0:00

It's very important that at

0:02

a time when we're going

0:04

to be driving real productivity

0:06

across so many different industries

0:09

that we don't lose sight

0:11

of the fact that, you

0:13

know, the customer experience can't

0:16

be, you know, forgotten about.

0:18

It has to be actually

0:20

at the forefront of ensuring

0:23

that this technology makes

0:25

the experience better, not

0:27

just cheaper faster. Ryan is

0:29

the Senior Vice President and Chief

0:32

Information Officer of Thermo Fisher Scientific,

0:34

a roughly $40 billion revenue company

0:36

that's a world leader in servicing science.

0:38

Ryan has been with the company for

0:40

11 years since it acquired his prior

0:43

company, Life Technologies. He's been the

0:45

Chief Information Officer since 2019. Ryan is

0:47

a big believer of weaving tech and

0:49

digital strategy into the business strategy

0:51

and as such sharing ownership of

0:54

topics like data and analytics and

0:56

artificial intelligence. having spent a meaningful

0:58

chunk of his career at GE, he's

1:00

also a process expert who thinks deeply

1:03

about the broader implications of trends before

1:05

acting on them. I look forward to

1:07

hearing more about the direction he's

1:09

pointing his department and his company

1:11

through this conversation. Ryan, welcome to

1:13

Technivation. It's great to speak with you today.

1:15

Great to be here, Peter. Hey, Ryan, I

1:17

thought we'd begin with Thermo Fisher Scientific, your

1:20

company. We thought you might be able to

1:22

take a moment and provide an overview as to

1:24

the business you're in. Yeah, so Thermo Fisher

1:26

Scientific. We are the world leader in

1:28

serving science, right? That's the core of

1:30

what we do. It's just north of

1:32

$40 billion in revenue. It's a

1:34

global company. It's a great mission,

1:36

right? It's one that I love, and it's one

1:39

that I think when you think about

1:41

a lot of people who join our

1:43

organization, they tend to want to stay

1:45

here. Our mission is we enable our

1:47

customers to make the world healthier,

1:50

cleaner, and safer. So we really

1:52

lean into that enablement aspect of

1:54

it. our customer success is

1:56

our success. So we're a

1:58

supplier of products. services

2:00

really for the entirety of

2:02

the life sciences industry. So

2:04

think about large pharma, biotech,

2:06

government, academia, anybody trying to

2:09

further science is a consumer

2:11

of our tools and services.

2:13

That's a great background. I appreciate

2:15

you sharing that. It's an

2:17

interesting mission as you point

2:19

out. Talk a bit about your background

2:22

and role, your purview is chief

2:24

information officer, if you would. Yeah,

2:27

so I've been with the organization

2:29

for I just passed my 20

2:31

year anniversary. So that was exciting.

2:33

That was in November this past

2:35

year. I've been the chief information

2:37

officer of the organization since

2:40

2019. So a fair amount of

2:42

time now to to steward the

2:44

technology decisions for the organization. It's

2:46

it's been a great journey. I've

2:49

worked in a number of the

2:51

different business units within the organization

2:53

leading up to this role and

2:55

I've moved around quite a bit, but

2:57

I have found my home here in, well,

2:59

cold Boston, Massachusetts as it

3:02

stands right now standing here

3:04

at February. And can you

3:06

describe a bit more about kind of

3:08

what's within your purview, how you, what

3:10

the role entails? Absolutely.

3:13

So it's a large organization, right? And

3:15

so given the, you know, the

3:17

diversity of all the things that

3:19

we do end to end, the

3:21

business is structured in a way

3:23

where... It all works together, so

3:25

certainly there's a method to bringing

3:27

all these different businesses that we've

3:29

acquired over the years together. But

3:31

there's a lot of very strong,

3:34

I'll say, relatively independent P&L, so

3:36

we're a division-led organization. And so

3:38

the way my organization has

3:40

evolved and has been structured is we

3:43

have very strong IT leaders that

3:45

sit in our partners with each

3:47

of the different general managers across

3:49

the organization. So... That has been

3:51

a real staple of really being

3:54

connected in with our business partners.

3:56

And then at the corporate level,

3:58

some things you might expect. where

4:00

we have infrastructure, cybersecurity, enterprise applications,

4:02

our global digital commerce team, as

4:04

well as more recently, we've brought

4:07

together our automation, our AI, and

4:09

our data teams together under one

4:11

leader to be a shared service

4:13

for all of our divisions trying

4:16

to advance our digital technologies, including.

4:18

software throughout our products and service

4:20

capabilities. So it's been, it's been

4:22

a fun evolution. It's one that

4:25

never stops changing, right? I often

4:27

describe our function as it's a

4:29

function in motion, right? It just

4:31

doesn't stand still. Yeah, and I

4:34

know from our past conversations, Ryan,

4:36

that you're a big believer that

4:38

technology and business strategy have to

4:40

be woven together. Talk a bit

4:43

about that insight and the way

4:45

in which that's that's realized in

4:47

an organization like yours. Yeah I

4:49

think it's one where you constantly

4:52

have to monitor this right because

4:54

on one end if the function

4:56

takes too much ownership of the

4:58

technology you end up with a

5:01

result where a lot of the

5:03

technology advancements become little science experiments

5:05

off in a back corner, right,

5:07

where it becomes kind of an

5:10

IT thing, and it's separate from

5:12

actually the core of what your

5:14

business is sitting around the table

5:16

talking about trying to solve customer

5:19

problems. But on the reverse, of

5:21

course, as you end up with,

5:23

you know, the proverbial shadow IT

5:25

where all of it essentially is

5:28

now being driven and inside of

5:30

the business with no real stakeholder

5:32

alignment to... the function. So what

5:34

we try to do is structurally

5:37

we have, you know, parts of

5:39

our organization that really sit at

5:41

every part of that, right, whether

5:43

it's the people in IT who

5:45

are directly sitting inside of the

5:48

business and sitting around the table

5:50

talking about strategies to the teams

5:52

that are more, I'll say, enablers

5:54

on the back end. who are

5:57

kind of looking for efficiencies and

5:59

trying to drive, you know, scale

6:01

when we deploy technology across the

6:03

organization. So I think it is

6:06

important that you have kind of

6:08

leaders who understand how to do

6:10

both of those different pieces of

6:12

it. And that's, you know, that's

6:15

where I think the magic can

6:17

happen, so to speak, when the

6:19

deployments really drive benefit for the

6:21

company. That's fantastic. And you

6:24

noted the extent to which you

6:26

have leaders who are embedded with

6:28

the general managers of each of

6:30

the businesses themselves and no doubt

6:32

that facilitates it as well. It

6:34

sounds like you correct me if

6:37

I'm wrong. Does that mean they

6:39

have sort of a foot in

6:41

each of those businesses as well

6:43

as a foot in IT and

6:45

offer sort of translation and advice

6:47

and in both directions along the

6:49

way? Yeah, it can be a

6:51

bit of a time overhead, right,

6:54

because oftentimes those individuals have to

6:56

sit on two staffs, right? So

6:58

you're, you're supporting both a business

7:00

strategy as well as aligning up

7:02

to technology strategy through my office.

7:04

But that is the model and,

7:06

you know, by and large it

7:08

works, I think, you know, and

7:11

we try to rotate people throughout

7:13

the organization as much as we

7:15

can without being disruptive, because I

7:17

do think the diversity of thinking,

7:19

as, you know, as you can

7:21

get ultimately is is also critical

7:23

when you're thinking about how do

7:25

you solve problems at these different

7:28

points of the scientific workflow, as

7:30

well as just the diversity of

7:32

being a back office IT person

7:34

versus being somebody who's more embedded

7:36

with the business. I think getting

7:38

the empathy on both sides of

7:40

those struggles is also, you know,

7:42

really paramount is where I see

7:45

it breakdown is you get divisions

7:47

between those two parts of the

7:49

organization and they stop working. really

7:51

hand in hand and you know

7:53

in efficiency groups and yeah that's

7:55

interesting. I know that your your

7:57

thought process about the necessity for

7:59

technology and the rest of the

8:02

organization to be woven together also

8:04

provide some interesting insights into how

8:06

you think about data that many

8:08

believe this to be a tech-led

8:10

owned subject. And I'd love to

8:12

have you talk a bit about

8:14

the way in which you think

8:16

about this a little bit differently.

8:19

You know, at the end of

8:21

the day, right, we're in the

8:23

middle of a true incredible opportunity

8:25

with artificial intelligence and the technologies

8:27

moving quickly, right? It's got from

8:29

hardware to software. in the manner

8:31

of just a year. But at

8:33

the core of that underneath it

8:36

all is your data, right? And

8:38

I think every single organization is

8:40

waking up to the fact that

8:42

it's going to be very important

8:44

for them to understand what data

8:46

do they have, what data don't

8:48

they have, and where's the value

8:50

in that data in terms of

8:52

driving a competitive advantage or potentially

8:55

creating new native solutions with technology

8:57

to support their customer base. And

8:59

so that idea of. really understanding

9:01

contextually of what good data means,

9:03

right? And I think that's the,

9:05

I'll say the mistake that can

9:07

happen is, you know, somebody essentially

9:09

says, IT, go clean up that

9:12

data. Many times the IT organization

9:14

really isn't the right team to

9:16

really have a clear understanding contextually

9:18

of what good data means, right?

9:20

And so it's that partnership. and

9:22

creating organizational data points for the

9:24

organization. I think having to think

9:26

about data as product, you're going

9:29

to need people actually that are

9:31

real experts, subject matter experts on

9:33

the business utility. And then you

9:35

need the architects and the subject

9:37

matter experts around, you know, what

9:39

does clean data really look like

9:41

and how do we advance getting,

9:43

you know, inquiring additional data points

9:46

for the organization. I think having

9:48

that construct set up in a

9:50

way where both the business and

9:52

the technology functions feel like they

9:54

have joint ownership of things to

9:56

me is is incredibly important. You

9:58

know. And again, it's one of

10:00

those things where you never get

10:03

it exactly right, but you know

10:05

when it's not working and you

10:07

just have to put the monitors

10:09

in place to make sure that

10:11

you're stepping in and constantly, you

10:13

know, shepherding that as a leader.

10:15

Yeah, well said, very interesting. I

10:17

love that perspective and ensuring that

10:20

there is that that partnership and

10:22

everyone is weighing in an essence,

10:24

as opposed to it being more

10:26

siloed within one organization. You mentioned

10:28

as you were talking about your...

10:30

your purview and your team that

10:32

you have brought together automation, AI,

10:34

and data all under one leader

10:37

and offered it as a shared

10:39

service for the rest of the

10:41

organization. Very interesting. I wanted to

10:43

double click on that point a

10:45

little bit further, especially now that

10:47

we've approached the topic of both

10:49

data and artificial intelligence. Talk a

10:51

bit about the rationale between bringing

10:54

the three of those together. Yeah,

10:56

Peter, we saw the opportunity, which,

10:58

by the way, everybody did, that

11:00

generative AI is going to be

11:02

truly a transformational, to use one

11:04

of the most overused words, technology.

11:07

But if you kind of look

11:09

in your rear v mirror, we've

11:11

been having a lot of these

11:13

transformational technologies come and sometimes stay

11:15

and sometimes go. So the way

11:17

that I thought about it was,

11:19

it's important that when you create

11:21

an organization that if you're a

11:23

general manager and you're looking to

11:25

drive real value through digital throughout

11:27

your organization, you don't want one

11:29

tool constantly at the forefront being

11:31

kind of advocated for, so to

11:33

speak, to say, you know, I

11:35

don't know what the problem is,

11:37

but I'm pretty sure the solution

11:39

is going to be X, right?

11:41

And I feel like right now

11:43

you could run into that danger

11:45

when it comes to generative AI.

11:47

And so the way we viewed

11:49

it was a cocktail of generative

11:51

AI. more traditional AI and machine

11:53

learning, all of it underpinned by

11:55

data, as well as some of

11:57

the capabilities. that have come about

11:59

in the last five, 10 years

12:01

or so around automation. If you

12:03

bring all of that together, it

12:05

will create an organizational construct where

12:07

I feel like the individuals that

12:09

come out of that team have

12:11

the opportunity to pick the right

12:13

tool to fix the problem or

12:15

drive a process improvement or what

12:17

have you that the business needs

12:19

versus kind of coming in and

12:22

if you will, more in an

12:24

advocacy role. So that's. That's the

12:26

concern. So if you will, it's

12:28

the old pick the right tool

12:30

to solve the problem and, you

12:32

know, the solution comes about much

12:34

faster. Yeah, keen insight and again,

12:36

really interesting to hear how you

12:38

think about that and then assess

12:40

you to ensure that not a

12:42

single tool is offered. With regard

12:44

to artificial intelligence, you've mentioned to

12:46

me in the past that you

12:48

have a three pillar approach to

12:50

this and I wondered if you

12:52

could maybe highlight those three pillars

12:54

and with a description as to

12:56

each of them as well. Yeah,

12:59

I wouldn't say they're mine. I'd

13:01

say they're the companies from our

13:03

CEO all the way through that

13:05

the company leadership team, the way

13:07

we've advanced the thinking for thermal

13:09

Fisher is, as you mentioned, there's

13:11

three real opportunities, right? So one

13:14

is, I would say, to make

13:16

the company run better. There's a

13:18

lot of exciting, you know, deployments

13:20

that are already taking place in

13:22

terms of finding efficiencies, you know,

13:24

the the opportunity with AI to

13:26

kind of summarize documents as well

13:28

as find information faster to create

13:30

kind of the assistant along the

13:32

way to make all of us

13:35

more productive day to day. How

13:37

do you bring that from an

13:39

individual all the way through and

13:41

scale that across the organization? It's

13:43

certainly an exciting opportunity to make

13:45

our company and frankly, probably every

13:47

company wants to to deploy this

13:49

to make themselves run more efficiently.

13:51

We also look at two other

13:53

lenses. One is around the actual

13:56

products and services we bring forward.

13:58

So we think about the products.

14:00

that we've had for years that

14:02

have been used by scientists in

14:04

their labs. You know, increasingly, it's

14:06

not just the hardware, it's software

14:08

and firmware that runs on those

14:10

machines. And if you look at

14:12

the opportunity that AI presents, it's

14:14

super exciting to advance for an

14:17

activity needs that our customers are

14:19

looking for. And then on the

14:21

service side, you know, likewise, we

14:23

offer clinical trial services as well

14:25

as manufacturing services. So tremendous opportunities

14:27

to. reduce the amount of time

14:29

that those services ultimately take to

14:31

get the customers to the answers

14:33

they need faster, which is, you

14:35

know, at the end of the

14:38

day, what they're looking to do.

14:40

And then finally is, and perhaps

14:42

the one I'm most excited about

14:44

is the customer experience, right? And

14:46

I feel like it's very important

14:48

that at a time when we're

14:50

going to be driving real productivity

14:52

across so many different industries that

14:54

we don't lose sight of the

14:56

fact that You know, the customer

14:58

experience can't be, you know, forgotten

15:01

about. It has to be actually

15:03

at the forefront of ensuring that

15:05

this technology makes the experience better,

15:07

not just cheaper faster. You know,

15:09

so we're very focused on that

15:11

when we think about how our

15:13

customers interact with a company like

15:15

Thermo Fisher. I love that point.

15:17

I would love to maybe go

15:19

explore that a little bit further

15:22

as well. Yeah, I love the

15:24

insight that, you know, as companies

15:26

focus on making the company run

15:28

better, they may make choices that

15:30

impede progress from an employee experience,

15:32

but also customer experience perspective. What

15:34

are some of the ways in

15:36

which you ensure that that isn't

15:38

lost beyond just recognizing it, which

15:40

is the first step? How do

15:43

you engage the employee base and

15:45

customer base in ways to ensure

15:47

that? their experiences are factored in.

15:49

It really is about governance. You

15:51

know, and that's, that's. something that

15:53

people say and sometimes they set

15:55

it up, but you really have

15:57

to ensure that governance is at

15:59

the core fabric of how you're

16:01

actually deploying a technology strategy. And

16:04

so what do I mean by

16:06

that? You know, it's the healthy

16:08

tension of you're trying to democratize

16:10

the technology so that everybody can

16:12

use it and go fast. But

16:14

there's a couple elements of governance

16:16

that we put in, which is,

16:18

you know, we're looking at what

16:20

are the high impact areas with

16:22

which we're deploying it. And at

16:25

the leadership level is we're making

16:27

sure that these things don't go

16:29

off in a siloed fashion, so

16:31

that for the over 120,000 colleagues

16:33

that work in our company, if

16:35

I think about internally, you know,

16:37

does that experience come together, right?

16:39

Versus, you know, it looking like

16:41

a hodgepodge of a bunch of

16:43

different tools and processes that are

16:46

difficult to navigate, right? The last

16:48

thing people need is more choice

16:50

and kind of another thing to

16:52

remember. And so having that governance,

16:54

I think makes sense. internally, the

16:56

thing about colleague experience. And then

16:58

likewise, when we think about the

17:00

experience for our customers, right, we

17:02

often talk about the total company

17:04

value proposition that Thermo Fisher creates

17:06

to be that trusted partner end

17:09

to end innovation and productivity that

17:11

we can drive for them. And

17:13

we have amazing people in our

17:15

organization who wake up and think

17:17

about that every day. So part

17:19

of my role is I think

17:21

about how do I tether together

17:23

the digital strategy that we're deploying

17:25

from an innovation perspective to really

17:27

be in lockstep with the strategy

17:30

that our people are talking about

17:32

and bringing to our customers on

17:34

a day-to-day basis. And then the

17:36

underpinning of all that is responsible

17:38

AI, right, is ensuring that every

17:40

step that you take through both

17:42

governance as well as tools that

17:44

are actually there's a lot of

17:46

exciting tools that are advancing around

17:48

the ability to make sure that

17:51

you're using it responsibly and ethically

17:53

and kind of aligned if you

17:55

will at the end of of

17:57

the day to the company's value.

17:59

So that's a lot of work,

18:01

right? And I think sometimes it's

18:03

the healthy tension of you want

18:05

to go fast, but it's super

18:07

important from my perspective to make

18:09

sure that you're putting in those

18:12

guardrails and that it's a very

18:14

cross-functional team that is kind of

18:16

overseeing that so that everybody feels

18:18

an ownership stake in this, right?

18:20

And I think that at the

18:22

end of the day is how

18:24

we think about it. Can

18:27

you talk about some of the

18:29

use cases leveraging AI that excites

18:31

you most? Yeah, so, you know,

18:33

I think about our services, certainly

18:35

the clinical trial space is one

18:37

where there's just a tremendous amount

18:39

of industry excitement, whether it's, you

18:41

know, trying to find the right

18:43

patients to be part of a

18:45

clinical trial, the amount of documentation

18:47

and summarization that can benefit from

18:49

it to how you can actually

18:51

service. the patients through that process,

18:53

there's a tremendous amount of focus

18:56

and excitement at Thermo Fisher, where

18:58

how can we lead in partnership

19:00

with our customers on that journey?

19:02

And, you know, that is a

19:04

huge amount of time when you

19:06

think about the overall time and

19:08

energy and cost to bring a

19:10

drug to market, the clinical trial

19:12

space is certainly top of mind

19:14

for us, internally, you know, I'm

19:16

very excited, well, selfishly about software,

19:18

you know, just like. Simple things

19:20

like what software developer likes to

19:22

document their code? The answer is

19:24

none of them. And so what

19:26

a great way to quickly advance

19:29

better code, better documentation. You take

19:31

some of your more junior software

19:33

developers and instantly make them a

19:35

lot better. So some of those

19:37

advancements we see whether it's software

19:39

developers, marketeers, people working with the

19:41

call centers. It's this idea of

19:43

how can you underpin. what they

19:45

do every day, but actually make

19:47

them better. So that's the way

19:49

we think about it internally. And

19:51

then, you know, as far as

19:53

the customer experience goes, you know,

19:55

one of the ones we're excited

19:57

about that we're piloting is bringing

19:59

AI onto our websites, right? How

20:02

do you help the customers find

20:04

the products faster, right? Or if

20:06

they have, you know, you're on

20:08

that product page and you have

20:10

a question, you know, we've implemented

20:12

tools where they can chat essentially

20:14

with the product itself, to ask

20:16

questions about maybe use cases or

20:18

how do I use this product.

20:20

You know, and that would typically

20:22

either be something they couldn't get

20:24

an answer to or they'd have

20:26

to call maybe their sales rep

20:28

or a customer service agent. Now

20:30

they can get those answers directly

20:32

online when they're deciding whether or

20:35

not to buy the product. I

20:37

mean, it's just it's incredible to

20:39

think about the number of use

20:41

cases. So I think actually the

20:43

biggest thing is how do you

20:45

make sure that you're focused right

20:47

on a handful so that you

20:49

can make the biggest impact and

20:51

go fast. So there's there's a

20:53

discipline element there too. I

20:56

think great examples, thank you for

20:58

sharing those. And obviously in many cases

21:00

what we're talking about is innovations

21:02

that your team are helping to drive.

21:05

And on the topic of innovation,

21:07

I recall a conversation you and I

21:09

had a while back where you

21:11

talked about the importance of empathy in

21:13

innovation. And I thought that was

21:15

an interesting framing. I'd love to have

21:18

you explain it for our audience,

21:20

why empathy is such an important aspect

21:22

to innovation. Yeah, for

21:24

me, it's it's it's central to

21:26

how I lead, you know, and

21:28

it's it's been a It's been

21:30

a refrain that I constantly remind

21:33

myself as well as my team

21:35

on how to be an effective

21:37

function Which is at the end

21:39

of the day, we're here to

21:41

serve the business and make the

21:43

business go in directions that, you

21:45

know, benefit business, our customers, our

21:47

shareholders, you can't lose sight of

21:49

that Sometimes functions can get so

21:51

wrapped up in making the perfect

21:54

function that they lose sight of

21:56

the fact that they're there to

21:58

serve the business. So it starts

22:00

with, you know, your purpose. And

22:02

when I look at my colleagues

22:04

who have to lead these incredibly

22:06

complicated businesses and solve problems every

22:08

day for their customers, they don't

22:10

often have time in the day

22:12

or the mind share to become

22:15

experts on all of these different

22:17

technologies that are coming. So I

22:19

always make sure that when I'm

22:21

communicating with my teams on, hey,

22:23

what makes a great IT partner?

22:25

It starts with empathy. Think about

22:27

and meet your business partner where

22:29

they are, right? So you may

22:31

have some who, by the way,

22:33

they may wake up every day

22:36

and think about technology because that

22:38

could be core to how they

22:40

run their business, which is great.

22:42

So meet them where they are.

22:44

And you may have another individual

22:46

who is leading a very complicated,

22:48

you know, scientific business, but that

22:50

isn't what they wake up and

22:52

think about every day. And so

22:54

meet them where they are, right?

22:57

And work with them from. whatever

22:59

level they are to figure out

23:01

how to improve their business. And

23:03

again, deploy the right degree of

23:05

technology to make their business better.

23:07

And so that's how we school,

23:09

if you will, and teach our

23:11

functional leaders on how to manage

23:13

within their organization. You know, start

23:15

with what the customer wants, then

23:18

work your way back to what

23:20

is the business trying to accomplish,

23:22

then develop empathy on how you

23:24

need to actually help your customer.

23:26

In this case, it could be

23:28

an internal customer on how to

23:30

develop a good technology underpin strategy.

23:32

Yeah, keen insight. I love that

23:34

approach and certainly a thread pulled

23:36

through the conversation more generally in

23:38

terms of the necessity to, you

23:41

know, know your colleagues, know your

23:43

customers well enough to understand what

23:45

it is that they need and

23:47

then deliver what they need to

23:49

them. I wanted to ask you

23:51

also as you look to the

23:53

future Ryan. What trends excite you

23:55

beyond some of the ones that

23:57

we've already noted anything additional ones

23:59

that you would underscore? Yeah, listen,

24:02

I think, um, you know, having

24:04

Talk to a lot of industry

24:06

leaders. One of the insights that

24:08

I've received is the mistake that

24:10

enterprise IT often makes when you

24:12

have a situation like what we're

24:14

dealing with around artificial intelligence is

24:16

the technology is moving so fast

24:18

that what you're deploying is tomorrow's

24:20

legacy today. And you have to

24:23

really make sure that you're thinking

24:25

about where the technology is going,

24:27

so that as you're deploying things,

24:29

you're doing it in a nimble

24:31

enough way to take advantage of,

24:33

you know, where this technology is

24:35

going, not being so fixated on

24:37

where the technology is today. And

24:39

so, you know, a few examples

24:41

of that I think about is,

24:44

you know, a lot of us,

24:46

you know, got familiar with Open AIs

24:48

ChatGPT platform and began to experiment right

24:50

away with prompting. And, you know, how

24:52

do we kind of take documentation and

24:55

summerization and all the great things that

24:57

it could do? But clearly, it was

24:59

going to go multimodal and now we're

25:01

there, right? And so I'm excited about

25:04

those opportunities where you start to think

25:06

about video speech are all just really

25:08

outputs, no different than text. So we

25:10

have to kind of unbox our thinking

25:13

when it comes to where is the

25:15

technology going? when we're conceiving of solutions

25:17

and helping those general managers and business

25:20

leaders on what could be. And just

25:22

more recently, when I think about chain

25:24

of thought and reasoning in terms of

25:26

how the language models are really going

25:29

to start to solve problems and break

25:31

them down into smaller increments, it just

25:33

opens up an unbelievable amount of opportunities

25:35

in terms of the types of problems

25:38

that you can bring the technology to.

25:40

Again, I'd be remiss if I didn't

25:42

say you have to obviously underpin your

25:44

responsible AI framework underneath all of that.

25:47

So you have to be sure that

25:49

you don't bring things into production that

25:51

aren't ready. Right. But at the same

25:54

time you have to have those experiments

25:56

going so that as the technology matures,

25:58

you brought the company and our business

26:00

leaders along with you. Right. And I

26:03

think that's something that when I look

26:05

at the trends and when I get

26:07

excited about these these areas, it's how

26:09

do I make sure that you don't

26:12

wait all the way until it's matured

26:14

to begin to have and engage our

26:16

business in those opportunities? You got to

26:18

bring them along. you got to bring

26:21

them along the way and there's a

26:23

big element of what we call literacy

26:25

and change management controls that we're working

26:27

with our company on as well to

26:30

make sure that people are preparing themselves

26:32

for, hey, wow, you know, the work

26:34

that you used to do this way

26:37

and maybe the same way the last

26:39

25 years is going to fundamentally change.

26:41

So how do you bring them along

26:43

when you're talking about these trends? Some

26:46

of them are just kind of hard

26:48

to believe quite frankly when you look

26:50

at it on the surface and it

26:52

may not manifest in the way the

26:55

tools are marketed to you today. Those

26:57

trends are certainly here and it's clearly

26:59

where the R&D and the industry is

27:01

going and so you may as well

27:04

start to plan for what's coming versus

27:06

just what's here now today. It's such

27:08

a keen answer Ryan, I appreciate that

27:11

and it brings to mind. My hypothesis

27:13

anyway for you to let me know

27:15

whether I've got right or not. Six

27:17

years enrolled, 20 years with the company,

27:20

you've had a long-term perspective as to

27:22

technology and its use within your organization

27:24

different from colleagues of peers of yours

27:26

who, you know, spend two years here,

27:29

three years there, four years here, two

27:31

years there in different organizations in each

27:33

of these cases, you've had a chance

27:35

to introduce the state of the art,

27:38

see it advanced, and actually see it

27:40

erode to the point where it needs

27:42

to be retired within your setting. And

27:44

counseled your organization on that very point.

27:47

It strikes me their advantages, not that

27:49

you have a second career that you

27:51

can compare to, where in fact you

27:54

did jump around from role to role

27:56

across companies, but it strikes me as

27:58

a great advantage that you have for

28:00

the way in which your company has

28:03

on, excuse me, your career has unfolded

28:05

to provide this sort of longer term

28:07

perspective that I'm hearing in the way

28:09

you just responded to my question. Is

28:12

that fair? Yeah, I think it's really.

28:14

The credit goes to, I think, how

28:16

the company is operationalized, right? Which is,

28:18

it is a relentlessly customer focused organization.

28:21

So we like to think that we

28:23

have an incredible amount of discipline on

28:25

how we deploy our capital, and that's

28:27

been proven over and over with our

28:30

shareholders. And our IT organization is no

28:32

different, right? So when we look to

28:34

deploy our strategies and when we build

28:37

our budgets and when we build our

28:39

budgets and our It really is one

28:41

where in lockstep with our finance partners,

28:43

with our process leaders, with our strategy

28:46

organization, we try to ensure that really

28:48

every dollar that we spend is truly

28:50

aligned to a customer need. And that

28:52

is both short term as well as

28:55

long term, right? So sometimes you got

28:57

to make short term sacrifices, but we're

28:59

never afraid to look at, you know,

29:01

what are those long term investments that

29:04

we have to make. You know, increasingly

29:06

we spend. 1.3 billion dollars per year

29:08

in R&D, which is an industry leader,

29:11

and increasingly more and more of that

29:13

is actually technology driven from a software

29:15

perspective. And so, you know, the opportunity

29:17

for our organization to help shape that

29:20

in terms of benefiting customers, as well

29:22

as obviously the things that you traditionally

29:24

do in an IT organization to support

29:26

your colleagues, right? We have 120,000 plus

29:29

those that we support every single day.

29:31

But I think it's it really is

29:33

just never losing sight of you're not

29:35

here to just deploy technology. And as

29:38

much as many people in my organization,

29:40

that's what they wake up and think

29:42

about and love, quite frankly, you know,

29:44

I always say never fall in love

29:47

with the technology because what you deployed

29:49

may at some point be a legacy

29:51

and you got to have the courage

29:54

to take it down and start all

29:56

over if it isn't the benefit of

29:58

furthering the business. And sometimes, by the

30:00

way, old technology works great. If you

30:03

have a part of the business that's

30:05

working fine and It's accomplishing what it

30:07

needs. You know, you don't need to

30:09

just keep upgrading for upgrade sake and

30:12

deploying new technology because it's newer. It

30:14

really is just staying disciplined on when

30:16

and why you actually need to deploy

30:18

other resources of function. I wanted to

30:21

ask you as we close your Ryan.

30:23

Anything you've recently under your voracious reader,

30:25

for example. either you've recently read or

30:28

watched or listened to as the case

30:30

may be that you'd recommend to this

30:32

audience? I do try to consume as

30:34

much as I can because it is

30:37

a fast-moving area, whether it's books, podcasts,

30:39

I try to alternate between somewhat heavy

30:41

books and maybe something lighter so that

30:43

I don't totally lose my mind. But

30:46

when I think about AI and some

30:48

of the opportunities that are coming, I

30:50

think it's important to have a future

30:52

back view, right? And so one of

30:55

my favorite futurists is Ray Kurzweil. who

30:57

just wrote the singularity is nearer. What

30:59

I liked about the book in particular

31:01

was, you know, it's one version of

31:04

what could happen, but he touches on

31:06

so many important aspects of where the

31:08

advancements of the technology are going, the

31:11

impacts to the human race, right, all

31:13

the ethics that we have to ensure

31:15

that we're instilling along the way. And

31:17

it just seems like as a conversation,

31:20

that is very, very important for everybody

31:22

to be engaged in. And so I

31:24

love to kind of hear how some

31:26

people paint the picture of the future

31:29

and it just helps shape my thinking

31:31

to help guide in my role as

31:33

a leader in my organization. So that's

31:35

that. That's certainly one

31:38

one I would recommend. thank

31:40

you for that. that. And

31:42

thank you more

31:45

generally more a phenomenal

31:47

conversation. conversation. It's understand further

31:49

the areas that

31:51

you and the team

31:54

are focused on, the

31:56

team the way in

31:58

which you are

32:00

leading the organization, some

32:03

of the counterintuitive

32:05

but really powerful insights

32:07

that you've had had

32:09

that have really shaped

32:12

the way in

32:14

which you lead as

32:16

well. well. been been

32:18

to to with you

32:21

today. you today. Well, thanks,

32:23

Peter. I enjoyed it.

32:26

it.