Meeting Title: Omni Introduction - PharmOps Date: 2026-02-25 Meeting participants: Fireflies.ai Notetaker Katie, Greg Stoutenburg, Brad Messersmith, Katie Kramer, Sara Neubauer
WEBVTT
1 00:04:23.870 ⇒ 00:04:25.179 Brad Messersmith: Hey, hello.
2 00:04:25.470 ⇒ 00:04:28.180 Greg Stoutenburg: Hi, Brad, nice to meet you. Seen your name around.
3 00:04:28.630 ⇒ 00:04:30.830 Brad Messersmith: Yeah, nice to meet you too, Greg. How you doing?
4 00:04:31.100 ⇒ 00:04:38.600 Greg Stoutenburg: Doing well, doing well. Yep, halfway through the week, just swimming in Omni land. Yeah, how about you?
5 00:04:39.470 ⇒ 00:04:45.480 Brad Messersmith: Yeah, swimming in some land, I don’t know what to call it these days, but yeah.
6 00:04:45.840 ⇒ 00:04:46.660 Greg Stoutenburg: Yeah.
7 00:04:47.100 ⇒ 00:04:50.890 Greg Stoutenburg: Yeah, let’s see, so we’ve got,
8 00:04:51.340 ⇒ 00:04:59.430 Greg Stoutenburg: Okay, us, Katie, and Sarah have said yes, Rebecca declined, but that’s okay, we can catch up with her later.
9 00:05:01.140 ⇒ 00:05:02.300 Greg Stoutenburg: Hi, Katie.
10 00:05:02.960 ⇒ 00:05:04.309 Katie Kramer: Hey, Greg, how you doing?
11 00:05:04.500 ⇒ 00:05:06.000 Greg Stoutenburg: I’m doing alright, how are you?
12 00:05:06.410 ⇒ 00:05:07.590 Katie Kramer: Doing pretty well.
13 00:05:07.860 ⇒ 00:05:08.829 Katie Kramer: Nice to meet you as well.
14 00:05:08.830 ⇒ 00:05:13.679 Greg Stoutenburg: Yeah, nice to meet you too. As I was saying to Brad, I’ve seen both of your names on things,
15 00:05:14.300 ⇒ 00:05:15.550 Greg Stoutenburg: Haven’t actually talked.
16 00:05:18.410 ⇒ 00:05:19.579 Brad Messersmith: Where are you out of?
17 00:05:19.760 ⇒ 00:05:20.350 Brad Messersmith: Greg?
18 00:05:20.350 ⇒ 00:05:24.579 Greg Stoutenburg: I live in York, Pennsylvania, which is a little under an hour from Baltimore and Harrisburg.
19 00:05:24.830 ⇒ 00:05:25.570 Brad Messersmith: Oh, okay.
20 00:05:25.730 ⇒ 00:05:27.360 Greg Stoutenburg: Yeah, yeah, how about you?
21 00:05:27.730 ⇒ 00:05:36.140 Brad Messersmith: We’re both Midwest, Indiana and, Michigan. I’m in Indiana, and Michigan, not too far from each other, but a lot of snow recently.
22 00:05:36.140 ⇒ 00:05:41.429 Greg Stoutenburg: Okay, well, let’s see, if you’re Indiana and she’s in Michigan, then that’s… I mean, the furthest north she could be is Grand Rapids.
23 00:05:41.800 ⇒ 00:05:51.280 Katie Kramer: Nope, I’m, more east. He’s west from me, like, 2 hours, and I am east, like, 30 minutes from Ann Arbor.
24 00:05:51.420 ⇒ 00:05:52.320 Greg Stoutenburg: Oh, nice.
25 00:05:52.420 ⇒ 00:05:53.660 Katie Kramer: Where exactly?
26 00:05:53.970 ⇒ 00:05:58.270 Katie Kramer: It’s a little tiny town called Pinckney. Nobody’s ever heard of it, but…
27 00:05:58.270 ⇒ 00:05:58.800 Greg Stoutenburg: Yes, I have.
28 00:05:58.800 ⇒ 00:06:00.470 Katie Kramer: Yes, I should. Really?
29 00:06:00.470 ⇒ 00:06:09.089 Greg Stoutenburg: Yeah, yeah, I, let’s see. I’m trying to think about how you get… trying to think about how you get to Pinckney. So, out in Pinckney, so you’re on your way to, Whitmore Lake.
30 00:06:09.230 ⇒ 00:06:16.699 Greg Stoutenburg: Yup, and that’s where… that’s where I go out to play paintball. And my brother’s friend, so I’m from Livonia.
31 00:06:17.520 ⇒ 00:06:24.569 Katie Kramer: Oh, that makes sense, then! That’s why you’ve heard of Pink Me. I was getting a little nervous. How does Pennsylvania know about my little hometown?
32 00:06:24.570 ⇒ 00:06:30.600 Greg Stoutenburg: I know, that’s right, and yeah, and this is not a trick, I don’t have, like, an AI thing that’s just giving me everybody’s location data.
33 00:06:31.360 ⇒ 00:06:32.230 Katie Kramer: That’s awesome.
34 00:06:32.230 ⇒ 00:06:39.590 Greg Stoutenburg: No, that’s very cool. Yeah, I’m from Livonia. My brother is a good friend when he was in, like, third grade. The family moved out to Pinckney as well, so…
35 00:06:39.590 ⇒ 00:06:43.599 Katie Kramer: That’s awesome. We’ve got some cool paintball spots over here, so I can understand why you were doing that.
36 00:06:43.600 ⇒ 00:06:45.869 Greg Stoutenburg: Man, what was it called? It’s called Future Ball.
37 00:06:45.910 ⇒ 00:06:49.919 Katie Kramer: It’s called Hellfire now, because we’re next to Hell, Michigan, so they…
38 00:06:49.920 ⇒ 00:06:50.330 Greg Stoutenburg: Really.
39 00:06:50.330 ⇒ 00:06:57.539 Katie Kramer: I bought it, and now that’s what it’s called. Pretty cool out there. They have, like, a, scary forest around Halloween, and hay.
40 00:06:57.540 ⇒ 00:06:57.970 Greg Stoutenburg: Nice.
41 00:06:57.970 ⇒ 00:06:59.249 Katie Kramer: through it. It’s pretty cool.
42 00:06:59.380 ⇒ 00:07:02.700 Greg Stoutenburg: That’s amazing. Yeah, wow, small world.
43 00:07:02.700 ⇒ 00:07:03.600 Katie Kramer: Right?
44 00:07:03.660 ⇒ 00:07:10.099 Greg Stoutenburg: Cool. Alright, well, I’m glad everyone got to see this, like, Michigan intro chat. Hi Sarah, just saw you sign on there.
45 00:07:10.450 ⇒ 00:07:12.759 Greg Stoutenburg: I’m Greg. Nice to meet you.
46 00:07:13.030 ⇒ 00:07:14.699 Sara Neubauer: Hi there, nice to meet you!
47 00:07:15.580 ⇒ 00:07:17.090 Katie Kramer: Sarah, I miss you!
48 00:07:17.670 ⇒ 00:07:20.140 Sara Neubauer: I miss you, too!
49 00:07:20.700 ⇒ 00:07:21.720 Sara Neubauer: I hope you weren’t right.
50 00:07:21.720 ⇒ 00:07:24.250 Katie Kramer: Farm is doing well, going well, Armine.
51 00:07:25.470 ⇒ 00:07:28.830 Katie Kramer: Or building the farm should be going well at this point.
52 00:07:31.230 ⇒ 00:07:33.109 Greg Stoutenburg: Did I hear Sarah’s building a farm?
53 00:07:34.810 ⇒ 00:07:36.759 Katie Kramer: Last I heard.
54 00:07:36.760 ⇒ 00:07:43.220 Sara Neubauer: Yes, the farm building is well underway, still in progress.
55 00:07:43.640 ⇒ 00:07:45.040 Sara Neubauer: Coming soon.
56 00:07:45.770 ⇒ 00:07:47.529 Greg Stoutenburg: Very cool. Alright.
57 00:07:48.730 ⇒ 00:08:07.000 Greg Stoutenburg: All right, well, yep, nice to meet you all. We can get rolling then. So, the goal of this was to offer you a half an hour to get a sort of overview of what Omni is going to offer, get you familiar with using it, and then just see if you have any questions. Real sort of lightweight intro.
58 00:08:07.000 ⇒ 00:08:29.410 Greg Stoutenburg: the… the goal for Omni has been to enable better self-service for Eden. So, one of the things that we saw is that with Tableau, if there were a question that someone had that wasn’t already answered in a dashboard that had been set up for you, that you had to put in a request, an engineer has to take it, has to fit it in their work schedule, has to build something, has to get the report back from you. And so, what we wanted to do is just
59 00:08:29.410 ⇒ 00:08:44.919 Greg Stoutenburg: put the data that’s already available, because it’s just in your BigQuery tables being sent into, you know, basically, you know, a visualization tool, was to take the data that you already have and just make it easier for you to work with and get answers quickly. So, that’s the… that’s the goal of Omni, and
60 00:08:44.970 ⇒ 00:08:52.900 Greg Stoutenburg: By chance, did any of you see the little preview video that I sent around, last week? Late last week?
61 00:08:53.550 ⇒ 00:08:55.600 Greg Stoutenburg: No, it’s a perfectly fine answer.
62 00:08:55.870 ⇒ 00:08:58.579 Katie Kramer: I’ll be honest, I did not see that come through.
63 00:08:58.860 ⇒ 00:09:00.010 Brad Messersmith: All right.
64 00:09:00.010 ⇒ 00:09:00.550 Katie Kramer: Yeah.
65 00:09:00.550 ⇒ 00:09:25.189 Greg Stoutenburg: No problem at all, yeah. So, I have sent, I’ve sent invitations to your email to join Omni. At the end of this call, we’ll get added to the Omni Slack channel as well, where they’ve got their support rep who’s gonna be in touch at all times. But I’ll just, I’ll just show you what Omni’s gonna offer. So, when you sign in, you’ll see this sort of blank area. An organization admin can designate certain dashboards to appear here in a list.
66 00:09:25.450 ⇒ 00:09:28.870 Greg Stoutenburg: But you’ll see this sort of blank view.
67 00:09:28.870 ⇒ 00:09:51.240 Greg Stoutenburg: And then, what we wanted to do is start by having you go to Hub here, and then these five folders are the different groupings of dashboards that you had in Tableau already. So what we tried to aim for, first of all, is just to get one-to-one parity between Tableau and Omni. So what you’re used to seeing in Tableau, you’ll be able to see here as well.
68 00:09:51.840 ⇒ 00:09:58.690 Greg Stoutenburg: So if you, if you sign in, you’ll come here and go to…
69 00:09:58.770 ⇒ 00:10:01.740 Greg Stoutenburg: FarmOps, because that’s your department.
70 00:10:01.820 ⇒ 00:10:21.499 Greg Stoutenburg: here are your dashboards that you would have interacted with, and, we can just… we can just pick one. Now as we’re looking at this, this is, you know, we can think of this as, like, beta week. We’ve got all of the tables in, but are still working on some… some QA. So, if anything seems off, please do flag it for me, and we’ll make sure to get it taken care of.
71 00:10:22.380 ⇒ 00:10:31.849 Greg Stoutenburg: So this is the order dashboard. This should look like what you would have seen in Tableau. The visualization’s gonna be slightly different, but it’s the same basic charts. Now…
72 00:10:31.930 ⇒ 00:10:51.330 Greg Stoutenburg: If what you need to do is just look at a dashboard that you’re familiar with, and you, you know, you get the information that you need and you move on, then fine, you’re all set. But where Omni becomes really powerful is with that self-service element. So, if you go, then, to here, you can go to Explore.
73 00:10:52.210 ⇒ 00:10:54.580 Greg Stoutenburg: And open up the workbook.
74 00:10:55.320 ⇒ 00:11:08.189 Greg Stoutenburg: you can click this button here, these little stars, and Blobby, the AI system, will come up. And they made… they made a little Eden hat for you. Now, here you can just ask any question.
75 00:11:08.530 ⇒ 00:11:27.420 Greg Stoutenburg: And what it’s gonna do is, is there’s an LLM that’s gonna run this, but what’s really cool about Eden is, unlike just, say, asking ChatGPT, where it’s gonna just feed in any information that it’s got, and sort of, you know, make a guess, kind of, to give you an answer, it’s going to start by selecting
76 00:11:27.470 ⇒ 00:11:51.039 Greg Stoutenburg: topics. So it’s gonna figure out the subject matter of the question that you’re asking, and the subject matter is called a topic, and that’s a join on the various dashboards that you have in BigQuery that were being sent into Tableau that are now being sent into Omni. So what’s cool about that is that anytime you ask a question or you ask Blobby to do something, it’s gonna first relate that to designated datasets that the Brainforge team has created.
77 00:11:51.040 ⇒ 00:11:57.340 Greg Stoutenburg: So to make sure that you’re getting, you know, information that’s actually relevant and accurate. So,
78 00:11:57.340 ⇒ 00:12:02.149 Greg Stoutenburg: So, that’s pretty neat. From here, you can do a couple of things.
79 00:12:02.530 ⇒ 00:12:16.569 Greg Stoutenburg: probably the two most important right now are just ask a question about your data, and another thing that you can do is ask Blobby to, like, create something. So, maybe we want… maybe we want just something like this. I’ll just ask a simple question to start. How about,
80 00:12:19.010 ⇒ 00:12:24.579 Greg Stoutenburg: What is the sum of orders Over the last 90 days.
81 00:12:25.220 ⇒ 00:12:30.680 Greg Stoutenburg: I’ll say, include all… pharmacies.
82 00:12:34.290 ⇒ 00:12:39.909 Greg Stoutenburg: And then it’ll write some SQL that, again, is gonna use the information that’s in the topics that we’ve designated.
83 00:12:47.300 ⇒ 00:12:51.539 Greg Stoutenburg: And then here, it’s just giving you an answer, just spitting out an answer, instead of having to look at it.
84 00:12:52.580 ⇒ 00:13:01.799 Greg Stoutenburg: It also set this filter up here, and gave you a chart and wrote in the past 90 days for the filter. So, that’s pretty cool. Now let’s ask it to do something.
85 00:13:02.390 ⇒ 00:13:15.269 Greg Stoutenburg: About… Create a chart to show me Sales by Pharmacy.
86 00:13:19.450 ⇒ 00:13:28.809 Greg Stoutenburg: Yeah, let’s see what it does here. So, it should at least create a chart, and then what I really want for it to do is to group them by which pharmacy made how many sales.
87 00:13:30.120 ⇒ 00:13:30.959 Greg Stoutenburg: There you go.
88 00:13:31.940 ⇒ 00:13:37.669 Greg Stoutenburg: Pretty cool. Nice starting point, little zigzaggy, we might want to touch it up, you know, before we put it on executive slides.
89 00:13:39.780 ⇒ 00:13:43.989 Greg Stoutenburg: There you go, it’s giving you the sum. Oh, still working on the visualization, cool.
90 00:13:51.330 ⇒ 00:13:56.599 Greg Stoutenburg: Alright, cool. So it’s ranked pharmacies by sale. Does that look…
91 00:13:57.230 ⇒ 00:14:01.250 Greg Stoutenburg: Is this, like, reasonable? Is this, like, within the bounds of reality?
92 00:14:03.920 ⇒ 00:14:04.750 Katie Kramer: I would…
93 00:14:04.750 ⇒ 00:14:10.190 Brad Messersmith: Time frame, maybe. Boothwind seems a little high, but depends on how far back you’re going, probably.
94 00:14:10.810 ⇒ 00:14:16.630 Katie Kramer: I was gonna say, this looks like about, last July orders.
95 00:14:16.890 ⇒ 00:14:21.440 Greg Stoutenburg: Okay. Okay. Yeah, and let’s see, did it give me…
96 00:14:24.450 ⇒ 00:14:29.140 Greg Stoutenburg: Well, I’ll just ask, what is the date range that you used?
97 00:14:35.270 ⇒ 00:14:40.240 Greg Stoutenburg: Didn’t apply a filter. Okay, so it just sort of… it took… it… it just went and counted.
98 00:14:40.240 ⇒ 00:14:43.149 Brad Messersmith: As far back as they go. That makes more sense, then.
99 00:14:43.150 ⇒ 00:15:02.629 Greg Stoutenburg: Yeah. I know, I was thinking, like, wow, that was a nice quarter. Okay, so let’s say we like this chart, and we think, alright, now, not everybody on the team needs to have access to this chart, needs to look at this chart all the time, so I’m not gonna, not gonna add it to the FarmOps folder, but what I am gonna do is I’m just gonna create my own dashboard.
100 00:15:02.810 ⇒ 00:15:12.690 Greg Stoutenburg: And then just kind of, like, save it in my own private workspace area. So I’ll just say this is my, sales revenue by pharmacy.
101 00:15:13.750 ⇒ 00:15:15.700 Greg Stoutenburg: chart, right? And I can save it.
102 00:15:18.530 ⇒ 00:15:23.600 Greg Stoutenburg: And now… Nope. That’s not what I wanted it to do.
103 00:15:24.700 ⇒ 00:15:29.970 Greg Stoutenburg: Get it added here… No, go back. Do not publish that.
104 00:15:31.580 ⇒ 00:15:41.679 Greg Stoutenburg: Okay, I wanted to save this, yes. Okay, Gregory’s documents, good. That is what I wanted it to do. Cool, so it just saved it in my documents.
105 00:15:42.500 ⇒ 00:15:51.599 Greg Stoutenburg: And now, if I click that, I’ll see this here. Now, if there’s some common set of dashboards or charts that I think I’m gonna use often.
106 00:15:52.050 ⇒ 00:15:58.309 Greg Stoutenburg: I can add it to my favorites, so maybe I’ll add this to favorites, and maybe I’ll add,
107 00:15:59.240 ⇒ 00:16:08.550 Greg Stoutenburg: you know, in farm ops, I’ll add, you know, pharmacy by state to my favorites, because what I really want to do is look at those most often. So when I navigate to favorites, I’ve got these set up here.
108 00:16:10.650 ⇒ 00:16:25.879 Greg Stoutenburg: Alright, that is the very, very basic overview of how to use Omni to, to use the AI to create things, to ask questions about your charts, and to navigate what’s been built already, and save other things, and create new workbooks.
109 00:16:28.250 ⇒ 00:16:30.410 Greg Stoutenburg: Anything else you want to try to do while we’re here?
110 00:16:30.770 ⇒ 00:16:32.789 Greg Stoutenburg: Or maybe sign in and try it out while I’m on.
111 00:16:35.660 ⇒ 00:16:41.630 Brad Messersmith: I’m on here, I think I probably, honestly, just need a little more time to digest this and play around with it.
112 00:16:41.630 ⇒ 00:16:42.240 Greg Stoutenburg: Sure.
113 00:16:42.460 ⇒ 00:16:49.249 Brad Messersmith: Who do we go to, like, if we have trouble or need support, are you the right person to kind of reach out to if we run into issues, or…
114 00:16:49.300 ⇒ 00:17:12.739 Greg Stoutenburg: Yeah, the Brainforge team will continue to provide support. I’ll have you added to the Omni channel, and you can ask questions there as well. I’m leading the migration over to Omni, and then reporting needs will be met by Brainforge the way that we’ve always done it. You know, just like if you had an issue with Tableau, the same, you know, protocols there will apply for Omni.
115 00:17:13.270 ⇒ 00:17:19.759 Brad Messersmith: Okay, so if we wanted to convert one of our dashboards into Omni.
116 00:17:20.099 ⇒ 00:17:23.729 Brad Messersmith: Like, for the first time, could you help us do that, or is that, like…
117 00:17:23.950 ⇒ 00:17:34.369 Greg Stoutenburg: I’d be happy to. Yeah, be totally happy to. And if it’s something that you know is gonna be, like, a little bit of a project, you can also just say, like, hey, here’s another dashboard that we want built into Omni.
118 00:17:35.050 ⇒ 00:17:35.730 Greg Stoutenburg: Okay.
119 00:17:35.730 ⇒ 00:17:44.429 Brad Messersmith: Yeah, what I’m thinking, we have an individual on our team that’s kind of currently working on building a dashboard, or some dashboards.
120 00:17:44.430 ⇒ 00:17:48.270 Greg Stoutenburg: And he’s using .Omni, obviously, at this point, so… Yeah.
121 00:17:48.290 ⇒ 00:18:02.199 Brad Messersmith: we’re kind of like, you know, one foot in, one foot out, but if you’re willing to help support, he’s a little bit inexperienced on some of the data side of it, right? So, like, he might not… he’s pretty technically oriented, though. He’s pretty sharp.
122 00:18:02.250 ⇒ 00:18:03.140 Greg Stoutenburg: Yup.
123 00:18:03.140 ⇒ 00:18:09.399 Brad Messersmith: At some point, it might be good if we could connect you with him for maybe a half hour and point him in the right direction on converting that.
124 00:18:09.780 ⇒ 00:18:11.140 Greg Stoutenburg: Yeah, sure.
125 00:18:11.680 ⇒ 00:18:13.460 Greg Stoutenburg: Yep. Yeah, we can work on that.
126 00:18:13.460 ⇒ 00:18:18.460 Brad Messersmith: I think we can spend some time in here and see what we can do on our own, and then, you know…
127 00:18:19.050 ⇒ 00:18:38.079 Greg Stoutenburg: Yeah, that’d be great. So what I would recommend doing, like, as getting started is, get in, look around at the dashboards that you would normally use, feel free at this point, to just go, you know, how does this line up with what I’m used to seeing in Tableau? If you see anything like a discrepancy, do let us know. Like I said, this is beta week, but everything should be in there now.
128 00:18:38.080 ⇒ 00:18:57.539 Greg Stoutenburg: I would recommend also, like, because you can, go ahead and set up a custom workspace, you know, add things to your favorites that you think you’ll use often. The cool thing, again, the cool thing about Omni is just the way that it’s gonna enable self-service for you, so that, you can just, you know, you can get your questions answered without having to reach out for help as often.
129 00:18:58.980 ⇒ 00:19:00.610 Greg Stoutenburg: Yep. Cool.
130 00:19:01.070 ⇒ 00:19:02.030 Brad Messersmith: Sounds great.
131 00:19:02.030 ⇒ 00:19:07.879 Greg Stoutenburg: All right, anyone else, Katie or Sarah, anything else you wanted to try out, or…
132 00:19:08.700 ⇒ 00:19:09.620 Greg Stoutenburg: Anything?
133 00:19:10.750 ⇒ 00:19:18.450 Katie Kramer: No, so far it looks really cool. I like that I’ll have a bot to just ask questions to, and then it can spit out the answers, so that was a really cool.
134 00:19:18.450 ⇒ 00:19:19.000 Greg Stoutenburg: Yup.
135 00:19:19.250 ⇒ 00:19:26.750 Katie Kramer: feature of the platform to see. But yeah, it’s looking really cool, and I appreciate that you’re willing to work with Jason on some of this.
136 00:19:26.750 ⇒ 00:19:28.490 Greg Stoutenburg: Yeah, yeah, yeah, cool, happy to help.
137 00:19:28.730 ⇒ 00:19:29.580 Greg Stoutenburg: Awesome.
138 00:19:31.630 ⇒ 00:19:34.349 Sara Neubauer: Yep, no, no questions. I think I just need to…
139 00:19:34.350 ⇒ 00:19:39.119 Greg Stoutenburg: Play around in it and figure things out, and we’ll reach out for any questions.
140 00:19:39.320 ⇒ 00:19:50.509 Greg Stoutenburg: Yep, you got it. Awesome. Yeah. Yeah, we’ll poke around, and, you know, reach out for help, or, provide any feedback, and, and, yeah. Alright, enjoy! Hope you love it.
141 00:19:51.430 ⇒ 00:19:52.030 Katie Kramer: Thank you.
142 00:19:52.380 ⇒ 00:19:53.069 Brad Messersmith: Sounds good.
143 00:19:53.830 ⇒ 00:19:55.020 Greg Stoutenburg: Nice to meet you all, and take care.
144 00:19:55.020 ⇒ 00:19:56.169 Katie Kramer: Nice to meet you.
145 00:19:56.380 ⇒ 00:19:57.270 Greg Stoutenburg: Bye.