For Your Innovation Podcast: Innovation in motion

0:09 Hello everyone and welcome back to FYI

0:13 for your innovation a series on

0:15 healthcare innovation that we started a

0:17 few months back. In the last few

0:19 episodes we spoke about the why and the

0:21 what. Today we're going to focus on the

0:23 how and one of the critical elements of

0:26 how is technology. uh emerging

0:28 technology and how AI and other

0:31 technologies are really transforming the

0:33 way we look at innovation in healthcare

0:35 and making sure that healthcare is

0:37 changing innovating on a daily basis.

0:40 Today for this conversation I have with

0:42 me Harish Kodi CIO of Optimum India.

0:45 Harish welcome to FYI.

0:47 Rohit thank you very much. What a

0:49 pleasure it is to be here today. I

0:51 really love the play with words FYI for

0:54 your innovation.

0:55 Thank you. Thank you. Now we're excited

0:57 to have you here. Excited to kind of get

0:58 your take on technology and the role of

1:01 technology in healthcare innovation. And

1:03 maybe we start with that. Maybe we start

1:04 with the larger picture. Sure.

1:06 There's a tremendous amount of change

1:08 that's happening in healthcare. Um as

1:10 you know over the last few years,

1:12 technology is a key role plays a key

1:14 role in that. Uh if you think about

1:16 technology like AI, like cloud, they're

1:19 not just buzzwords anymore. They're

1:21 making fundamental changes to the way

1:24 healthcare is delivered on a day-to-day

1:26 basis. Just the pace of these

1:28 technologies making change in healthcare

1:30 is immense. Right. So I wanted to get

1:32 your thoughts on how technologies like

1:35 AI cloud are really really changing the

1:38 way changing healthcare over the next

1:41 few years.

1:42 Yeah Rohit um great question and you're

1:45 absolutely right. A lot is happening in

1:47 this space and this whole combination of

1:51 AI

1:53 uh all the new techniques we have with

1:54 data and cloud all coming together is

1:58 starting to change the landscape on AI

2:00 totally right but we should remember

2:03 that with the use of more technology

2:06 comes a lot of responsibility because we

2:08 are in the space of healthcare so

2:10 I want to start by saying that the first

2:12 things that technologists have to be uh

2:15 on top of in their game they need to

2:17 make sure u you know responsible use of

2:19 AI right what is data used for making

2:22 sure there is ethics is right making

2:24 sure the biases are not there I think

2:27 that's sacro sign because all of us

2:29 first of all carry a huge responsibility

2:32 on our shoulders of getting it right the

2:34 first time see because after all we're

2:36 dealing with human lives here right now

2:40 with that said with that being the

2:41 overarching thing that we'll be careful

2:43 about huge amount of things happening

2:46 Whether it is on the payer side,

2:48 provider side, consumer side. Let me

2:51 talk start with consumer first, right?

2:54 More and more consumer are wanting the

2:56 kind of experiences they have in retail

2:58 and in banking and other industries in

3:00 healthcare too. So consumer centric

3:03 healthcare is becoming sacrosan is

3:06 becoming the most important. Some of the

3:08 things that are going on and we've done

3:09 that inside our organization too is

3:12 looking at consumerf facing

3:14 applications. We kind of now have the

3:16 number one app out there in healthcare

3:18 which is able to help consumers with

3:20 seamless access to care, appointments,

3:24 scheduling, understanding status of

3:26 their services and status of their

3:28 claims and being able to you know price

3:30 and find care. I think these are all the

3:32 things that are happening from a

3:34 consumercentric point. Now it feels like

3:37 hey this is one good design front end UI

3:40 app but behind the scenes there's a lot

3:42 of interplay of data AI and analytics

3:45 that has to come together to give

3:48 consumers this experience.

3:50 Let's look at uh what are what are the

3:53 standard let's pick one challenge right

3:55 the consumer has a question has a query

3:59 they've probably interacted a couple of

4:01 times and are looking for a good quick

4:04 and good solution today what AI is able

4:07 do is identify which consumers need

4:10 help integrate data across systems

4:14 across departments based on uh usage

4:17 that is allowed and put together like a

4:20 view for our ad advocate to tell them

4:24 what this consumer is looking for and

4:26 how can you help them. What this does it

4:29 reduces a lot of friction abrasion

4:31 because in one call now I'm able to

4:34 address what the consumer is looking

4:36 for. AI is taking it even a step

4:38 further. We are able to identify

4:43 reasons why the consumer might call

4:46 tomorrow or in the future.

4:48 And AI is able to extrapolate all that

4:50 information and let us know that hey

4:53 this consumer might have a need. You may

4:55 want to proactively address that. Now

4:57 that can be done either through the app

4:58 or through digital media. What this does

5:01 is satisfies the need of the consumer

5:04 and they feel like hey look I'm

5:07 proactively being given the information

5:09 that I wanted anyway. And I think that's

5:12 the magic that AI is able to create

5:13 today on the consumer space. Let's look

5:16 at payer practitioner care provider

5:19 space.

5:20 What is their biggest challenge today?

5:23 Huge amount of procedures uh in terms of

5:27 documentation and things to be done and

5:29 followed

5:31 and hence uh physician fatigue less time

5:35 to actually do what is more important

5:37 which is empathize and spend time with

5:39 the patient. Today we have technologies

5:42 that are able to help note takingaking

5:45 to take away the administrative roles of

5:47 the care providers so that they they can

5:50 focus on what is most important for them

5:52 which is taking care of the patient and

5:54 taking the right decisions for them.

5:56 Last but not the least a lot of effort

5:59 being made to make the healthare system

6:01 work better for everyone

6:03 by making provider payer transactions

6:07 seamless. Like we now have products out

6:10 there that we use internally and in the

6:11 market as well

6:13 to seamlessly be able to you know work

6:17 with claims across payers and providers

6:20 so that

6:22 it's easy and there are it happens in

6:24 first pass and there's not multiple

6:26 rounds in this entire ecosystem.

6:28 Everybody's benefiting because the

6:30 member gets what they want faster sooner

6:32 the payers the providers get what they

6:34 want faster sooner

6:35 and the overheads of rework and you know

6:38 going through back and forth multiple

6:39 times on data to get the decisions

6:42 is also simplified. So these are the

6:44 kind of intervention that are happening

6:45 in the ecosystem today.

6:46 No thanks a lot. Uh I love the point

6:49 around consumerism right

6:51 because at the end of the day you know

6:52 healthcare I think is perhaps the place

6:56 where you know this entire industry

6:58 needs to be extremely extremely about

7:00 the consumer because it's very personal

7:02 right it impacts lives right

7:04 and that is why the more we able to

7:06 focus on the consumer keep the consumer

7:08 at the center I think the better our

7:10 focus on providing the right solutions

7:12 and making sure that we innovating

7:14 keeping the consumer at the center

7:16 absolutely

7:16 I also love the fact of you know what

7:18 you mentioned around you know being a

7:20 little bit more uh proactive right you

7:22 know rather than being very reactive in

7:25 the way we think about solutions think

7:27 about you know healthcare uh you know

7:29 being a little bit more predictive being

7:31 a bit more precise being very personal I

7:34 think that's the only way we can really

7:35 drive healthcare innovation and then do

7:37 it at a way that it can be scalable

7:40 across the entire value chain

7:41 so you talked about being more

7:43 predictive and being able to understand

7:45 outcomes and get better outcomes

7:47 VBC right value based care where we're

7:50 trying to build affordability engines to

7:52 look at how can we standardize care how

7:55 can we reduce errors

7:57 y

7:57 so that um you know care protocols are

8:00 standardized

8:01 um and you know delivered without much

8:04 error so value based care is a big part

8:06 of what you as well

8:08 no absolutely and you know I think all

8:10 of these solutions put together will

8:12 just help make sure that you know we

8:14 becoming um you know like you may

8:16 mentioned in the taking consumer focus

8:18 but you know as a company right we're

8:20 known as you know the

8:22 innovators around uh healthcare uh so so

8:25 great great thoughts right I think also

8:28 if you really think about all of this

8:29 innovation cannot happen in silos right

8:32 uh it needs to be done in a way that

8:34 you're bringing multiple elements

8:36 multiple people multiple voices uh

8:39 together right collaboration becomes so

8:41 critical right um you know gone of the

8:44 days when you can think about you know

8:46 small elements of the problems that you

8:47 solve. A lot of the small hanging

8:49 lowhanging fruits are already taken away

8:51 and the only way that you can solve

8:53 large big problems is by um you know I

8:57 think you mentioned it data process

8:59 technology all coming together uh I know

9:02 we do this really well on optimum um so

9:04 what are your thoughts and you know some

9:06 of the ways in which optimum technology

9:08 and optimum operations coming together

9:10 to really drive innovation? Beautiful

9:13 question. Um, innovation happens at the

9:16 seams. Cutting edge innovation happens

9:19 at the edges, right? Which means it's

9:21 happens at the edges where ops meet

9:23 tech. It happens at the edges where

9:26 engineering meets ops. It happens at the

9:28 edges where product meets tech and ops.

9:30 And of course all the practitioners out

9:32 there uh who are the caregivers, nurses,

9:35 practitioners.

9:37 Uh obviously you're aware of the program

9:39 that we are running currently which is

9:40 called hash sitwithops.

9:43 This is about not sitting in your cube

9:47 or corner office and imagining what

9:50 somebody might want versus going zero

9:53 distance and sitting down with them on

9:55 the daily basis to see what they go

9:57 through as an advocate to see what

9:59 members go through from a you know

10:01 experience perspective to see what nurse

10:04 practitioners and providers go through

10:06 on a daily basis. When you zero in and

10:09 go deep, you're able to do real

10:12 solutions and you're able to do

10:13 solutions that are at the intersection

10:16 of all these, you know, people who are

10:19 using your solutions and also at the

10:21 intersection of data and the cloud and

10:24 etc. I think that's a big thing that's

10:27 really really worked for us. Um if you

10:30 look at um advocates out there, you

10:33 know, they're trying to do good work but

10:36 they're overburdened again by administrative

10:38 tasks that they sometimes have to do.

10:41 Uh there is toggle tasks um toggle tax,

10:44 there is uh multiple applications they

10:48 have to go to to look up information. A

10:50 lot of the quick AI is also able to help

10:54 get all these interfaces and seamlessly

10:56 together to be able to help the advocate

10:59 spend time on what it matters and not on

11:01 this administrative lookup.

11:03 Remember it also reduces a lot of

11:06 friction and frustration in the in the

11:08 minds of these people who are working

11:10 for them. The most important thing to be

11:13 successful is not the tech and not just

11:16 the job of getting these tasks done but

11:20 to be able to empathize

11:23 with the end user member on the other

11:25 side and if that's the focus you can't

11:28 be frustrated yourself and these are

11:30 things that we're trying to do

11:31 in the system to enable that then of

11:33 course

11:34 right behind you innovate right

11:36 so all bottomup ideas bright ideas tech

11:39 tank that all roll

11:41 into groundup ideas because sometimes

11:44 you don't see the ground level

11:48 challenges uh when you come up with top

11:50 down approaches. So it's very important

11:51 to take bottom and top down approaches

11:54 and make the ends meet to give the real

11:56 innovation to people who matter. great

11:58 examples uh you know sit with ops you

12:01 know I've seen this in action over the

12:02 last two years or maybe a little bit

12:04 more than that right and you know

12:06 whenever you do this yourself as well as

12:08 whenever you see people doing it you

12:10 know you can literally see those light

12:12 bulbs you know flashing right and it's

12:14 just an amazing way of you know getting

12:17 the right people together and helping

12:19 people really empathize you know on the

12:23 problems that everyone else is facing

12:24 right tech understanding the ops

12:26 problems ops understanding understanding

12:28 road maps ops understanding what are the

12:30 new changes that are coming

12:31 and that I think intersection is so so

12:34 important to drive innovation

12:36 and technology is helping even in these

12:38 interventions today right if you look at

12:40 task mining or process mining even that

12:43 is now getting so highly powered by AI

12:46 true

12:46 that we are able to like take 10,000

12:49 advocates who are doing particular

12:50 process you know obviously there's

12:51 multiple streams and complications there

12:54 but if I put a process and task mining

12:56 AI I led on top of all of that we're

12:59 able to garner these insights and say

13:01 here are the top eight things if I solve

13:04 I can reduce the average handling time I

13:06 can increase my advocate NPS

13:08 and be able to reduce frustration

13:10 correct a

13:10 lot of technology is enabling even these

13:12 discovery

13:13 absolutely absolutely yeah

13:14 and you spoke about innovate right

13:16 innovate which is our innovation

13:17 platform right it's really helping us

13:20 democratize innovation right it's

13:21 helping us make sure that whether you

13:23 are a frontline agent the advocates that

13:25 are handling calls uh claims associates,

13:28 right? Or you are executives in the

13:30 company, managers, leaders, right? It's

13:33 creating a common language that everyone

13:35 can use to talk about ideas and ways in

13:38 which they can solve problems. Again,

13:40 keeping the consumer at the center. It's

13:42 bringing together like I mentioned

13:44 earlier, data, technology, process

13:46 insights, deep insights that we get from

13:49 task mining. all of them together to be

13:51 able to create solutions that are

13:53 focused on the right problems and are

13:56 helping us deliver value and solutions

13:57 at scale right and I think that is a

14:00 very critical element of you know how we

14:02 drive innovation none of that though is

14:05 possible without the people right and I

14:07 think with the advancement of technology

14:10 I think it's very important for our

14:11 talent to also make sure that they are

14:13 future ready

14:14 right and I think the tech talent the

14:17 way that they are making sure that they

14:19 drive the innovation

14:20 is going to be critical for the future.

14:22 So Harish, I wanted to get your thoughts

14:24 on the role of technology talent in the

14:27 future of innovation and healthcare.

14:31 That's a very interesting question, very

14:34 obvious answer, but let me break this

14:36 down a little bit. Right? We're talking

14:39 of technology here, but the talent is

14:41 not just technology, right? Talent needs

14:44 to have technology, needs to understand

14:47 the business domain and principles and

14:50 need to know how to articulate and tell

14:53 a good story.

14:56 Technology, you know, we already talked

14:58 about the fact that you really have to

15:00 be good at AI. It's AI in everything.

15:02 Cloud is important. Data and analytics

15:04 is all important. And these have to all

15:06 come together. From a tech talent

15:09 perspective, we have a lot of

15:11 investments in training that we are

15:13 doing. across the enterprise.

15:15 Um for example, we work we've worked on

15:18 an AI dojo certification

15:21 which is kind of becoming the leading AI

15:23 certification in healthcare. They end

15:25 with healthcare examples, healthcare use

15:28 cases and healthcare capstone. Uh we run

15:30 this with the optim university and more

15:34 than 60 70% of our staff now is actually

15:38 AI dojo certified. Then of course we

15:40 have cloud trainings on various cloud

15:42 models because we are a multi cloud

15:44 environment um that we have

15:46 certifications there in data and

15:47 analytics but um look more importantly

15:52 it's

15:54 imperative that our people understand

15:57 business domain well right

16:00 you can you can train on AI

16:03 you can train on business separately

16:06 but the advantage that we have at optim

16:09 is we have people who've been in the

16:11 organization for a long time now.

16:13 True.

16:13 And the journey of transforming the

16:16 existing talent into AI first talent

16:19 using

16:20 you know interventions like AI dojo and

16:22 you know co-pilot certifications that we

16:24 are doing makes a big difference to add

16:27 to that uh you know we have um good

16:31 number of ops correct training that is

16:34 in progress. In fact, as part of some of

16:37 the tech training, particularly on

16:38 co-pilot where you can, you know, play

16:41 uh with technology even though you may

16:43 not be a real coder

16:45 u more than 500 600 people from ops have

16:48 also participated in that and ideated as

16:51 part of that. I think that ecosystem has

16:54 really come out well. Obviously from

16:56 time to time we uh you know we instill

17:00 fresh talent as well from the outside

17:03 who are AI first talent.

17:05 When these two powerhouses come together

17:08 ingrown AI talent which is deep in

17:10 domain and have transformed themselves

17:13 and AI talent that may not necessarily

17:15 be healthcare but has come from the

17:16 consumer industry come from the retail

17:18 industry come from consulting

17:20 industries. When you combine all of

17:22 these and create solutions, magic

17:24 happens. Right? Uh the reason I'm saying

17:28 magic happens in this model is because

17:32 people who work on these problems have

17:34 to have a deep understanding of

17:36 healthcare, healthare policies,

17:39 healthcare technologies, healthcare

17:41 compliance, right? And deep domain

17:44 knowledge. Without that, this

17:46 transformation does not happen. Last but

17:48 not the least, you have a great idea,

17:51 but you can't tell a good story.

17:53 You can never convince anybody that it's

17:55 a great idea, right? Yes, you might get

17:57 lucky. You might had somebody who really

17:58 really listens well and sees that light

18:01 bulb go off. But I think it is very

18:03 important that all our talent know

18:06 y

18:06 to innovate and to tell the story of

18:09 what they're proposing because that's

18:11 when you can bring it to life. I think

18:14 this is what makes talent well-rounded

18:17 and not just some one technology tool

18:20 that I can use and make a difference

18:21 happen.

18:22 Well, that's so true. Right. And I love

18:24 your point on domain because this is an

18:27 industry, this is a place where without

18:29 understanding the underlying factors,

18:31 the process, the technology, your

18:34 ability to make changes is not going to

18:36 be easy, right? Um like I said gone of

18:39 the days when you know a simple fix

18:40 could solve problems and bring a lot of

18:42 value. Now we solving really complex

18:45 problems and your understanding of your

18:47 domain combine that with technology and

18:50 just the hunger to look at innovation is

18:52 so critical. I love the I love the way

18:54 we're thinking about um you know

18:56 training on AI which is very persona

18:58 based which is making sure that we're

19:00 capturing and going out to various

19:04 personas and people that are existing

19:06 within the organization. So it's not

19:08 just technology, it's you know all of

19:10 technology, all of operations, all of

19:12 functional areas and catering to

19:14 different levels of the organization

19:16 because at the end of the day when you

19:17 put technology and talent together, I

19:19 think that's the only way we can drive

19:20 innovation. Innovation which is

19:22 sustainable and can really scale across

19:24 the organization. Harish this was really

19:27 wonderful. Thanks a lot for your

19:29 thoughts. Uh thanks a lot for your

19:30 insights. It's clear that innovation at

19:32 Opterum is obviously trying to make

19:34 things better is is really rapidly

19:38 making changes to the lives of the

19:40 people that we serve but it is also

19:42 sustainable. It is also deeply deeply

19:44 human which I think is something that

19:46 you know we as a company strive for.

19:49 It's there in our mission. It's there in

19:50 our vision. So thanks a lot for your

19:52 insights. You know, if you think about

19:53 like you mentioned AI, if you think

19:55 about cloud, if you think about, you

19:57 know, the focus on domain, the focus on

19:59 talent, I think those elements coming

20:01 together is making sure that we really

20:03 making changes that are not just, you

20:06 know, vision, it's making changes that

20:09 are real and that are changing dayonday

20:12 lives of the people that we serve. So,

20:14 thanks a lot for your inputs.

20:16 Absolutely, Rohit. So, let me just say

20:19 this one more thing, right? Yes, we're

20:22 making a big difference with technology

20:24 in innovation in Optim and at UG. But

20:28 look, remember what's our mission? Yeah,

20:31 we are here to help people live

20:33 healthier lives

20:34 and to help make the health system work

20:36 better for everyone. Mhm. So as

20:38 technologists out there in the industry,

20:39 we are also out there with solutions,

20:42 products and services that are available

20:45 to the healthcare ecosystem with a sing

20:48 simple and single motive of making it

20:51 better for everybody out there and not

20:53 just for ourselves. Rohit, thanks a lot.

20:57 It was a pleasure talking to you and um

21:00 I hope we can do this more often.

21:02 Likewise, Harish. Thanks a lot. And to

21:04 the people that are tuning in, thanks a

21:06 lot for watching. Thanks a lot for

21:08 listening to the fourth edition of FYI.

21:11 Hey, remember uh innovation that is

21:14 driven by empathy, powered by passion,

21:16 and enabled by technology is the kind of

21:19 innovation that will last. It's the kind

21:21 of innovation that will stick and make

21:24 sure that we changing lives on a

21:25 day-to-day basis. Thanks a lot for

21:28 watching. Keep innovating on a daily

21:30 basis. Thank you.