0:00

We pride ourselves in leading in flavor

0:02

and predicting future flavor forecasts. And so

0:04

for us to be effective and continue

0:06

to be a leader in the market,

0:09

we pride our best to predict what's

0:11

coming, then bring those flavors into our

0:13

products and then serve consumers with those

0:16

flavors. Welcome to Technivation. I'm your host

0:18

Peter High. My guest today is Guy

0:20

Perry. Guy is the Chief Information and

0:23

Digital Officer of McCormick & Company, a

0:25

135-year-old organization that's a leader in flavor

0:27

and flavor. and earns $6.7 billion in

0:29

annual revenue. Guy's been in roll for

0:32

about six months. He's led a

0:34

remarkable digital transformation in that time,

0:36

and has leveraged his depth of

0:38

experience as a leader in data

0:40

and analytics to help transform the

0:42

company's use of it, first and

0:45

focused on data hygiene, governance, and

0:47

quality, and now better taking advantage

0:49

of AI. I look forward to hearing

0:51

more about his journey through this conversation.

0:53

Guy, welcome to Technivation. It's

0:56

great to speak with you, Peter. Well, Guy,

0:58

I thought we'd begin with the company that

1:00

you help lead. You are the chief information

1:02

digital officer of McCormick and company, as I

1:05

noted. I'd love to talk about the company

1:07

first and foremost. For those who might be

1:09

less familiar, can you give an overview of

1:11

the business you're part of? Yeah,

1:13

McCormick is a 135 year old

1:16

company and we are a global

1:18

leader in flavor and really well

1:20

positioned in flavor both in our

1:22

consumer business which serves 150 countries

1:24

around the world and in our

1:27

flavor solutions business which flavors a

1:29

lot of Other brands around the

1:31

world. We like to say that

1:33

we flavor every step at every

1:35

bright across channels in and away

1:37

from home and in every occasion.

1:39

So we're really passionate about flavor

1:41

Some of the brands that we

1:43

have in our portfolio may be

1:45

familiar to many of us. McCormick

1:47

obviously is one of the brands. In

1:50

Europe we have bikini and ducro which

1:52

is very famous and popular brands

1:54

and then Franks Red Hot, Touloula,

1:56

French's Old Bays, Adirain. So

1:59

phenomenal brands. iconic in many

2:01

parts of the world. Fantastic, yeah,

2:03

great overview, and certainly I've got

2:05

several of those in my own,

2:07

myself at home, as I'm sure

2:09

many of our listeners and viewers

2:11

do as well. Let's talk about

2:13

your role, if you don't mind,

2:15

guy. I mentioned you're the Chief

2:17

Information and Digital Officer. Talk a

2:19

bit about your purview and what's

2:21

within your Hispanic control. Yeah, so

2:23

my span and control and responsibilities

2:26

are really kind of developing and

2:28

leading the implementation of our enterprise

2:30

digital transformation strategy. And that is

2:32

everything from the foundational tech that

2:34

we run our company by, which

2:36

includes the infrastructure, all of the

2:38

cloud capabilities, ERP, etc. to the

2:40

data platforms and AI capabilities that

2:42

we use in the company. all

2:44

the way to the transformation initiatives

2:46

that we have across every part

2:48

of our company. So a fairly

2:50

large rebate with of course cyber

2:52

security wrapping around that entire responsibility.

2:55

You alluded to digital transformation there,

2:57

and I know as you as

2:59

you point out a big part

3:01

of your responsibilities Development and implementation

3:03

of digital transformation to find that

3:05

a little bit further Obviously, that's

3:07

a broad umbrella and a lot

3:09

of things fit underneath it Can

3:11

you talk about some of the

3:13

highlights of areas that you're focused

3:15

on as you as you contemplate

3:17

that? So let's start with the

3:19

Cormex business strategy. Our digital transformation

3:22

is anchored right to it. So

3:24

our business strategy and we have

3:26

a strategic roadmap and driving growth

3:28

and performance and accelerating digital transformation

3:30

is the core part of that

3:32

roadmap. So we're very connected to

3:34

serving consumers, customers, employees through digital.

3:36

And the elements of the digital

3:38

strategy are kind of fourfold. One

3:40

is driving demand creation. And so

3:42

that is how do we meet

3:44

consumers where they are provided them

3:46

the right targeted media and content

3:48

to inform them about our other

3:51

brands and help them through their

3:53

path to purchase. So that's one

3:55

one pillar. Another one is accelerating

3:57

product innovation. So how do we

3:59

leverage digital and AI to get?

4:01

insights on trends in the flavor

4:03

space and bring those products to

4:05

market in an accelerated way. A

4:07

third area is how do we

4:09

optimize our retail execution for us

4:11

of the store environment both online

4:13

and offline is critical and so

4:15

how do we provide a delightful

4:17

experience there? And then the fourth

4:20

area is around operational efficiency. So

4:22

how do we leverage digital and

4:24

AI to to optimize not only

4:26

how we buy our ingredients as

4:28

a flavor company, raw materials is

4:30

everything for us. And so sourcing

4:32

those raw materials, making sure we

4:34

have highest quality that we put

4:36

through our brands is important. So

4:38

we leverage digital and AI heavily

4:40

in that space, as well as

4:42

operational efficiency on our planned floor

4:44

and doing a lot of smart

4:46

manufacturing and smart forecasting is this

4:49

corridor strategy. So those are kind

4:51

of the key domains that we're

4:53

focusing on. In multiple parts

4:55

of your response there, you talked about

4:57

consumers and customers, and I know that

5:00

you're passionate about building trusted relationships with

5:02

them, and the extent to which building

5:04

and forging great bonds with them accelerate

5:06

the development of products and services that

5:09

delight those same constituents. Talk a bit

5:11

about the pathways to do so, the

5:13

means by which you and your team

5:16

draw those insights such that you can

5:18

ensure that you're building better opportunities for

5:20

them. all its service to consumers customers

5:23

employees that's the core to what are

5:25

McCormick strategies centered on and it's definitely

5:27

the core to what digital you know

5:29

our analytic strategy centered on and you

5:32

know digital allows us to have such

5:34

a close proximity to what's on consumers

5:36

minds and we leverage the digital thread

5:39

that we get through social and through

5:41

other means and our first party data

5:43

to truly understand consumers at a much

5:46

deeper level than we were able to

5:48

historically. And then that translate into delightful

5:50

and superior products that then hopefully serve

5:52

our customers efficiently and effectively throughout our

5:55

supply chain. So one of the things

5:57

I forgot to mention in the opening

5:59

on McCormick is we pride ourselves in

6:02

leading in flavor and predicting future flavor

6:04

forecasts. And so for us to be

6:06

effective and continue to be a leader

6:09

in the market, we try our best

6:11

to predict what's coming, then bring those

6:13

flavors into our products and then serve

6:15

consumers with those flavors. So we have

6:18

an annual flavor forecast that we've published

6:20

every year. We just published our 25th.

6:22

flavor forecast. We've been doing it since

6:25

2000. To give you a couple examples

6:27

of flavors that we predicted, pumpkin pie

6:29

spice, we predict that one, Chipotle, Korean

6:32

barbecue, which is one of my favorites,

6:34

and then spicy, which is combination of

6:36

sweet and spicy flavors, which has been

6:38

awesome. And this year's prediction is Aahi

6:41

Amarillo. It's a South American spice that

6:43

we believe is going to go massively

6:45

large in its combination of fruity tropical

6:48

notes and a little bit of heat.

6:50

I've had it, it's amazing. And so

6:52

we expect that over the next couple

6:55

years that might become mainstream. So, you

6:57

know, I mention all that because in

6:59

order to get that kind of insight,

7:01

we need incredibly detailed data on trends,

7:04

on geographic preferences, and all those digital

7:06

capabilities I mentioned help us, help us

7:08

inform our predictions. Yeah, talk a little

7:11

bit about that. That's so fascinating that

7:13

this whole notion of the flavor forecast.

7:15

I realize it's probably your team, but

7:17

also the broader team that gets deeply

7:20

involved with this. I can only imagine

7:22

the scientists that are hard at work

7:24

in developing these ones the forecasts is

7:27

set as well. Can you talk a

7:29

bit about how a pumpkin pie spice

7:31

or a Chipotle or Korean barbecue, etc.

7:34

the pathway to the insight that would

7:36

suggest that that's what's to come. Talk

7:38

a bit more about that if you

7:40

would. Yeah, this is absolutely a multidisciplinary

7:43

sport. And so R&D, marketing, innovation teams,

7:45

we have culinary chefs who are full-time

7:47

experts on creating dishes and tech. them

7:50

with consumers and so these insights come

7:52

from all those teams around the world.

7:54

We have about 40 years. of sensory

7:57

science data that we pull into our

7:59

qualitative and quantitative research, including on the

8:01

ground research. And then we leverage our

8:03

social listing tools and searchings and optimization

8:06

trends and many more tools that help

8:08

us triangulate all these data points. And

8:10

it's a fascinating process and I'm more

8:13

and more impressed every time I see

8:15

it in action. And then also see

8:17

the actual the accuracy of these predictions

8:20

coming to life. Super interesting. Thank you

8:22

for sharing that. You have a deep

8:24

background in data and analytics. You talked

8:26

about that among the areas of responsibility

8:29

you have. You were also the first

8:31

ever chief data and analytics officer at

8:33

P&G, a company you were with for

8:36

28 years. I can only imagine that

8:38

those set of responsibilities color the way

8:40

in which you think about your current

8:43

post. And I want to get some

8:45

insights from you about your data strategy,

8:47

how you think about the use of

8:49

data. We've already talked about some of

8:52

the. broader implications of how that can

8:54

be used creatively to develop new products,

8:56

but we'd love to understand a bit

8:59

more about the specifics of the data

9:01

program you're putting in place. Sure. So

9:03

as the first sheet data analytics officer

9:06

at P&G, I've learned three things. I

9:08

was in that role for six years,

9:10

and it was phenomenal learning, and I

9:12

feel really blessed to have had that

9:15

experience. And I take these three things

9:17

with me to McCormack, and they're very

9:19

much alive and well in our current

9:22

strategy. The first one is anchored anchored

9:24

on business value. There's a lot of

9:26

things we can do with digital data

9:29

and analytics. There's only a few things

9:31

that are material. And so really focusing

9:33

on the few things that really matters

9:35

kind of step one in our journey.

9:38

And I've learned this both from a

9:40

few successes, but many failures in my

9:42

journey. So a lot of these insights

9:45

are linked to those experiences. So value

9:47

creation is the first thing. The second

9:49

thing is the strategic nature of data.

9:52

A lot of people like to talk

9:54

about AI and AI. I mean, I'm

9:56

of those individuals. However, there's none of

9:58

that without quality data. And so being

10:01

intentional on data strategies, being intentional on

10:03

all things data management in terms of

10:05

quality, reliability, bias, all those things that

10:08

are associated with modeling the data is

10:10

super important and it may not be

10:12

the sexiest of topics. But mission critical

10:15

for us to operationalize data and enterprise.

10:17

And the third and final learning is

10:19

process integration. So this is as much

10:21

about operating model transformation as it is

10:24

about data analytics and digital. And our

10:26

strategy is very much people, process, and

10:28

then technical and digital. And I think

10:31

the final. leg of that three leg

10:33

of school is about 20% of the

10:35

transformation. 80% is about transforming work processes,

10:38

upskilling the organization to work in a

10:40

new way, rewarding them differently, and growing

10:42

career paths where people that are applying

10:44

digital and analytical capabilities are rewarded in

10:47

working in a new way in the

10:49

future. So we're working on all of

10:51

those three legs and I'm bringing a

10:54

lot of those learning from P&T. That's

10:56

really well articulated. Thank you so much

10:58

for sharing those. You mentioned there in

11:01

the process of upskilling the team, rewarding

11:03

them differently. Can you talk a bit

11:05

about what some of that entails? What's

11:07

different in the current environment relative to

11:10

years or decades past? Yeah, I think

11:12

what we do in any enterprise, including

11:14

McCormick, really doesn't change. At the end

11:17

of day, we're here to serve consumers

11:19

and customers in a voice. That what

11:21

doesn't change. pretty much everything about how

11:24

we do that changes with digital and

11:26

and AI and and so what we

11:28

what we're trying to do and we

11:30

talk about this often in the management

11:33

committee and the operating committee that I'm

11:35

part of is really finding how do

11:37

we transform work upskill individuals to be

11:40

successful in that new world and then

11:42

catch them doing it right and put

11:44

a big spotlight on them reward them

11:47

bring them to the global town halls

11:49

have them described their from to experience

11:51

and then recognize them and that's how

11:53

cultures are shifted. When people see individuals

11:56

who used to work one way, apply

11:58

a different approach with digital analytics and

12:00

then talk about how their life is

12:03

different and how they're driving better outcomes

12:05

as a result of that application and

12:07

that's how cultures over time change. And

12:10

so we're still very much on that

12:12

journey of McCormick but we have a

12:14

lot of great examples of where that's

12:16

already been operationalized and making a big

12:19

difference. I love the way in which

12:21

you describe the necessity to have the

12:23

foundational elements of data analytics. right in

12:26

order to better take advantage of artificial

12:28

intelligence, analytical AI, generative AI, agentic, as

12:30

you noted, and clearly you're in the

12:33

process of making sure that that hygiene

12:35

is appropriately in place. Talk about, though,

12:37

you also mentioned that you are among

12:39

the leaders who are very excited about

12:42

the power of AI and the continuum

12:44

that you mentioned that I just reiterated.

12:46

Can you talk a bit about what

12:49

excites you most? What are some of

12:51

the applications either already? in place at

12:53

McCormack or that you foresee being put

12:56

in place that are going to add

12:58

more value to those same consumers and

13:00

employees who are the constituents you serve?

13:02

Yeah, so current capabilities in place that

13:05

I'm really excited about and really proud

13:07

of what McCormick has done is the

13:09

predictive analytic capabilities that we have. We've

13:12

applied a lot of that to how

13:14

we predict our procurement and our raw

13:16

material pricing. So we're able to, with

13:19

the 30 years of procurement data that

13:21

we have, plus a lot of external

13:23

signals. fairly accurately predict price points of

13:25

our raw materials and for a company

13:28

like us that's mission critical to be

13:30

able to understand where those those curves

13:32

are going and so we do a

13:35

lot of prediction in sourcing and in

13:37

procurement we're doing a lot of prediction

13:39

in how we think about forecasting whether

13:42

it's demand planning supply planning or financial

13:44

planning we're well we're on that journey

13:46

but being able to more effectively predict

13:48

the demand signal and then how that

13:51

affects our overall. operations, another great example.

13:53

And then lastly, our problem. product formulation.

13:55

So we're using a lot of modeling

13:58

to enable our development of products and

14:00

formulations and frankly recipes and then being

14:02

able to substitute out different ingredients at

14:05

a fraction of the time it used

14:07

to take us to do that. AIs

14:09

enabling all that. So really exciting capability

14:11

that is already being operationalized and the

14:14

things that I'm most excited about going

14:16

forward is, you know, agentic is I

14:18

think going to be a really powerful.

14:21

capability, kind of the next generation of

14:23

automation in RPA in my view, and

14:25

looking at how does that, how do

14:28

the agents all work with each other

14:30

and what is the new role of

14:32

the human talent and new organization in

14:34

working and co-working with these agents. And

14:37

so I'm really excited about that. I'm

14:39

going to school learning as much as

14:41

I can on those on those topics

14:44

and we'll be experimenting with that at

14:46

McCormick. Really interesting and I'd love to

14:48

understand what conclusions you're drawing about that

14:51

collaboration. I love the way you put

14:53

that, the role of human talent in

14:55

co-working with agents. What conclusions are you

14:57

drawing? These obviously are going to be

15:00

new ways of working. It will mean

15:02

changing who does what and how. Talk

15:04

a bit about how you've thought about

15:07

that interaction between the humans and the

15:09

agents. Yeah, I think there's kind of

15:11

two levels of interactions. First, the more

15:14

transactional work that we all do. that

15:16

will likely be fully automated and objective

15:18

will take care of most of that

15:20

on our own. So the future workforce

15:23

will be upskilled to not only work

15:25

well with agents and make sure the

15:27

right data and the algorithms are operating

15:30

properly. I think I think the future

15:32

of every role will be a citizen

15:34

data scientist that's a financial planner or

15:37

a citizen data scientist that's a demand

15:39

planner and they will be working with

15:41

algorithms as a co-pilot to help them

15:43

get their work done and instead of

15:46

doing a lot of muscle in doing

15:48

the forecasting that many of us do

15:50

today including ourselves it will be doing

15:53

a lot of working on the exceptions

15:55

and making sure that the algorithms remain

15:57

unbiased, are fed proper data, and are

16:00

operating effectively. And so there's a different

16:02

set of skills that we're going to

16:04

be focusing on upskilling our talent on,

16:06

but it's really exciting. I'm really excited

16:09

about what that future could look like

16:11

and how the company will operate differently

16:13

through these capabilities. And it's somebody who

16:16

obviously grew up with immersed in technology.

16:18

Talk a bit about the opportunity now

16:20

for non-technology because as I hear you

16:23

talking about the impact, I'm at least

16:25

translating in my mind the impact not

16:27

only of course to members of your

16:29

team, but your colleagues outside of technology

16:32

who now can interact with it in

16:34

ways that would have been esoteric perhaps

16:36

in the past or maybe even non-existent

16:39

frankly because of the complications and necessity

16:41

of deep technical talent in order to

16:43

you coax out the right the right

16:46

responses. along the way. Talk a bit

16:48

about what excites you perhaps about your

16:50

non-technical talent being able to interact in

16:52

new ways with the technology. Yeah, I

16:55

think techno. has been more and more

16:57

democratized not only in terms of from

16:59

a consumer perspective all of us have

17:02

our smartphones and we have expectations of

17:04

technology that we simply didn't have in

17:06

the past because it wasn't as accessible

17:09

all the way to AI being accessible

17:11

with the GPT capabilities and that's just

17:13

going to continue and so you no

17:15

longer need a PhD in data science

17:18

to work with AI models and that

17:20

for me is super exciting so most

17:22

of the time I spend while we're

17:25

building our IT and strategic IT skills

17:27

in McCormic I spend a lot of

17:29

time on how do we build the

17:32

business skills in the digital fluency space

17:34

and how do we help everyone become

17:36

more fluent in how to leverage some

17:38

of these skills. And I think there's

17:41

two insights I've gotten. One is the

17:43

tools themselves have to be designed to

17:45

be consumer-friendly or what I call Apple

17:48

Simple. And the more simpler we design

17:50

the tools, the easier it will be

17:52

to adopt. And so that's the first

17:55

pretty obvious insight, but sometimes the tools

17:57

we think are easy to use are

17:59

not. They're very technically designed versus, you

18:01

know, end-user designed and we need to

18:04

make sure we're user-centric in our design.

18:06

And the second thing is, they'll just

18:08

be based skill sets that are going

18:11

to be required that everyone, no matter

18:13

what role you have in the enterprise,

18:15

will need to have. And so... I've

18:18

done some benchmarking with other companies and

18:20

I've really been inspired by the idea

18:22

of everybody needs to understand what is

18:24

a basic machine learning model. Everyone needs

18:27

to understand how data is fed into

18:29

a machine learning model, how predictions are

18:31

made, just the basics of how digital

18:34

works is going to be a common

18:36

understanding of every role because those tools

18:38

will be applied to pretty much every

18:41

role in the enterprise. Any

18:43

particular flavors that you have become your

18:45

favorites since joining McCormick I'm sure like

18:47

all of us you use McCormick products

18:50

before joining the company What are some

18:52

of the ones that you're shaking on

18:54

top of your food or cooking with

18:56

these days? Yeah before I joined I

18:58

was a big Lowry fan still have

19:00

I didn't even realize Lowry was over

19:02

by McCormick. I was delighted to find

19:05

that out and then the love I

19:07

love Frank's red hot and tulula. It's

19:09

a kind of a toss-up depending on

19:11

what I'm eating on those two And

19:13

then some of these future flavors that

19:15

I've been able to test with our

19:17

culinary staff are just phenomenal. I can't

19:20

wait until they bottle up and allow

19:22

me to purchase them in store because

19:24

they're just phenomenal. So the cool thing

19:26

about MacLoram because we have so many

19:28

different, because we have so many different

19:30

light extensions and so many kind of

19:33

leading edge flavor extensions. It's kind of

19:35

an endless list of favorites. And right

19:37

when I get to one favorite, I

19:39

find another one. So it's been fun.

19:41

a remarkable tenure you had a P&G,

19:43

almost three decades with the organization. And

19:45

I've always been impressed by the diaspora

19:48

of technology talent that has emerged from

19:50

that company. And I wonder if you

19:52

could reflect for a moment on what

19:54

made that experience special for you, special

19:56

enough to stay with the company for

19:58

28 years, but now as someone who

20:00

is. taken on a leadership role of

20:03

consequence as the head of information digital,

20:05

the chief digital information officer of the

20:07

organization, the impact you feel from your

20:09

time as you now have a little

20:11

bit of distance to reflect upon it.

20:13

Yeah, as I reflect on my PhD

20:16

time first of all, I feel blessed

20:18

I've had the 28 years experience a

20:20

great company and an amazing space to

20:22

learn and you know, I have a

20:24

number of colleagues who are also CIDOs

20:26

and other companies and we stay very

20:28

connected and as we talk about what

20:31

is the call the formula that we

20:33

were exposed to a P&G that helped

20:35

us become, you know, CIDOs of our

20:37

respective organizations. There was kind of three

20:39

things. One is we started with the

20:41

business and you know, as early as

20:43

you know, 1999, I remember talking about

20:46

our GBS, our global business services, was

20:48

all about transforming the way business is

20:50

done. And we were always about being

20:52

business leaders first that brought strong technology

20:54

and analytics expertise to the table. And

20:56

we never reversed that. And that's something

20:59

that I think was built into our

21:01

DNA. The second thing is we were

21:03

able to experiment a lot and we

21:05

failed a lot. But we learned through

21:07

those failures. And so, you know, we

21:09

had a really nice platform from which

21:11

to learn. And the third is we

21:14

were able to implement capabilities at scale.

21:16

You know, doing a pilot is easy,

21:18

scaling and operationalizing it and addressing all

21:20

the things Peter that you mentioned around

21:22

people and process and culture. That is

21:24

where the challenge is and being able

21:26

to do that at scale multiple times

21:29

and having many at that to doing

21:31

that I think really shape one professional's

21:33

career and so again very very blessed

21:35

to have had that experience and all

21:37

those experiences are directly applicable to McCormick

21:39

and me by team are busy at

21:42

work applying those. So

21:44

interesting. I appreciate those reflections. I wanted

21:46

to ask, I mean, we've talked about

21:48

a number of trends through this conversation,

21:51

data analytics, trends, artificial intelligence, as we've

21:53

covered in some detail as well. Guy,

21:55

as you think about the future, anything

21:57

else come to mind? that particularly excites

21:59

you starting to make its way onto

22:02

your road map? Yeah, I think the

22:04

adjective we... touched on a bit. I

22:06

think that's going to be a big,

22:08

a big, important trend. I also think

22:10

the, the idea of, IOT will continue.

22:13

So the number of sensors that we

22:15

have, not only in our manufacturing lines,

22:17

which is much more mature with robotics

22:19

and sensors online, but also in our

22:21

products, we're going to have smarter and

22:24

smarter products that will help us better

22:26

serve consumers and personalized experiences to levels

22:28

that we've never been able to personalize

22:30

before because the data streams will be

22:33

flowing. that are exciting areas that we're

22:35

also experimenting in. And then the third

22:37

area is with those capabilities transform business

22:39

models. I think we're going to be

22:41

able to create completely new business models

22:44

that monetize a lot of those capabilities

22:46

and create new revenue streams that could

22:48

be exciting for enterprises. So really a

22:50

lot of exciting opportunities ahead. keeping eyes

22:52

open as to the progress that's made

22:55

in those very areas. I also wanted

22:57

to ask you guy, anything you've recently

22:59

read, watched, and or listened to, that

23:01

you'd recommend to peers? Yeah, I'm rereading

23:03

a book called Computing in the Age

23:06

of AI, Karim Lacani, wrote it, Professor

23:08

in Harvard, and Marcos, his colleague. I

23:10

read it a number of years ago

23:12

when it was released, and Brendan, our

23:14

CEO just... bought a copy of that

23:17

for our management committee and operating committee,

23:19

our leadership of McCormick. So I'm rereading

23:21

it, just to make sure I'm up

23:23

to speed on the latest. And I

23:26

find it's a really good book that

23:28

brings very practical use cases and case

23:30

studies and shows how a lot of

23:32

this capabilities applied for really tangible outcomes.

23:34

A great suggestion. Thank you for offering

23:37

that. Well, Guy Perry, thank you so

23:39

much for taking time with me today.

23:41

Fascinating to hear about your experience now,

23:43

just five months in. at McCormick, the

23:45

remarkable change you're already ushering, as well

23:48

as a bit more about your career

23:50

journey as well. It's been fascinating to

23:52

learn from you and thank you so

23:54

much for a great conversation. Thank

23:56

you for having

23:59

me. been my pleasure.

24:01

my pleasure.