What's in this episode?
Season 1, Episode 11: This episode will focus on new functionality in the Accruent Data Insights 3.0 release, including the My Institution Reports module where insights about AEM Opportunities, long term Part Cost forecasts, and Benchmarking can be easily uncovered. Additionally, the expanded device catalog, new data attributes, increase in partnership with Attainia and an integration with Connectiv will all be discussed.
Welcome to the Healthcare Chats podcast where your hosts, Al Gresch and Mike Zimmer, will bring you insights to take your HTM and HFM from the basement to the boardroom. Healthcare Chats podcast starts now.
Mike Zimmer: Hey, good afternoon, Al. How are you doing?
Al Gresch: I'm doing fantastic. How are you, Mike?
Mike Zimmer: I am doing great. Thank you for asking. We're having, obviously, another podcast episode, so that's always something to look forward to. Having a good week other than that. Let's jump right into it. Al, who are we talking to today? Who is joining us on our podcast?
Al Gresch: Mike, today we have Eric Fischer who is the senior product manager for Data Insights. And let me give you a little bit of background on Data Insights if the listeners aren't familiar.
Al Gresch: Back about two years ago, we recognized the fact that because we have 55% of the CMMS market in the US, we had access to a lot of data. And what made that data so valuable is, it was real, live work-order data that we could draw from and help our customers make decisions with, so things like reliability and the way things fail and how they fail.
Al Gresch: Within the period of time since then, there's been just an incredible amount in development and innovation, and I have to tell you that within all of the verticals of our company, to me, this is one of the most innovative. We released, I would say about a year ago, the first version of Data Insights and gave it for free to some customers just to get some feedback. There were some that were early adopters of it and just continued to get some excellent feedback from customers based on how they think they can use it and how it can bring value. But it not only benefits the clinical engineering or HTM community but the supply chain community as well to help them make the right decisions. And we've talked to a lot of those leaders in that space, and, no, they have products that they currently rely on, and I won't mention them, but there are tools out there where you can get reliability data.
Al Gresch: The difference here is that what they get from those other sources is, basically, survey data. It's not real work-order data. And when I asked them how much they rely on that or put stock in it, pretty much the pat response was, "Well, it's not the best, but it's the best that we have." I think this takes it to a whole other level. So that's a little bit about the history and background on DI.
Mike Zimmer: So I think you actually left something out that I wanted to call out here because you said that the Data Insights team has been around for two years plus at this point. You also said that their first release of Data Insights occurred a year ago. So my question for you, Eric, is what were you doing from the inception of your team to when you first released the first version of the solution?
Eric Fischer: All right. Yeah. Thanks, Mike, for asking that pointed question about what I've been working on because, yeah, that's always a good question to start with. We've been pretty busy. We have been 100% focused on this very unique problem around medical device models and how do we understand them
Eric Fischer: So the medical device industry itself is a fragmented industry. There are hundreds of manufacturers, and each manufacturer publishes different models. Unfortunately, not everybody even refers to those models the same way, and those manufacturers are merging constantly, so we have been trying to track all that down, and we feel like we're doing a good service for our customers and our potential customers in that regard. So we've been cleaning data, is one of the main things we've done.
Mike Zimmer: Yeah. I was trying to give you guys some props because anybody listening to this that has ever interacted with the CMMS, they're like, "Well, holy smokes. Our data's a mess." I can't imagine what that data set looked like coming into you guys. I'm sure you just looked at this data set and you're like, "Oh, goodness me. We got our work cut out for us."
Eric Fischer: Exactly. Right. Yeah. So I mean, just to give you a couple of stats, right? So on average, every model has about 20 different aliases, and it's 20 different ways of calling it the same thing. We've also found that about 67% of the devices don't have any price data associated with it, which that's going to make it difficult to make good financial decisions.
Eric Fischer: We've talked to a couple of CFOs as well who feel like fixed assets are going to be a very important thing to keep track of in the next five years. 75% of capital for an organization is wrapped up in these fixed assets, things like price, things like maintenance costs, so we've been trying to track that down. We finally, with this current release, have provided a little bit of insight into the total cost of ownership. I think we're one of the first, if not the only, solution that provides that type of insight, which is valuable when it comes to evaluating equipment, budgeting, and planning for costs, and then improving processes.
Mike Zimmer: Wow.
Al Gresch: From the standpoint of being able to predict the time that it takes to service a certain piece of equipment if something is new to your organization, how do you budget for that? You have no idea whether or not the time required to maintain it is in line with what you're replacing. Or if it's a completely new device to your organization and a new set of device types, how do you plan for that from a budgetary standpoint? So being able to provide that information based on real service criteria from our other customers can help you do that.
Mike Zimmer: That's crucial. So in addition to the kind of cost comparison, or far look out into the future around what this model is going to end up costing your organization, both the upfront cost, as well as the ongoing maintenance and total cost of ownership, what are some of the other insights that are displayed in the solution today? And then I want to get into what's coming up next for Data Insights, too.
Eric Fischer: Yeah. So just thinking of some of the things that we have recently worked on, we spoke with a CFO of a major regional institution, and the main focus that they have on their radar is extending the life of assets. So we did a little bit more work on the understanding of life expectancy of each model. And so, historically, most people just try to map as best they can to AHA, which we know is a very imperfect science, right? Categories that in and of itself are very difficult to map. And even if that exercise is done, it's not exactly the right data. So we have undergone a lot of effort to provide life expectancy, but not only just what do most people do, but how do you extend the life of that asset?
Eric Fischer: In the COVID-19 era, hospitals are going to be really stretched. They don't have a budget to go spend a lot of capital on new equipment, so they need to extend the life of that equipment. So one of the new features we created was called the max recommended life, and so it really helps the institution use data to understand how far can you extend the device.
Eric Fischer: One of the CFOs we talked to talked about it sweating the equipment. You want to sweat the equipment. You want to extend it and work it as hard as you can before you have to spend a lot of money replacing a new one, right? It's kind of like your car. How do you get the most out of it? And so we spent a little bit of time developing that data attribute as well as the age of the model itself.
Eric Fischer: And we've also have the cost of service ratios, started to develop AEM metrics a little bit more trying to understand what's the right mix of PM and CM maintenance, took a long listen to Al Gresch's AEM Best Practices, the last webinar that was done. And so it's great to have someone like Al to help kind of guide us in this effort and look at AEM as sort of the two-way street that he describes and develop an ideal data solution around that.
Eric Fischer: So that's what's coming up next, I think, is having a better view into your processes for maintaining things and optimizing them. And then we also have quite a bit of good innovation coming up with Attainia, who is a very complementary product to Accruent, and they have a catalog and a lot of data that we can share. So that's what's coming up next for us, and we hope it's going to provide a lot of value.
Al Gresch: Mike, I want to elaborate a little bit on the topic that Eric brought up around sweating equipment. Just in the course of looking at the tool that's been developed and the trending that it provides around repair time and repair cost, there were some models where you would see the cost and the repair time start to climb up, and, ordinarily, somebody would look at that and say, "Oh, time to replace that because this thing's going to start eating our lunch." And on some of those models, it's just a blip that goes up and then levels back out again. And if you have that data and that understanding of what it's going to do over 10 years, you might not replace that. You might say, "You know what? If I hang on to this and I make it through that blip, this thing's going to run very, very well for me for a number of years to come."
Mike Zimmer: This is the break-in period.
Al Gresch: Exactly.
Mike Zimmer: Right. So this may open up a can of worms, but I think it's an interesting thread to follow. When you're looking to sweat equipment, how do you balance that against any additional risk it might pose to the organization, Al?
Al Gresch: Well, it's been my experience, Mike, that with anything, and having worked in the industry for many decades, there are certain things that, just because you can repair them, doesn't mean you should, right? Just because you can make a device last a couple more years, you have to ask yourself the question, does it do clinically what's today's standard for delivering care with that type of device? Certainly, the service data is only one component of that. That's where your in-house HTM group would evaluate that and assess where that thing is from a technology standpoint. And actually, that was one of the components of Data Insights where they show based on what's in the industry, or what's the prevalence of that particular model, is it new to the industry? How many years has it been in play, or is it a mainstream type of a product, or is it something that is really long in the tooth? And so that's information that you can glean from the product as well. Eric, you want to talk a little bit about that piece of it?
Eric Fischer: Well, actually, I'd like to put the question back on Mike. And it was a very pointed question, right? Of what's the flip side of extending sweating the asset. What was your thought when you asked that question, Mike? Did you think there's some risk with more failures as devices get older? Is that the thinking?
Mike Zimmer: Yeah, so I think if we moved out of the realm of sweating a piece of equipment if we're just going to keep up with this metaphor, and really go to a stretching of the equipment. And Al hit the nail on the head, you have to consider, clinically, does it do what it needs to be doing when compared to other models in the same category that might be a little bit newer to the market? And that is really a great place for the HTM leadership to step into the decision-making process and say, "Yeah, this is a really mature, long-in-the-tooth kind of product. Yeah, we can get a couple more years out of it, but it's time to go ahead and switch it out for something better, get an upgrade," right?
Eric Fischer: Yeah. We've spoken with a number of supply chain experts and clinical engineering folks and CFOs. It does really sound like the hospital administrators come to the table and make the best decision.
Eric Fischer: And you mentioned how do you balance the risk? I think every organization does that a little bit differently. What we want to do with Data Insights is to give you the numbers and give you the data so you can make the best decision on how you want to manage risk.
Eric Fischer: Maybe for some organizations, it's getting the best price upfront. For some organizations, it's having the least amount of failures because maybe they're stretched on their engineering workforce. So it is going to be different. And everybody has a little bit of a different driver, both financially, and just in the way that the hospital is.
Eric Fischer: We have some university hospitals that have different goals than some of the not-for-profit or for-profit hospitals, so it is something that we're keeping in mind and trying to give the right data back to those various people making some of these decisions.
Al Gresch: Right, and that's-
Eric Fischer: To put it back on the host there, Mike, but just wanted to ask what you meant by that question.
Mike Zimmer: Oh, yeah. It was just some curiosity. And it is really cool that regardless of what, let's call it a procurement strategy, might be in place across these different types of healthcare organizations, that it actually doesn't really matter how they're going to use the data. What you and your team have provided to them is this extremely objective, operationally-obtained information for them to help make those decisions a little bit better informed. Very cool stuff.
Al Gresch: Mike, I often tell people, as well, that the data provides value whether you go with a certain brand that might be the higher total cost of ownership, but if you have that knowledge, you can leverage that to negotiate those upfront costs down to say, "Look, your acquisition cost is a little bit lower than your competitor, but I know that over the life of this equipment, it's going to cost me more to maintain. So I want that reflected in my acquisition cost." That's a lot of power to put in the hands of a supply chain exec.
Mike Zimmer: So, Eric, you had mentioned the work that you have coming up with our partner Attainia. What else is on the roadmap? What is part of the new release of Data Insights?
Eric Fischer: Yeah, so Attainia's been a really good partner. They have a huge catalog and their focus mainly has been on the capital planning front and providing the list price as well as other price metrics and specifications, so that complements us very well. So, currently, what we've done is we've mapped a good chunk of our catalog to their catalog, so we have 4,000 device models that are matching, and we have an integration already between the two products. So if you go to Attainia and if you're also a subscriber to Data Insights, then you get the insights that we have right there in that Attainia catalog so you can make the best decision when you're acquiring that equipment.
Eric Fischer: And then the future is really bright, I think, for our two integrations. I think Data Insights is just very critical as Accruent and Attainia sort of figure out the right blend for our customers. And there's always sort of this dream that you can use the inventory in your SIMA mass and have that drive your capital plan, the budget module within Attainia just an amazing, full-featured way to do that. So we envision sort of this integration. We feel like we're the bridge between Connective and Attainia. Being able to take the data in Connective, map it over to Attainia, that's something that we've already done so we've solved that problem. And then it's just a matter of figuring out the features.
Eric Fischer: There's a natural fit that we feel with their budget module to be able to take an item that is flagged as needing replacement and going through the full budget module and getting stakeholders on board, approving the budget, understanding what to replace that model with. That's all a very natural fit with Attainia and something we'll be looking at further in the future.
Mike Zimmer: And so you mentioned that you're the bridge between, let's just say it, like a CMMS and Attainia. And so I checked out the integration on the Attainia side. It's very, very cool because they're not just bridging it from a functionality data perspective, but what you're also doing is sharing very tactical, operational data with stakeholders that are involved with equipment planning that generally aren't exposed to that in a way that they can really gather any sort of insight out of it, so that when an equipment planner is meeting other stakeholders that are part of a major build, and let's say there's HTM leadership at the table, and there typically is, that equipment planner from day one can say, "Well, I'm taking a look at these two models of the device, let's say infusion pumps, for us to fill the space once it's constructed. I see this information from a cost-of-service-ratio perspective across these two models. Which one would you guys prefer to us to go ahead and procure and outfit the space with?"
Mike Zimmer: From a persona and the reputation that's going to immediately build between the equipment planner and the more tactical, operational HTM folks, I mean, that's going to really help build that relationship on the front end of a project. And I know that might sound kind of soft and woo-woo, but there are so many advantages to having a really clear line of communication between those various stakeholders during a project like a remodel or a build of a new tower or something along those lines.
Eric Fischer: Yeah. And we're hoping it makes that collaboration a little bit easier. We found that it takes a lot of time, right, to foster those relationships with equipment planners and supply chain. And if everybody's going back to clinical engineering and saying, "Hey, do you have data on this device? Do you have data on this device?", it becomes a little exhausting. So I think it's a big selling point for what we're developing is just the time savings. The time to create a capital plan is reduced. The time to look up data on a model is drastically reduced.
Mike Zimmer: Change orders would be reduced, too, and those change orders are expensive on the construction side of things.
Eric Fischer: Oh, right. Good point. Yeah. Excellent point, Mike.
Al Gresch: Well, and these tools, both Data Insights and Attainia are directly in line with what our strategy is as an asset-management company. A lot of people call themselves an asset-management solution, but the full life cycle components of that are the technology assessment and asset planning, the asset acquisition support part of the life cycle, and then at the end, the equipment disposition. And so many focus only on that support part of the life cycle, and with these tools, we're filling out the front end and currently are working on filling out every piece of that capital life cycle to serve our customers in a way that brings them value from cradle to grave.
Eric Fischer: And I'll just add on that because, Mike, you had asked before what's the roadmap on things. We're hitting a couple of different people in the hospital, right? We can provide data for the clinical engineer. We can provide data for the supply chain folks. We can even do some stuff that appeals to the CFO and the equipment planner. But this is just the beginning, I feel. There are so many different personas that come to the table within the institution to make decisions. You have patient risk, and you have the medical practitioners themselves. So there's external data beyond what Accruent holds from all their customers. There is data on recalls, there's data on-
Al Gresch: Vulnerability.
Eric Fischer: ... adverse... Yeah, security vulnerabilities and adverse events, and those things all exist at the model level. And so we're really trying to create this 360-degree view of all of your equipment. And I think once we get there, that's going to be extremely powerful and make a lot of different stakeholders in the hospital pretty happy.
Al Gresch: Agreed.
Mike Zimmer: That is awesome stuff. Eric, what else have you been working on recently?
Eric Fischer: Well, we have a good team of pre-sales engineers that we're working with who have tackled this really complex problem of how do we do a quick and easy integration of Accruent, Data Insights, back over to Connective? And we've started to talk with our customers about where do you want to see this data? And some people want to see it in Connective. Some want to see it in the separate app that we created called Data Insights. Some may just have a really good data analytics team and they want to pull it out into their own data warehouse. So we're trying to be flexible with that, but we do realize that Connective is something that we really wanted to focus on, so we found a way to integrate things back into Connective, and that can open up another whole world of workflows, right? Because ServiceNow is workflow software.
Eric Fischer: We've had people who want to understand what's the maximum part cost that we want to sink into this device before we go and replace it, for example, and that we can start flagging thresholds and route those for approvals and auto-approve certain things. So that's pretty exciting to open up that whole world of how the data can then be pulled back into your workflow system and being used intelligently to improve operations. So pretty excited about that.
Mike Zimmer: Yeah, that does sound really cool. And it is tempting to get into the solutioning there because I'm already starting to think about some of those workflows myself, that maybe that may be a conversation for another time.
Mike Zimmer: But Eric, I just really wanted to say thank you so much for joining us today. Al and I appreciated you sharing the history of Data Insights and the future that it holds. I, for one, am super excited about getting this out in front of our customers and prospects and really sharing the value that this is going to be able to bring to their organization. So thank you.
Eric Fischer: Yeah. Thanks for having me, Mike.
Al Gresch: Yeah. Thanks so much, Eric. Good talking with you, man.
Eric Fischer: Likewise, Al.
Mike Zimmer: All right, gentlemen. Well, have a great rest of your week and we'll talk to you next time.
Al Gresch: Stay tuned for more episodes from the Healthcare Chats podcast. Submit your questions online and let us know what topics you'd like us to cover. Peace out.