Home Health 360: Presented By AlayaCare

Benchmarking that Actually Moves the Needle with Alex Skinner

• Erin Vallier • Season 1 • Episode 81

Share episode

Send us a text

What does “good” actually look like in home-based care? We dig into a clear, practical answer and show how a four-pillar maturity model transforms messy data into confident decisions. With AlayaCare’s Alex Skinner, we break down operational excellence, employee experience, health outcomes, and financial performance, then map them to the few metrics that truly move the needle.

You’ll hear why benchmarking needs two angles — trend your own progress and compare against look-alike peers — to avoid blind spots and focus on the right bets. Alex walks us through live examples of scheduler productivity and authorization utilization, revealing how standardized definitions, quartiles, and time-series views help leaders see impact fast. We also explore why some tempting metrics got cut, how customer success coaching adds crucial context, and how to resist “what’s easy to measure” in favor of “what’s worth measuring”.

Episode Resources:

If you liked this episode and want to learn more about all things home-based care, you can explore all our episodes at alayacare.com/homehealth360.

Alex Skinner:

We actually had a really difficult time at the beginning of trying to land on what do we want to measure, because it started with the question what does good look like in home care? We had a bunch of subject matter experts, a bunch of people that have been in the industry forever, sat down in a room, had a bunch of big whiteboards, and we just brainstormed for hours and hours. And there's a lot of heated debate on that conversation. But what that conversation really led to was a categorization of about four themes. And so that's really what it came from. What matters in home care, what does good look like? And that's where we got the back office, the caregiver experience, the health outcomes, and financial performance.

Erin Vallier:

Welcome to another episode of the Home Health 360 podcast, where we speak to home-based care professionals from around the globe. I'm your host, Aaron Valier, and today I am joined by Alaya Care's very own Alex Skinner to talk about benchmarking. Alex is our senior customer insights and strategy manager and is a strategic leader at Alaya Care with hands-on experience across every phase of the customer journey. He contributed to the design of our ROI framework and later led the development of the customer maturity model, which is a framework that 90% of enterprise accounts use to benchmark performance and guide value realization strategies. Welcome to the show, Alex.

Alex Skinner:

Thanks for having me, Erin. I'm super excited to be here.

Erin Vallier:

Oh, I'm excited to have you. This is an exciting topic. Everybody wants to know how well their business is performing and what they can do better. So let's just dive right in, but I want to start with the basics here. What is benchmarking in the context of home-based care and why is it such a critical piece of the customer maturity model?

Alex Skinner:

For us, there's a belief that data is relative. So without a perspective on what good looks like, at the end of the day, we would just be showing numbers. So for us, we we think that benchmarking is really important because it allows us to look in two ways at what good looks like. One, against oneself. How do we improve over time so we can benchmark against ourselves, but also benchmarking against other organizations in the same cohort. So how are we doing against a look-alike? And both of those really help us kind of frame a perspective on are we doing better or worse than the median? Are we in a top quartile or on the works at the bottom quartile? So that's a core thesis into the customer maturity model, is really just being able to have those reference points to look at.

Erin Vallier:

Gotcha. So it really does help the organization understand where they stand today and possibly identify where they can improve. I love it. Can you talk us through how we're currently using benchmarking with EliyaCare customers against each other? And what can listeners expect as we expand this across the wider industry?

Alex Skinner:

Yeah. The way we use it against each other is it really helps to sort of track performance on our four categories. We'll get into that in a second. But against each other, it's really talking about are we more operationally efficient or less operationally efficient, for example? Do we have a better financial performance or worse financial performance than other organizations in the same cohort? Where it really gets interesting in the sense of us as a tech provider is talking about this improvement over time. So, what's the impact of an intervention? If we had a strategic goal that we want to improve our back office operation, maybe we want to make support more clients, deliver more service hours with the same amount of staff. And we've defined a strategy that we're going to put in place, whether it's a product or an improved process. This allows us to have the historical picture before the intervention and the historical picture and the future picture after the intervention. So really there's a very clear-cut view on we put this in place and what was the direct impact of that or indirect impact depending on the metrics that we're looking at. So really it's intending to one, start and spark conversation, two, help us track our strategic goals, and then three, really determine the impact of our interventions as they get rolled out.

Erin Vallier:

And that's against Alya Care customers right now, the like current users. Is there any thought about expanding that to non-AlyCare users?

Alex Skinner:

There certainly is. Part of it is that we have access to the anonymized data where it makes sense to roll that into our centralized framework. So that's the alli care database. And then part of the other thinking is we think there's a ton of value in being able to see how other organizations on other softwares are performing as well. And that would probably come a bit more from a survey standpoint or some other external databases that perhaps we'd export in the future.

Erin Vallier:

And I think you have some stuff to show us today. Is there like a visual about what the benchmarking kind of looks like?

Alex Skinner:

So what I've pulled up here is an example of our customer maturity model applied for an organization. So for our listeners that aren't able to see this, what we've got is a value for this customer on their scheduler productivity. So how many visits does each scheduler do per month? And then we're also looking at the sort of quartiles of look-alike organizations. So they deliver the same service of the same size. And so we've got a bottom quartile, a medium quartile, and a top quartile. So here we're able to say, hey, this customer is in the top quartile. They're doing quite well. But there's also a graph that's showing us their performance over the last 12 months. So when we talked about looking against organizations in the same cohort, that's one perspective. The graph gives us the other perspective. So here they started closer to the median 12 months ago. And over time, 11 months later, they are certainly in the top quartile, delivering some really key results. So that's an example of how we might be looking at this data for a customer. I'll pull on another example here being the authorization utilization. So this is one where we're saying essentially how much of the pie have we consumed? If we're authorized to deliver 100 hours of care, have we delivered 100 hours or have we only delivered 50 hours of care and what's left for us to go again? So this is one that we think is really important to help ensure that organizations are performing best. And if there are things that are in the way that don't allow them to get that max authorization, we need to be addressing those as a team together. So in this case here, the customer was in the bottom quartile in February, and then three months later, they're up to about 82% in May. Let's call it. So this would be a perfect example of let's say between February and March, we applied an intervention and it allowed us to track that progress over the next few months. So just another example of where we might leverage this together.

Erin Vallier:

I love these two examples because when I'm speaking to customers, it's something that it's a really hot topic. I want to know how my schedulers are going to perform, and I want to know that I'm not scheduling over auth and I'm maximizing my auth and they're tied together. But I love this because it allows the user to see how am I performing today and how am I performing today against all the other users. Once I've deployed this particular feature or this process change with Elia Cair, how does that improve my performance over a period of time? It's valuable information. I love this.

Alex Skinner:

I should also call out that this is a data model that requires context. And so we arm our CSMs with this information so that they can provide that coaching or strategic consultation to our organizations, really to make sure that we continue to track the goals that they want to achieve. And if there are things that we think need to be on the radar and we have a path forward to it, we can then start that conversation together. So it's a tool that gets packaged in with a bit of the strategic lens.

Erin Vallier:

Fantastic. Is there a big difference between what's easy to measure and what's meaningful to measure? I imagine so. And how did we land on the right indicators for our maturity model?

Alex Skinner:

It's actually a point that I find a lot of organizations can get caught up on is just measuring what's right in front of them. But at the end of the day, that's not necessarily providing the best insights. It's really just saying, hey, we can see this and now we can see it, versus I'm curious about A, B, C, D, A, B, C, D or what matter to us. How can we measure that most effectively? We actually had a really difficult time at the beginning of trying to land on what do we want to measure, because it started with the question, what does good look like in home care? We had a bunch of subject matter experts, a bunch of people that have been in the industry forever, sat down in a room, had a bunch of big whiteboards, and we just brainstormed for hours and hours. And there's a lot of heated debate on that conversation. But what that conversation really led to was a categorization of about four themes. And so that's really what it came from. What matters in home care, what does good look like? And that's where we got the back office, the caregiver experience, the health outcomes, and financial performance. And those four are what we defined as our customer retreating model pillars. The first one is operational excellence. So how efficient is the back office operation? The second one is the employee experience. So are caregivers having a good experience? Are they leaving the organization? Are they staying? That sort of thing. The third is health outcomes. So what are the outcomes that are being delivered to clients? Is the quality of care good? Are we having consistency in that care and keeping folks out of hospital? And number four is financial performance. So is the organization growing? Are they being able to stay afloat with the way they manage their cash flow? What does that look like? So really there are those four categories. And it came to the conclusion that it's our belief the best organizations are strong in these four pillars. So that's sort of what defined the main thesis of the customer maturity model. And then we started to dig deeper and say, how do we measure those specifically, which led to about 20 different metrics that we track now.

Erin Vallier:

Ah, 20 different metrics. Wow. Were there any surprising data points that were originally thought as important that didn't make the cut?

Alex Skinner:

There were a lot, to be honest. And I think part of the conversation, I'll use authorization utilization in this case here. That was always one that we knew was going to be very difficult to measure because authorizations come in so many different ways hours, units, visits, dollars, and there has sort of normalization across that to be able to standardize. We actually chose to select some very ambitious metrics in cases like this. And we chose to go through the difficult exercise of finding ways to standardize them. I would say we had to drop a few, more so related on the health outcome side. For example, length of stay was one that we thought was going to be very interesting and very important. But the realization came to the fact that at the end of the day, the length of stay is so dependent on the services that are being provided, and it's really hard to benchmark organizations that are delivering different services in that way.

Erin Vallier:

Yeah. That's fair.

Alex Skinner:

A long-winded answer of essentially saying we decided to choose some pretty difficult metrics and go through the complex exercise of standardizing them, which starts with standard definitions that we can apply across the board.

Erin Vallier:

Gotcha. Now, once an organization receives their benchmarking results, how should they actually use that data to improve operations and outcomes?

Alex Skinner:

That's also a really good question, Aaron. I would say the best way to think about this is as an executive, there are so many inputs that are coming in. It can be difficult to think about where do I focus? Where do I place my bet? What should I lean into? And there's a book called Thinking and Bets that we've really brought into our structure. And the whole concept of the book is that every decision you make has these probabilistic outcomes. There's a probability of a good outcome happening and a probability of bad outcome happening. And there's always a factor of luck in there. And at the end of the day, we're playing poker, not chess in life. And so we need to be able to use this information to place our bet strategically. Say we have enough info to lean into one particular path. And so it's our belief that with the customer maturity model, this helps us sort of understand the different cards that are on the table, gives us a bit of an insight into perhaps what's in the other people's hands so I can determine what are we going to do with our bet. So to sort of bring that back, the idea is that when we have all of these different inputs, being able to show how we're performing on these categories against ourselves and against other organizations gives us really good insight into figuring out does this line up with my strategic priority, or should I be putting this on the docket for our next project? At the end of the day, when we think about this implementation, a lot of the time we're focusing on if we were to go down this path and make this change, how much of an effect is it going to have on the downstream factors? And we know that about 20% of inputs giving 80% of outputs. And so if we can focus our attention, use this to say, hey, there's an issue in intake or there's an issue in scheduling, there's an issue in visit verification, that's gonna have some downstream effects. And this sort of really helps with the orientation process there.

Erin Vallier:

Gotcha. So really digging in and finding that 20% of things that can get you 80% of your results, and that's where you start. And the benchmarking data is gonna help you really identify what those things are. Okay.

Alex Skinner:

Exactly. Yeah, it helps identify where maybe we're bleeding most as well as where do we expect maybe this effort will have a big downstream impact for sure.

Erin Vallier:

Do you have an example of a customer who's seen success from leveraging their maturity insights?

Alex Skinner:

Yeah. One of the recent examples was related to an organization that was looking to improve their scheduling productivity. So we had talked through a number of different metrics and we had identified that the scheduler productivity was the place to go because they were significant. They were sort of in the bottom quartile in that case. And we discussed a number of different strategies. One of their desires was to explore a visit optimizer tool, which for the folks that aren't familiar is an AI-based algorithm that we have in the system that allows to compare every employee against a list of vacant visits, run all those scenarios, and select the best match for each visit. So it allows us in bulk to manage, let's say, 100 visits and find the best employee for it without a scheduler having to go do that whole run around. So they wanted to explore that option. So the maturity model helped us identify that, but it also helped us benchmark the improvement. So when they started to use the visit optimizer, we saw some really positive trends in this pilot site and something that they decided to roll out for the rest of the organization. So not only did scheduler productivity jump up about 20%, but we also saw that mileage went down about 40 or 50%. We had some qualitative benefits of people saying they had better work-life balance, that they weren't working on weekends anymore. It gave them better confidence, less stress in the management of visits, and they could also see in the future that there were less vacant visits for next week. So just some really positive stories that we saw come from the implementation of that intervention.

Erin Vallier:

Oh, that's fantastic. So I imagine that also had an impact on their retention. If everybody's happier and less stressed out, not driving as much. There's a dollar amount on that that is priceless, actually. So where do you see this benchmarking model going in the next year or two? Is there anything coming up that will elevate how providers assess and improve their maturity?

Alex Skinner:

Yeah, there are a few of the things that we're very focused on, one of them being looking at external data, as you called out earlier in our call. So we benchmark these same metrics on other systems. What does that look like? Also leveraging a bit more of a predictive analytics engine. So we have started to ingest a lot more usage data into our tool. And so being able to say the usage of these very specific features, for example, how does that correlate to the outcomes that people are experiencing? And can we start to predict how an organization might be doing in a few months, or if things are trending down because they stopped using certain features, or really just help with that data-backed strategy for course correction? So those are two things that are really on the docket for our thinking. The third one I would say is a bit more of benchmarking reports to be able to put them out there and say these are the strategies and trends that we're seeing in the organization. Let's publish these regularly.

Erin Vallier:

Gotcha. Gotcha. So you hit on predictive analytics. Is there any other upcoming innovations? I know AI is a big buzzword right now that might also influence future iterations.

Alex Skinner:

I think there's a lot to uncover with that for sure, especially as you know, agentech workflows come into place. A lot of things that we maybe don't have time or opportunity to do can become possible. I would say right now, predictive analytics is the big focus, but we will certainly continue to be exploring what other doors open up.

Erin Vallier:

This has been really informative. I guess I only have one more question for you. I know that this is a model that is used mostly in the enterprise space. And right now it's just available for the Elijah users. For those who are interested in participating, is there a way that they can inquire, get involved? What does that look like?

Alex Skinner:

I would say two elements to that. One, stay tuned, because as we called out, we're excited to get to a point where we can start publishing some more external-facing benchmarking reports. And so that will be certainly a product of this. But secondly, one of the benefits of working with Eli Care is that we do track this kind of data and we do allow our teams to coach on them and make sure that we carve out a data back strategy for success. If you are interested, there is opportunity to explore Lie Care. It's one of the great add-ons that I would say we're proud of.

Erin Vallier:

Fantastic. Again, thank you so much for joining the show today and for sharing about benchmarking. I think this is incredibly exciting and it's just going to level up, maybe even have some little healthy competition among the users to see who's the best at utilizing the product. So I'm excited to see where this goes.

Alex Skinner:

Amazing. Thank you for having me, Aaron.

Erin Vallier:

Home Help 360 is presented by Elijah here and hosted by Erin Valier. First, we want to thank our amazing guests and listeners. Second, new episodes air every month. So be sure to subscribe today so you don't miss an episode. And last but not least, if you like this episode and want to learn more about all things home based care, you can explore all of our episodes at ayacare.com slash home health360 or visit us on your favorite podcast platform.