 00:00:25.870 ⇒ 00:00:27.189 Mustafa Raja: Yeah, I’m doing good.
5 00:00:29.800 ⇒ 00:00:34.329 Mustafa Raja: Let’s wait a couple minutes for Amber, and then let’s get started.
6 00:00:35.870 ⇒ 00:00:36.770 Rebecca Emch: Yeah, sure.
7 00:00:50.660 ⇒ 00:00:51.490 Greg Stoutenburg: Hey, team.
8 00:00:52.520 ⇒ 00:00:53.370 Mustafa Raja: Hey, how are you?
9 00:00:54.740 ⇒ 00:00:56.020 Greg Stoutenburg: Doing great, how are you?
10 00:00:56.360 ⇒ 00:00:56.770 Amber Lin: Feathers!
11 00:00:58.020 ⇒ 00:00:59.560 Greg Stoutenburg: Hey, Amber, that’s a cool background.
12 00:01:00.370 ⇒ 00:01:04.840 Amber Lin: Well, you have that, too. It’s in our folder. Hi, Rebecca!
13 00:01:05.209 ⇒ 00:01:06.229 Rebecca Emch: Hello!
14 00:01:06.920 ⇒ 00:01:07.730 Greg Stoutenburg: Hello?
15 00:01:08.700 ⇒ 00:01:11.010 Rebecca Emch: Brain Forge! I like it!
16 00:01:11.410 ⇒ 00:01:15.100 Amber Lin: Yeah. Our design team’s great. They made this for us.
17 00:01:18.350 ⇒ 00:01:19.130 Rebecca Emch: Nice.
18 00:01:19.130 ⇒ 00:01:20.669 Amber Lin: So where are you based in?
19 00:01:20.820 ⇒ 00:01:21.910 Amber Lin: Oh, yeah.
20 00:01:22.650 ⇒ 00:01:24.919 Rebecca Emch: I’m in Atlanta, Georgia.
21 00:01:25.520 ⇒ 00:01:26.880 Amber Lin: Oh, wow.
22 00:01:27.620 ⇒ 00:01:29.510 Amber Lin: Cool, I’m in LA, so…
23 00:01:29.970 ⇒ 00:01:30.650 Rebecca Emch: In LA.
24 00:01:30.650 ⇒ 00:01:32.320 Amber Lin: I’m different. Yeah, I’m in LA.
25 00:01:32.690 ⇒ 00:01:35.269 Rebecca Emch: Oh, wow. Well, that’s a fun place to live.
26 00:01:35.270 ⇒ 00:01:38.169 Amber Lin: It’s very sunny today, it’s kinda hot.
27 00:01:39.230 ⇒ 00:01:40.060 Rebecca Emch: Okay.
28 00:01:40.430 ⇒ 00:01:43.010 Rebecca Emch: Where are the rest of you guys located?
29 00:01:45.710 ⇒ 00:01:47.810 Mustafa Raja: I am living in Pakistan.
30 00:01:49.430 ⇒ 00:01:50.880 Greg Stoutenburg: I’m in York, Pennsylvania.
31 00:01:52.340 ⇒ 00:01:54.870 Rebecca Emch: Oh, wow. Did you say Pakistan?
32 00:01:54.870 ⇒ 00:01:55.610 Mustafa Raja: Yeah.
33 00:01:56.160 ⇒ 00:02:00.790 Rebecca Emch: Okay, so we’re all over the place. All the time zones are covered here.
34 00:02:02.740 ⇒ 00:02:05.949 Greg Stoutenburg: Oh, sorry. My dog heard me talking, so now he has to go out.
35 00:02:06.350 ⇒ 00:02:10.110 Rebecca Emch: Of course Aww, what kind of dog is that?
36 00:02:10.610 ⇒ 00:02:13.270 Greg Stoutenburg: He’s an Irish wolfhound.
37 00:02:13.720 ⇒ 00:02:19.750 Greg Stoutenburg: And but he forged some paperwork early in his life to make it appear that he was a Labradoodle.
38 00:02:20.050 ⇒ 00:02:29.429 Greg Stoutenburg: But, yeah, he’s a foot too tall and 60 pounds too big to be a Labradoodle, plus I don’t like one at all.
39 00:02:30.190 ⇒ 00:02:30.810 Rebecca Emch: Good.
40 00:02:30.810 ⇒ 00:02:31.350 Greg Stoutenburg: Yeah.
41 00:02:32.200 ⇒ 00:02:36.560 Rebecca Emch: Okay, yeah, I have a yellow lab. I love big dogs.
42 00:02:36.560 ⇒ 00:02:45.239 Greg Stoutenburg: Okay, yeah, yeah, yeah. He’s a good boy. He’s, he’s about 120 pounds, and I can pet him standing up. I don’t have to bend down at all. That’s kind of nice.
43 00:02:45.570 ⇒ 00:02:46.650 Rebecca Emch: Wow.
44 00:02:46.900 ⇒ 00:02:47.630 Greg Stoutenburg: Now…
45 00:02:48.230 ⇒ 00:02:50.960 Rebecca Emch: Growing like a moose, not a dog.
46 00:02:50.960 ⇒ 00:02:53.639 Greg Stoutenburg: Yeah, that’s right. That’s right, yeah.
47 00:02:55.530 ⇒ 00:02:57.420 Rebecca Emch: Alrighty, so…
48 00:02:58.140 ⇒ 00:03:06.639 Rebecca Emch: I have, a couple of things on our agenda for today. Amber, I didn’t know if you wanted to…
49 00:03:06.790 ⇒ 00:03:19.330 Rebecca Emch: you know, kick off with any preliminary questions or anything about the Omni reports. This is the first time I’ve ever used Omni. I liked what you sent over. Those reports look nice. The visuals… the visuals are nice.
50 00:03:20.380 ⇒ 00:03:29.349 Amber Lin: Yeah, so just a quick overview. We have recreated, most of the dashboards that we had in Tableau, and,
51 00:03:29.700 ⇒ 00:03:34.359 Amber Lin: so Greg and Mustafa is the main people that help us do that, and
52 00:03:34.360 ⇒ 00:03:52.589 Amber Lin: We have some cool features in Omni that let us do what we couldn’t have done in Tableau, so I think part of this meeting would be them kind of introducing you to what Omni is and what it can enable you to do. And I know that you said you have some reporting you want to make for the ELT, so go
53 00:03:53.290 ⇒ 00:04:10.099 Amber Lin: hopefully we can talk here about what you want that to look like. Greg and Mustafa can help you see, when we can build it, how we can build it. So, I think those are the two main things I wanted to cover today. So, Omni and the report you want.
54 00:04:10.680 ⇒ 00:04:11.550 Rebecca Emch: Perfect.
55 00:04:12.700 ⇒ 00:04:27.569 Greg Stoutenburg: Sure, yeah, so, I think maybe the best way to get started, and I’ll have a hard stop at half past the hour, but maybe I could just do, like, a brief overview of Omni, and then, and turn it back to you for particular questions or anything like that, if that sounds good.
56 00:04:28.550 ⇒ 00:04:29.130 Rebecca Emch: Yeah.
57 00:04:29.290 ⇒ 00:04:32.009 Greg Stoutenburg: Do that? Okay. Here we go.
58 00:04:34.400 ⇒ 00:04:36.550 Greg Stoutenburg: Were you in Tableau previously?
59 00:04:37.790 ⇒ 00:04:38.809 Rebecca Emch: Yes, I was.
60 00:04:38.810 ⇒ 00:04:45.200 Greg Stoutenburg: You were personally? Okay, great. So, what… step one was to achieve parity with Tableau, so if you go here for Hub.
61 00:04:45.620 ⇒ 00:04:51.100 Greg Stoutenburg: you’ll see the familiar folders that you used to see in Tableau for the published dashboard. So,
62 00:04:51.260 ⇒ 00:05:05.309 Greg Stoutenburg: these folders here contain all of those charts and dashboards that you would have seen in Tableau, and they match the data that was in Tableau, you know, point by point, filter by filter, everything like that. So,
63 00:05:05.680 ⇒ 00:05:13.550 Greg Stoutenburg: From here, what’s cool about Omni, that you didn’t have access to in Tableau, is the AI Assistant. So…
64 00:05:13.760 ⇒ 00:05:28.809 Greg Stoutenburg: from anywhere in the Omni, sort of, home screens, you can click here for the AI Assistant and type any question you’d like to type, and see this… this character is called Blobby, and you’ll see Blobby proudly wears an Eden hat for fun.
65 00:05:28.810 ⇒ 00:05:29.440 Rebecca Emch: Thank you.
66 00:05:29.870 ⇒ 00:05:52.989 Greg Stoutenburg: The other way to access Blobby, which I’ll show you in just a second, is once you’ve selected a dashboard and you want to explore a dashboard. Now, as we know, LLMs make stuff up. So, but in order to prevent folks from getting bad information, what Omni brings to the table is a layer between the data that’s coming in from, in your case, BigQuery.
67 00:05:52.990 ⇒ 00:05:58.679 Greg Stoutenburg: And, and the queries that you would want to ask of it by defining what are called topics.
68 00:05:59.110 ⇒ 00:06:17.159 Greg Stoutenburg: a… when you ask a question, then, for Blobby, Blobby sort of routes that through what’s called a topic that we’ve built at Brainforge that sort of constrains the answers that Blobby will give to be ones that pull data from particular sets of tables that are joined based on
69 00:06:17.220 ⇒ 00:06:30.260 Greg Stoutenburg: questions that we know you’re interested in. So, and what that means is we just… we sort of took all our records together, and our engineers created these topics, so when you ask a question, it gets routed to the right data sets.
70 00:06:31.610 ⇒ 00:06:33.490 Greg Stoutenburg: Okay.
71 00:06:33.720 ⇒ 00:06:43.710 Greg Stoutenburg: Sorry. So if you’re going to ask a question, you know, something that’ll be a product ops question, you know, probably it’s going to come from… or, sorry, FarmOps question. Probably something like.
72 00:06:43.910 ⇒ 00:06:48.699 Greg Stoutenburg: It’ll come from, like, operations and fulfillment, and maybe pulls… pulls tables from here.
73 00:06:49.110 ⇒ 00:06:52.590 Greg Stoutenburg: That way, you get information that is useful and accurate.
74 00:06:53.960 ⇒ 00:06:56.470 Greg Stoutenburg: Does that make… sort of make sense? It’s like, what Omni…
75 00:06:56.470 ⇒ 00:06:56.860 Rebecca Emch: He’s doing…
76 00:06:56.880 ⇒ 00:06:57.490 Greg Stoutenburg: Okay.
77 00:06:58.190 ⇒ 00:07:02.320 Greg Stoutenburg: Alright, so now let’s just go back here, back to the hub, and…
78 00:07:02.450 ⇒ 00:07:11.880 Greg Stoutenburg: click on FarmOps, these are the tables that you would have seen previously. And let’s say that there’s… let’s say that, you know, you… you use the order refund summary
79 00:07:12.030 ⇒ 00:07:12.960 Greg Stoutenburg: A lot.
80 00:07:13.450 ⇒ 00:07:22.489 Greg Stoutenburg: From here, this should be the tables as you saw them in Tableau previously. And if you want to explore your data a little more, you can click Explore.
81 00:07:23.400 ⇒ 00:07:40.430 Greg Stoutenburg: And here, you can… you can do the familiar sorts of things that you would do with, you know, with the dashboarding tool. You can, you know, you can move columns around, you can add calculations, things like that, if you would do that kind of work. Or even better, you can click that AI Assistant button again.
82 00:07:40.830 ⇒ 00:07:44.080 Greg Stoutenburg: And ask questions right here about this information.
83 00:07:44.770 ⇒ 00:07:51.340 Greg Stoutenburg: And in addition to being able to ask questions, you can also get it to create new stuff. So let’s just jump right into that.
84 00:07:52.080 ⇒ 00:07:57.189 Greg Stoutenburg: Here. Alright, let’s just look at our column G, and I’ll say, create a,
85 00:07:57.350 ⇒ 00:08:10.789 Greg Stoutenburg: Chart that uses a trend line to show average Refund amount… On a daily basis.
86 00:08:11.830 ⇒ 00:08:15.730 Greg Stoutenburg: Over the last… 90 days.
87 00:08:16.880 ⇒ 00:08:17.620 Greg Stoutenburg: Alright.
88 00:08:17.960 ⇒ 00:08:19.050 Greg Stoutenburg: This should work.
89 00:08:19.730 ⇒ 00:08:24.330 Greg Stoutenburg: But this is a live demo, and I just made up this question, so… Wish us luck.
90 00:08:25.540 ⇒ 00:08:29.509 Greg Stoutenburg: Okay. It did what I wanted to.
91 00:08:30.070 ⇒ 00:08:37.489 Greg Stoutenburg: It’s… well, part of it, right? And it’s saying, now I’ll create the line chart with the trend line. Cool. So this new chart should be coming out.
92 00:08:43.789 ⇒ 00:08:44.599 Rebecca Emch: Okay.
93 00:08:45.290 ⇒ 00:08:49.079 Greg Stoutenburg: Slick, huh? Pretty cool. Now…
94 00:08:49.350 ⇒ 00:09:05.480 Greg Stoutenburg: From here, you can edit this thing if you want to, or maybe this is something that you think, like, oh, I’ve got to give a presentation later, and I need some images that I’m going to put in my slide. This would be a good representation of this. This thing I need to talk about, I can hit this dashboard button here.
95 00:09:05.480 ⇒ 00:09:19.919 Greg Stoutenburg: And, you can sort of save it in, like, a private workspace. So, I can have my, you know, my refund charts for execs, or whatever, or my, you know, Rebecca scratch pad, or whatever. You can name it, just hit save, and then you’ll have your own private workspace.
96 00:09:20.240 ⇒ 00:09:21.720 Rebecca Emch: Wow, love that.
97 00:09:21.720 ⇒ 00:09:28.230 Greg Stoutenburg: Yeah, so, and then finally, let’s see, let’s get out of here. Give me, get me out.
98 00:09:29.510 ⇒ 00:09:30.280 Greg Stoutenburg: Go back.
99 00:09:31.930 ⇒ 00:09:34.029 Greg Stoutenburg: Nope, did that already. Let me out.
100 00:09:35.770 ⇒ 00:09:36.630 Greg Stoutenburg: Nope.
101 00:09:39.800 ⇒ 00:09:44.290 Greg Stoutenburg: Okay, I’m gonna go back to the hub, because I got myself trapped.
102 00:09:44.390 ⇒ 00:09:57.670 Greg Stoutenburg: And if there is some… some chart or some dashboard that you know you’re interested in, you want to refer to often, you can… you can just star it, add it to your favorites, and then, in that way, have your own sort of curated favorites area here that you refer to regularly.
103 00:09:58.090 ⇒ 00:09:58.830 Rebecca Emch: Okay.
104 00:09:59.600 ⇒ 00:10:00.610 Rebecca Emch: Alright. Very nice.
105 00:10:00.610 ⇒ 00:10:05.050 Greg Stoutenburg: that’s the 6-minute overview of Omni.
106 00:10:05.050 ⇒ 00:10:05.500 Rebecca Emch: Love them.
107 00:10:05.500 ⇒ 00:10:09.319 Greg Stoutenburg: Any questions or anything else you’d like to see dug into a little more?
108 00:10:09.770 ⇒ 00:10:25.539 Rebecca Emch: So, for my intents and purposes, you know, Eden Holdco is… has 4 different business units, right? They have Eden Telehealth, which all of this is made based off of Eden Telehealth, so pulling from BigQuery.
109 00:10:25.590 ⇒ 00:10:36.360 Rebecca Emch: I’m the vertical owner of Eden Pharmacy, and so we pull all of our data from Pharmedica prescription software processing system, so…
110 00:10:37.090 ⇒ 00:10:45.029 Rebecca Emch: I guess… Have you guys… Henry was working on this previously? Have you guys already…
111 00:10:45.210 ⇒ 00:10:55.479 Rebecca Emch: looked at the API docs that they have. Have you guys already integrated, or… not integrated, but do you guys already have access to pull the information?
112 00:10:55.700 ⇒ 00:11:01.009 Rebecca Emch: that you need to pull in order to create some of these charts from Pharmetica? Sure.
113 00:11:01.750 ⇒ 00:11:20.219 Greg Stoutenburg: Were these charts charts that existed in Tableau already, that were active and being used? Okay, alright, I just wanted to clarify that point. Okay, I can’t speak to Pharmetica specifically, but, I can ask the team if anyone has access to that or has been working with that, and, you know, we can do what we need to do to get the right data into Omni.
114 00:11:21.000 ⇒ 00:11:45.919 Rebecca Emch: Okay, perfect. I can also, if you don’t have it for whatever reason, which I believe that y’all do have what y’all need, but in case if you don’t, I can introduce y’all to Michelle, who is our rep at Fermetica, and she can give you our own API docs. We had to sign a whole bunch of stuff to get it, so I know that we have it somewhere. I can even see if I can track it down, but just let me know who I need
115 00:11:45.920 ⇒ 00:11:49.470 Rebecca Emch: to include on those emails to get that information.
116 00:11:49.470 ⇒ 00:12:04.379 Rebecca Emch: And then we’ll just be able to pull whatever we need to pull into Omni. But I want to see, certain things, and I can send you what these, charts are, or I guess the things that I want to be able to present to ELT on a weekly basis.
117 00:12:04.420 ⇒ 00:12:17.429 Rebecca Emch: But they want to know what is our average turnaround time internally for just our pharmacy, for our orders. They want to know, what’s our revenue for Eden Telehealth look like versus non-Eden telehealth revenue.
118 00:12:17.550 ⇒ 00:12:32.669 Rebecca Emch: What are our script counts, and then be able to, like, filter that by, you know, certain time periods, certain days, by certain clinics, even. So, those are… those are all things that I would want to…
119 00:12:32.690 ⇒ 00:12:47.200 Rebecca Emch: be able to pull information from, and then whenever y’all pull that information, I can then probably use that AI assistant to make a line chart, because they want to know, are we in the green? Are we actually,
120 00:12:47.400 ⇒ 00:12:55.499 Rebecca Emch: like, what’s our trend to budget? Are we actually hitting our revenue goals or not? Are we hitting our SLA targets or not?
121 00:12:55.500 ⇒ 00:12:56.579 Greg Stoutenburg: Yep.
122 00:12:56.580 ⇒ 00:13:03.070 Rebecca Emch: They want, like, a red, yellow, green type of, like, visual that shows the health of the business.
123 00:13:03.320 ⇒ 00:13:05.600 Rebecca Emch: And it’s trend over time.
124 00:13:06.230 ⇒ 00:13:06.790 Greg Stoutenburg: Yep.
125 00:13:07.000 ⇒ 00:13:30.879 Greg Stoutenburg: Okay, yeah. I mean, the dashboarding work is certainly possible, right? You know, you just showed it. So, yeah, let’s, let’s figure out what next steps are as far as getting the right sources connected, and scoping out exactly what that dashboarding need is, and what that would look like. And, yeah, we can go from there. So, I think the initial next step would just be, we can use the transcript from this call.
126 00:13:30.880 ⇒ 00:13:39.580 Greg Stoutenburg: to understand what the need is, and we’ll, we’ll, you know, we’ll get back to you on what to do. I’ll have to just ask around internally about, you know.
127 00:13:39.580 ⇒ 00:13:51.330 Greg Stoutenburg: who… who knows, who knows about Pharmetica? I don’t off the top of my head, forgive me, I’ve only been working on Eden since sort of late January, and this… that wasn’t the, the subject of it, but yeah, we can… we can look into that.
128 00:13:51.940 ⇒ 00:13:57.820 Rebecca Emch: Okay, Robert, I believe, was copied on some of those emails with Henry, so he might know.
129 00:13:58.430 ⇒ 00:14:08.949 Rebecca Emch: API docs. We do pay for the Enterprise API package right now, so I don’t know what all is in that package versus the standard.
130 00:14:09.190 ⇒ 00:14:28.009 Rebecca Emch: package. We want to get rid of the Enterprise API package, because it’s an additional $3,000 a month that we don’t really use for anything. So, we want to get rid of it. So I would just maybe keep that in mind and see if you’re able to still access the data without that package, or if we have to keep it just for reporting purposes.
131 00:14:28.150 ⇒ 00:14:29.780 Greg Stoutenburg: Yeah, okay, yeah, okay.
132 00:14:29.980 ⇒ 00:14:35.809 Greg Stoutenburg: Okay, yeah, sounds good. Need, need heard, and we’ll follow up.
133 00:14:36.470 ⇒ 00:14:45.080 Rebecca Emch: Awesome. And then, should I just send you my request list for, like, revenue, turnaround time, script volume?
134 00:14:45.650 ⇒ 00:14:49.639 Greg Stoutenburg: Yeah, that sounds great. Yeah, go ahead, Amber. I think this part’s more you.
135 00:14:50.020 ⇒ 00:15:05.010 Amber Lin: Yeah, if you have those requirements, just drop them in the channel that we’ve already been talking, and we also have what we… what we talked about in this meeting. We’ll consolidate them, confirm what we have on Pharmedica, and then, we’ll see what we can
136 00:15:05.010 ⇒ 00:15:11.060 Amber Lin: map out for individual requirements, can we do this, can we not do this? So, we’ll get back to you.
137 00:15:11.650 ⇒ 00:15:13.310 Rebecca Emch: Alright, perfect.
138 00:15:13.840 ⇒ 00:15:14.380 Greg Stoutenburg: Yep.
139 00:15:14.720 ⇒ 00:15:16.479 Rebecca Emch: Alrighty, any other questions for me?
140 00:15:17.400 ⇒ 00:15:28.570 Greg Stoutenburg: Cool, I don’t think so, off the top of my head. The folder that I showed with FarmOps, tables and dashboards, do you… do you use those?
141 00:15:28.850 ⇒ 00:15:30.810 Greg Stoutenburg: Regularly as they are, or is there anything.
142 00:15:30.810 ⇒ 00:15:44.009 Rebecca Emch: I used to, whenever I worked for Eden Telehealth, but I don’t work for Eden Telehealth anymore. I work for Eden Pharmacy now, so I… now that I’ve transitioned over to this land, I almost never, ever look into stuff like that anymore.
143 00:15:44.010 ⇒ 00:15:44.780 Greg Stoutenburg: Okay.
144 00:15:44.780 ⇒ 00:15:45.659 Amber Lin: Oh my gosh.
145 00:15:45.660 ⇒ 00:15:51.930 Rebecca Emch: don’t really, like, mean anything to me anymore. I used to oversee… I used to be Brad in the previous position.
146 00:15:52.980 ⇒ 00:16:05.059 Rebecca Emch: Whenever I moved over to become the vertical owner of pharmacy. So all of that stuff, like the order journey, all that stuff that y’all had previously, those were based off of a lot of my requests that I put in a long time ago.
147 00:16:05.060 ⇒ 00:16:06.100 Greg Stoutenburg: Okay.
148 00:16:06.130 ⇒ 00:16:10.510 Rebecca Emch: And I feel like we were working with Robert and, like, a whole team of different people, and then Amy.
149 00:16:10.510 ⇒ 00:16:14.410 Amber Lin: Yeah, that makes sense. I remember making those dashboards with you.
150 00:16:14.410 ⇒ 00:16:15.450 Rebecca Emch: Yeah.
151 00:16:15.680 ⇒ 00:16:16.460 Amber Lin: Yeah, yeah.
152 00:16:16.460 ⇒ 00:16:17.040 Greg Stoutenburg: Okay.
153 00:16:17.040 ⇒ 00:16:17.410 Rebecca Emch: Yes.
154 00:16:17.410 ⇒ 00:16:27.239 Greg Stoutenburg: Okay, got it, yeah. Yeah, so maybe… maybe Amber’s a good first point of contact for that then, and we’ll, you know, scope out the ask and… and look at what we need to connect.
155 00:16:27.840 ⇒ 00:16:31.939 Rebecca Emch: Alright, perfect. Sounds great. Well, this is good. Thank you.
156 00:16:32.060 ⇒ 00:16:32.920 Greg Stoutenburg: Fantastic.
157 00:16:33.640 ⇒ 00:16:34.260 Amber Lin: Excellent.
158 00:16:34.960 ⇒ 00:16:38.270 Rebecca Emch: Alrighty then, well, I will message y’all on the channel.
159 00:16:38.540 ⇒ 00:16:39.070 Amber Lin: Interesting.
160 00:16:39.230 ⇒ 00:16:42.180 Greg Stoutenburg: All right. Thanks. Thanks, yeah. Bye.