Full Transcript for IFMA Facility Support Services Benchmarking Survey discussion, with author Steven Call

hospitals. 00:04:45.062 --> 00:04:51.173 Hospitals are part of the medical center, but there's a lot of other buildings within that campus that we're also trying to capture. 00:04:51.273 --> 00:04:59.026 So it was, you know, a little bit unique in the name, but that was the idea of capturing what this report really entails. 00:04:59.713 --> 00:05:04.559 I find it's always difficult to name things, kind of this environment. 00:05:05.379 --> 00:05:06.961 Sometimes there's different nomenclatures. 00:05:07.041 --> 00:05:09.845 People call things by different names. 00:05:10.026 --> 00:05:11.627 You're trying to capture a lot. 00:05:11.687 --> 00:05:12.689 You know, you did a lot. 00:05:12.809 --> 00:05:16.593 So sometimes I find that just naming things is one of the most difficult challenges. 00:05:16.612 --> 00:05:16.653 It 00:05:17.733 --> 00:05:17.954 is. 00:05:17.975 --> 00:05:24.281 You're trying to name something where people understand what it is, but also be true to, you know, the... 00:05:25.057 --> 00:05:27.661 the actual information, but yeah, it's part of the fun. 00:05:27.920 --> 00:05:28.221 Yeah. 00:05:28.420 --> 00:05:29.021 And 00:05:30.142 --> 00:05:34.627 since it's North America, obviously United States and Canada hospital, hospitals and medical centers. 00:05:35.267 --> 00:05:35.649 Yeah. 00:05:35.728 --> 00:05:35.988 Yes. 00:05:36.149 --> 00:05:37.310 US and Canada. 00:05:37.370 --> 00:05:41.173 We actually have some, for the first time, we actually have some international data. 00:05:42.355 --> 00:05:54.641 So if you're in Europe or Asia and you're just trying to get kind of a really high level benchmarking information, we actually have an appendix to the report that, that's unique in that area. 00:05:54.781 --> 00:05:57.165 But limited responses in those areas. 00:05:57.206 --> 00:06:02.976 So we didn't provide a lot of information, but really robust data and information for North America. 00:06:03.458 --> 00:06:04.980 How many hospitals are captured in here? 00:06:05.040 --> 00:06:05.923 Do you recall? 00:06:06.805 --> 00:06:13.437 Well, we have over 200 medical centers across the US and into Canada. 00:06:14.081 --> 00:06:19.750 Now, keep in mind that those 200 medical centers on average have eight to 10 facilities. 00:06:19.829 --> 00:06:25.858 So there's about 2,000, you know, data from about 2,000 facilities in this report. 00:06:26.278 --> 00:06:27.319 That's a lot of facilities. 00:06:28.382 --> 00:06:28.882 Yeah. 00:06:28.922 --> 00:06:29.283 Yeah. 00:06:29.382 --> 00:06:30.403 Some good information. 00:06:30.805 --> 00:06:31.365 Yeah. 00:06:31.725 --> 00:06:33.208 When did you begin working on this report? 00:06:33.267 --> 00:06:40.237 I know when we spoke in October, November timeframe, you were finishing up, couldn't talk about it a lot, but when did you start for this particular iteration? 00:06:40.398 --> 00:06:40.478 Yeah. 00:06:41.377 --> 00:06:47.413 uh i think this was started the data the research project was started in summer of 2023 00:06:47.994 --> 00:06:48.855 okay 00:06:49.197 --> 00:07:02.002 so we started pretty pretty heavy into data collection we had a really great advisory team that supported it folks from some of the largest medical centers around, you know, the VA, MD Anderson, Common Spirit, Banner Health. 00:07:02.062 --> 00:07:07.730 So it was a really great, a lot of credit goes to those individuals that really helped support and drive this forward. 00:07:07.850 --> 00:07:12.576 So it happened, got a lot of good information and analysis happened pretty quick. 00:07:12.656 --> 00:07:13.899 So it was great. 00:07:14.519 --> 00:07:26.932 So I do want to ask you obviously about the findings of your survey, but from a process perspective, when you do something like, you know, when you conduct this type of research, what are some of the challenges that you face conducting the research? 00:07:29.456 --> 00:07:39.031 A lot of it is just trying to get enough data or enough information to have some statistically valid information to share. 00:07:39.271 --> 00:07:40.653 We only get two or three responses. 00:07:40.673 --> 00:07:49.125 It would be impossible for us to say, well, we can broadly make some broad assumptions based on these two hospitals. 00:07:49.247 --> 00:07:50.387 It's just impossible. 00:07:50.428 --> 00:08:03.754 So we want to get enough enough responses and enough robust responses because maybe a hospital or a medical center only provides information on plant operations, but we don't get anything on EVS or laundry. 00:08:03.795 --> 00:08:10.824 And so we're trying to get a high number of responses, but also a complete data set of responses from folks. 00:08:10.843 --> 00:08:12.245 So that's usually the hardest. 00:08:12.865 --> 00:08:14.608 Look, we're all very busy. 00:08:14.668 --> 00:08:19.454 Nobody wants to spend hours taking a survey. 00:08:20.129 --> 00:08:28.742 Um, you know, so those are usually the challenges, but like I said, the advisory team through our, our, our network and I've been around for, for, for a long time. 00:08:28.783 --> 00:08:30.365 I know, I know some great folks. 00:08:30.406 --> 00:08:34.251 So it was, you know, calling a friend and say, Hey, can you, can you provide us some information? 00:08:34.292 --> 00:08:40.240 So that's usually the biggest challenge when it comes to, um, generating this, this type of research. 00:08:40.642 --> 00:08:51.269 And then again, I guess, secondly, I would just say understanding what you're trying, you know, developing the survey, to make sure you get the information you're wanting so that you can have a report that's beneficial. 00:08:52.892 --> 00:08:56.256 You mentioned that laundry was covered in survey. 00:08:58.239 --> 00:08:59.321 I was interested to hear you say that. 00:08:59.400 --> 00:09:01.244 Are most organizations outsourcing laundry? 00:09:01.423 --> 00:09:04.948 I know it's not the sexiest thing in the world, but it just stood out to me.

00:09:04.989 --> 00:09:05.929 What's going on with laundry? 00:09:05.950 --> 00:09:06.510 What'd you find? 00:09:06.551 --> 00:09:08.474 Yeah, so... 00:09:08.738 --> 00:09:16.172 Most healthcare, you know, most facility managers have either they do it internally or they outsource their laundry and linen. 00:09:17.052 --> 00:09:30.398 Most healthcare facilities are contracting that work out, but they usually have, whether it's a separate department, usually a lot of times it's baked into the EVS department and they have a couple departments. 00:09:30.529 --> 00:09:32.091 folks that are, that are dedicated to that. 00:09:32.133 --> 00:09:37.681 But yeah, most of that work is, is not done in house as far as the actual cleaning of the, of the lender. 00:09:37.881 --> 00:09:44.451 I mean, they're, they're bringing, they're handling it and distributing it throughout the hospital, but that's primarily been more and more of an outsourced activity. 00:09:45.113 --> 00:09:45.374 Yeah. 00:09:45.614 --> 00:09:45.854 Yeah. 00:09:46.254 --> 00:09:53.225 So what did you, you know, I just want to, I'm going to read something that you wrote in on your LinkedIn profile back in the summer time. 00:09:54.466 --> 00:10:00.594 You said, my summer was spent developing a 2023 medical survey benchmark report sponsored by IFMA. 00:10:00.875 --> 00:10:08.985 In addition to updating staffing and operating costs for facility engineering and EVS, the report includes new information to better support the built environment. 00:10:09.225 --> 00:10:18.639 And you mentioned four things, facility infrastructure, capital renewal benchmarks, cost of deferred maintenance, compliance as a percent of maintenance costs. 00:10:18.960 --> 00:10:20.181 I saw what that percentage was. 00:10:20.241 --> 00:10:20.942 I'm sure we'll get to it. 00:10:21.023 --> 00:10:22.224 That was intriguing to me. 00:10:22.965 --> 00:10:28.730 And- compensation expenses in relationship to staffing levels. 00:10:30.014 --> 00:10:40.821 So I guess, Steve, within those four little buckets of information, what did you find that was surprising or eye-opening for you or just revelatory that you think for the people listening? 00:10:42.754 --> 00:10:50.693 Well, as I mentioned earlier, trying to develop surveys to gather data that can actually produce reports that can be helpful. 00:10:51.075 --> 00:11:12.471 There was always a couple, I'll maybe start, I'll try to address all four of those, but there was always a gap In the previous reports, and one of those gaps was we could predict or show, okay, this is what my FTE numbers should be for my facility engineers based on gross score footage, whatever it might be. 00:11:13.231 --> 00:11:17.198 But the challenge is we never had data that showed compensation. 00:11:17.239 --> 00:11:25.313 So it was very difficult for me to say, well, yeah, maybe the benchmark says I should have 10 facility engineers. 00:11:26.081 --> 00:11:35.374 But I have 15, but how do I know that I'm just not spending significantly less on my outsourcing costs? 00:11:36.215 --> 00:11:37.657 And so it evens out. 00:11:37.756 --> 00:11:42.984 Even though my FTE levels are higher than my peers, I'm actually overall saving money because... 00:11:43.024 --> 00:11:45.366 And so that piece was never there. 00:11:45.407 --> 00:11:59.424 And so now we have data that shows not only this is what your compensation expense should be for your staff, this is the actual number And it also shows your contract expenses. 00:11:59.465 --> 00:12:07.236 So between those three, you can really paint a true picture of, is my facility program, is it running efficiently? 00:12:07.277 --> 00:12:08.798 Does it have the right number of employees? 00:12:08.859 --> 00:12:10.380 Are we spending the right amounts? 00:12:11.042 --> 00:12:19.082 And so that's a new feature that we can now compare to make sure we're comparing apples to apples between what we're doing and what a different organization is doing. 00:12:20.144 --> 00:12:23.210 The other big issue is aging infrastructure. 00:12:23.269 --> 00:12:27.657 That's a topic that I think we're going to continue to hammer over the years within hospitals. 00:12:27.716 --> 00:12:33.245 We just have not had the capital resources to stay on top of that aging infrastructure. 00:12:33.265 --> 00:12:35.690 So we've got growing deferred maintenance backlogs. 00:12:36.211 --> 00:12:44.974 And so this was enough to say, historically, we've always tracked Our operation spending, how much should I be spending on maintenance, on utilities? 00:12:45.955 --> 00:12:49.217 But the other question is, how much should we be spending on capital renewal? 00:12:49.278 --> 00:12:52.902 Not on growth, but on just the renewal of the existing infrastructure. 00:12:52.961 --> 00:12:54.043 What does that number look like? 00:12:55.043 --> 00:13:03.591 And so that's a new finding as well to show, hey, there's a real annual cost that we should all be budgeting for our capital renewal. 00:13:03.611 --> 00:13:07.895 We all know we need that, but now we actually have some information that can support that. 00:13:08.336 --> 00:13:09.778 Tied into that is deferred maintenance. 00:13:10.466 --> 00:13:28.811 So now the data can help support facility managers in developing business cases to reduce their deferred maintenance because, for example, it's three to four times the cost to eventually address deferred maintenance than it was originally. 00:13:28.850 --> 00:13:37.142 So, for example, if I had a roof that needed to be replaced that was a million dollars and I say, well, I don't have the capital, I'm going to defer that. 00:13:37.889 --> 00:13:44.422 Eventually that ends up costing three to four times more than it would have just to address it right when we needed to address it. 00:13:44.522 --> 00:13:50.832 So you think about developing those ROIs that we can then communicate the need for that capital money. 00:13:51.595 --> 00:13:53.759 This information,

this report is helpful for that. 00:13:55.322 --> 00:13:56.844 So I think, yeah, go ahead. 00:13:57.546 --> 00:14:02.033 Within that deferred maintenance, Steve, did you break that down by component? 00:14:03.586 --> 00:14:11.174 By like building, you know, if you got a route, you know, by the building envelope, by infrastructure, how did you break that apart? 00:14:11.254 --> 00:14:12.255 I mean, that's a big nugget. 00:14:13.398 --> 00:14:16.041 Yeah, it is not broken down by building systems. 00:14:16.100 --> 00:14:26.974 So it's just generally how much our hospital spending or should be spending every year on capital renewal costs. 00:14:27.138 --> 00:14:34.066 Now, exactly how that's broken up, like 10% goes to roofs and 5% goes to parks, that's not included. 00:14:34.126 --> 00:14:36.009 Now, we do that for operating expenses. 00:14:36.068 --> 00:14:40.153 We know what percent is going to different areas within our plant operations. 00:14:40.214 --> 00:14:45.780 But this was really the first attempt to just say, just for budgeting purposes, what's the number? 00:14:45.880 --> 00:14:46.822 So that's what it provides. 00:14:47.042 --> 00:14:47.682 Yep, yep. 00:14:48.384 --> 00:14:56.173 And relative to going back up to talking about the aging infrastructure and the cost, how did you... 00:14:57.505 --> 00:15:04.192 How did you define, I guess, did you define it just by the infrastructure's years past useful life? 00:15:04.232 --> 00:15:09.057 How did you attempt to put some definition around defining aging infrastructure? 00:15:11.260 --> 00:15:13.623 Well, again, this is benchmarking. 00:15:13.743 --> 00:15:24.575 So we're just taking an average of what folks are currently spending on capital renewal and say, on average, this is what folks are spending. 00:15:24.595 --> 00:15:31.080 Now, there's an argument to be made that well, we all feel like we're not probably spending enough. 00:15:31.841 --> 00:15:39.932 And so even though that benchmark is available, arguably we could say, well, it's probably still lower than it should be. 00:15:39.993 --> 00:15:48.086 But for a benchmarking perspective, it's interesting to say, well, this is what other peer hospitals are doing as far as their annual renewal expense. 00:15:48.105 --> 00:15:50.710 So that was part of the survey to ask that question. 00:15:50.789 --> 00:15:53.293 How much are you spending on capital renewal, et cetera? 00:15:53.313 --> 00:15:57.246 And I know that you obviously can't, divulge everything. 00:15:57.407 --> 00:16:05.337 Cause you know, at the end of the day, you're also, if you're selling a product and that's certainly understandable, but I, if, so if I ask you something, you can't answer, feel free to say, Hey. 00:16:05.899 --> 00:16:06.119 Yeah. 00:16:06.278 --> 00:16:11.145 And let me mention, let me mention, yeah, this, this, this report is available for anybody to purchase. 00:16:11.225 --> 00:16:12.447 It's at the IFMA bookstore. 00:16:12.467 --> 00:16:18.755 I, I, I

want to say it's around$250 for the report, but it's a great report. 00:16:18.796 --> 00:16:22.761 And if anybody's interested, you just can go to the website and purchase it. 00:16:23.234 --> 00:16:25.976 I've got the one from 2014 right over there in the bookshelf. 00:16:25.996 --> 00:16:27.979 You go to it all the time. 00:16:29.159 --> 00:16:30.140 It's a good resource. 00:16:30.360 --> 00:16:32.243 It's well worth the investment. 00:16:33.104 --> 00:16:50.861 Did you find, and again, I have to tell myself it's a benchmarking report, but relative to the aging infrastructure, are organizations, I'm assuming they're behind in their renewal, but were you able to come to any determinations on that in that regard? 00:16:52.193 --> 00:16:52.573 Yeah. 00:16:53.995 --> 00:16:55.197 So yes. 00:16:55.437 --> 00:17:03.988 So we, we, we did ask, I think we found that approximately 50% of hospitals are in a state of deferred maintenance. 00:17:05.108 --> 00:17:05.189 Okay. 00:17:05.209 --> 00:17:13.219 Meaning they have, they at least have some significant amount of money that, that they have, that they need to address their deferred maintenance. 00:17:13.239 --> 00:17:15.500 So about half the hospitals are experiencing that in the U S. 00:17:17.123 --> 00:17:18.704 Is that a high, your opinion? 00:17:18.785 --> 00:17:20.988 Is that a, Is that a high number? 00:17:21.067 --> 00:17:22.388 Is that what you expected to see? 00:17:22.449 --> 00:17:23.509 Did you have expectations? 00:17:23.971 --> 00:17:24.371 It's high. 00:17:24.412 --> 00:17:27.915 It doesn't seem as high as maybe I thought it might be. 00:17:28.536 --> 00:17:34.001 Yeah, you would think, oh, you know, every hospital's dealing with this as far as referred maintenance. 00:17:34.583 --> 00:17:47.369 But no, I think there are a lot of hospitals that have adequate resources And there's a lot that don't. 00:17:47.390 --> 00:17:51.694 So I do think there's a have and a have not situation right now with a lot of medical centers. 00:17:51.714 --> 00:18:05.453 That's why I think you're seeing a lot of mergers, for example, just because this lack of capital is sometimes driving these needs to merge and continue to be viable. 00:18:06.255 --> 00:18:09.538 Did you get a lot of responses from, or a lot, how do you define a lot? 00:18:09.578 --> 00:18:19.343 But did you get responses from like, critical access or community hospitals or any of those rural hospitals that we figure are suffering for a number of different reasons? 00:18:19.983 --> 00:18:23.087 Did you get responses and were you able to determine anything? 00:18:24.190 --> 00:18:32.661 Yeah, that specific question, you know, to say, hey, is deferred maintenance an issue more for rural hospitals than it is for urban hospitals? 00:18:33.722 --> 00:18:39.413 That I probably can You know, find that that's not necessarily in the report. 00:18:39.473 --> 00:18:42.018 Now, that's something we could probably dig out for the data. 00:18:43.259 --> 00:18:47.445 But I don't know the answer to that as far as, you know, which of these types of hospitals. 00:18:47.886 --> 00:18:57.662 I will say I'm just looking at the report now that, you know, the breakout as far as the response, we had about 60 percent were just general acute care patients. 00:18:58.018 --> 00:19:03.986 And then about 25% was specialty acute care with some military and some academic teaching. 00:19:04.686 --> 00:19:16.563 So we didn't, I don't think we had enough responses from a robust data set up from, these are rural hospitals versus urban to break that data out on the report. 00:19:16.603 --> 00:19:19.066 But that's something that, good question, Pete. 00:19:19.226 --> 00:19:21.449 Maybe we can chat after the call and I can get that to you. 00:19:23.392 --> 00:19:25.114 You have enough going on. 00:19:25.134 --> 00:19:25.213 Yeah. 00:19:25.506 --> 00:19:33.316 Going back to the FTE, the very first thing that you mentioned, and I mean, you know this because you do all your research and you're involved. 00:19:33.936 --> 00:19:36.160 The FTE issue is always a massive one. 00:19:36.180 --> 00:19:43.189 So I would just say, let's say one FTE for 40,000 square feet if it's a new hospital, one FTE for 75,000 square feet. 00:19:43.209 --> 00:19:44.250 I mean, the other way around. 00:19:44.570 --> 00:19:46.773 Old hospital, 40, new hospital, say 70. 00:19:47.114 --> 00:19:53.669 So your benchmarking that old calculation, whatever, that's kind of removed. 00:19:54.711 --> 00:20:12.391 Can you talk a little bit about the measurement and did you find any determination, and maybe this wasn't your intent, if you keep insourced, was there a savings by insourcing versus outsourcing to subcontractors and the like? 00:20:12.451 --> 00:20:13.571 Did you determine anything? 00:20:13.612 --> 00:20:36.584 Yeah, to answer your first question, what I've What I always found curious when we were, you know, early on and when folks were benchmarking FTEs is I always had the questions, how do we know that that metric, so typically area or growth score footage, how do we know that's actually correlated to FTE? 00:20:37.144 --> 00:20:46.459 I mean, so the way to think about that, just pick any metric in the hospital, you could use, you know, the number of nursing staff. 00:20:47.180 --> 00:20:48.342 How do we not, how do we... 00:20:48.801 --> 00:20:59.112 what if our FTE was more aligned with the number of nurses or what if it was aligned more with the number of beds or patient days, right? 00:20:59.132 --> 00:21:00.673 There's all these different metrics to say. 00:21:01.012 --> 00:21:09.161 And so nobody had really ever looked statistically to say, yes, there is a statistically significant association to those metrics. 00:21:09.181 --> 00:21:32.750 We've always just kind of used gross per footage, but a lot of healthcare facilities kind of had heartburn about gross per footage, for example, because it's saying, well, it's not really fair to

compare myself to an outpatient facility growth score footage versus an inpatient facility because there's all of these additional complex equipment and such. 00:21:32.810 --> 00:21:37.738 So that's when I started originally doing some of the research to say, where can I show these ties? 00:21:37.758 --> 00:21:50.265 So what I found was the strongest predictor or the strongest association to FTEs is actually is actually driven by the value of the assets within the facility. 00:21:50.305 --> 00:21:56.435 So that can be determined by something on the balance sheet that's plant property and equipment. 00:21:56.476 --> 00:22:01.064 So the value of that building and those assets is what's really driving it. 00:22:01.183 --> 00:22:15.550 So the more expensive, the more comprehensive or complex that medical center is, it's probably gonna require more FTE to maintain it and troubleshoot and those sort of things. 00:22:15.590 --> 00:22:18.355 So that's kind of a key finding. 00:22:18.414 --> 00:22:26.306 This is previous to this report, but now this report's showing, yeah, it still shows gross score footage, but it also shows current replacement value. 00:22:26.365 --> 00:22:31.132 It shows patient days, it shows admissions, and it does actually show site population. 00:22:31.172 --> 00:22:40.505 So if we have a total population of staff of X, then we can actually predict what our maintenance staff will look like. 00:22:41.314 --> 00:22:43.577 There's a number of metrics that you can look at. 00:22:44.378 --> 00:22:50.087 Maybe your CFO has really said, I only care about patient days or I only care about admissions. 00:22:50.528 --> 00:22:51.049 That's fine. 00:22:51.210 --> 00:22:59.042 Now we have a metric that can be used to then make sure we're selling the value of this report. 00:23:00.605 --> 00:23:01.967 That's interesting. 00:23:02.327 --> 00:23:12.252 So you've broken it down by a number of different areas that a facilities person could use to hopefully satisfy the CFO and what they want to see. 00:23:12.292 --> 00:23:14.816 That's the idea, yeah. 00:23:14.915 --> 00:23:20.722 And most importantly, like I said, that asset value is what's driving it. 00:23:20.742 --> 00:23:23.185 So there's options here. 00:23:23.226 --> 00:23:36.682 The other example is if you're in a hospital, for example, that's more outpatient or a medical center that has more outpatient space, you might... 00:23:37.314 --> 00:23:45.423 You might not want to use bed count, for example, as your metric because it's gonna under-represent the real cost of your facility. 00:23:46.025 --> 00:24:00.582 So you kind of have to think about, okay, well, what I like to do is I like to look at all of the metrics and kind of see how they play out because you're gonna see variations in all, primarily just because the different structure of the hospital and also there's a little bit different association between the metrics. 00:24:00.623 --> 00:24:04.768 So it's a little bit more, I think, progressive way to look at benchmarking. 00:24:04.788 --> 00:24:06.750 Yeah, yeah. 00:24:06.945 --> 00:24:18.942 And I'd imagine, too, kind of along those lines, you were talking about with the medical center that's got a lot of outpatient, but then if you've got a lot of outpatient on the outskirts and your folks are traveling back and forth, that's obviously going to play into your calculation as well. 00:24:19.583 --> 00:24:20.022 That will. 00:24:20.083 --> 00:24:40.204 And I will say on this report, we intentionally did not include, we really tried to say what we're looking at is our traditional medical center campus, and that campus typically includes has about 10 facilities, obviously usually has a standalone hospital with some outlying outpatient buildings, et cetera, because that's a question I get sometimes. 00:24:40.224 --> 00:24:47.773 What about the clinics that are 50 mile radius around and how do we benchmark those? 00:24:47.834 --> 00:24:56.965 And I don't have a really good answer for that because we haven't really been successfully captured the data, but this report's really looking at traditional medical center type environment. 00:24:58.241 --> 00:25:09.778 Did I hear you say, and I know it had been measured in the past, can you talk again to the relationship between more complex equipment and number of FTEs? 00:25:10.199 --> 00:25:13.443 Did you find that you need more FTEs when you have more complex equipment? 00:25:13.763 --> 00:25:14.925 What did you determine? 00:25:15.586 --> 00:25:19.613 Yeah, so it drives FTE count and it drives operating expense. 00:25:19.653 --> 00:25:35.335 So the higher value of that asset you're going to be able to predict higher levels of staffing and higher levels of operating expense. 00:25:35.875 --> 00:25:44.936 So there's a direct correlation between the value of the asset and what we're experiencing as far as FTEs and operating expenses. 00:25:46.849 --> 00:26:00.424 So more complex equipment, I was thinking about it in terms of more complex equipment, more ability to automate and to, I was thinking like of, you know, a BAS where you have a person sitting there. 00:26:00.444 --> 00:26:02.866 That's not necessarily a correct. 00:26:02.886 --> 00:26:12.458 No, when I say complex, I'm typically talking, I'm just kind of painting the picture about why a more complex medical center. 00:26:12.478 --> 00:26:25.163 So think about maybe a, maybe a, you know, a pediatric hospital that maybe has, you know, more complex, more robust medical equipment. 00:26:25.262 --> 00:26:37.982 And so that value of those assets, whether it's medical equipment or the facility or whatever it is, that value is what we're finding has a very strong predictor to our FTE numbers and our operating expenses. 00:26:38.583 --> 00:26:38.844 Okay. 00:26:39.064 --> 00:26:39.404 Gotcha. 00:26:39.684 --> 00:26:40.006 Gotcha. 00:26:43.170 --> 00:26:56.619 Relative to the FTE, and I'm Only focus, and I think you said you prefer the,

you like looking at a number of different data points, but is there one that you find more valuable than another, or it's just dependent on the facility you're measuring? 00:26:58.782 --> 00:27:18.866 So as I said, the plant property and equipment values, which is a number that's found in the balance sheet of an organization, which is really saying this is the value of the asset, the value of the physical asset, It's showing that it has the strongest predictor to FTEs, to operating expenses. 00:27:18.967 --> 00:27:26.538 And what's beautiful about that metric is it also typically addresses whether you have a very small hospital or a very large hospital. 00:27:26.557 --> 00:27:29.141 It doesn't seem to deviate much. 00:27:29.221 --> 00:27:37.142 When you look at gross score footage, for example, you find that when you go into smaller or even patient days. 00:27:37.682 --> 00:27:43.674 So some of the early reports, like in 2010, 2013, they had adjusted patient days as their primary metric. 00:27:44.236 --> 00:27:52.731 And what we found is in smaller, more rural hospitals, it actually had zero statistical correlation to FTEs and operating expenses. 00:27:52.751 --> 00:27:59.246 So that's why a lot of smaller hospitals were kind of scratching their heads saying, these benchmarks just don't seem to align. 00:27:59.686 --> 00:28:01.751 It's because it had no relationship. 00:28:01.771 --> 00:28:03.415 So pick any metric you want. 00:28:03.476 --> 00:28:07.284 I talk about here in the Pacific Northwest, number of pine trees. 00:28:08.162 --> 00:28:09.763 You know, we laugh about that. 00:28:09.884 --> 00:28:13.849 Oh, what if I use the number of pine trees, you know, per FTE? 00:28:13.869 --> 00:28:21.401 I mean, in some senses, that's exactly what was happening with some of these metrics because they had zero correlation to operating expenses. 00:28:21.902 --> 00:28:34.400 So the plant property equipment values or current replacement values is a really strong metric that holds its association regardless of location, of size. 00:28:34.420 --> 00:28:35.561 So it's a really great metric. 00:28:36.577 --> 00:28:39.442 I know you've done a lot of research into salaries. 00:28:40.384 --> 00:28:41.928 You've produced a lot of information. 00:28:41.968 --> 00:28:46.175 Did this particular survey go into anything relative to salary? 00:28:46.215 --> 00:28:47.218 It 00:28:47.258 --> 00:28:50.284 didn't break down salaries by level. 00:28:50.364 --> 00:29:03.298 No, it did provide a holistic view to say, this is how much you should be spending on your, you know, your EVS department should be expecting this number as far as your total compensation. 00:29:03.979 --> 00:29:05.060 So it did provide that. 00:29:05.101 --> 00:29:09.165 It didn't say, well, you know, if you're a manager, you should be paid this. 00:29:09.247 --> 00:29:13.231 And if you're a, you know, a technician, it doesn't break it out that level. 00:29:14.294 --> 00:29:16.316 It also shows specific

to that. 00:29:16.376 --> 00:29:23.378 It does show a breakout in the facility engineering It'll show a breakout by role. 00:29:23.440 --> 00:29:34.560 So it'll show of the 50 FTEs that I'm saying I should have, what percentage of those should be mechanics, what should be plumbers or carpenters or HVAC techs. 00:29:34.641 --> 00:29:37.606 It does break it down by that level of detail. 00:29:38.228 --> 00:29:39.170 How did you determine that? 00:29:40.738 --> 00:29:43.142 Uh, again, it's through, it's through surveys. 00:29:43.241 --> 00:29:49.510 So, you know, the hundreds of hostels, we've said, well, what, what percent of your staff is our carpenters or what percent of your staff are HGC? 00:29:49.530 --> 00:29:59.026 So when we, when we average those things together, that's what we found is, is, is we could accurately and reliably predict, okay, this is kind of the breakout traditionally. 00:29:59.386 --> 00:30:01.128 And again, again, it's a benchmark. 00:30:01.209 --> 00:30:13.806 So yeah, you might have some variation, uh, with, within your group, but it should be You know, if you're seeing this huge difference, like I, based on the size of my hospital, I'm showing I should have two carpenters and I have 15. 00:30:13.826 --> 00:30:18.017 Then you start saying, ah, okay, what's going on here? 00:30:18.057 --> 00:30:24.874 If you have, you know, if the report says you should have two and you have one, okay, you know, that's nothing to be worried about. 00:30:25.442 --> 00:30:33.878 Now, I have to keep reminding myself that you did a benchmarking survey and you weren't doing a trending survey, but you've done a lot of research and I'm sure you can't turn your mind off. 00:30:34.279 --> 00:30:45.721 Did you find anything, though, when you were looking at staffing, size of staffing, anything that kind of, you know, a light in your head and said, oh, that's really interesting just based on what you know about the industry? 00:30:45.741 --> 00:30:47.365 Yeah. 00:30:48.673 --> 00:31:04.717 What I found interesting, I guess I will say, was something new we did was understanding a portion of facility engineering work group by shift, for example. 00:31:04.737 --> 00:31:05.557 That's never been looked at. 00:31:05.597 --> 00:31:10.945 So to say, well, OK, previous reports said I needed 20 facility engineers. 00:31:11.554 --> 00:31:17.540 Now we can actually show, oh, well, this percent should be at first shift, this percent at second shift, this percent at third shift. 00:31:17.561 --> 00:31:27.574 So there's just some, it wasn't surprising, but I just thought this is really helpful, I think, for facility managers to say, there's some real value in this information. 00:31:27.594 --> 00:31:33.701 So that was one area I was kind of proud of to say, I think we've really addressed some gaps in those previous reports. 00:31:34.369 --> 00:31:39.538 The one thing I'll back up to one of your early questions about this compliance issue. 00:31:39.557 --> 00:31:41.220 So what was surprising or interesting? 00:31:43.002 --> 00:31:46.989 That was always a topic that I've heard at various ASHE conferences. 00:31:47.068 --> 00:31:56.983 And as I've met with facility leaders around the country is, you know, we're really getting a lot of pressure for a lot of budget pressures. 00:31:58.306 --> 00:32:10.709 And when it comes to compliance issues, If a CFO says, hey, I need you to cut your budget by 10%, you can't go cut your compliance budget by 10%. 00:32:11.490 --> 00:32:12.511 You can't do that. 00:32:12.551 --> 00:32:22.268 And so what I think folks were looking for is to say, well, if you tell me to cut my budget by 10%, I can't cut my compliance budget. 00:32:22.607 --> 00:32:27.997 So the other areas of my budget is going to be cut by 15% because I'm compensating. 00:32:28.673 --> 00:32:33.662 And so we were able to determine, I think it was about 25% of your maintenance budget is compliance. 00:32:34.242 --> 00:32:39.351 So that's helpful now because, and again, I had no idea. 00:32:39.371 --> 00:32:42.435 I really had no idea how that was going to play out, what it was going to look like. 00:32:42.476 --> 00:32:45.119 But yeah, 25% of your budget is compliance. 00:32:45.140 --> 00:32:55.797 So now again, you have a little, some real data that you can go back to your, potentially to your budget group and say, look, I know you want to cut X, Y, and Z, but we can't cut compliance. 00:32:55.936 --> 00:32:59.648 So You know, really, you're asking probably more than I can handle. 00:32:59.868 --> 00:32:59.969 Right. 00:33:00.009 --> 00:33:04.734 So it's just that that's helpful, I think, for any facility leaders that have that in power with that information. 00:33:05.415 --> 00:33:05.576 It is. 00:33:05.736 --> 00:33:14.666 And so they actually I found that online where a portion of maintenance expense by category reactive was 31 percent preventive. 00:33:15.186 --> 00:33:21.595 You had 41 and then compliance was I'm going to ding you by one percent, 26 percent. 00:33:21.674 --> 00:33:21.835 Yeah. 00:33:21.855 --> 00:33:22.496 So you were close. 00:33:22.816 --> 00:33:23.277 You were close. 00:33:24.238 --> 00:33:24.317 Yeah. 00:33:24.513 --> 00:33:33.644 Yeah, it would be interesting if, and you've got it in this one, so now you can measure it going forward, but historically, I wonder what that number had been for compliance. 00:33:33.663 --> 00:33:40.151 It would be interesting to compare over the years as there's such a focus on compliance and regulatory and risk. 00:33:40.551 --> 00:33:42.473 I have to assume that number is rising? 00:33:42.513 --> 00:33:58.962 Yeah, again, so now that we're tracking that, I'm assuming, I hope that further iterations will continue to track that so we can, again, look at those trends and say, well, actually, we're seeing the portion of our maintenance costs is growing in compliance, for example. 00:33:59.763 --> 00:34:01.505 You also mentioned reactive, right?

00:34:01.525 --> 00:34:10.193 I think we all pride ourselves on being very preventative, but the reality is there's still a huge portion of our maintenance costs that are reactive. 00:34:11.554 --> 00:34:17.501 So that's another trend I hope we see dropping to show, hey, we're becoming less reactive, we're being more predictive. 00:34:18.722 --> 00:34:20.182 So that would be a goal I'd like to see. 00:34:22.244 --> 00:34:34.802 Relative to the compliance portion of it, are you able to, or were you able to break it down again, benchmarking survey, but how much is in-house versus out-house or out-of-house spending for compliance? 00:34:36.485 --> 00:34:55.867 We show what portion of your overall budget, not specific to compliance, but just specific, like what portion is going towards contracted expense, We also show what portion of our workforce is outsourced versus in-house. 00:34:55.947 --> 00:35:00.077 So you can say, okay, I can kind of understand that mix. 00:35:00.376 --> 00:35:07.914 So we have management to staff mix to understand, hey, you know, what... 00:35:08.610 --> 00:35:11.972 what percentage of my program should be management versus staff. 00:35:12.474 --> 00:35:16.538 And we also look at that as a portion of our workforce that are contracted. 00:35:17.038 --> 00:35:21.643 And whether that's biomedical or facility engineering or VS, we show that information. 00:35:23.023 --> 00:35:28.630 Getting back to the, you were talking about the shifts and the three different shifts. 00:35:29.130 --> 00:35:41.166 So were you able to break it down that first shift is more on the reactive second shift predict kind of the PMs and the work order management. 00:35:41.485 --> 00:35:46.670 Were you able to find anything like how people compose those shifts and what they do on those different shifts? 00:35:48.672 --> 00:35:50.094 No, no, sorry. 00:35:50.134 --> 00:35:54.358 Yeah, we didn't dig into that detail to say, well, what's actually happening? 00:35:54.398 --> 00:35:55.480 And that's a great question. 00:35:55.800 --> 00:36:04.668 But this is what's helpful, Pete, is what's fun about this is people get this report and they say, ah, you know, did you get this information? 00:36:04.748 --> 00:36:05.929 I said, well, no, I didn't. 00:36:06.338 --> 00:36:15.713 I take a note and the next iteration, we try to dig into that because this is the beauty of this is we're trying to help the industry move forward and we're trying to help people answer questions. 00:36:16.034 --> 00:36:20.021 So I love these types of questions that I get from people to say, hey, did you dig into this? 00:36:20.141 --> 00:36:24.007 And sometimes I say, no, I didn't, but we'll try to get that next round for sure. 00:36:24.148 --> 00:36:32.101 Well, I got to imagine too, from like a process, like once you define what you want to do, again, you're not working in a vacuum and you're not new to the industry. 00:36:32.514 --> 00:36:37.862 You must see these different tangents, but

you must just stay focused on that mission for this, right? 00:36:37.903 --> 00:36:40.588 Because you can't go all over the place because you'd never complete anything. 00:36:41.228 --> 00:36:51.588 Yeah, and there's a fine line with benchmarking because we want it to be easy, reliable, but easy to use. 00:36:52.509 --> 00:36:54.813 And we don't want this... 00:36:55.777 --> 00:36:58.181 you know, 50 page report that gets confusing. 00:36:58.862 --> 00:37:12.927 So again, you know, we're always trying to find that balance between good information that's helpful without getting too much, you know, the academic side of things that can like, here's so much information that's not useful. 00:37:13.208 --> 00:37:15.952 Like we really, we really try to shy away from that. 00:37:16.052 --> 00:37:17.494 At least, you know, that's my goal. 00:37:18.135 --> 00:37:20.880 And I think we've, we're getting better and better at that. 00:37:21.000 --> 00:37:34.259 And again, besides my own background, we had an advisory team of folks, and they're recognized in the report as well, that I reached out and said, hey, what's something you'd like to know? 00:37:34.559 --> 00:37:36.141 What's not been captured before? 00:37:36.202 --> 00:37:42.070 And so we got a lot of that feedback before we developed the survey to make sure we were trying to capture the right information. 00:37:43.231 --> 00:37:49.472 From both a positive surprise and maybe a a concerning type surprise. 00:37:49.512 --> 00:37:55.599 Was there a positive benchmark that you found and one that was kind of a concerning benchmark? 00:37:59.003 --> 00:38:03.027 I'm looking at the report right now to see if I can... 00:38:07.711 --> 00:38:16.181 So the area that I was most excited about to learn was really this... 00:38:16.545 --> 00:38:24.137 issue of deferred maintenance or aging infrastructure because it's such a big topic that nobody's really ever benchmarked that before. 00:38:24.157 --> 00:38:31.929 So yeah, it was concerning to me when I saw that there was a high level of deferred maintenance. 00:38:32.170 --> 00:38:38.320 It is costing us three to four times the amount that it probably should if we just had the money available. 00:38:39.905 --> 00:38:42.708 But what I, so I'm concerned about that. 00:38:42.989 --> 00:38:46.452 And also most of the time there's an unplanned shutdown. 00:38:46.512 --> 00:38:48.815 It's because it was in deferred maintenance. 00:38:50.016 --> 00:38:56.885 It wasn't, you know, there's all these shutdowns that are happening is because we're not being proactive and we're putting them in deferred maintenance. 00:38:57.385 --> 00:39:02.590 So not only is it costing us more, but it's also most of the time it's impacting revenue as well. 00:39:03.152 --> 00:39:03.891 So we don't necessarily, 00:39:05.253 --> 00:39:05.653 go ahead. 00:39:05.795 --> 00:39:07.016 I think that's where you were just talking. 00:39:07.036 --> 00:39:08.757 I was gonna say, were you able to quantify

that? 00:39:10.018 --> 00:39:21.713 Yeah, so we actually show, well, we weren't able to say, well, it's this dollar amount, but we were able to say most of the time a shutdown occurs, it's impacting revenue. 00:39:22.534 --> 00:39:27.581 So not only does it cost us three or four times more, but on top of that, we're losing revenue. 00:39:28.541 --> 00:39:44.380 So even though this is kind of a negative in that we're showing, wow, deferred maintenance is really costing us a lot of money, There's a positive spin to that to say, well, now we actually have data that can support us in developing a business case. 00:39:45.282 --> 00:40:00.893 Instead of just kind of saying, hey, we're all really nervous that, you know, something might, you know, something might shut down and we really, you know, this boiler is really on its last leg and it's all, you know, historically, it's all been kind of quantitative or qualitative. 00:40:01.173 --> 00:40:02.215 We don't feel good about it. 00:40:03.277 --> 00:40:10.148 But now we have real dollars and cents that facilities leaders can use to now compete, right? 00:40:10.228 --> 00:40:11.371 Because there's limited capital. 00:40:11.992 --> 00:40:20.925 And so we're competing against a lot of times revenue generating proposals to say, hey, if I buy this new MRI, we're going to see this ROI, right? 00:40:21.378 --> 00:40:27.686 Now we can actually compete on level ground with those type of capital requests because of the data that we now have. 00:40:28.628 --> 00:40:28.708 Yeah. 00:40:28.728 --> 00:40:29.250 Yeah. 00:40:29.269 --> 00:40:38.143 So this is, excuse me, this is information that a director can take right up to the CFO and tie it directly there to a cause. 00:40:39.605 --> 00:40:40.626 I think that's the beauty of it. 00:40:40.686 --> 00:40:40.927 Yeah. 00:40:41.067 --> 00:40:50.840 So it's information that can now be used to develop capital requests that can compete fairly with an ROI attached to it, to other assets. 00:40:51.713 --> 00:41:00.045 I don't know if you mentioned this, and I don't know if it was part of it, but did you do anything relative to, did you do anything, you didn't do enough, Steve, do more next time. 00:41:00.065 --> 00:41:10.980 I don't mean it that way at all, but relative, did infrastructure, aging infrastructure, renewal, anything from like a capital planning perspective included in the survey? 00:41:11.019 --> 00:41:13.583 Well, absolutely. 00:41:13.643 --> 00:41:23.918 So when you talk about capital planning, saying, well, how much, you know, based on our size, on our, whatever metric you want to pick, right? 00:41:23.958 --> 00:41:26.824 Beds, replacement value. 00:41:27.244 --> 00:41:34.797 Based on whatever metric, there's a benchmark now saying, well, this is how much you should be spending every year in capital renewal, right? 00:41:34.878 --> 00:41:36.340 It's not operating expense. 00:41:37.282 --> 00:41:38.945 It's just in a renewal. 00:41:38.985 --> 00:41:51.324 So

I should be, you know, based on the hospital, I should be spending X number of dollars on, you know, on capital renewal to make sure I'm not falling into a state of disrepair. 00:41:51.824 --> 00:41:59.677 So facilities can use that now to say, hey, capital planning, I know how much, at least based on a benchmark, I should be spending every year. 00:42:00.217 --> 00:42:02.541 So it's really helpful in that sort of area. 00:42:03.501 --> 00:42:18.094 I know it wasn't part of your survey, but whether it be anecdotally, did you find that our facilities folks, so I guess I'm concentrating more on the facilities, are they getting pulled in different directions than in the past? 00:42:18.135 --> 00:42:22.400 Maybe more kind of like on a real estate component or on a sustainability. 00:42:22.440 --> 00:42:26.184 We all know that there's so many priorities and the priorities are increasing. 00:42:26.204 --> 00:42:32.172 So I guess what I'm asking is, are you able to determine, are they doing more kind of outside of their core functions? 00:42:33.894 --> 00:42:45.202 Yeah, this survey didn't necessarily touch on that, but just anecdotally, and I would say The industry is maturing. 00:42:45.222 --> 00:42:53.717 I will say the expectation of what a healthcare facility leader does, it's changing, right? 00:42:53.797 --> 00:43:01.773 The expectation is it's becoming more of a strategic partner for the business as a whole. 00:43:01.813 --> 00:43:13.005 Now, whether we're adequately responding to that through our development of our own skills and delivery of those things, that's to be determined. 00:43:13.065 --> 00:43:17.590 I think that's some of our biggest problem is the industry is really demanding this, right? 00:43:17.630 --> 00:43:27.639 They're demanding folks that understand sustainability, that understand operating processes, that understand real estate strategy. 00:43:27.679 --> 00:43:55.664 Whether we actually are developing people that can do that, I think that's part of the issue we're having within Within workforce development is we can't find a lot of kind of more senior level people that have that robust background just because historically how we've kind of developed and and you know trained our folks to be so dedicated to the kind of the operation of the hospital that that we really need to start. 00:43:56.385 --> 00:43:57.306 preaching that. 00:43:57.367 --> 00:44:01.733 Now, that's not to say that that's not very important, but that's my feel on that. 00:44:01.833 --> 00:44:02.333 I guess that's the 00:44:02.353 --> 00:44:02.614 topic. 00:44:02.733 --> 00:44:05.117 And you've done research into that as well. 00:44:05.498 --> 00:44:06.398 A little bit, yeah. 00:44:06.719 --> 00:44:07.340 Yeah, a little bit. 00:44:07.601 --> 00:44:10.463 I want to ask two more questions, be respectful of time here. 00:44:10.483 --> 00:44:25.907 I guess relative to FTEs, are you able to tell, is FTEs, and you're not looking at it as an issue, but any concerning trends around FTEs, I guess, Are people being more outsourced? 00:44:25.969 --> 00:44:27.411 Are people not being replaced? 00:44:28.311 --> 00:44:30.755 Is FTE count concerning? 00:44:31.818 --> 00:44:32.719 Or it's not concerning? 00:44:32.818 --> 00:44:37.967 Yeah, and that's something, again, this is the first time we've looked at contractors as a percent of workforce. 00:44:38.447 --> 00:44:45.278 So that's an answer that I hope we could have maybe next time we do this report is to say, what trend are we seeing? 00:44:45.360 --> 00:44:48.083 Is outsourcing becoming more prevalent? 00:44:48.965 --> 00:44:49.146 Yeah. 00:44:49.538 --> 00:44:51.179 I don't know that yet. 00:44:51.380 --> 00:44:56.146 I mean, we definitely have kind of a snapshot of the current state. 00:44:56.166 --> 00:45:02.512 I don't know if that's good or bad, but again, if you have the report, you could look at that and say, well, that's interesting. 00:45:02.753 --> 00:45:07.177 My staff is different or it's the same, I don't know. 00:45:07.338 --> 00:45:12.264 But that's something that hopefully we can start tracking is to say, how is that affecting what we're doing? 00:45:12.364 --> 00:45:23.956 So not only, and I can't remember actually the top of my head, but I think we have portion of outsourcing as a percentage of management, not just, you know, technical staff. 00:45:23.976 --> 00:45:27.501 So of my management team, you know, what percentage of that is outsourcing? 00:45:27.521 --> 00:45:38.476 Because that I believe is becoming, that's really the potential area where outsourcing is becoming more prevalent is on the management side of the equation. 00:45:38.496 --> 00:45:45.186 So would that be Outsourced to like a Croftal or Sodexo or CBRE, any one of those third parties. 00:45:45.266 --> 00:45:45.766 Typically, yeah. 00:45:45.806 --> 00:45:55.797 That's really what we're seeing is it's more of those larger facility services groups that are potentially making inroads. 00:45:55.856 --> 00:45:57.518 We don't know, right? 00:45:57.538 --> 00:46:00.981 Because we just have that data now. 00:46:01.061 --> 00:46:02.342 So we'll see how that goes over the years. 00:46:02.844 --> 00:46:03.244 Interesting. 00:46:03.503 --> 00:46:04.344 You must love this. 00:46:04.784 --> 00:46:05.525 Do you enjoy this? 00:46:07.288 --> 00:46:07.827 Yeah, I do. 00:46:07.947 --> 00:46:08.148 I do. 00:46:08.228 --> 00:46:09.068 I love it because... 00:46:10.465 --> 00:46:26.865 I think one reason I got into this area was because I saw so much opportunity to help move the industry forward because there was so much missing research. 00:46:27.766 --> 00:46:36.425 And again, it all started when I would go to these ASHE conferences year after year after year, and they'd say, We're all getting old, look around, look at all the gray hairs. 00:46:36.927 --> 00:46:39.550 And I'd sit there thinking, oh, great, who has the answer? 00:46:39.650 --> 00:46:43.596 And then we moved on to

talking about boilers and chillers. 00:46:44.657 --> 00:46:47.760 I thought, gosh, we know this is a huge problem. 00:46:47.820 --> 00:46:50.905 Why isn't anybody, and I think things were being done, right? 00:46:51.025 --> 00:46:53.208 Oh, let's do internships or let's do this. 00:46:53.648 --> 00:47:17.427 But nobody actually looked at the data to say what's really happening and what is the data showing that can really help And so now, whether it's workforce planning or whether it's aging infrastructure, whatever topic it is, my goal and my passion is developing research that can actually be applied in the industry to help healthcare organizations be successful. 00:47:18.128 --> 00:47:23.416 And what is usually a time length between, like, you've talked about a next area. 00:47:23.496 --> 00:47:26.322 How long do you usually have to give that before you... 00:47:27.041 --> 00:47:35.451 survey again to to be able to assess kind of trends and to have the info still be valuable is there is there a length or is it whenever it happens 00:47:36.773 --> 00:47:58.275 yeah i you know um i don't know if i have the answer that my my feel is you at least i wouldn't say more uh every year would be too much i think yeah every every other year would probably every two to three years is probably the sweet spot You could argue something like COVID, for example, like pre-COVID, post-COVID, like that will be in there. 00:47:58.295 --> 00:48:00.077 Like, okay, something dramatic has happened. 00:48:00.117 --> 00:48:00.998 We should be analyzing. 00:48:01.300 --> 00:48:03.963 So that would be an example where you might try to make them a little closer together. 00:48:04.865 --> 00:48:10.936 But yeah, historically, you know, this information has not been kind of routinely updated. 00:48:10.956 --> 00:48:13.719 So IFMA has really made a commitment to do that to help the industry. 00:48:13.760 --> 00:48:16.744 So I'm excited and we'll hopefully keep doing this every couple of years. 00:48:17.250 --> 00:48:20.557 Yeah, if you think about it, I mean, you know, 2014 was the ice ages now. 00:48:20.597 --> 00:48:24.346 It's just everything. 00:48:24.726 --> 00:48:25.628 Everything. 00:48:25.668 --> 00:48:26.311 Yeah, yeah. 00:48:26.570 --> 00:48:28.456 I mean, costs have gone crazy. 00:48:28.655 --> 00:48:36.373 And again, this is what we're trying to say is, if we're still looking at 2014 as our, as our basis for how we're generating our budget. 00:48:36.802 --> 00:48:39.847 we're really hampering, you know, hurting ourselves. 00:48:39.887 --> 00:48:41.550 So this information can be really helpful. 00:48:41.891 --> 00:48:51.949 I think even just taking your FTE data and data and breaking it apart, you know, not by square footage, but by that number of different ways, that's helpful in and of itself, because that's always the question. 00:48:51.989 --> 00:48:53.150 Am I appropriately staffed? 00:48:53.190 --> 00:48:55.135 Well, what are you using as a metric? 00:48:55.454

--> 00:48:57.277 Is there anything Steve and Dr. 00:48:57.318 --> 00:49:09.244 Stephen Call, Assistant Professor, Washington State University, were talking about the North American Medical Center Facility Support Services Benchmarking Report that you've done for IFMA, and I'll put a link to it in the video. 00:49:09.505 --> 00:49:18.318 Is there anything I should have asked you about or anything in the report that you'd want to get out before as we leave? 00:49:18.358 --> 00:49:21.483 Any interesting research or anything I should have asked you that I didn't? 00:49:22.304 --> 00:49:24.487 I think you've asked some great questions. 00:49:26.402 --> 00:49:48.494 The only thing I, kind of what's interesting about this report, what we find interesting, I will say it may be surprising, but when we looked at utility expenses, for example, when we looked at utility expenses across the nation, we actually didn't find a statistically significant difference on location. 00:49:48.733 --> 00:49:58.313 So whether you have a hospital in Michigan or a hospital in California, if you're looking at costs, There's no significant difference between a hospital in different parts of the country. 00:49:58.894 --> 00:50:00.275 So that's really surprising to folks. 00:50:00.356 --> 00:50:01.237 It's like, what do you mean? 00:50:01.717 --> 00:50:10.027 How can, and I think it has to do with, you know, just, this is my own guess, but the data shows that there's no significant difference. 00:50:10.047 --> 00:50:12.028 Yeah, there is some significant, you know, there's some difference. 00:50:12.108 --> 00:50:16.134 There's, you know, five or six cents or whatever. 00:50:16.173 --> 00:50:17.494 There's some difference. 00:50:18.655 --> 00:50:25.275 But what, for example, California, you know, utility consumption is probably lower but costs might be higher. 00:50:25.836 --> 00:50:28.340 And in Michigan, costs are lower, consumption's higher. 00:50:28.380 --> 00:50:30.222 So it kind of evens out, I think. 00:50:30.503 --> 00:50:31.644 I think that's the explanation. 00:50:32.085 --> 00:50:39.456 So historically, we've always said, okay, well, I need to know, I need to find, okay, I'm in Michigan and now I'm in this region and this is my cost. 00:50:39.996 --> 00:50:47.907 We found that you can just use a simple predictor number and poof, you've got your data regardless of where. 00:50:48.068 --> 00:50:53.534 Now, I did go ahead and include that in the report because I think there was a lot of like, wow, we've never done that before. 00:50:53.596 --> 00:50:54.697 So I still allow that. 00:50:54.737 --> 00:50:58.161 You can search by your region and your state and find your cost. 00:50:58.201 --> 00:51:04.389 But I found that really, really interesting that that's how the kind of the data played out. 00:51:05.150 --> 00:51:05.829 Yeah, no, I would agree. 00:51:05.851 --> 00:51:08.673 I mean, cause you always look where I am, you know, the Northeast, it's more expensive. 00:51:08.693 --> 00:51:09.534 You're going to pay more. 00:51:09.554 --> 00:51:10.695 So that's an interesting finding. 00:51:12.518 --> 00:51:13.440 Yeah, it was, it was. 00:51:13.559 --> 00:51:15.222 And so what that does, it just makes it easier. 00:51:15.242 --> 00:51:16.824 It just makes it easier. 00:51:17.605 --> 00:51:24.920 And again, I guess one last thing I want to say is This is, as we mentioned, this is a benchmarking tool. 00:51:25.922 --> 00:51:31.927 Some folks want benchmarks to tell them exactly what, you know, this is exactly what my FTE count should be. 00:51:31.987 --> 00:51:35.251 This is exactly what I should be spending on, on utilities. 00:51:35.811 --> 00:51:41.777 And benchmarking is just simply an estimate based off of a number of factors. 00:51:41.856 --> 00:51:43.599 It tries to say, am I in the ballpark? 00:51:43.659 --> 00:51:46.762 Am I 10 to 15% within my peers? 00:51:46.842 --> 00:51:48.262 If I am, I should be happy with that. 00:51:48.324 --> 00:51:52.840 If we really are trying to figure out what am I, what am I, What should I really be spending? 00:51:52.880 --> 00:52:00.246 That's a process that should be done through the CMMS and understanding what my actual costs are. 00:52:01.168 --> 00:52:04.711 But Benchmark is beautiful because it's reliable, but it's very easy. 00:52:04.992 --> 00:52:06.532 So it's a really good place to start. 00:52:07.034 --> 00:52:07.735 Yeah, yeah. 00:52:08.275 --> 00:52:11.978 And even I could use it going through those pages, and I'm sure this is even easier for you. 00:52:12.059 --> 00:52:15.862 So, Steve, thank you for your time today. 00:52:15.882 --> 00:52:16.523 I appreciate it. 00:52:17.585 --> 00:52:18.005 You're welcome. 00:52:18.045 --> 00:52:18.425 It's always a 00:52:18.465 --> 00:52:18.746 pleasure. 00:52:19.329 --> 00:52:20.050 My pleasure too. 00:52:20.070 --> 00:52:22.275 So go and buy the IFMA survey. 00:52:22.295 --> 00:52:23.436 I'm going to link to it. 00:52:23.496 --> 00:52:27.864 So if you want to get in that survey benchmark, you've said benchmark how many times and I'm calling it a survey. 00:52:29.146 --> 00:52:29.186 Dr. 00:52:29.206 --> 00:52:30.650 Stephen Call, thank you for your time. 00:52:31.630 --> 00:52:33.434 Peter Martin for the Healthcare Facilities Network. 00:52:33.474 --> 00:52:36.699 As always, thank you for tuning in and we will be back in the future. 00:52:36.940 --> 00:52:37.442 Have a great day.