October 22, 2025 • 18 mins
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:
- Webinar: Harnessing data intelligence for better outcomes: How data-driven insights are transforming home-based care
- Blog: 3 steps to leverage data science in home care
- Toolkit: Growth in home-based care: How to make the most out of your data
- Video: Elara Caring: Harnessing data for better patient outcomes
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.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Alex Skinner (00:00):
We actually had a really difficult time at the
beginning of trying to land onwhat do we want to measure,
because it started with thequestion what does good look
like in home care?
We had a bunch of subjectmatter experts, a bunch of
people that have been in theindustry forever, sat down in a
room, had a bunch of bigwhiteboards, and we just
brainstormed for hours andhours.
And there's a lot of heateddebate on that conversation.
(00:20):
But what that conversationreally led to was a
categorization of about fourthemes.
And so that's really what itcame from.
What matters in home care, whatdoes good look like?
And that's where we got theback office, the caregiver
experience, the health outcomes,and financial performance.
Erin Vallier (00:44):
Welcome to another episode of the Home Health 360
podcast, where we speak tohome-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 totalk about benchmarking.
Alex is our senior customerinsights and strategy manager
(01:05):
and is a strategic leader atAlaya Care with hands-on
experience across every phase ofthe customer journey.
He contributed to the design ofour ROI framework and later led
the development of the customermaturity model, which is a
framework that 90% of enterpriseaccounts use to benchmark
performance and guide valuerealization strategies.
(01:27):
Welcome to the show, Alex.
Alex Skinner (01:29):
Thanks for having me, Erin.
I'm super excited to be here.
Erin Vallier (01:32):
Oh, I'm excited to have you.
This is an exciting topic.
Everybody wants to know howwell their business is
performing and what they can dobetter.
So let's just dive right in,but I want to start with the
basics here.
What is benchmarking in thecontext of home-based care and
why is it such a critical pieceof the customer maturity model?
Alex Skinner (01:51):
For us, there's a belief that data is relative.
So without a perspective onwhat good looks like, at the end
of the day, we would just beshowing numbers.
So for us, we we think thatbenchmarking is really important
because it allows us to look intwo ways at what good looks
like.
One, against oneself.
How do we improve over time sowe can benchmark against
ourselves, but also benchmarkingagainst other organizations in
(02:13):
the same cohort.
So how are we doing against alook-alike?
And both of those really helpus kind of frame a perspective
on are we doing better or worsethan the median?
Are we in a top quartile or onthe works at the bottom
quartile?
So that's a core thesis intothe customer maturity model, is
really just being able to havethose reference points to look
(02:34):
at.
Erin Vallier (02:34):
Gotcha.
So it really does help theorganization understand where
they stand today and possiblyidentify where they can improve.
I love it.
Can you talk us through howwe're currently using
benchmarking with EliyaCarecustomers against each other?
And what can listeners expectas we expand this across the
wider industry?
Alex Skinner (02:55):
Yeah.
The way we use it against eachother is it really helps to sort
of track performance on ourfour categories.
We'll get into that in asecond.
But against each other, it'sreally talking about are we more
operationally efficient or lessoperationally efficient, for
example?
Do we have a better financialperformance or worse financial
performance than otherorganizations in the same
cohort?
Where it really getsinteresting in the sense of us
(03:17):
as a tech provider is talkingabout this improvement over
time.
So, what's the impact of anintervention?
If we had a strategic goal thatwe want to improve our back
office operation, maybe we wantto make support more clients,
deliver more service hours withthe same amount of staff.
And we've defined a strategythat we're going to put in
(03:37):
place, whether it's a product oran improved process.
This allows us to have thehistorical picture before the
intervention and the historicalpicture and the future picture
after the intervention.
So really there's a veryclear-cut view on we put this in
place and what was the directimpact of that or indirect
impact depending on the metricsthat we're looking at.
So really it's intending toone, start and spark
(04:00):
conversation, two, help us trackour strategic goals, and then
three, really determine theimpact of our interventions as
they get rolled out.
Erin Vallier (04:07):
And that's against Alya Care customers right now,
the like current users.
Is there any thought aboutexpanding that to non-AlyCare
users?
Alex Skinner (04:17):
There certainly is.
Part of it is that we haveaccess to the anonymized data
where it makes sense to rollthat into our centralized
framework.
So that's the alli caredatabase.
And then part of the otherthinking is we think there's a
ton of value in being able tosee how other organizations on
other softwares are performingas well.
And that would probably come abit more from a survey
(04:38):
standpoint or some otherexternal databases that perhaps
we'd export in the future.
Erin Vallier (04:43):
And I think you have some stuff to show us
today.
Is there like a visual aboutwhat the benchmarking kind of
looks like?
Alex Skinner (04:49):
So what I've pulled up here is an example of
our customer maturity modelapplied for an organization.
So for our listeners thataren't able to see this, what
we've got is a value for thiscustomer on their scheduler
productivity.
So how many visits does eachscheduler do per month?
And then we're also looking atthe sort of quartiles of
look-alike organizations.
(05:10):
So they deliver the sameservice of the same size.
And so we've got a bottomquartile, 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'sshowing us their performance
over the last 12 months.
So when we talked about lookingagainst organizations in the
same cohort, that's oneperspective.
(05:31):
The graph gives us the otherperspective.
So here they started closer tothe median 12 months ago.
And over time, 11 months later,they are certainly in the top
quartile, delivering some reallykey results.
So that's an example of how wemight be looking at this data
for a customer.
I'll pull on another examplehere being the authorization
utilization.
So this is one where we'resaying essentially how much of
(05:53):
the pie have we consumed?
If we're authorized to deliver100 hours of care, have we
delivered 100 hours or have weonly delivered 50 hours of care
and what's left for us to goagain?
So this is one that we think isreally important to help ensure
that organizations areperforming best.
And if there are things thatare in the way that don't allow
them to get that maxauthorization, we need to be
(06:13):
addressing those as a teamtogether.
So in this case here, thecustomer was in the bottom
quartile in February, and thenthree months later, they're up
to about 82% in May.
Let's call it.
So this would be a perfectexample of let's say between
February and March, we appliedan intervention and it allowed
us to track that progress overthe next few months.
So just another example ofwhere we might leverage this
(06:35):
together.
Erin Vallier (06:36):
I love these two examples because when I'm
speaking to customers, it'ssomething that it's a really hot
topic.
I want to know how myschedulers are going to perform,
and I want to know that I'm notscheduling over auth and I'm
maximizing my auth and they'retied together.
But I love this because itallows the user to see how am I
performing today and how am Iperforming today against all the
(06:58):
other users.
Once I've deployed thisparticular feature or this
process change with Elia Cair,how does that improve my
performance over a period oftime?
It's valuable information.
I love this.
Alex Skinner (07:10):
I should also call out that this is a data model
that requires context.
And so we arm our CSMs withthis information so that they
can provide that coaching orstrategic consultation to our
organizations, really to makesure that we continue to track
the goals that they want toachieve.
And if there are things that wethink need to be on the radar
and we have a path forward toit, we can then start that
(07:33):
conversation together.
So it's a tool that getspackaged in with a bit of the
strategic lens.
Erin Vallier (07:39):
Fantastic.
Is there a big differencebetween what's easy to measure
and what's meaningful tomeasure?
I imagine so.
And how did we land on theright indicators for our
maturity model?
Alex Skinner (07:51):
It's actually a point that I find a lot of
organizations can get caught upon 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 aboutA, B, C, D, A, B, C, D or what
matter to us.
How can we measure that mosteffectively?
(08:12):
We actually had a reallydifficult time at the beginning
of trying to land on what do wewant to measure, because it
started with the question, whatdoes good look like in home
care?
We had a bunch of subjectmatter experts, a bunch of
people that have been in theindustry forever, sat down in a
room, had a bunch of bigwhiteboards, and we just
brainstormed for hours andhours.
And there's a lot of heateddebate on that conversation.
(08:32):
But what that conversationreally led to was a
categorization of about fourthemes.
And so that's really what itcame from.
What matters in home care, whatdoes good look like?
And that's where we got theback office, the caregiver
experience, the health outcomes,and financial performance.
And those four are what wedefined as our customer
retreating model pillars.
The first one is operationalexcellence.
(08:53):
So how efficient is the backoffice operation?
The second one is the employeeexperience.
So are caregivers having a goodexperience?
Are they leaving theorganization?
Are they staying?
That sort of thing.
The third is health outcomes.
So what are the outcomes thatare being delivered to clients?
Is the quality of care good?
Are we having consistency inthat care and keeping folks out
(09:15):
of hospital?
And number four is financialperformance.
So is the organization growing?
Are they being able to stayafloat with the way they manage
their cash flow?
What does that look like?
So really there are those fourcategories.
And it came to the conclusionthat it's our belief the best
organizations are strong inthese four pillars.
So that's sort of what definedthe main thesis of the customer
(09:36):
maturity model.
And then we started to digdeeper and say, how do we
measure those specifically,which led to about 20 different
metrics that we track now.
Erin Vallier (09:43):
Ah, 20 different metrics.
Wow.
Were there any surprising datapoints that were originally
thought as important that didn'tmake the cut?
Alex Skinner (09:51):
There were a lot, to be honest.
And I think part of theconversation, I'll use
authorization utilization inthis case here.
That was always one that weknew was going to be very
difficult to measure becauseauthorizations come in so many
different ways hours, units,visits, dollars, and there has
sort of normalization acrossthat to be able to standardize.
We actually chose to selectsome very ambitious metrics in
(10:16):
cases like this.
And we chose to go through thedifficult exercise of finding
ways to standardize them.
I would say we had to drop afew, more so related on the
health outcome side.
For example, length of stay wasone that we thought was going
to be very interesting and veryimportant.
But the realization came to thefact that at the end of the
day, the length of stay is sodependent on the services that
(10:40):
are being provided, and it'sreally hard to benchmark
organizations that aredelivering different services in
that way.
Erin Vallier (10:45):
Yeah.
That's fair.
Alex Skinner (10:47):
A long-winded answer of essentially saying we
decided to choose some prettydifficult metrics and go through
the complex exercise ofstandardizing them, which starts
with standard definitions thatwe can apply across the board.
Erin Vallier (10:59):
Gotcha.
Now, once an organizationreceives their benchmarking
results, how should theyactually use that data to
improve operations and outcomes?
Alex Skinner (11:08):
That's also a really good question, Aaron.
I would say the best way tothink about this is as an
executive, there are so manyinputs that are coming in.
It can be difficult to thinkabout where do I focus?
(11:28):
Where do I place my bet?
What should I lean into?
And there's a book calledThinking and Bets that we've
really brought into ourstructure.
And the whole concept of thebook is that every decision you
make has these probabilisticoutcomes.
There's a probability of a goodoutcome happening and a
probability of bad outcomehappening.
And there's always a factor ofluck in there.
And at the end of the day,we're playing poker, not chess
(11:51):
in life.
And so we need to be able touse this information to place
our bet strategically.
Say we have enough info to leaninto one particular path.
And so it's our belief thatwith the customer maturity
model, this helps us sort ofunderstand the different cards
that are on the table, gives usa bit of an insight into perhaps
what's in the other people'shands so I can determine what
are we going to do with our bet.
(12:12):
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 categoriesagainst ourselves and against
other organizations gives usreally good insight into
figuring out does this line upwith my strategic priority, or
should I be putting this on thedocket for our next project?
(12:34):
At the end of the day, when wethink about this implementation,
a lot of the time we'refocusing on if we were to go
down this path and make thischange, how much of an effect is
it going to have on thedownstream factors?
And we know that about 20% ofinputs giving 80% of outputs.
And so if we can focus ourattention, use this to say, hey,
there's an issue in intake orthere's an issue in scheduling,
(12:57):
there's an issue in visitverification, that's gonna have
some downstream effects.
And this sort of really helpswith the orientation process
there.
Erin Vallier (13:04):
Gotcha.
So really digging in andfinding that 20% of things that
can get you 80% of your results,and that's where you start.
And the benchmarking data isgonna help you really identify
what those things are.
Okay.
Alex Skinner (13:17):
Exactly.
Yeah, it helps identify wheremaybe we're bleeding most as
well as where do we expect maybethis effort will have a big
downstream impact for sure.
Erin Vallier (13:26):
Do you have an example of a customer who's seen
success from leveraging theirmaturity insights?
Alex Skinner (13:31):
Yeah.
One of the recent examples wasrelated to an organization that
was looking to improve theirscheduling productivity.
So we had talked through anumber of different metrics and
we had identified that thescheduler productivity was the
place to go because they weresignificant.
They were sort of in the bottomquartile in that case.
And we discussed a number ofdifferent strategies.
(13:52):
One of their desires was toexplore a visit optimizer tool,
which for the folks that aren'tfamiliar is an AI-based
algorithm that we have in thesystem that allows to compare
every employee against a list ofvacant visits, run all those
scenarios, and select the bestmatch for each visit.
So it allows us in bulk tomanage, let's say, 100 visits
(14:12):
and find the best employee forit without a scheduler having to
go do that whole run around.
So they wanted to explore thatoption.
So the maturity model helped usidentify that, but it also
helped us benchmark theimprovement.
So when they started to use thevisit optimizer, we saw some
really positive trends in thispilot site and something that
they decided to roll out for therest of the organization.
So not only did schedulerproductivity jump up about 20%,
(14:35):
but we also saw that mileagewent down about 40 or 50%.
We had some qualitativebenefits 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 alsosee in the future that there
were less vacant visits for nextweek.
So just some really positivestories that we saw come from
(14:58):
the implementation of thatintervention.
Erin Vallier (15:00):
Oh, that's fantastic.
So I imagine that also had animpact on their retention.
If everybody's happier and lessstressed out, not driving as
much.
There's a dollar amount on thatthat is priceless, actually.
So where do you see thisbenchmarking model going in the
next year or two?
Is there anything coming upthat will elevate how providers
(15:21):
assess and improve theirmaturity?
Alex Skinner (15:23):
Yeah, there are a few of the things that we're
very focused on, one of thembeing looking at external data,
as you called out earlier in ourcall.
So we benchmark these samemetrics on other systems.
What does that look like?
Also leveraging a bit more of apredictive analytics engine.
So we have started to ingest alot more usage data into our
(15:43):
tool.
And so being able to say theusage of these very specific
features, for example, how doesthat correlate to the outcomes
that people are experiencing?
And can we start to predict howan organization might be doing
in a few months, or if thingsare trending down because they
stopped using certain features,or really just help with that
data-backed strategy for coursecorrection?
(16:06):
So those are two things thatare really on the docket for our
thinking.
The third one I would say is abit more of benchmarking reports
to be able to put them outthere and say these are the
strategies and trends that we'reseeing in the organization.
Let's publish these regularly.
Erin Vallier (16:20):
Gotcha.
Gotcha.
So you hit on predictiveanalytics.
Is there any other upcominginnovations?
I know AI is a big buzzwordright now that might also
influence future iterations.
Alex Skinner (16:30):
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 maybedon't have time or opportunity
to do can become possible.
I would say right now,predictive analytics is the big
focus, but we will certainlycontinue to be exploring what
other doors open up.
Erin Vallier (16:48):
This has been really informative.
I guess I only have one morequestion for you.
I know that this is a modelthat is used mostly in the
enterprise space.
And right now it's justavailable for the Elijah users.
For those who are interested inparticipating, is there a way
that they can inquire, getinvolved?
What does that look like?
Alex Skinner (17:10):
I would say two elements to that.
One, stay tuned, because as wecalled out, we're excited to get
to a point where we can startpublishing some more
external-facing benchmarkingreports.
And so that will be certainly aproduct of this.
But secondly, one of thebenefits of working with Eli
Care is that we do track thiskind of data and we do allow our
(17:30):
teams to coach on them and makesure that we carve out a data
back strategy for success.
If you are interested, there isopportunity to explore Lie
Care.
It's one of the great add-onsthat I would say we're proud of.
Erin Vallier (17:42):
Fantastic.
Again, thank you so much forjoining the show today and for
sharing about benchmarking.
I think this is incrediblyexciting and it's just going to
level up, maybe even have somelittle healthy competition among
the users to see who's the bestat utilizing the product.
So I'm excited to see wherethis goes.
Alex Skinner (18:00):
Amazing.
Thank you for having me, Aaron.
Erin Vallier (18:03):
Home Help 360 is presented by Elijah here and
hosted by Erin Valier.
First, we want to thank ouramazing guests and listeners.
Second, new episodes air everymonth.
So be sure to subscribe todayso you don't miss an episode.
And last but not least, if youlike this episode and want to
learn more about all things homebased care, you can explore all
(18:25):
of our episodes at ayacare.comslash home health360 or visit us
on your favorite podcastplatform.
We actually had a really difficult time at the
beginning of trying to land onwhat do we want to measure,
because it started with thequestion what does good look
like in home care?
We had a bunch of subjectmatter experts, a bunch of
people that have been in theindustry forever, sat down in a
room, had a bunch of bigwhiteboards, and we just
brainstormed for hours andhours.
And there's a lot of heateddebate on that conversation.
(00:20):
But what that conversationreally led to was a
categorization of about fourthemes.
And so that's really what itcame from.
What matters in home care, whatdoes good look like?
And that's where we got theback office, the caregiver
experience, the health outcomes,and financial performance.
Erin Vallier (00:44):
Welcome to another episode of the Home Health 360
podcast, where we speak tohome-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 totalk about benchmarking.
Alex is our senior customerinsights and strategy manager
(01:05):
and is a strategic leader atAlaya Care with hands-on
experience across every phase ofthe customer journey.
He contributed to the design ofour ROI framework and later led
the development of the customermaturity model, which is a
framework that 90% of enterpriseaccounts use to benchmark
performance and guide valuerealization strategies.
(01:27):
Welcome to the show, Alex.
Alex Skinner (01:29):
Thanks for having me, Erin.
I'm super excited to be here.
Erin Vallier (01:32):
Oh, I'm excited to have you.
This is an exciting topic.
Everybody wants to know howwell their business is
performing and what they can dobetter.
So let's just dive right in,but I want to start with the
basics here.
What is benchmarking in thecontext of home-based care and
why is it such a critical pieceof the customer maturity model?
Alex Skinner (01:51):
For us, there's a belief that data is relative.
So without a perspective onwhat good looks like, at the end
of the day, we would just beshowing numbers.
So for us, we we think thatbenchmarking is really important
because it allows us to look intwo ways at what good looks
like.
One, against oneself.
How do we improve over time sowe can benchmark against
ourselves, but also benchmarkingagainst other organizations in
(02:13):
the same cohort.
So how are we doing against alook-alike?
And both of those really helpus kind of frame a perspective
on are we doing better or worsethan the median?
Are we in a top quartile or onthe works at the bottom
quartile?
So that's a core thesis intothe customer maturity model, is
really just being able to havethose reference points to look
(02:34):
at.
Erin Vallier (02:34):
Gotcha.
So it really does help theorganization understand where
they stand today and possiblyidentify where they can improve.
I love it.
Can you talk us through howwe're currently using
benchmarking with EliyaCarecustomers against each other?
And what can listeners expectas we expand this across the
wider industry?
Alex Skinner (02:55):
Yeah.
The way we use it against eachother is it really helps to sort
of track performance on ourfour categories.
We'll get into that in asecond.
But against each other, it'sreally talking about are we more
operationally efficient or lessoperationally efficient, for
example?
Do we have a better financialperformance or worse financial
performance than otherorganizations in the same
cohort?
Where it really getsinteresting in the sense of us
(03:17):
as a tech provider is talkingabout this improvement over
time.
So, what's the impact of anintervention?
If we had a strategic goal thatwe want to improve our back
office operation, maybe we wantto make support more clients,
deliver more service hours withthe same amount of staff.
And we've defined a strategythat we're going to put in
(03:37):
place, whether it's a product oran improved process.
This allows us to have thehistorical picture before the
intervention and the historicalpicture and the future picture
after the intervention.
So really there's a veryclear-cut view on we put this in
place and what was the directimpact of that or indirect
impact depending on the metricsthat we're looking at.
So really it's intending toone, start and spark
(04:00):
conversation, two, help us trackour strategic goals, and then
three, really determine theimpact of our interventions as
they get rolled out.
Erin Vallier (04:07):
And that's against Alya Care customers right now,
the like current users.
Is there any thought aboutexpanding that to non-AlyCare
users?
Alex Skinner (04:17):
There certainly is.
Part of it is that we haveaccess to the anonymized data
where it makes sense to rollthat into our centralized
framework.
So that's the alli caredatabase.
And then part of the otherthinking is we think there's a
ton of value in being able tosee how other organizations on
other softwares are performingas well.
And that would probably come abit more from a survey
(04:38):
standpoint or some otherexternal databases that perhaps
we'd export in the future.
Erin Vallier (04:43):
And I think you have some stuff to show us
today.
Is there like a visual aboutwhat the benchmarking kind of
looks like?
Alex Skinner (04:49):
So what I've pulled up here is an example of
our customer maturity modelapplied for an organization.
So for our listeners thataren't able to see this, what
we've got is a value for thiscustomer on their scheduler
productivity.
So how many visits does eachscheduler do per month?
And then we're also looking atthe sort of quartiles of
look-alike organizations.
(05:10):
So they deliver the sameservice of the same size.
And so we've got a bottomquartile, 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'sshowing us their performance
over the last 12 months.
So when we talked about lookingagainst organizations in the
same cohort, that's oneperspective.
(05:31):
The graph gives us the otherperspective.
So here they started closer tothe median 12 months ago.
And over time, 11 months later,they are certainly in the top
quartile, delivering some reallykey results.
So that's an example of how wemight be looking at this data
for a customer.
I'll pull on another examplehere being the authorization
utilization.
So this is one where we'resaying essentially how much of
(05:53):
the pie have we consumed?
If we're authorized to deliver100 hours of care, have we
delivered 100 hours or have weonly delivered 50 hours of care
and what's left for us to goagain?
So this is one that we think isreally important to help ensure
that organizations areperforming best.
And if there are things thatare in the way that don't allow
them to get that maxauthorization, we need to be
(06:13):
addressing those as a teamtogether.
So in this case here, thecustomer was in the bottom
quartile in February, and thenthree months later, they're up
to about 82% in May.
Let's call it.
So this would be a perfectexample of let's say between
February and March, we appliedan intervention and it allowed
us to track that progress overthe next few months.
So just another example ofwhere we might leverage this
(06:35):
together.
Erin Vallier (06:36):
I love these two examples because when I'm
speaking to customers, it'ssomething that it's a really hot
topic.
I want to know how myschedulers are going to perform,
and I want to know that I'm notscheduling over auth and I'm
maximizing my auth and they'retied together.
But I love this because itallows the user to see how am I
performing today and how am Iperforming today against all the
(06:58):
other users.
Once I've deployed thisparticular feature or this
process change with Elia Cair,how does that improve my
performance over a period oftime?
It's valuable information.
I love this.
Alex Skinner (07:10):
I should also call out that this is a data model
that requires context.
And so we arm our CSMs withthis information so that they
can provide that coaching orstrategic consultation to our
organizations, really to makesure that we continue to track
the goals that they want toachieve.
And if there are things that wethink need to be on the radar
and we have a path forward toit, we can then start that
(07:33):
conversation together.
So it's a tool that getspackaged in with a bit of the
strategic lens.
Erin Vallier (07:39):
Fantastic.
Is there a big differencebetween what's easy to measure
and what's meaningful tomeasure?
I imagine so.
And how did we land on theright indicators for our
maturity model?
Alex Skinner (07:51):
It's actually a point that I find a lot of
organizations can get caught upon 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 aboutA, B, C, D, A, B, C, D or what
matter to us.
How can we measure that mosteffectively?
(08:12):
We actually had a reallydifficult time at the beginning
of trying to land on what do wewant to measure, because it
started with the question, whatdoes good look like in home
care?
We had a bunch of subjectmatter experts, a bunch of
people that have been in theindustry forever, sat down in a
room, had a bunch of bigwhiteboards, and we just
brainstormed for hours andhours.
And there's a lot of heateddebate on that conversation.
(08:32):
But what that conversationreally led to was a
categorization of about fourthemes.
And so that's really what itcame from.
What matters in home care, whatdoes good look like?
And that's where we got theback office, the caregiver
experience, the health outcomes,and financial performance.
And those four are what wedefined as our customer
retreating model pillars.
The first one is operationalexcellence.
(08:53):
So how efficient is the backoffice operation?
The second one is the employeeexperience.
So are caregivers having a goodexperience?
Are they leaving theorganization?
Are they staying?
That sort of thing.
The third is health outcomes.
So what are the outcomes thatare being delivered to clients?
Is the quality of care good?
Are we having consistency inthat care and keeping folks out
(09:15):
of hospital?
And number four is financialperformance.
So is the organization growing?
Are they being able to stayafloat with the way they manage
their cash flow?
What does that look like?
So really there are those fourcategories.
And it came to the conclusionthat it's our belief the best
organizations are strong inthese four pillars.
So that's sort of what definedthe main thesis of the customer
(09:36):
maturity model.
And then we started to digdeeper and say, how do we
measure those specifically,which led to about 20 different
metrics that we track now.
Erin Vallier (09:43):
Ah, 20 different metrics.
Wow.
Were there any surprising datapoints that were originally
thought as important that didn'tmake the cut?
Alex Skinner (09:51):
There were a lot, to be honest.
And I think part of theconversation, I'll use
authorization utilization inthis case here.
That was always one that weknew was going to be very
difficult to measure becauseauthorizations come in so many
different ways hours, units,visits, dollars, and there has
sort of normalization acrossthat to be able to standardize.
We actually chose to selectsome very ambitious metrics in
(10:16):
cases like this.
And we chose to go through thedifficult exercise of finding
ways to standardize them.
I would say we had to drop afew, more so related on the
health outcome side.
For example, length of stay wasone that we thought was going
to be very interesting and veryimportant.
But the realization came to thefact that at the end of the
day, the length of stay is sodependent on the services that
(10:40):
are being provided, and it'sreally hard to benchmark
organizations that aredelivering different services in
that way.
Erin Vallier (10:45):
Yeah.
That's fair.
Alex Skinner (10:47):
A long-winded answer of essentially saying we
decided to choose some prettydifficult metrics and go through
the complex exercise ofstandardizing them, which starts
with standard definitions thatwe can apply across the board.
Erin Vallier (10:59):
Gotcha.
Now, once an organizationreceives their benchmarking
results, how should theyactually use that data to
improve operations and outcomes?
Alex Skinner (11:08):
That's also a really good question, Aaron.
I would say the best way tothink about this is as an
executive, there are so manyinputs that are coming in.
It can be difficult to thinkabout where do I focus?
(11:28):
Where do I place my bet?
What should I lean into?
And there's a book calledThinking and Bets that we've
really brought into ourstructure.
And the whole concept of thebook is that every decision you
make has these probabilisticoutcomes.
There's a probability of a goodoutcome happening and a
probability of bad outcomehappening.
And there's always a factor ofluck in there.
And at the end of the day,we're playing poker, not chess
(11:51):
in life.
And so we need to be able touse this information to place
our bet strategically.
Say we have enough info to leaninto one particular path.
And so it's our belief thatwith the customer maturity
model, this helps us sort ofunderstand the different cards
that are on the table, gives usa bit of an insight into perhaps
what's in the other people'shands so I can determine what
are we going to do with our bet.
(12:12):
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 categoriesagainst ourselves and against
other organizations gives usreally good insight into
figuring out does this line upwith my strategic priority, or
should I be putting this on thedocket for our next project?
(12:34):
At the end of the day, when wethink about this implementation,
a lot of the time we'refocusing on if we were to go
down this path and make thischange, how much of an effect is
it going to have on thedownstream factors?
And we know that about 20% ofinputs giving 80% of outputs.
And so if we can focus ourattention, use this to say, hey,
there's an issue in intake orthere's an issue in scheduling,
(12:57):
there's an issue in visitverification, that's gonna have
some downstream effects.
And this sort of really helpswith the orientation process
there.
Erin Vallier (13:04):
Gotcha.
So really digging in andfinding that 20% of things that
can get you 80% of your results,and that's where you start.
And the benchmarking data isgonna help you really identify
what those things are.
Okay.
Alex Skinner (13:17):
Exactly.
Yeah, it helps identify wheremaybe we're bleeding most as
well as where do we expect maybethis effort will have a big
downstream impact for sure.
Erin Vallier (13:26):
Do you have an example of a customer who's seen
success from leveraging theirmaturity insights?
Alex Skinner (13:31):
Yeah.
One of the recent examples wasrelated to an organization that
was looking to improve theirscheduling productivity.
So we had talked through anumber of different metrics and
we had identified that thescheduler productivity was the
place to go because they weresignificant.
They were sort of in the bottomquartile in that case.
And we discussed a number ofdifferent strategies.
(13:52):
One of their desires was toexplore a visit optimizer tool,
which for the folks that aren'tfamiliar is an AI-based
algorithm that we have in thesystem that allows to compare
every employee against a list ofvacant visits, run all those
scenarios, and select the bestmatch for each visit.
So it allows us in bulk tomanage, let's say, 100 visits
(14:12):
and find the best employee forit without a scheduler having to
go do that whole run around.
So they wanted to explore thatoption.
So the maturity model helped usidentify that, but it also
helped us benchmark theimprovement.
So when they started to use thevisit optimizer, we saw some
really positive trends in thispilot site and something that
they decided to roll out for therest of the organization.
So not only did schedulerproductivity jump up about 20%,
(14:35):
but we also saw that mileagewent down about 40 or 50%.
We had some qualitativebenefits 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 alsosee in the future that there
were less vacant visits for nextweek.
So just some really positivestories that we saw come from
(14:58):
the implementation of thatintervention.
Erin Vallier (15:00):
Oh, that's fantastic.
So I imagine that also had animpact on their retention.
If everybody's happier and lessstressed out, not driving as
much.
There's a dollar amount on thatthat is priceless, actually.
So where do you see thisbenchmarking model going in the
next year or two?
Is there anything coming upthat will elevate how providers
(15:21):
assess and improve theirmaturity?
Alex Skinner (15:23):
Yeah, there are a few of the things that we're
very focused on, one of thembeing looking at external data,
as you called out earlier in ourcall.
So we benchmark these samemetrics on other systems.
What does that look like?
Also leveraging a bit more of apredictive analytics engine.
So we have started to ingest alot more usage data into our
(15:43):
tool.
And so being able to say theusage of these very specific
features, for example, how doesthat correlate to the outcomes
that people are experiencing?
And can we start to predict howan organization might be doing
in a few months, or if thingsare trending down because they
stopped using certain features,or really just help with that
data-backed strategy for coursecorrection?
(16:06):
So those are two things thatare really on the docket for our
thinking.
The third one I would say is abit more of benchmarking reports
to be able to put them outthere and say these are the
strategies and trends that we'reseeing in the organization.
Let's publish these regularly.
Erin Vallier (16:20):
Gotcha.
Gotcha.
So you hit on predictiveanalytics.
Is there any other upcominginnovations?
I know AI is a big buzzwordright now that might also
influence future iterations.
Alex Skinner (16:30):
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 maybedon't have time or opportunity
to do can become possible.
I would say right now,predictive analytics is the big
focus, but we will certainlycontinue to be exploring what
other doors open up.
Erin Vallier (16:48):
This has been really informative.
I guess I only have one morequestion for you.
I know that this is a modelthat is used mostly in the
enterprise space.
And right now it's justavailable for the Elijah users.
For those who are interested inparticipating, is there a way
that they can inquire, getinvolved?
What does that look like?
Alex Skinner (17:10):
I would say two elements to that.
One, stay tuned, because as wecalled out, we're excited to get
to a point where we can startpublishing some more
external-facing benchmarkingreports.
And so that will be certainly aproduct of this.
But secondly, one of thebenefits of working with Eli
Care is that we do track thiskind of data and we do allow our
(17:30):
teams to coach on them and makesure that we carve out a data
back strategy for success.
If you are interested, there isopportunity to explore Lie
Care.
It's one of the great add-onsthat I would say we're proud of.
Erin Vallier (17:42):
Fantastic.
Again, thank you so much forjoining the show today and for
sharing about benchmarking.
I think this is incrediblyexciting and it's just going to
level up, maybe even have somelittle healthy competition among
the users to see who's the bestat utilizing the product.
So I'm excited to see wherethis goes.
Alex Skinner (18:00):
Amazing.
Thank you for having me, Aaron.
Erin Vallier (18:03):
Home Help 360 is presented by Elijah here and
hosted by Erin Valier.
First, we want to thank ouramazing guests and listeners.
Second, new episodes air everymonth.
So be sure to subscribe todayso you don't miss an episode.
And last but not least, if youlike this episode and want to
learn more about all things homebased care, you can explore all
(18:25):
of our episodes at ayacare.comslash home health360 or visit us
on your favorite podcastplatform.
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