Speaker 1: Hey everyone, welcome back to Data and Donuts. My name is Aaron. I'm here with my friend and colleague, Daniel Martinez. Today we're going to talk about metrics in relation to enrollment management, data trends and the like. But before we get into our conversation today, I'd like Daniel to tell us a little bit about himself.

Speaker 2: Hi, I'm Daniel Martinez. Next week, I don't know when this episode will drop, but July, the first week in July, I will be starting as the Director of College Research at Santa Ana College. So I'm pretty excited about that opportunity. It's going to be cool. I've been doing community college work for over 30 years, older than Aaron, certainly older than his beard. But I've learned a few things, but still have a lot to learn. So I'm glad to be here.

Speaker 1: And that's something I always appreciate about Daniel. He's always willing to try and learn and even ask questions. What's the new thing? And I think that's something that's really big. It kind of leads into our first question today. You know, the first question I really want to look at is how do you track enrollments in full-time equivalent students or FTES?

Speaker 2: Yeah. So actually, to be fair, when I got here at College of the Desert, so I didn't say that. So this was being recorded on my next to last day at College of the Desert. And I will be starting at Santa Ana College next week. So when I got to College of the Desert, the college had contracted with a company to do an FTES thing. And what that required was that one of the analysts at College of the Desert would run a report in Excel and upload that file three times a day. So this company could then spit back information to us, to the college and say, you know, here's what your FTES numbers look like. The problem was that the company was a little slow in responding to some requests. And so people were very unhappy with it. And the tool itself was, it was, to call it clunky is to be generous with how it looked. So thankfully, the person who ran those reports, she was a gifted Excel programmer. And one day she tells me that on her own, she decided to see if the data from that company was correct. And she said that it was. And of course, I took what she said to say, you did that on your own, on your computer? And she said, yeah. I said, great. Now we don't need that company. And so, and that was a good thing because then we were able to make changes according to what people wanted here on campus. And we could do it immediately because it was, I mean, it was our own data in the first place, but now we had a process to do that. The process looks at two different things. We do two extracts. One is the 320 report. We run that every day during the enrollment period and then once a week thereafter. And then a course section download that has enrollments and things like that. And those two files are the backbone to this process where we then collect and report out the 320 report. I mean, the enrollment. But it's a very, it's an accurate process. And we try to make sure that it's up to date with FTSR, with the, with, I can't think of the word. You're going to have to cut this part out. Okay. All good. What's that called? The, the, the, the factor?

Speaker 1: Oh, the term length multiplier?

Speaker 2: The term length multiplier. Thank you very much. I have to change over time. So the term length multiplier that has changed over time since I've been here. And, but it's accurate. And we actually use that report as part of our official 320 reporting as well. So it's with that tool, and that has then helped our office to then communicate this with the, the college campus. To let them know that, you know, here's the numbers we have. And no, we don't have, we don't have information on positive attendance courses because we don't get that data until at the end of the term. And so it's been a very useful, it's been a very useful process for us. And then what we've done is then we've taken that information and we've made it more accessible using data visualization software. So when we send out this information on a daily basis to the college community, they can just see at a glance, you know, how we're doing good, bad, or otherwise. So that's how, that's how we've been doing it. And I, I'm sure that that's what we'll do at Santa Ana College too.

Speaker 1: I think that's really helpful. And you really just bring it down to other people's level and giving them the opportunity to look at that, you know, because a lot of individuals just working just from our experiences is they'll go to the schedule and try to scroll through and just do maybe some, some snapshots or cherry picking some of the classes they're looking at, but it doesn't give them the full picture of what's actually happening. And I think that's really key of what you're doing and, you know, it's hopefully something others can follow in your steps. So I think that's super helpful. And then I think the other part that you mentioned is really giving the opportunity to have the conversation. I think what's going on, how do we pivot? Sometimes we feel that schedules and plans are always in concrete, but the reality is, is they're very nimble and we can change and modify and that's where that data can help. So that's a great approach to doing that. So my next question as we start thinking about enrollment management is, go ahead, Daniel, please.

Speaker 2: Yeah. Yeah. Before, before you, before you ask the next question, one of the, one of the things that came out of this process, and it still comes from those two tools, those two downloads we do, is we were able to create a fill rate table and visualization. The college didn't have it before, but by looking at that information, the fill rates, the deans and vice president of instruction, they use that on a pretty constant basis at the beginning of the term to see how, what sections could be closed, what students could be moved from one section to another. And so that's been a, that whole process has been an extremely helpful process to the college. You know, so we get those two files that we create the enrollments and such. We've also been having some, some, some, some children, if you will, you know, that fill rate tables, which has been extremely helpful. Yeah.

Speaker 1: That does help.

Speaker 2: I'm, I'm, I'm, I'm, I'm still going to kick thunder, I think, to the next question. Because, because that, that also then allows us to compute efficiencies on a daily basis also for enrollment management and, and that kind of thing. So it's all there, you know, from those two files, it's really helpful.

Speaker 1: That is super helpful. And I think to me, when you package it as a, as a single package, it's easier to consume that in a manner that as opposed to try to treasure hunt for that type of data all over the place. So that's, that's a great approach. And so what, and you didn't just mention, you're right, we're leading to the next question is what metrics do you use to measure efficiency?

Speaker 2: But we use the standard, the 5.5. And we, I could try to remember what that, that, because it's a full-time student over two semesters, taking three-unit courses, something like that. Right.

Speaker 1: So the FTF 30, and then they have the FTS to FTF, and then the WISH to FTF.

Speaker 2: Right, right, right. One of the interesting things we've heard from others that when it calls and modifies your calendars, that 525 number should actually be a different number. I think it's 595. Are you familiar with that?

Speaker 1: Yeah, it depends on if your schedule is like a condensed schedule, like a 16-week schedule, that's usually shifted to 595. Wow.

Speaker 2: So, so then they're trying to understand that particular metric, the 525 or the 595. That means that, and did the contact hours for the course actually increase? Because they should have increased. And if they did increase, then you can look at 595 as that metric. But we didn't do that. And so we still use the 525 as the base. And so trying to understand what that means, and these numbers, they're, how can I say this? You can see through, by understanding those equations, and it's not like it's really hard, some basic algebra thing. But you can see that small changes to the schedule, like contact hours, can have a huge impact on both efficiency and FTS. I mean, if you add five minutes to a class, for instance, the increase, I mean, it's only five minutes, but the increase to FTS is huge. And then what that means, then, is that the bottom line is, is impacted very favorably, even with those change, you know, as small as that.

Speaker 1: Those are good metrics to really look at. I remember, historically, fill rate used to be something, and typically for face-to-face it was, but it also depends upon how big your course is. Because if you had a fill rate of like 70% or 60%, but say if you're in a class that holds 500 students, you're doing all right. But if you're in a class that holds like 10 students, right, so it has to add that context, I think. And that's where I've seen some people use it, but then some people don't, just given the context.

Speaker 2: And you're exactly right. You do need that context. And when we do create the fill rate table, there are certain courses that we don't include because for registration processes, they have this huge fill rate. To be honest, what I think is a funny story, the first time I was playing with fill rates, and that was 20 years ago, I was looking at course capacity and enrollment, you know, because the basic idea is pretty simple. And so we had a file that everybody liked and then had a fill rate and had a capacity, and so I did the math. And boy, the administration didn't like that because they're like, we're telling students that there's no room, but these fill rates say we're only at 60%. And I said, well, then maybe the capacities are incorrect. You know, let me pull up a class, you know, do we really have a capacity of 300 in this nursing class? I don't think so. You know, so. That should always be, wow. Right. It's like, I mean, here's the data, you know, always people who work for me, people I interact with, I was like, you have to look at your data to see if it's, and then we as researchers, we can do the math or we can do whatever we're doing. But if the data itself doesn't look right, you know, then you got to go back to the drawing board and say, you know, we need to have maybe more appropriate capacity for these particular courses.

Speaker 1: Most definitely. And I think, you know, you really touched on some key areas. You know, you talked about talking to VPs, deans, presidents, and then also others like admissions and the like. And so when you look at this data, it might be FTES enrollment or efficiency. How do you approach different constituencies or stakeholders with this information? Or how do you share it with them, I should say?

Speaker 2: That's probably a question better asked of the constituents. Because I think, to me, I do a brilliant job. I mean, it's like, how can you not understand? I mean, I'm clear as glass. But I think I'm trying. I try to be very aware that when a lot of people that I've interacted with, they get uptight when it comes to talking about numbers. And so I try to approach it in a very, very relaxed and I don't want to say simple way, but in a way acknowledging that people may be uncomfortable with it. So I need to make, if I can't explain it clearly, then that's on me and not on the other person. So I then may try to try it. Let me try it this way or let me try it this other way. So I try very, very hard to make data as clear as possible to the users when we're talking about that.

Speaker 1: And I think that's really the thing is a lot of times we have these complex analyses. You talked about someone who was really good at Excel and could reformulate and calculate all the great stuff. But the reality is when you had to come and present it to people, they don't need to know the math behind it. They need to know the statistical analyses or what's the p-value. It's really about what's the purpose of our conversation, like you said, and just put it just barely. And it doesn't have to be simple. Just directly to them. So take out all the fantastic math and stuff behind it, but what's the question that we're looking to answer? And it sounds like that's what you do really easily. And I think that's something that people like.

Speaker 2: I try to, I have a, I don't have a motto per se, but I use this mantra that it's as simple as it needs to be. Which means then when somebody is asking a complex question, then we have to go deeper. I remember, it's not related to FTS, but I remember when we were talking about scorecard data, if you remember that. And there was a metric about progression from ESL to causable English. It used the top codes for ESL and then checked to see if those students went into a top code for English. And I had a faculty member who was like, well, I don't understand what this metric is saying. I said, well, if you want to dig into it, I'm happy to do it and I can show you what it is. And so we went down. But that person really appreciated it and got it and was a very ardent supporter of the office once we were able to dig into that together. So that was really nice.

Speaker 1: I think that builds a lot of trust. I mean, I think to me, if someone has inquisitive questions to learn, like, you know, you and I get questions all the time when someone just asks questions to be silly or just to ask questions. It's nice to know. Even the nice to knows can really help educate and inform others. So it builds that trust. And I think that's the biggest thing that our field really has is how do you build trust to strengthen your integrity and others will then leverage or utilize the work that we provide or the services we provide. I think that you gave a brilliant example of that, where someone who may not be as comfortable with data got a little bit more detail and now is more or less a follower collector of the data. So I think that's great.

Speaker 2: It was great. We developed a really nice relationship.

Speaker 1: Excellent, excellent. So I get to my final question. So the bonus question this year is what do you prefer more, coffee or tea? And which kind?

Speaker 2: That's not even a question for me. It's coffee. I'm a I'm a self-proclaimed coffee snob. OK, so I don't know how much you're going to use for this, but I'm going to tell you the story anyway. I used to get when even when I was high school, I would get coffee from Sweden because I saw something and I said, oh, let me get this coffee. Sounds good. But the story I'm going to tell you is that back in 2015, we went to Italy's poor cooking school and one of the dishes we learned to make was tiramisu. Come back from that and we started making tiramisu for various parties and whatnot. At the time, we were using folders or something, you know, which is fine. Get the cookies, whatever. And we were making it one time. We ran out of coffee. So I say to my fiancee, not my fiancee, I say to her, do you have more coffee? So she starts to rummage through to her, her pantry and she finds some coffee. And I said, where'd you get it? She said, I don't know. She said, we've had it before. She said, no, I haven't. And I said, OK, well, let me let's let's try it. I was fully expecting to be completely disappointed. For the coffee, I breathe it very strong. I put it in a dish and then I start to soak the cookies and put it in the thing. And as I, as I, it smells really good and I'm dipping the cookies and the smell is just really rich. And so then I get a spoon and I try it. I said, this coffee is fantastic. It's unbelievably great coffee. And I, it's a coffee from, I'm not, I don't have stock of it. This company, if you're interested, ask me, but I had it there from Alaska, if that tells you anything. And I had been ordering five pounds of coffee on a monthly basis ever since. It's been six, seven years now. It, it, I have just, I love this coffee. It's one of the best coffee I've ever had. That's amazing. What's the brand name? If you can recall. The brand name is. Ravensbrew Ravensbrew in a particular, they have different blends. The particular one that I love is, it's called the Bruin blend. Bruin blend. So it's a, it's a medium coffee. Of course I like the French press. I love my espressos and yeah, but yeah, but I have my coffee here too. Excellent. Excellent. No, I just looked it up right now. And so I'm going to probably order myself some as well.

Speaker 1: And we'll have to exchange different coffee types. Awesome. Awesome. Thanks for sharing that. They have a, they have like a, like a sampler pack. And there's, I forget the name of the book, so that story won't work, but.

Speaker 2: There's one about a goat. It's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a, it's a goat. It won't work, but there's one about a goat. I won't give the name, but when you see the name, you'll appreciate it. I think you'll appreciate it. But they have, they have dead man's brew and they have a whole bunch of them, but that, that the Bruin blend is my favorite. I just love that. But I warned you, I warned you that if you, if you try it, you know, I think you'll be hooked. If you're a coffee person, I, you know, it's, it's, it's amazing. It really is.

Speaker 1: Awesome. Cool. Well, Daniel, that's been not just educational today, talking about enrollment management metrics, but also the coffee that that's, like I said, now I, now I've started purchasing something else. So thanks so much friend and congratulations on the, on the new job when this posts, it'll probably be like the normal job, but, but for now congrats on that. So, so cool. And I'll see you around and we'll talk later. Have a good one. All right. All right.