0:01

The power of data is

0:03

undeniable and unharnessed, it's nothing

0:05

but chaos. The amount of

0:07

data, it was crazy. Can I trust it?

0:09

You will waste money, help the other way duct

0:12

tape to defy you. This season we're

0:14

solving problems in real time to reveal

0:16

the art of the possible. Making data

0:18

your ally, using it to lead with

0:20

confidence and clarity. Helping communities

0:23

and people thrive. This

0:25

is Data Driven Leadership, a show by

0:28

resultant. Hey

0:31

guys, welcome back to Data Driven Leadership. On

0:34

today's episode, you're going to hear from

0:36

Peter Krambeck. He's the director of data

0:38

operations at the Indiana State Department of

0:40

Health. Peter's a really

0:42

incredible leader and what I appreciate about him

0:44

is that he doesn't just dive into things

0:47

like his data governance experience or how to

0:49

change culture in an organization, which he can

0:51

speak to eloquently. He

0:54

actually unpacks what it looks like

0:56

and how he approaches it.

1:00

How he handles these tasks, why he does what

1:02

he does the way he does. And I

1:04

think often in society on

1:06

podcasts and LinkedIn, people

1:09

are talking about the what and

1:11

the actual magic is in the

1:13

how. Their approach,

1:15

their style is what makes it different.

1:17

And while we shouldn't aim to replicate

1:20

someone else's style, I've come a long

1:22

way by just trying other people's style

1:24

on the first 10 years of my

1:26

career. And then having to figure out

1:28

what pieces do I want to keep and what pieces do I

1:30

want to shed to make it my own. Peter

1:32

is definitely someone that is impressive when it

1:34

comes to observing his style. I

1:37

think one of the things that stood out the

1:40

most to me is his emphasis on understanding who

1:42

is everyone that needs to participate in a change

1:44

in your culture around data and how

1:46

to make sure they're getting in the boat with

1:48

you and you're not leaving anyone behind. What

1:50

I mean is, there's

1:53

often that you're working on an initiative and

1:55

you think about your core team or your

1:57

core end user and you miss people that

1:59

are adjacent. and really important actually

2:01

for adoption or leverage in the

2:03

initiative you're taking on. He's very good

2:05

at thinking about how do I cast

2:08

the widest net for the best

2:10

outcomes. He's naturally team

2:12

oriented, extremely self-aware and really

2:15

passionate about data. I

2:17

am excited about this episode and I hope you like it.

2:23

Welcome back to Data Driven Leadership. I'm

2:25

your host Jess Carter and with me

2:27

today is Peter Krombach, the Director of

2:29

Data Operations at the Indiana Department of

2:31

Health. Hey Peter. Hi. Thank

2:34

you for being here. Yeah, thanks for having me. I am so

2:36

excited to have you here. This is long overdue. Definitely. We

2:38

discussed this in March, May. But

2:41

I've been secretly pleading to be on this

2:43

for a year. We've been secretly pleading

2:45

for you to be on it for a year and for you to

2:47

even say that is sort of a, I

2:50

don't know, compliment because we've barely been

2:52

here for a year. Yeah. But

2:54

you're passionate about data. That's why you're excited, right? Yeah,

2:56

definitely. So I'm gonna get into

2:58

this right away. Were you

3:00

always interested in data? No.

3:03

I feel like it always came naturally

3:06

but as any data

3:08

thing evolved, I feel

3:10

like as I continue

3:12

to get older, was noticing patterns and

3:14

behaviors in different aspects of life. I

3:17

was used to think I was gonna go into

3:19

the medical field as like a primary care physician

3:21

or... Oh, interesting. First stream was always pediatric oncologist

3:24

which is beyond what this scope is. But

3:26

it's kind of being in the right place

3:28

at the right time has been my professional

3:31

journey into data and it

3:33

just makes sense. Like data is always something

3:35

that unfortunately sometimes makes sense to people and

3:37

other times doesn't and you can train that

3:39

up. But my data journey has

3:41

always just been taking the

3:43

opportunities as I come and just like diving straight

3:45

in. That's amazing. Can you tell me more about

3:47

that? Because you have this interesting career and where you

3:49

sort of following it is this fun map into where

3:52

you are today. So can you walk us through that?

3:54

I use different analogies depending on who I talk

3:57

to and like how much time I always have to

3:59

talk about it. But... But I've always

4:01

been very non-traditional. Don't claim

4:03

to be a data scientist, don't claim to be

4:05

a data architect, even though they've been in my

4:07

job. Sure. That's my job title.

4:09

Credits to people who've just hired me because of

4:12

my skill set, and I'm proud of that. But

4:14

a lot of it is just right place, right

4:16

time and evolving with the context that I make

4:18

and just my interests as they grow. Since

4:21

traditionally I had background

4:23

and education as an epidemiologist getting my

4:25

master of public health, but

4:27

after that it was, hey, we

4:29

want to introduce you to health informatics. Kind

4:33

of figure out what that was, what SQL

4:35

and certain data processing was, and just ran

4:37

with it. That's so cool. So

4:41

everywhere that I've gone, I've gained new skills, and

4:43

that's kind of something that I've liked in roles,

4:45

where you can learn a new tool, you're not

4:47

trying to only focus on one methodology, and

4:50

gaining a lot more tools in your tool belt to be

4:52

able to consult on that and just help creatively

4:55

solve solutions. Well, and

4:58

you've been in health, so we're going to have

5:00

to unpack. Most people may not

5:02

know what an epidemiologist is. How would

5:04

you explain that to my grandma? That's

5:07

a great question. So the first thing I always

5:09

say is we are not dermatologists. You get that

5:11

a lot. Because

5:13

it's similar to epidermis in a way,

5:16

and so we used to have these little ones who make stickers

5:18

and be like, we are not skin doctors. We cannot consult on

5:20

your mole. I

5:24

just like to say we are individuals

5:26

who are passionate about monitoring

5:28

diseases and identifying areas

5:30

where there may be

5:34

populations that are disproportionately affected. So I

5:36

mean, you go back to the

5:39

initial cholera outbreak with the evolution of John

5:42

Snow and the actual John Snow, who

5:44

actually was a person, and the

5:46

Broad Street water pump. Just

5:49

surveying outbreaks and saying, hey, we're good at counting things.

5:52

Can we turn that into, instead of

5:55

counting individual groups, the entire

5:57

population? And so that's kind of evolved into the

5:59

population health. It's

6:02

a little bit similar to the medical

6:04

field because yes, we do consult with

6:06

physicians and our commissioner is a physician

6:09

herself. So there is that play in

6:11

between utilizing these broad population view at

6:14

the same time. So you're not,

6:16

you can't look at a mole and

6:18

evaluate it, but you can help public

6:20

health better understand what diseases,

6:22

new or continuing diseases, we

6:25

can track them, trend them and how

6:27

they're impacting public health more generally and

6:29

specific people groups. Exactly. And

6:31

a lot of it is we're just a resource

6:33

to use to consult because some of these physicians,

6:35

unless you're like an infectious disease doctor, may not

6:38

see this in their career. So, oh, I have

6:40

a case of a GI

6:42

illness that I never have seen before.

6:44

What am I responsible for reporting? So

6:47

we can do whether it's from reporting or

6:49

disease prevention mechanisms or just saying, hey, this

6:51

is a problem. Let's try to figure out

6:53

a way to address it. Do

6:55

you feel like the entire world finally knew

6:57

what you did during the pandemic? In

7:00

a way, it also felt like validating is like,

7:02

oh, is this like by just chance

7:04

that I was always like secretly dreaming of a

7:06

pandemic and never wanting it to happen? Because

7:10

like when I used to have to explain what

7:12

epidemiologist was, it was kind of trying

7:14

to convince myself that I knew what it was because

7:17

some epidemiologists don't really deal with data all

7:20

the time. They're just a very consultant and

7:22

deal with the prevention aspects, but then others

7:24

do have those skills. Wow. So

7:26

suddenly it mattered. Yeah. To

7:28

everyone. And everyone had an opinion on what it

7:30

should be and how we should present data. And

7:33

of course, that was always water that you have

7:36

to navigate as a leader, just trying to understand,

7:38

okay, how can we mitigate any potential negative

7:41

feedback that we would get? But it's

7:43

kind of embracing that at the same time.

7:45

Yeah. I mean, that's how

7:48

you iterate through maturity, right? As

7:50

we actually collect that feedback and figure out how to

7:52

make better visuals or better explanations of

7:54

what we're doing, right? Right. Well,

7:56

and that seems like... So one of the questions I have is

7:59

in your role. So you've played a lot,

8:01

you've kind of had multiple roles, we're going back to

8:03

your whole story. So you've had these multiple roles in

8:06

public sector health mostly,

8:08

right? But around

8:10

data. And so, but not all at the

8:12

same agency. You weren't always at Department of Health, where were you

8:14

before? So I started

8:17

out at the Department of Health and I

8:19

was like, I've had three instants there in

8:21

different roles, this is my fourth one, total.

8:23

But I've also had experience at Indiana University

8:25

doing clinical research, helping be a data manager

8:27

over there. And then I was also doing

8:30

a similar capacity for the School of Nursing

8:33

at IU in Indianapolis. And

8:36

always just my go-to bread and butter is

8:38

like, I like helping people

8:41

find solutions to problems in a way

8:43

where they never thought was possible because

8:45

whether they've always had that mantra, I've always done

8:47

it this way, this is what works. And

8:50

just trying to show that value of, hey, I can

8:52

potentially automate this process for you so you don't have

8:54

to spend 40 hours a week and I can just

8:56

run this report for you in an hour. And

8:59

that's kind of where I fit in. But

9:02

the thing that's been the common theme is just

9:04

being able to look ahead and not wanting to

9:06

settle with the minimum and just be like, hey,

9:08

I know there's, even if I don't know the

9:10

way myself, let's try to figure it out

9:12

together and move

9:14

forward and try to embrace the fear

9:16

of failure. Yeah, well, tell me

9:18

more about that. So I've

9:20

been in public sector consulting for almost

9:22

a decade and there's certainly, I mean, there's

9:25

real elements that are different than private. There

9:27

are elections that come up, there's more fear

9:29

of what if something gets in the paper,

9:32

we wanna take care of public citizens, we

9:34

wanna make sure that we're taking, we're responsibly

9:36

managing dollars. So there's a lot of reasons

9:38

to be afraid. So

9:40

how do you navigate that in an environment

9:42

that is kind of full of fear? It's

9:46

all about the opposite of fear, is like

9:48

trying to build trust and confidence that we're

9:51

all working on that shared mission. Whether

9:53

we don't have the understanding of what

9:55

this individual does to contribute to that

9:58

task, like holistically, we are all responsible.

10:00

were the same deliverable. I

10:02

find it fantastic that everyone likes to take

10:04

ownership of the products that we release and

10:06

that's something that I encourage everyone to focus

10:09

on is like, hey, there

10:11

may be potential snags or roadblocks that we

10:13

hit, but we're trying to focus on that

10:15

core goal. The fear

10:18

part is just not wanting to have any

10:20

negative feedback directly on you because from a

10:22

liability perspective, it never feels good as a

10:24

professional. Right. To have that negative feedback and

10:26

it's like, oh, is my job going to

10:28

be at risk? Is someone going to say

10:30

something that we'll get in trouble for? Right.

10:32

And that's not necessarily a bad thing.

10:35

Yes, it does happen, but it's trying to

10:37

frame it in a way where you

10:39

can move on from it because yes,

10:41

we are in the public sector. So

10:43

every mistakes that are made are made

10:46

very public and can potentially

10:48

have consequences, but hopefully you

10:50

just need to lean into

10:52

that and try

10:54

to move on and like craft

10:56

that narrative about yes, we understand and

10:58

own that mistake and understand that that happened and

11:01

say, these are the steps that we're doing to

11:03

mitigate that. It's a big deal.

11:05

I mean, that is a, the

11:08

risks, the healthy risks

11:10

an agency can take to transform

11:13

are just significantly different if you

11:15

have that mindset. Exactly. If you're,

11:17

if, if anytime you're in the

11:19

paper, anytime there's a negative outcome

11:22

that's in the public eye, we

11:24

failed, right? You will actually hamper

11:26

innovation in your agency. I don't

11:28

know that everybody realizes that. And

11:30

that's something that the pandemic taught

11:32

us and we're trying to continue to

11:34

sustain that model of yes,

11:36

we know that these roadblocks exist. Let's not

11:39

try to go back to our old ways

11:41

just because we're not in an emergency anymore.

11:43

So let's try to work together. And a

11:46

lot of it for us is like top down leadership,

11:48

just trying to lead by example. Cause

11:51

I always just like, I need to own my

11:53

mistakes if I make one. And so hopefully those

11:55

who, whether it's reporting to me or just work

11:58

with me can feel that same. way.

12:00

Yeah, but yeah, it's, it's

12:02

always depending on the person, it's very

12:04

person centric and not procedure centric

12:07

because the procedures can come and go but

12:09

it's really trying to build that collaborative trust

12:11

between everyone in your agency. How it

12:14

surprises me that you would say that

12:16

COVID helped to bring that to bear.

12:18

Because I feel like in COVID the

12:20

opposite could also be true where you're

12:22

so terrified to make a mistake. Right.

12:24

Nothing. So unpack how,

12:27

I don't know, I'm intrigued about how COVID

12:30

allowed for more of

12:33

this vulnerability in agency. How does that happen? Do

12:35

you think? I think it was

12:38

a blessing and a curse in terms of I

12:40

came at it from a different perspective. Like I wasn't

12:42

there at the beginning, but I came in in May

12:44

as kind of like the support staff for the CDC

12:46

foundation as a data scientist. So I have a different

12:48

view on that. But I think it

12:50

just caused us actually stop and say, okay,

12:52

we literally have to drop everything that we're

12:54

doing and everyone in the agency is supporting

12:57

one common task. I see. And so we

12:59

had so many barriers that because we weren't

13:01

just doing our day to day work, yeah,

13:03

that were just highlighted. And so

13:05

of course, having the governor's

13:07

public health commission and doing these broad

13:10

scale assessments, that helped of course, but

13:12

I think it was just the,

13:14

oh crap, we have to do

13:16

something brand new. Yeah, we can't really use

13:19

old processes because we try to surf that

13:21

over, right? Not necessarily not worked for that

13:23

solution. So it forces to innovate. And

13:25

I think that was a good thing. Well, and you

13:27

were, so you've said this twice,

13:29

but to emphasize it, because I think

13:31

it's significant. You found, you found

13:34

a way to align everyone to

13:36

a common goal or mission. It

13:39

was, I mean, I remember even the concept of most

13:42

data people are not in the business

13:44

where they're going to get a chance

13:46

to actually reduce outcomes for people that

13:48

might be deceased based on a Pandemic.

13:51

And So there's a sense of, you can actually make

13:53

a significant difference that you never knew you were going

13:55

to be able to make in your career. I Think

13:57

that that can be super unifying. Right. So The sense

13:59

of. We're not worried about these reports

14:01

over here in our we're trying were actually

14:03

the business. Of saving lives,

14:06

a break and a pandemic where normally

14:08

the businesses airline like seriously and an

14:10

emergent rare just a numbers as is

14:12

Jewish and to me that has. The.

14:14

Power to really unite people? That did. You guys do

14:17

feel like you sense that as an agency we did

14:19

I think of as a little bit. Because everyone

14:21

just with burn out just how professional nature

14:23

what our going around the clock. It's hard

14:25

sir celebrate those ones because of everything that's

14:28

happening around you. I'm from what I've seen,

14:30

just aftermath I think that or District continuing

14:32

to try to sustain that really encourage people

14:34

of course trying to mitigate burn Out and

14:37

do what we can with your network developments.

14:39

But. Ah, I think it's

14:41

been positive. I'm. Alice. From

14:43

the data perspective than. One, What about

14:46

so. I think about your

14:48

career and you have Then you've done a lot

14:50

in in a small number of our or years

14:52

and so when I look at your career do

14:54

you have any thoughts about am. And

14:57

he'll be easy to be sort of it at

14:59

the right place at the rates name but not

15:01

have the right mindset and be in your head

15:03

of hours to. I have the right to say

15:05

something that I've the right so I don't know

15:07

if you would normally close of a risk taker

15:09

but it seems like you can be a in

15:11

so. I'm very risk averse am I

15:13

personally have that professionally? I think it's

15:16

just. Learning to trust her got

15:18

instant because everyone has one arm but the

15:20

fear internally about we talked about and just

15:22

like the imposters and like am I qualified

15:24

enough to do this that everyone goes through

15:27

cause like I talked to my siblings or

15:29

talk to other professional lives the guys do

15:31

feel that. Same. Way but

15:33

everyone just as a different way of

15:36

addressing that and for me it is.

15:39

The. Understanding of if I don't know something,

15:41

be that first, be like your own

15:43

advocate and ask those questions and a

15:45

met. Hey, I'm not going to be

15:47

able to do this. I need some

15:49

additional training rave. I'm okay, so that's

15:52

kind of. Then My mindset is just

15:54

trying some like as lean, lean into

15:56

at all and just ah, Of

15:58

course, just address that for years. The move there

16:00

out because yeah, for Thursday's or I'm

16:02

still stressed out about something that going,

16:04

I'm yeah and it takes that second

16:06

to step back and say okay, clear

16:08

mind. And. Just focus on that angle.

16:11

You know how enjoy blood is to hear

16:13

someone on a data podcast? A Trust your

16:15

got him. Because it is, it's easy to

16:17

it is it's a get into this spiral of

16:19

i need data speeds, attitude and leader in. that

16:21

means I have have just the right reports and

16:23

there was a reality and so these instances where

16:25

you didn't have all the data you rate and

16:27

you had to make a decision and so the

16:29

this is where it's still data at the com,

16:31

the your experience frame or to call to some

16:33

to borrow someone elses lens or experience. It's not

16:35

just that everything has to be in a dashboard

16:37

perfect guy race and so that's where my it

16:39

again Pozner been shot for me when. I

16:42

think everyone else is more technical than mean everyone else

16:44

has praised more data than the race and the the

16:46

reached. The point is you're in the room the gear

16:48

the person assigned to lead the data organization and you

16:50

understand what this is he to be. Make. Rate that

16:53

you're not. be confident that people who are in

16:55

leadership positions are looking to you and are actually

16:57

like even if they're not directly telling you all

16:59

the time that they trust and you to do

17:01

a good job again wouldn't be there unless you

17:04

are meant to be there. Yes did you

17:06

have an Emmy for real? It's easy to

17:08

look back and me that's do you remember

17:10

a specific instance or to where you you

17:12

are going into a meeting and it was

17:15

Whether it was the pandemic isn't they also

17:17

in you can have had a walk yourself

17:19

through this. In Quito. So I was

17:21

thrown into the deep and a little

17:24

bit right away because as we were

17:26

noticing does the elderly population and those

17:28

a long term care facilities were really

17:31

both were relayed. i'm advert are at

17:33

risk rub additional negative consequences whether that's

17:35

hospitalization or enforcement leave death rays and

17:37

we needed a better way to track

17:40

that. And so I was bolland hold

17:42

or just took that position of okay

17:44

we need to collect data from all

17:47

of our healthcare facilities that focus on

17:49

long term care or gas and homes

17:51

and then we need to have a

17:54

mechanism for reporting that moving forward to

17:56

be able to have a surveillance dashboard

17:58

around her. I'm so. Like

18:01

not an hour later was already on a call

18:03

with a couple of exacts whether both from results

18:06

and and the state governments like okay, are we

18:08

gonna do this and I did have that ideas

18:10

like I'm just gonna own it. This.

18:12

Is a way that we have that I

18:14

know me work on my me investigate a

18:16

little bit more. Yeah just kind of drive

18:18

forward. And of course

18:21

I would want to be a team

18:23

approach. In that case it was individual

18:25

decision initiative to go. Yeah, by that's

18:27

not support that I thought from everyone

18:29

else that was participating on whether that's

18:31

individuals on engineering team and actually use

18:33

the data that I was collecting and

18:35

cleaning orders. From the executive Perks perspective

18:37

that we're trusting him and decisions and

18:39

I made help make that a little

18:41

bit easier. Yeah, it's this and it's

18:43

interesting to me to hear you than replay that

18:45

and think at some point like to see where

18:47

that created be are you are open and you

18:50

are willing. To. And it was

18:52

like you were willing to get on the call.

18:54

You are open of our ideas you had and

18:56

rape and you were gonna be easily offended if

18:58

someone else had a better one for it was

19:00

just about the outcome. See, were tied to the

19:02

mission. You're trying to accomplish things you're open, unwilling,

19:04

not defensive nights. My idea has to be right.

19:06

Seventy three it wasn't about this is Peter Sunde

19:09

to shine in linguistics health of about race as

19:11

really And that is an interesting way to overcome

19:13

imposters in that it's nights about. The. Leaving

19:15

you are amazing in the the

19:17

antidote to imposter syndrome might be

19:19

being willing and open right to

19:21

participating in dissolution not necessary being

19:23

to suddenly so egotistical you know

19:25

you're great right? Because I used

19:27

to think. Oh. You know you've

19:29

made it if you're gonna be that big

19:31

leader who can be willing to speak in

19:33

front of a group of my own and

19:35

like say yes as as I'm agency days.

19:37

But it's finding those waves. and if you're

19:40

not in that role just knowing how you

19:42

contribute and I'm still looking for those opportunities

19:44

of course, where you can show your skillset.

19:46

Laugh! At. Different times like

19:48

leadership and data specific leadership.

19:51

Means. Different things to different people.

19:53

Rain and. You. find successful

19:55

like actual good leaders in positions where

19:57

they will never see the spotlight and

20:00

And that's something that they're okay with, but they're still

20:02

excellent leaders. Right. I like that you

20:04

just made the concept too of a data-driven leader

20:06

is accessible by anyone. You can

20:08

be a data-driven leader by having a sense

20:10

for the highest and best use of yourself

20:12

today and leveraging yourself in that

20:14

way. Like I think there's some self-management there too,

20:17

right? And it's to your point, it's not about

20:19

the limelight, it's about impact. And

20:21

just because I have the director in my title or someone

20:23

would have a chief in their title that

20:26

they just play a different role in

20:28

our entire data landscape that

20:31

they may be able to

20:33

go back and develop a

20:35

model as a data scientist or run

20:37

some analytics. But that's

20:40

not the role that they're playing at that

20:42

point. So it's all just, again, trying to

20:45

focus on that team-based approach. I like that.

20:47

The team emphasis too, I think takes some

20:49

of the ego out. It's all about

20:52

what are we trying to accomplish. Right. So

20:54

when you look at the last half decade,

20:56

the last three years probably feel like an

20:59

eternity. I

21:01

kind of feel

21:04

like you've seen these moments where you've managed

21:06

and harnessed data for specific use

21:09

cases. But there's now

21:11

this pretty large change, it's like a wave

21:13

coming over state government where data is really

21:15

being seen as an asset. It's

21:17

not just a data project with this one

21:19

set of data and this one research. How

21:22

do we manage the asset that is our data?

21:26

I guess I would ask you in that journey, what

21:28

has surprised you along that journey? I

21:32

think it's just the continued

21:34

commonalities that everyone has

21:36

that mutual understanding of hey, we

21:38

know something about data. They might

21:41

not be exclusively data literate that

21:43

they can be able to explain

21:45

the complex processes, but they still

21:47

are wanting to be willing to

21:49

understand it. I

21:53

think it's just instances where you see kind of

21:55

both sides of the spectrum where it's a

21:58

historically In just any data system. Then there's

22:00

specific data silos and always exist and you

22:02

have some projects where people are willing to

22:04

say let's just completely break down the walls,

22:07

blow it all up yeah and treat this

22:09

new model but then you try to as

22:11

leverage that against individuals like oh, this is

22:13

process has always been the way it does.

22:15

It works well. we're trying about to do

22:17

that forward thinking yeah to use it as

22:19

an acid to say hey, I don't understand

22:22

that you collect data and one system but

22:24

look at all these other possibility that we

22:26

can do with the data that will then

22:28

possibly impact your program. So it's

22:30

just trying to balance both sides to

22:32

say yes, we will set up the

22:34

governance and necessary for everyone to use

22:36

this as a shared assets to build

22:38

that trust and like to mitigate their

22:40

fears of it being misused or riot

22:43

an appropriately and I'm with but still

22:45

that fast enough for you to that

22:47

to be okay with us assessing Rain

22:49

because it's pretty critical information like we're

22:51

talking about and individuals health record at

22:53

times rain and so of course everyone

22:55

is on the same page as. We.

22:57

Just need to line back at that as we.

23:00

Are. Committed to protecting and promoting the

23:02

house of All Hoosiers and that

23:04

includes keeping the information confidential and

23:06

like making sure that we have

23:08

the right sucks and place for

23:10

the metrics that we deliver. That

23:12

is eloquently said. we want to access

23:14

it, but we also want to protect

23:16

that and leveraging for their mouth and

23:18

am okay. See you mentioned governance which

23:20

I sort of men enjoying having a

23:22

conversation about. Given to the few people

23:24

on the podcast, they think that. It.

23:27

Isn't it is a little the as.

23:30

A My observations it seems like governance is

23:32

more and more as am like. It

23:35

depends on who you're talking. rowdy, me and stuff.

23:37

When it comes to leveraging data and

23:40

pretty together. Governance structures? What's.

23:42

The hardest part in your opinion? Ah,

23:46

That's a great question because like the first

23:48

one I was recruited back to idea waits

23:50

for their. Fourth, Century suffered from

23:52

as as as a my Dad regional

23:54

title was just Director of Engagement and

23:56

Governance and As I was tasked with

23:58

helping to build out art Executive. The

24:00

governance board that we have and it

24:02

that's a make like you said governance

24:04

means a lot of different things to

24:07

depending on who you are. Yeah, I'm

24:09

a lot of the struggles that I've

24:11

worked through is just balancing the necessary

24:14

policies and procedures and security that you're

24:16

required. Of course, to say federally compliant

24:18

frame me systems still remain for a

24:21

reason, some because for me they're just

24:23

hard to interpret like a security policy

24:25

will get a bunch of additional acronyms

24:28

to understand arms. But it's also. Trying

24:30

to incorporate. Governance.

24:32

Also can mean developing best practices whether

24:34

it's been a centre of excellence for

24:37

business intelligence or data and analytics. Yeah,

24:39

but it's getting individuals the tools to

24:41

say, hey, we're gonna, we're not telling

24:43

you what to do As says, here

24:46

are all the options to expand that

24:48

scope. Ah, I'm. And like drop

24:50

pushing them in the right direction to

24:52

like governance to me can be though

24:54

like metal bar the you can't move

24:56

out of raise a guard rail or

24:58

what analogy want to use but I

25:00

also think it's a building your boat

25:02

a little bit bigger to be able

25:04

to say oh you might not have

25:06

known that this tool as assessable more

25:08

this analytical methods there but built in

25:10

with an art governance. Whether it's a

25:12

better focus on data quality yeah or

25:14

a better focus on let's make sure

25:16

analytics or automated it just me absolutely

25:18

making it all encompassing. Yeah, there's

25:20

this pivot I saw fan.

25:23

Ah, data. And that

25:25

a. Hasidic that a project of

25:27

data products in a month of rip what's

25:29

repeatable rate and how do we? How do

25:31

we get that govern the things that are

25:33

repeatedly useful? That's your plan. Really appreciate the

25:35

emphasis you on that that it was created

25:37

for a reason resources Sam and making sure

25:39

we understand the intents and purposes in that

25:42

system that we're honoring what that was supposed

25:44

to use for Sam. Is of.

25:46

Also that's hard to government hard to make sure

25:48

that there's trace ability between the data that exists

25:50

up know that netted that around it and it's

25:52

original intent and whether we can use it for

25:54

these other thing, race and and then also thuggery

25:56

Now ah, how do you paint that picture for

25:58

people who want to leverage. How do you

26:00

hope and see a picture almost like a

26:03

Whole Foods or something? You're walking on a

26:05

shopping I'll and you look And to solve

26:07

the complex from hundred years Understand there's a

26:09

few more isles when it comes is I

26:11

still know people who think that every time

26:13

they need new data they have to update

26:15

their sources. Embrace field and I'm like will

26:17

hang on. You might have the data somewhere

26:19

else and there's just interoperability under finity Is

26:21

that than their up there are fewer interoperability?

26:24

The answer is this: This this challenge of

26:26

it's maturing quickly. There's amazing potential outcomes and

26:28

value. And the literacy pieces? So yeah. recall.

26:30

That I think that's a lot to juggle.

26:32

Yeah, and I think it's like. Trying

26:34

to have conversations as early as

26:37

you can because it. Was

26:40

given the nature public health be can sometimes

26:42

be reactionary and nature or with poll that

26:44

we had to be reaction rate as we

26:46

didn't know what it was and so we

26:48

were just reacting to the new same way

26:50

by it and principal Public Health is supposed

26:52

to be proactive population health? Yeah and so

26:54

that's something that I think translates ball into

26:57

any data products that you develop because I'm.

26:59

One. Solution is now is not one size

27:01

fits all right by a can be repeatable

27:04

so as just like as long as you

27:06

try to engage the data professionals or whatever

27:08

name you wanna get them as early as

27:11

you can in your process. Not a

27:13

try to dictate what goes on but just

27:15

say here is the art of the possible

27:17

yes and then talk through it and have

27:19

that all the stakeholders at the table

27:22

to say hey we will try to translate

27:24

as best we can and help you understand

27:26

some other engineering that is too complex really

27:28

time rank right. Out or Communicate and

27:30

a one line email by. We do

27:33

have that shared vision again to deliver

27:35

the most useful product to your team.

27:37

Yeah, When that com o two and

27:39

three for eating at this so. You're.

27:41

You're. An energy is

27:43

spent on data down and usefulness

27:46

effectiveness, governance, engagement day, Literacy. you

27:48

really can't do that without i t

27:51

that's really interesting to to realize like

27:53

those to have to marry system and

27:55

there are times where of the biggest

27:57

challenges data solution isn't the data it's

27:59

how it's interrupt or it's the IT side

28:01

where it's like we actually have to support each

28:03

other to reach these amazing outcomes. Is that something

28:05

you've experienced too? Yeah, and I think it was

28:07

a good test because like our ops

28:09

of data analytics was invented, well rebranded

28:11

I guess you could say during the

28:13

pandemic itself. Okay. But we

28:16

do have like an intimate working relationship with

28:18

our IT organization, whether it's internally

28:20

in our office of technology and cybersecurity

28:22

or even with just the state Indiana

28:24

office of technology. Right. And

28:27

a lot of it is just what they

28:29

bring to the table is that really technical

28:31

privacy security lens that we have to follow

28:33

and give us those good guardrails. But they

28:36

also give us the knowledge of, hey, this

28:38

is the current state of this information system

28:40

because they are the subject matter experts. And

28:44

I think the things that I thought

28:46

have been amazing partnership ideas is when

28:48

you talk about data quality, they know,

28:50

oh, we can't

28:52

change this yet because we have to

28:54

go, we might have to go through

28:57

an extra step to reach out to

28:59

a vendor to get the source system changed.

29:02

And so that's not necessarily like that. It's

29:04

not a solution. It just brings that extra

29:06

lens to show because

29:09

sometimes people think that I always like

29:11

to say like, we're not magicians, we're

29:13

data professionals. And so using

29:15

that literacy component is saying, hey, this

29:18

is everything that goes into this process.

29:21

So it can't just be like a light switch. Yeah.

29:25

I think that that's really important because I think a

29:27

lot of people will just try and run with their

29:29

data and they end up with a whole bunch of

29:31

technical that because they either left their IT department and

29:33

awake behind them and built a bunch of stuff that

29:35

they didn't know they'd have to support one day and

29:37

the IT department didn't know how. And

29:39

so there's this piece too of how

29:41

can you be the high side that raises all those. And

29:44

that really is this combo. And you've done, I think,

29:46

again, a great job sort of

29:48

speaking in harmony about the business

29:51

objectives, mission outcomes and

29:53

the data. The data should

29:55

be driven by the mission. But Then there's

29:57

this IT department too that is this core

29:59

foundation. How it's old, I'm actually I those

30:01

three are in some. Kind of acute triangle

30:04

and press somebody Stocking Lisa how critical

30:06

s and is to likes It also

30:08

focuses on because our success as an

30:10

agency of course is to improve the

30:13

populations health and try to make people

30:15

live as long as possible and as

30:17

fruitful as they can. Nights buy it.

30:20

At the same time there's a challenge is

30:22

that you go into because the products that

30:24

you build it may be requested by an

30:27

individual and then go away. So you try

30:29

to mitigate that as much as you can

30:31

be as. Especially now I'm

30:33

as modernization era and trying to

30:35

toggle interoperability. You really need to

30:38

just. Have purpose driven

30:40

data product rain and not just

30:42

oh, I need this analysis complete

30:44

now. Rather liked it because ad

30:46

hoc requests will never go away.

30:49

Kit it's building and those components

30:51

a collaboration that will continue to

30:53

sustain that product whether it is

30:55

a dashboard are some other procedure

30:58

yeah to be used holistically. Longtime.

31:00

Yeah you private in a situation to I think

31:02

about people who are drowning and data requests to

31:05

and they don't even understand why people are asking

31:07

half the when they're afraid and aim in a

31:09

private sector be like our board like if they

31:11

came in their ask questions and were wrestling to

31:13

get the data together. My first things I want.

31:16

To know as do should We already know

31:18

the answer. That's nice. Thing is that should we

31:20

be operating in managing our business and we were we

31:22

can we can rattle off that the answer to that

31:24

question or are they asking because it's a one time

31:26

thing and so I'm sure you guys have some of

31:28

that see were tape. What? Did it

31:30

to someone need? Why do they think they need

31:32

it? Is there a better way to get it

31:35

to them dirty? Help them with their own com

31:37

that that's that's you. Good data driven leadership access.

31:39

The request process is also key, occasion Mrs making

31:41

sure we actually understand each other around to do.

31:44

and we've talked about it in terms of

31:46

a change manage measures like you always have

31:48

to talk about the why yeah and for

31:51

mean by has always driven my professional career

31:53

because i've seen in public service because i

31:55

have that shared why rain and yard data

31:57

as the extra bonus that helps me stay

32:00

because it's an awesome thing

32:02

that lets us do innovative

32:04

projects in general. So

32:07

being able to start with why, I think there's

32:09

a book that I have on my desk that

32:11

starts with why. Maybe

32:14

that's been imprinted on my brain for a while,

32:16

but that is something that I pride

32:19

myself on doing. That's awesome. Also,

32:21

it made me laugh. The two times that you said,

32:23

this is your fourth stint, you

32:25

reminded me, very few people know this, but I

32:27

may or may not have been a cracker or

32:30

a waitress. Does that shock you? No. I would

32:32

always joke that I had three stars if I

32:34

had four, I was there for too long. So

32:37

that was my go-to joke when people would say, I'm going to get

32:39

you a fourth star. I was like, you can't really get me a

32:41

fourth star. It has to do with training. I haven't gone through. But

32:44

it made me laugh to think about, even when

32:46

we talk about imposter syndrome and some of the

32:48

things about how do you handle your

32:50

career when it's growing this quickly too and the

32:52

ability to just say, I love that I'm open,

32:54

I'm willing, we're going to try to help, I'm

32:57

tied to the mission. And it seems like the

32:59

team piece, you're very thoughtful. So Peter, I might

33:01

ask you about this. Yes.

33:03

You're very thoughtful. When you talk about team,

33:06

you're good about thinking about who's everyone that

33:08

needs to win. Did you

33:10

learn that through stepping in it someday

33:12

or have you always sort of been

33:15

oriented towards making sure you really appreciate

33:17

who's everyone on the team? That's

33:19

a great question because I think that is one

33:22

of the correlations that does transfer into

33:24

my personal life is I

33:27

used to tie my happiness to

33:29

others' opinions of me. Of course,

33:31

as every individual does, who is

33:34

an empathetic driven person. But

33:36

it morphed into just knowing that

33:38

you care about the success of

33:41

others. And yes, at times

33:43

I prioritize, I used to say I prioritize

33:45

my happiness with others' happiness. But

33:48

in the professional sphere, it's flipping

33:50

that mindset and saying, I am not

33:53

successful unless the people around me are

33:55

successful because I'm not being a good leader

33:57

if we're not delivering good products. I love

33:59

that. can get more promotion and promotion and

34:01

my focus on, oh, here are the wins.

34:03

But it's actually saying, am I

34:07

building up my team to take over for me if

34:09

I go away? And

34:11

I think that that is something that I

34:13

wish I wish you were a magician and

34:15

you could help everybody because I think that is 90% of problems

34:19

I see, right around data and tech are not

34:21

data. They're not tech. They're people problems. Exactly. And

34:23

if people understood that you were inherently on their

34:26

team, when we first started the project, I just

34:28

think a lot of those problems go away. It's

34:30

just really interesting. And that's how we

34:32

communicate it too, because like trying to

34:34

loop in literacy as like a theme

34:36

is some people are just very afraid

34:38

because they don't feel confident in their

34:40

skills. So just like, what can you

34:42

do to make sure that everyone

34:46

is on the same shared understanding. And

34:48

I think that helps projects because people

34:52

learn and communicate in much different ways. And

34:54

so you have to always be thinking of

34:56

the multiple different approaches that you have, even

34:59

if it is on the same project to have everyone

35:01

have that shared understanding. And I think, to

35:03

me, that is like what I pin success

35:05

on at times is because if like

35:09

our data and analytics team would get pulled in a

35:11

different priority, a programmer may have to support

35:14

this technology or vice versa. Right.

35:16

So if there's not that shared

35:19

understanding, then we're not successful again. Yeah.

35:21

Do you have like one piece of advice

35:23

on how somebody could quite

35:25

pragmatically take a step toward creating

35:28

that kind of a culture if they can, if

35:30

they self realize, we're not there?

35:32

Right. How do I take one practical

35:34

step toward that kind of culture or

35:36

dynamic? That's a great question.

35:39

For me, it's just

35:41

trying to find innovative

35:43

ways to have business

35:45

be exposed to technology and data

35:47

and analytics, and vice versa. So

35:49

a project that I thought was very successful

35:52

that I'll credit one of my

35:54

old co workers Courtney Lambert with and we called

35:56

it our pie in this guy project. Okay, we

35:58

worked with our infectious disease team. I

38:01

mean, that's basically a masterclass in how do you

38:03

help break down silos period. So that

38:05

I think it's so cool. Okay, maybe my last question, I

38:07

reserve the right to look at these. If

38:11

you had one wish, if they're

38:13

one of the magician, we both had that and they could

38:15

they could grant or I guess it would be a genie

38:17

one wish for you in in the state in public

38:20

sector and health and data, but

38:23

they only granted one, what wish would you ask for?

38:26

I would say like a friend's answer and just

38:28

be I'd have a million grant me unlimited wishes

38:30

after that so that I could solve all the

38:32

problems because I feel like I forget what it

38:34

was like. Oh, if I was a minute, but it for a day,

38:36

I'd be an imminent forever. But

38:39

for me, I

38:41

don't know. I think because I don't

38:43

think that there is that magic potion to

38:45

solve it. It's because it's a

38:47

person thing and people have these different

38:49

opinions. I think I

38:53

don't know. That's a great question. And

38:57

for me, it comes down to the people. So

38:59

it was just like, how can we unite

39:01

together? Yeah, that common cause. And

39:03

so maybe it is just that moment

39:05

that it has of instead of wanting

39:07

one solution, because you can have unlimited

39:09

funding and still make mistakes or have

39:11

a measly budget, but still figure out

39:14

how to work it. Yeah, just continue

39:16

to be blessed with a lot like

39:18

a team that sticks around forever and

39:20

has a good camaraderie because yeah, so

39:22

yeah, maybe I'll just say my wish

39:24

would be to have that good data

39:26

driven culture that makes everyone want to stay

39:28

and make each other better. Yeah, what I just heard was

39:30

you want peace on earth. Probably.

39:32

I mean, because like I like drama more than

39:34

anyone else. And of course, there's always going to

39:36

be conflict. But I

39:39

don't know at the heart of it, we all have

39:41

a shared mission. And that is to make

39:43

everyone else better. And so trying to I'm

39:45

always an advocate of this, like, yes, I

39:47

can get in ruts where I am very

39:49

pessimistic and don't think things are very optimistic.

39:52

But at the end of the day, inherently,

39:54

you want to see the good in others. And

39:56

even from a professional standpoint, I think with data

39:58

is just like. we want to get

40:01

the best outcomes we can and that starts with

40:03

using data as a strategic asset. Yeah. And then

40:05

the rest will hopefully come later, but then continuing

40:07

to build that culture of trust between everyone else.

40:09

You basically I mean, you

40:11

somehow you've avoided saying human

40:13

centric when this entire conversation,

40:15

right, your leadership style

40:18

is obviously very human centric. And

40:20

I just think it's genius because

40:22

if you it's hard to

40:24

convince people that that matters. But once they

40:26

do, it's like a superpower. Right. And so

40:28

it's just interesting to me to talk to

40:30

have a conversation with someone who's who's so

40:32

data savvy. And it still comes back to

40:34

us about the people, right? Every time it's

40:36

actually about the people. And I think that's

40:38

just something that luckily, I've had an

40:41

innate knack for that I've tried to

40:43

continue to sustain because I will admit

40:45

to anyone like I am a data

40:47

professional, but like I'm dangerous enough to

40:49

potentially make a mistake. And I think certain

40:52

individuals who are in the data

40:54

sphere struggle with potential leadership positions

40:56

because they get away from what they

40:59

want to do. Right. And I want to code

41:01

every day, I want to build a dashboard. And

41:03

that still is being a data leader. It's because

41:05

they're knowing their place and their limitations. And for

41:07

me, I think I had

41:09

to learn to feel confident with not doing that

41:11

regular basis or doing data work, if you can

41:14

say that on a regular basis and creating that

41:16

new data work, where it is

41:18

trying to be that people organizer that

41:20

relates to someone on a personal level.

41:24

Because I don't know, for me, maybe

41:26

it's just the generation that we grew

41:28

up in. But I try

41:30

to bring as much personality as I can

41:32

to the professional sphere to try to not

41:34

necessarily be the one be like, Oh, you

41:36

can wear jeans and sandals all day, you

41:38

don't have to wear a suit, right, but

41:40

trying to bring as much personal life as

41:42

you can, but still have that balance where

41:44

you can find that level of separation when

41:46

it comes to your boarding structure, at least.

41:49

But yeah,

41:51

I, I don't know, I like to

41:53

mitigate awkward cringy moments, even though we like to

41:55

talk about them. And so that's

41:57

just like, because I don't know, we used to

41:59

say like

44:00

I've cared for you now today, Peter, can

44:02

we get on? It's so inauthentic. And people

44:04

can tell, everyone can tell. The people who

44:07

are not great at people can tell that

44:09

it was inauthentic. And so that's hard too,

44:11

right? Well, because like, I think not

44:13

to knock anyone in the IT space, because

44:16

I'm in the IT space, you can be

44:18

a little bit more introverted. But introversion necessarily

44:20

doesn't mean that you're not a people person.

44:22

And so like flipping that label, but yeah,

44:24

it's moving away from okay, we had an

44:26

icebreaker too. That's good. Okay, everyone. Let's have

44:28

it in the introduction. Like I love them,

44:30

I will try to come up with icebreakers

44:32

myself. But like, that's not the only thing

44:34

that can make a meeting personable. Right.

44:36

Do you have, I'm sorry to put you on the spot.

44:38

I'm just curious. Do you have like one more leave? It's

44:41

not an icebreaker with something else someone can do to

44:43

make their meeting more personable. So the things that

44:45

I do is always around music just because I

44:47

don't know. You're super into music? Well, I am

44:49

in terms of I just have a knack of

44:51

like always having a song. Okay. And so something

44:54

that I thought was super successful that I'm trying

44:56

to do, it just takes a lot of legwork

44:58

to organize is when you have

45:00

these breakout groups, whether you're in a collaborative meeting,

45:02

you have everyone go away while you're waiting to

45:05

be assigned to a group, then you have a

45:07

song that plays. And then you

45:09

have to vote on what the song title and

45:11

artist is. So just like, that's cool. Like,

45:13

oh, so one of the themes that I

45:15

think I did, like female artists from each

45:17

decade from the 70s to 2010, I just

45:20

had people vote. They got

45:22

like candy at the end, they won so creative, but

45:24

it's just something that's small because it injects a little

45:26

bit of me and what my passions are to try

45:28

to share those with others. I am

45:30

so excited and thankful you're here today because I

45:32

think that this is a very different unique

45:35

take on the podcast where we've talked

45:37

about some of the concrete stuff. People

45:39

are used to governance and strategy and

45:41

team Unitedness, but there's so much more

45:43

of an emphasis on this human

45:46

centered leadership of data that I

45:48

think is actually the special sauce.

45:50

Right. I can build a zillion technical solutions,

45:52

but no one, I mean, one of the

45:54

things I say is, I mean,

45:56

Peter, you've been the person that no matter what

45:58

results it has built. You're

46:01

the person in the agency that's so passionate about

46:03

putting it to use. And I'm like otherwise that

46:05

could sit on shelves and it wouldn't be valuable.

46:07

It would be potentially valuable. So I

46:09

get excited that you walked us through a whole bunch of

46:11

specials last day so thank you. And

46:14

the work member goes away. No, I didn't. But the

46:16

people change and I think that's why the biggest change

46:18

is people. Absolutely. So if we can get that good

46:20

camaraderie even if you have a lot of turnover or

46:22

whatnot. Then you have a culture that people jump in and they

46:24

kind of get it. Yeah. And you'll

46:27

want to recruit new talent and be like, yes, I want to work for the Department

46:29

of Health. I want to be in public service

46:31

longer. It is truly a

46:33

genius move. I love it. Well played both

46:35

because it's sincere but also because it is

46:38

a smart strategy. It's both of those things. I hope

46:40

so. Thank

46:45

you for listening. I'm your host Jess Carter.

46:47

And don't forget to follow the Data Driven

46:49

Leadership wherever you get your podcasts. Rate and

46:51

review letting us know how these data topics

46:54

are transforming your business. We can't wait for you

46:56

to join us on the next episode. Thank

46:59

you.