Everyone. This is Jacob Emerson with the Becker's
Health IT podcast.
Thrilled today to be joined by CVS Health's
vice president of enterprise customer experience and insights.
Sri, thank you so much for taking the
time to be with me on the podcast
today. Pat, thanks, Jacob. Appreciate the time. Excited
to be here with you. Likewise. And before
we dive into everything we wanna talk with
you about, some interesting new tech that CVS
has been rolling out, can you first tell
our audience a little bit more about yourself,
your background in health care, and a little
bit about your role at CVS today?
Yeah. So,
as you mentioned, I lead, customer experience and
insights for CVS Health. I I started my
career actually as an economist.
So,
looking more at, you know, markets and evaluating
them for competitive dynamics and
defending mergers and and acquisitions to department of
justice.
And, you know, that's where I kinda first
got exposed to health care. I used to
look at things like hospital mergers and and,
you know, medical device mergers, and I got
really fascinated by health care. And then my
career kinda took a a bit of a
winding path. I worked at, you know, GE,
including GE Healthcare,
Did spend some time at Wells Fargo,
you know, in the banking industry, so got
a little bit more exposure to the to
the regulated banking industry
before joining here, at CVS Health. And my
role at CVS Health
is I look at all of the consumer
feedback we get, whether that's through surveys
or,
social media data, digital session data,
call transcripts, whatever we can get our hands
on
to understand,
what are some of the patient client, you
know, member pain points that we have across
our entire enterprise, so retail at
health care delivery, Caremark.
And how do we improve the experiences for
those stakeholders and make sure that we're delivering
best in class experiences
so that those people can get the health
care they need.
When I when I kinda give my team
a tagline, I say our job is to
learn from the past, improve the present, and
predict the future,
particularly with respect for our members who we
serve as the internal advocate for
across all of our our internal teams, whether
that's in technology or the business or elsewhere.
Understood. So your background is more in the
business and finance sector. Now you're here at
CVS,
modeling what patients and and customers
are doing. And and you're here with us
today, Shree, to talk a little bit about,
something really interesting that we I I haven't
necessarily heard a lot from other health care
organizations, at least publicly.
CVS, since late last year, has been rolling
out Agentic AI twin simulations.
So talk to our audience about what that
is. When you talk about
agentic twins,
what does that actually mean, and and what
does that actually look like in practice
for CVS specifically?
Yeah. And I bet on this podcast, you
talked to a lot of leaders who talk
about being consumer centric. Right? And I think
that's something that
everyone says. You probably see it in every
single 10 k
out there, every CEO,
dialogue. I I think what's hard is being
consumer centric is really difficult. Getting the voice
of that customer into all of the aspects
of what you do
is challenging because it's hard to get to
customers. It's hard to talk to them. It's
hard for you to test things with them
or and learn from them.
You're limited in terms of how you can
outreach these folks. You know, you can leverage
surveys or maybe the scale.
You know, you have to do pilots.
And
it's being consumer centric is challenging. You have
that challenge simultaneously
with
the advent of AI and all the advancements
you're having in AI.
And what we realized in in working with
these, you know, company from Stanford founded by
a bunch of PhDs and computer science from
Stanford
is that we can actually build
agentic twins of our customers or or patients
or clients
where we can actually
build the way they make decisions.
So not just what they did in the
past, but how do they actually make decisions?
How do they actually,
handle trade offs? What are the behaviors that
they they would exhibit in a given situation?
And then we can generalize that to new
scenarios and new situations. So if you do
that at scale, and in our case, something
like a 100,000
plus
Agenctic Twins,
you will have a set of customers with
you all the time
that are, you know, effectively amplifying the consumer
voice.
So they are with you from when you
develop the product, when you wanna test the
outcome, if you wanna test some operational change.
And they it creates that real consumer centricity
because
that representation of the consumer, how they think,
how they behave is with you throughout the
entire process.
So, you know, it's the way we've gone
about doing that is we ingest a lot
of different information. Of course, all consumer consented,
but we take things like a a short
behavioral interview, behavioral signals,
spend data, things like that where we can
build a twin
of each individual consumer. And, again, you do
that at scale
where you actually have their thought process with
you, and this agentic twin of the customer
lives on and is always on,
for you to investigate and challenge new concepts,
new ideas, and to actually even perform dress
rehearsals of new things you're trying to launch
out. And it's really helped our decision making
our understanding of the consumer throughout the whole
product life cycle,
and and really just it's brought them to
life in a way that I don't think
was possible in the past.
And now, we really we really do. It's
kinda putting your money where your mouth is
in terms of centricity.
You're having these customers with you across the
entire journey.
Wow. I mean, this is fascinating. You you
literally copy and pasted
your customer base, and and now you can
see how they interact with all your different
businesses.
So
back backing up here, Sri, why did CVS
wanna go down this route? How why do
you wanna leverage this kind of technology?
And what does it actually do problem wise
for your patients and for your customers?
How does it solve issues for them on
the ground?
Yeah. So I think the reason you would
wanna we wanted to undertake this is we
really do take consumer centricity seriously. I mean,
we wanna build products and services
that help people access health care in an
effective way
and really solve the big challenges with The
US health care system around, you know, simplicity,
you know, ease of access, all those things
that you hear about constantly from from patients.
And I think where we we're we're landing
is we have the ability to get to
these folks via traditional methods, whether that's panel
research or surveys
or even to a degree looking at operational
data. But each one of those things had
challenges. Right? Either it was
speed, you know, or fidelity or any of
those things that
that challenge you in terms of getting to
that group. So when we heard about this
methodology and this approach, it was really exciting
because
it would it would really unlock what we've
been trying to do, which is get the
patient
front and center on the way we build
things. And I think if you if you
look at what we've seen so far, the
four main things we've gotten out of these
twins,
just in terms of the value of how
we build, is one speed.
You go from weeks to months to generate
insights. So if you have to go get
a panel and test something, whether that's messaging
or some product or service,
it takes time. You gotta go find those
patients. You have to go interview them. You
know, you have to you have to distill
those insights.
Now we're talking about fifteen to thirty minutes.
And, you know, I'll tell you honestly, Jacob,
the first handful of times we did this,
I was stunned. Like, things that would take
us eight weeks, we were doing in fifteen
to twenty minutes.
The second is fidelity.
You know, you you can only test so
many things with a human being. Right? There's
only so many
scenarios you can put in front of them
before their brain sort of breaks. They'll get
fatigue. You know, the signal quality reduces.
They're not able to answer. With these AI
representations,
you can test thousands of real world scenarios,
and you're not extrapolating out what they're gonna
what they're gonna do in a given situation.
You can present them with tons and thousands
of different scenarios or situations
and see how they'll actually behave. And that
actually also solves a big problem in research
where you have what's called stated intent.
So what someone tells you and what they'll
actually do. And here with this scenario testing,
just because you've generalized how someone makes a
decision or how they think,
you can actually get to the actual behavior
and even understand that gap between stated intent
and actual behavior.
The scale here, you have all these folks
on
all the time, so you don't have to
generalize the small pilots.
You know, you have thousands,
tens of thousands, and so some cases for
the populations we looked at, agentic twins available
to us at all times. So that scale
of the consumer voice is is tremendous
and now available to us to access,
you know, as we go forward. And then
the final component is the reach. Like, these
hard to reach populations
that we often have,
you know, whether that's particular disease states or
conditions where it's just difficult to find those
people or that can be really costly.
Now we only have to really find them
once because then we can create this twin
of that person, and then they'll be with
us the whole time. And it goes back
to, I think,
amplifying that consumer voice with that hard to
reach population particularly because
that's a group that's, you know, often
marginalized because we can't get to that group,
to understand what they're experiencing.
So if you if you wrap all that
up, we're getting away from reacting
to small groups
and with long timelines to get their feedback,
to predicting behavior, acting almost in near real
time, and having these consumers with us along
the entire journey,
it's transformative. It's it's changing the way we
deliver care because we're able to understand
what's gonna actually impact our consumers in a
real way while we're building these products
and not having to do things like, you
know, really narrow pilots and constant testing.
We can go out with a lot more
confidence in what we're doing
because we've been able to dress, rehearse it
with, you know, tens of thousands of customers
before we actually hit the market, and and
anyone has to actually experience what we're building.
Absolutely. I mean, listening to you talk about
this is incredible. It it it sounds transformative.
I I I've done marketing initiatives myself in
terms of doing those panels like you said
that take eight weeks and boiling that down
to fifteen minutes is that's incredible.
Not to mention what to hook on the
last part of your answer, the
the equity of it all of being able
to reach your entire customer base and know
how they all respond,
and not having to put everybody into pockets.
It's it's amazing. I I can't imagine what's
gonna be coming from this. And so I
think that's that's the natural follow-up question here,
Sri, is how does this change the way
that CVS
makes decisions compared to those traditional approaches you
just laid out for us even just from
a marketing perspective. But maybe you could expand
a bit on in terms of clinical decisions,
other areas of the pharmacist of the of
the industry that the company reaches.
How does this change the day to day
for CVS and and the business overall?
Yeah. And I I can give you a
couple of just concrete examples of that we've
that we've tried so far, that we've seen
success with. I think one, you know, one
classic one for us in the pharmacy side
is adherence.
That's an area we we've got a tremendous
amount of focus. Obviously, we want people to
be adherent to their medication. We want them
to stay healthy.
Accessing medications
is really important to
us. That can be a a difficult group
to talk to, particularly nonadherent patients. There's a
lot of reasons people don't, you know, adhere
to medication. Some of them related to stigma,
fear.
And you're in a sense, if you're going
to talk to that group,
you're making them relive whatever that was the
challenge that they had. And that can be
really difficult that you it can lead to
false signals. It can lead to, you know,
different types of challenges in terms of getting
to the population,
fatigue, lack of sample, those sorts of things
because they're just a difficult group to reach.
What we were able to do with the
twins is we were able to actually go
through and and investigate in detail adherence issues.
So get because you don't have to face
that and it's you know, you don't have
that same sort of challenge
with the Gentic twins because they're AI representations,
we were able to get way deeper than
I think we could have in a standard
qualitative or even quantitative interview.
What we're we were able to figure out
is a lot of the things about adherence
were the same that you would expect that
we've always seen.
You know, it's,
you know, fear of side effects and fear
of, you know, you know, not being able
to talk to a clinician and all those
things that we've been solving,
over the, you know, course of the past
few years.
But a new one's emerged, and it was
really around
the fear of getting a refill, which sounds
really you know, it sounds a little bit
strange. It wasn't what we expected, but we
were able to see, like, you know, a
lot of what we were observing was people
were saying, okay. Now once I start a
medication, how do I make sure I'm always
gonna get it? What happens if I can't
get that medication?
You know, does that is that gonna have
outcomes for me? And all those things that
we were able to see that that were
clear in the data.
And I think what what it pointed to
is that we have a lot of best
in class digital tools we're building and can
have built
that are making accessing medications
much easier. So it gave us a lot
more confidence
in those tools we're building. And in addition,
we're able to actually look at how do
we optimize some of those tools to ensure
that,
you know, we're we are making it as
easy as possible on the refill.
And I I think what it really pointed
out is
this anxiety, and it's patient anxiety that you
were able
that you were able to see in in
the agentic twins around all the process related
to the prescription. So it wasn't just the
medication.
It was the process
and the experience
that led to adherence. And, you know, we
were able to back that up with a
lot of the actual data we were able
to we were collecting from the customers.
When I say actual, I mean, operational data
that we were collecting from the customers.
It it it was a it's a it
was a way for us to unlock something
that we didn't we didn't see in the
past.
And I think what's particularly unique about it
is we're talking about effectively about robots here,
Jacob. We build robots that represent customers,
but they were unlocking
something that's as that's superhuman
and anxiety.
And so we were able to get to
the emotion through these agentic twins, which I
think is a really fascinating
use case for us.
And then just a a quick related one
just because you mentioned marketing. Another one was
related to our PetRx.
I'm gonna just tell a story really quickly.
You know, PetRx is our our you know,
we're looking to to move into pet care,
and we're looking at how do we message
to those to those, pet parents, if you
will. I'm a pet parent. I've got a
dog.
And, you know, there was a lot of
the data we were expecting, like emotional data
that people care a lot about their pets.
They become, like, family members.
One of the more interesting things we saw
from the Agenctic twins was
people were saying, you know, that even giving
medication to a pet was an act of
devotion, not necessarily a chore.
So any messaging appealing to the emotions was
gonna be successful.
But what the the agentic twins allowed us
to do is present scenarios
beyond that. And what we found was it
wasn't enough
to just be
connecting emotionally. You had to show that we
had the capability to actually get the the
scripts from the veterinarians,
have an understanding what those scripts are, how
the side effects work. That was really important
to the pet parents. So
by being able to drill in and get
to the kind of stated versus actual actual
behavior using the twins, we were able to
uncover
that the messaging needed to have both. It
wasn't sufficient to just have messaging and marketing
that was appealing to emotion. We had to
appeal to the tactical side too, because pet
owners are incredibly pragmatic despite this emotional connection
that I think we all observe and see.
So, anyway, those are two kinda quick examples
of where we've we've seen early wins.
And, you know, we're operating this at scale,
so there's more to come, I think, here
as we keep moving forward.
Oh, absolutely. I I can imagine so. And
for pretty much any company listening in right
now, I would imagine they are taking notes
on how to replicate something like this, Sri,
because the the possibilities seem endless just listening
to even those those two examples you shared,
and I really like how you framed it
of unlocking something that is human. You're you're
unlocking something that the humans on the other
side maybe hadn't been able to before, which
is really fascinating.
It's a really unique AI use case. You
know? It's not it's in a sense, it's,
it's not one of the ones that I
think are traditional,
and it's it's using AI to understand human
behavior,
which, again, sounds a little counterintuitive.
But I think No. It makes sense. Yeah.
Yeah. It's really creating this always on approach
with our customers. Definitely. Definitely. Is there anything
you'd add for for the health care audience
that's listening in terms of the value prop
here for the wider health care system?
Yeah. I think, you know, if you if
I were thinking about more broadly,
a EO, even things like patient experience
and and I'll use the experience tag because
that's that's where I, you know, tend to
focus.
It it's
ability to test messaging. Like, how do we
change in particular in health care is really
painful. That's observed everywhere.
You can see that across multiple populations when
you change people's
medications, when you change formularies, when you change
the way they access care, it's painful.
But what this allows you to do is
test different messaging and different approaches to see
how you how do you smooth that, how
do you make that easier on the patient.
And you're able to do that here in
a controlled, safe environment
that you you are able to see the
results before you actually have to go into
the market and test that. I think that's
a really big unlock for health care.
The the other one, I think, is understanding
journeys. Health care journeys are incredibly complex,
and, you know, it's it can be difficult
to actually get patient feedback along every aspect
of that journey.
But here, you can you can do that,
and you can see how people are experiencing
every aspect of where they engage with you.
And I think understanding quickly where you have
pain points and where you may need to
do some work and may where you're excelling
and maybe where you need to double down.
Health care in particular to me,
this is a way to
test and learn
quickly,
with those audiences.
And I think it's it's a major unlock
because I I think that's where and I
know I keep using the word unlock because
I think in in these populations,
traditionally, it's really difficult to get the feedback,
and they're also really difficult to pilot with.
Because if you're running tests, you're actually running
tests on someone that's experiencing something,
or trying to access care. And that's not
always easy, and that's not always right, and
it's it can be difficult.
Here, you're able to do those tests in
this controlled environment without having to worry about
the patient risk or outcome. It makes it
safer, and it and it makes it more
controlled.
And I think, you know, the follow on
effect is you're gonna deliver better care,
for those patients and for those stakeholders.
Sure. Let me ask you a a bit
of a prodding question.
Just as this technology
continues to develop, we'll continue to see it
across many companies,
different industries.
How are you thinking about how CVS wants
to
ensure responsible use
of of agentic twins at enterprise scale? You
know, you're able to now test an an
external pressure
on on your customer
base. How do you balance,
some of the potential negatives of that or
or ensure that there's gonna be human judgment,
trust,
good governance of this technology as it begins
to as already has started to influence,
real health care on the ground?
Yeah. It's a really important question.
I I think one, we do. We have
very strong controls around this, and there's a
couple different ways we do it.
We continuously test
these twins,
against not only our own data,
but third party studies
to ensure that we have the highest quality
information.
And, you know, one of the things that
we're doing that these twins do as well,
is they actually live in the world, so
they ingest current events.
You know, if you are a, if you
have a a twin that's a democrat, they'll
read democratic news organizations. If you have one
that's a republican, they'll read republican news organizations.
So you're able to actually keep them up
to speed,
you know, even on current events. But
regardless of that, we're always back testing. We're
always making sure that they're meeting our standards
of of
matching known,
human results,
that we have. The second is, you know,
right now, we have my team of researchers.
I have a team of,
you know, analysts
and market researchers that we have organizationally that
are are the ones who are administering this
test because they represent human behavior.
So you can lead the witness. So if
you don't have someone, you know, at the
controls who's engaging with effectively the way it
works is an agentic chat
and you're not asking the questions appropriately, you
can get results that are misleading. So right
now, it's my team of researchers
that are are looking at that information and
validating it, and making sure it's meeting the
standards that we would have for human studies.
But one of the things I point out
there, though, is not to live in an
echo chamber. On occasion,
the Agenent twins will teach us something new
we didn't know, and we shouldn't just be
sitting there saying,
oh, wait. It it didn't match exactly what
we thought in the past, so, therefore, it's
wrong. What we need to do is investigate
it further. So we make sure we have
that process,
built out.
And then I think the third thing and
probably most importantly, I feel like everyone always
frames AI as replacement.
And as like, what is this gonna replace?
It's always the first question you get when
you're deploying an AI solution. I don't think
this is replacing talking to our customers.
It's augmenting our understanding.
It's amplifying their voice, as I've said.
But, ultimately, we're gonna have to always talk
to our customers because that's important, and that's
what good companies do. You need to listen
to people, and you need to understand what
their friction and their pains are. And then,
also, it's important to do that to potentially
catch emerging issues and things like that. So
I view this as additive to what we're
doing with our human populations.
And I think if you you combine those
three things,
you know, the the the back testing,
the researcher at the wheel, and then always
talking to the human populations as well,
it's a major it's a it's a set
of governance that gives you a lot more
confidence in how the twins are operating.
And it also helps you amplify the impact,
because when you're going out to the various
stakeholders
and you're doing the change management of saying,
hey. Listen to listen to these agentic twins.
They're telling us, you know, what to do.
The people you're working with have more confidence
in you because they know that you're taking
the the care
and you're doing the work to make sure
these things are accurate.
Absolutely. And like you said, Shari, I mean,
this is it sounds like this is unlocking
things that your customers were already feeling and
thinking.
Anyway, this is now just another way for
you to for you to reach to reach
that. So really, really fascinating.
Anything else we're missing here? Any final thoughts
you wanna share with our audience?
Yeah. I think, you know, at at CVS
Health, it's not just that we're experimenting with
this because I think a lot of people
will frame this as it it's it is
new. And I I get it's an emerging
technology, but we were at the forefront here.
And I think it's gone beyond experimentation.
You know, we're we're at this point. We're
at operating at scale. As I mentioned,
a 100,000
twins. You know, my hope is to get
us to 300,000
or more in the in the future, but
we're using this responsibly at that scale to
improve people's lives.
And this is giving our teams unprecedented
clarity
and foresight
into, you know, what's happening in the industry,
what's happening with our consumers, how can we
better serve them, how can we build
better experiences? How can we learn faster,
and design better?
It's it's helping us it's a step change
for us in terms of how we actually
deliver,
health care.
And I think in the end, it's gonna
help us deliver better health and support for
every customer member,
that we serve, and we're gonna do it
with more confidence, empathy, and understanding.
And it's gonna help us achieve our goal
of being the most consumer centric company in
health care. So,
yeah, I I hope everyone listening out there,
particularly those in health care,
understand that
this is a,
this is a a a tool
that I think can really give your customers
an unprecedented voice in the way you operate.
100%. I mean, this does seem to be
the one of the largest
commercial rollouts we've seen of this technology or
that we've been, we've heard about in health
care on our end. So, Sri, really appreciate
you taking the time to chat with us
about this, and then please keep us updated
as as this all evolves. We'd love to
hear more about it. Yeah. Always a pleasure,
talking about this, and it was a pleasure
talking with you. So excited to come back
and tell you all the great things we're
doing in the future.
And to our audience, if you'd like to
listen to more podcasts from Becker's Healthcare, you
can visit beckershospitalreview.com.