January 7, 2025 • 29 mins
Transforming Businesses with AI: Insights from Ryan Mayes
In this episode of The Human Code, host Don Finley speaks with Ryan Mayes, a turnaround specialist and innovation leader at fleet Corp, about his approach to integrating AI in business operations. Ryan discusses the importance of focusing on people, processes, and technology to create sustainable change. He explains how AI can enhance customer experiences, differentiate competitive markets, and drive long-term growth. The conversation also touches on the challenges of user adoption, the value of incremental improvement, and lifelong learning. Ryan highlights the significance of understanding customer needs and leveraging AI to augment, not replace, human roles in organizations.
00:00 Introduction to The Human Code
00:49 Meet Ryan Mayes: Turnaround Specialist
01:56 Ryan's Philosophy: People, Process, and Technology
02:59 Leveraging AI for Business Transformation
04:07 Challenges and Successes in AI Adoption
07:05 Future of AI in Business Strategy
10:01 Customer Experience and AI Integration
20:09 Data Management and Performance Measurement
24:45 Advice for Aspiring AI Enthusiasts
28:40 Conclusion and Final Thoughts
Sponsored by FINdustries
Hosted by Don Finley
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Don Finley (00:00):
Welcome to The Human Code, the podcast where
technology meets humanity, andthe future is shaped by the
leaders and innovators of today.
I'm your host, Don Finley,inviting you on a journey
through the fascinating world oftech, leadership, and personal
growth.
Here, we delve into the storiesof visionary minds, Who are not
only driving technologicaladvancement, but also embodying
(00:23):
the personal journeys andinsights that inspire us all.
Each episode, we explore theintersections where human
ingenuity meets the cutting edgeof technology, unpacking the
experiences, challenges, andtriumphs that define our era.
So, whether you are a techenthusiast, an inspiring
entrepreneur, or simply curiousabout the human narratives
(00:44):
behind the digital revolution,you're in the right place.
Welcome to The Human Code.
Today, we're excited to welcomeRyan Mayes, a turnaround
specialist and innovation leaderwith a proven track record of
transforming high riskoperations into thriving
businesses as vice president ofprofessional services and
operations at fleet Corp.
(01:04):
Ryan oversee SAS delivery.
And corporate solutions acrossnorth America, consistently
driving growth, efficiency andcustomer satisfaction.
In today's episode, Ryan shareshis philosophy of focusing on
people, process and technologyto create sustainable change.
We'll explore how he'sleveraging AI to scale
operations, enhance customerexperiences and differentiating
(01:26):
competitive markets.
Ryan also highlights theimportance of lifelong learning.
Staying curious and adapting torapid technological advancements
to remain ahead of the curve.
Join us for an inspiringconversation about leadership
transformation and the practicalapplication of AI and reshaping
businesses for the future.
(01:47):
Ryan, it's a pleasure to haveyou.
And my first question is.
What got you interested in theintersection of humanity and
technology?
Ryan Mayes (01:56):
I think my, philosophy in my professional
roles has been to focus onpeople, process and technology.
When it comes to strategicinitiatives, strategic
roadmapping, I've keyed in onthose three areas.
And I have also believed thatThey're not isolated.
They're very much intertwined.
When you focus on one, you'reimpacting the other two.
(02:18):
And so I've had a lot of successin my career with, developing
plans and developing a visionand strategy with an executable
according to those three, mainthemes.
And so I have always thoughtthat.
People or team members are aidedor enhanced by using technology.
not as a replacement of team,because I think ultimately
whatever solution you're tryingto solve, people in many
(02:42):
organizations are considered tobe, a competitive advantage.
And so as you equip them withtechnology, not only are you
enhancing their ability toproduce or increase their
productivity, but the outcomesor solutions of which they are
providing either to an end useror to a customer are much more.
And so I think in my journeythrough, continual improvements,
(03:03):
Six Sigma and technologies suchas AI, I think there are
opportunities to, to be far moreaggressive with finding new ways
to do work, much more efficientand much more effective.
And I think in my experience,within the last year and a half
with AI, that falls right intomy methodology that I've
employed for many years.
(03:24):
In that AI is not a replacementof a solution per se, but it's a
wonderful tool to come to a moreeffective outcome quicker.
Don Finley (03:36):
and I think it's a nice paradigm to hold that
basically we're looking ataugmenting what people are doing
over the replacement idea And atthe same time it comes back to
this reflective point of whenwe're working on these things,
we're working on them for thesake of ourselves.
And I mean that not as a selfishendeavor, but in the endeavor of
we're doing it to solve problemsthat we have today, or we're
(03:59):
doing it to create somethingthat we've imagined that doesn't
exist today and To have toolslike AI can be really helpful.
in the last year, what have youseen as being the roadblocks to
your own adoption or, the areaswhere you thought it was going
to be super helpful and it, gaveyou pause.
Ryan Mayes (04:16):
I think some of the roadblocks that I've seen is, is
our team using the deliverablesor the output?
That I'm producing and that,that would be across the board
on any initiative.
But on, on this one, it's reallychanging the way that we work.
Instead of allowing a teammember or a salesperson or an
end user on the operations groupto solve the problem on their
(04:38):
own, we're coming alongside ofthem and providing them with.
Templates, articles, tools, newways of working.
And so user adoption, I think,is really key.
I don't think you necessarilyflip the switch overnight.
To say, now we're going througha new paradigm change and we're
going to work this way.
But I think you have to seeincremental change, and progress
(05:00):
and communicate those short termwins.
I've always been a bigproponent.
If you can't acquiretransformational change and then
at least try for incremental asopposed to doing nothing.
I think some of the successesthat I've seen is from a
marketing enablementperspective, providing our team
with far more, intimate anddetailed information on scripts,
(05:22):
playbooks, competitive analysis,landscape definition.
It really enables them to havemuch more one on one intimate
conversations with the customerthat are more targeted and more
pointed based upon who the enduser of the audience really is.
Don Finley (05:35):
And so I think you're using AI to help you to
create some of these artifacts.
Ryan Mayes (05:39):
Yes, because we went from, all right, we don't do
much to now we've gone from, nowwe have a catalog or a library
of content.
And I think it's not to me, thepart a, or the first part is,
okay, now we have content now,what do we want to do with it?
And I think, as I begin to takea look into next year, sort of
the year two, It's reallybringing all of that content
(06:01):
into a framework of, this is howwe work going forward.
This is the strategy or, thereal intent.
In terms of not just what weuse, but how we use it.
And the end result is, a greatervalue proposition, customer
conversation.
it's more targeted, I think,going forward as opposed to,
here's just a data dump.
And I think that's some of thethings that I'll probably key in
(06:24):
on next year.
to really key in on how weincrease our user adoption and
really increase our end resultsas well.
Don Finley (06:31):
it's funny.
So we were talking pre showabout the crawl, walk, run.
Kind of space, And what wasfunny is we were talking about
how you're in the crawl space ofHey, we're going to figure out
how we can utilize this.
It's a lot of trial and error.
It's seeing what sticks, findingthe places where it does add
value and you get morecomfortable with the solutions,
but then what you just describedis you're preparing to get into
(06:53):
that walk phase.
of actually making targetedapproaches and saying, Hey, if
we apply it here's how we knowwe can gain some efficiency.
And it's finding those three Xuse cases that enable you to
grow.
And so in thinking about 2025,what are some of the things that
excite you about this, liketechnology option that is,
coming to play?
what are some of the questionsthat you have there as
Ryan Mayes (07:15):
I think when I begin to consider what's next year,
you mentioned, crawl, walk, andI know we talked about that.
Pre show.
I'm a firm proponent oftransformational change.
I've been in situations in mostof my roles and most of my
career where you don't have theluxury of time to scale an
operation, to develop a visionthat has some type of, of an
(07:36):
aggressive, 18 month roadmap,you've got to, you've got to
move forward and prepare teamsfor.
Significant scale and scope,full well knowing that they're
not prepared for either one.
Because I've worked in manyorganizations in many roles
where there are hyper growth.
Environments, double digitgrowth year over year.
it would be very easy jokinglyto say, you know what?
(07:56):
I'll just shut this departmentdown for two years.
We'll retool and we'll startback up.
No, you have to do that whilethe bus is moving down the road
and the wheels are turning.
Now that's a very daunting,thought.
If you've never been in thatenvironment before, but as I've
matured throughout my career, Ilove those environments because
it's a wonderful opportunity.
You know what?
(08:16):
We're going to develop a plan.
we're going to really improveour team members experience by
focusing on people processingtechnology, like I said, and
within the current company thatI'm in now, I do believe that
using AI going forward as partof who we are and what we do,
that I think is the key goingforward.
It's not just what I'm doing.
(08:37):
Leading a particular corefunction within a business unit.
It's more or less transcendingto, what merchant services as a
real opportunity todifferentiate itself in the
marketplace, not just in termsof its value proposition, but
how we work, in terms ofdeveloping that value and what
we do with it to really provide.
More intimate and moresophisticated solutions to solve
(09:00):
our customer problems.
And I think that's where AIreally comes into allowing us to
scale more into thattransformative effort.
Like I mentioned,
Don Finley (09:08):
and coming into like the merchant services space, as
an industry, there are a lot ofsolutions in the merchant
services space for anybody who'staking payments in any form or
fashion.
And so like to be able to boththe services in new, innovative
ways, but additionally to helpthe customer to understand those
services.
(09:29):
cause it is somewhat daunting.
I spent some time in creditcard.
What's it when you actuallycreate the credit card?
I worked for Barclays for awhile.
we put credit cards on vendingmachines and help build like
Coke's platform as well.
And so I've seen it from numberof angles and the complexity of
the solutions that are availablethrough your business.
And that type of solution can bedaunting for a customer, but
(09:51):
then also understanding it on amonthly
Ryan Mayes (09:53):
it really is.
we're more or less working withthe retailer or the company, the
organization, but there is acustomer front end component.
the customer is I'm purchasingfuel.
I'm purchasing a product, andI'm swiping my card and then I'm
leaving.
But that's not the end of theorganization's responsibility.
There's the entire receiving ofthat payment.
(10:13):
And then there's the, all of thereconciliation and settlement
post transaction, the customeris long gone.
and so what we try to focus onis more of that end to end
customer experience, not justfrom the customer's perspective,
but also from.
the organization's perspectiveas well, and really, to your
point, I agree with you, thepayments industry, regardless of
(10:34):
whether it's fueling industry oranother sister type ancillary
industry is, could be conceivedas very commodity based.
everyone provides a point ofsale piece of hardware.
Everyone provides a paymentsolution.
Everyone wants to provide youwith a similar type experience.
But what I mentioned before is,what does our organization do
differently?
that really separates us fromour competitor base.
(10:55):
Our competitor base is.
It's regional, it's geographic,and it's also a nationwide or
enterprise.
So the way we go to market hasto vary based upon, are we
talking about, a national playor are we talking more of a
geographical or a regional playand I getting back to AI, I
think that's where we get into,much more sophisticated process
(11:16):
in terms of.
Defining our markets, definingour landscapes.
And then from there, how do weoperate within that particular
market or landscape differentlyin the Southeast than we would
say in California or in theWest, because they operate
differently.
In many ways, but you're right.
I think, transitioning a thoughtprocess into a value from a
(11:36):
commoditization type market intomore of a specialty, but also
focusing on scale and scope,because we have to not
necessarily churn throughcustomers.
That's not really who we are,but we have to reach solutions
faster.
And I think that's where AIreally comes into play with how
we operate our businessdifferently next year.
Don Finley (11:58):
it sounds like, you could come up with a, nationwide
plan, but have somehyperlocalization because of
what AI could help you
Ryan Mayes (12:06):
I think you're completely correct, Don.
our, our enterprise customersgenerate a certain percentage of
our revenue.
But when you start taking a lookat the base itself, now you're
starting to run into much more,what we call single or multi
unit owners.
And then what I call mid majors,they're geographically located
and they operate differently.
(12:26):
So we may sell one particularproduct or solution across all
three of those segments.
and most people do as well, theywill use that product
differently.
And I think that's where we getinto much more differentiation,
without, trying to figure out,we'll just go hire five more
people to run our marketingoutfit.
That's not really going tohappen.
And so I think using technologyto augment our current team.
(12:49):
and our base here is really oneof the things that I want to key
in on next year.
Don Finley (12:53):
Are you seeing any change in skills as far as your
base team in regards to how youwant to grow with, these
solutions that we're talking
Ryan Mayes (13:01):
Yes.
back in the day, sales cameeasier, and now they're not.
And I think within the fuelingindustry, it's far more
fragmented.
we have a lot of customers andcompanies that used to work with
us that no longer, becausethey're out of business.
And so the other thing that'shindering that is you see a lot
of new market, Now, they may benational, but they also may be
(13:21):
geographic as well.
So again, getting back to thatmarket landscape definition is
becoming more critical for us.
And then, pre show, we talkedabout within the fueling market,
a lot of our customers want toconsume solutions in the cloud.
So what is your product roadmap?
How are you moving in a way thatmeets customers where they are,
(13:42):
not necessarily where you wantthem to be?
And I think that is one of theother differentiators that I'd
like to key in on next year is,how do we meet customers and how
do we solve their problems wherethey are?
As opposed to, this is ourproduct.
Talking about your product orservice and your features is
always going to be important,but tying it into solving their
problems.
(14:03):
I think that's one of thedifferentiators that really
separates.
a growing company.
Don Finley (14:08):
Yeah.
what is that first order problemthat your customers are having
today?
That a new payment solutionwould help with, I know some of
our, for some of our like,service based businesses, Their
customer satisfaction is likenumber one as far as what's
driving decisions.
for other payment providers thatwe've worked with, like the,
(14:28):
their clients are looking forsomething along the lines of
like how quickly do they haveaccess to their cash?
what are the problems that yourcustomers are facing that you
feel like you could actuallysolve better, with AI
Ryan Mayes (14:42):
I think anyone, and we deal with this in our
personal lives as well.
customer support is usually onpage one, probably towards the
top third of the page.
if I call you, I want you topick up a phone.
If I email you, I want you towrite me back.
customer support is expensive.
in my previous organization, themethodology when I moved into
(15:03):
that new role was When we have acustomer call, we want a team
member picking up a phone.
That's great.
That worked when we were asmaller organization, but if we
want to continue to grow, that'sprobably not going to work.
And then we began to, do somedata analysis.
why are customers calling in?
they want to know where theirlocal store is.
(15:23):
They want to know if the storeis open today or their operating
hours.
Those were easy ones toautomate.
through an IVR.
And for us in the fuelingindustry, it's somewhat similar,
customer support, you can't hireenough people to pick up on
first ring, but what you can dois, what would life look like if
(15:44):
we provided customers with selfhelp?
what if we talked about maybeautomating some of those,
recurring questions that areeasily answerable?
and I think that's one area.
I think the other area iscommunicating to the customer
use cases.
white papers, maybe notnecessarily the documents
themselves, but what are othercustomers doing in working with
(16:08):
us, that are helping them runtheir business more profitable,
more profitably, helping themdrive revenue or increase market
share.
And I think, again, getting intothat, how do we somewhat
automate or provide additional.
AI type based resources toprovide with our sales team and
our sub support team.
really information that getsdown to the root cause of why
(16:29):
customers are even contacting usto begin with.
we're a market leader, we'rewell known, but.
Really getting beyond thecommodity type conversation into
problem solving and reallysolutioning and really growing
with customers as they grow.
I think those are some of thethings that we've had some
marginal success with to start,but I think really with AI
(16:52):
really getting into why wouldcustomers want to work with us?
Why would they not want to workwith a regional competitor who
might offer them a similar typeproduct at.
20 percent off list price thanwhat we could offer.
Now you're getting into not justthe total cost of ownership, but
the value really turning intowhat you do into, we provide
value and really turning thatinto customer speak in terms and
(17:16):
in language that they, clearlyunderstand.
Don Finley (17:18):
and I think that's the added benefit of what we're
seeing with some AI solutionstoday, is that you can have that
personalization, you can havethat connection to where the
client is at and what they'retrying to accomplish.
I know we're constantlyevaluating AI tools and in both
the solutions that we have, thatwe're currently using the
solutions that we're creating.
and one of those spaces thatI've always found interesting is
(17:42):
that inbound calling and ifsomebody is calling us, what are
they calling about?
and there's two areas to look atthis.
One, your IVR system today may,have some of the solutions.
but then additionally, when theydo get to a call, the transcript
is incredibly valuable, but forsomebody to listen in on,
thousands of hours of phonecalls and find the patterns,
(18:03):
it's not very effective.
Yet having an AI do that, youcan have it done in an hour and
it showcases Hey, If you addthis question to your IVR,
you've got a fairly low techsolution in the technology
space.
But then additionally, we canuse those transcripts to train a
customer service agent thatcould actually just be the AI
(18:23):
that answers the questions forthe client.
Helps to, propose solutions orat least identify it.
as well as logging thatinformation into your CRM so
that you can follow up on it
Ryan Mayes (18:34):
Yeah.
I,
Don Finley (18:35):
and so there's like varying levels of how you can
engage with this, both in a hightouch customer position, but
also a, Hey, this is for ourinternal benefit.
And then we'll make the
Ryan Mayes (18:45):
yeah, here within this last year, I can summarize
your call and send out themeeting notes.
the way that we do it at timesis, okay, I'm intensely
listening to you.
I'm typing.
And then after the call, I'mtaking 15 minutes to send a
summary.
that's a way to automate it.
I think you mentioned two usecases.
If I'm a customer calling you,you provide me with a
(19:06):
summarization of that phonecall.
So now you're providing apremium service to a customer
through automation that, priorto that, They would have to take
their own notes or take you attheir word.
And then from a team member oran internal perspective, what
are you using?
What are you doing to use thatinformation to, upscale your
team or to use that for someconstructive analysis in
(19:27):
enabling them to have a bettercall when that type of call
comes back?
I've in my previousorganization, we bolted on a
quality program that looked atkeyword research and, why are
customers calling us?
you've got the ticket count bytype.
that's great.
So you from a categorizationstandpoint, why they're calling
you, but getting into that voiceof customer program that takes
(19:47):
it much, much further in termsof customer sentiment and also,
tone.
And also some of the keywordsthat you can key in online.
Now I know, we've rolled out anew service, we've rolled out a
new program that transcendsticket types.
That voice of customer programthrough automation really comes
in handy and allows you and armsyou with.
(20:07):
Here's how we're going to runour business a little bit
different.
Don Finley (20:09):
Do you ever feel like inundated with information
now?
Ryan Mayes (20:13):
Yes.
I get just as much email asanyone else.
we're somewhat similar, like alot of organizations.
we have data everywhere.
We use more than one system.
And so the challenge of where'sthat one, consolidated database,
or that one customer record.
So, the other thing too is andI'm sure that you're aware of
(20:33):
this too, customers can reach anorganization through multiple
entry points.
They can talk to your salesteam, they can talk to your
operations team, maybe they talkto your product team.
And how would you know that?
and so not only are theremultiple entry points, there are
different types.
Of conversations.
I might talk to the operationsgroup or the customer support
team differently than I would mysales rep or my product,
(20:55):
engineer.
And so pulling all of thatconversation in to, this is
really what's going on with thecustomer.
Is difficult, it's challenging.
It's even more important if thecustomer is, a tier one type
customer.
They're spending a lot of moneywith you.
They're, they are integratedwith you at the hip and you're
going to grow with them.
(21:16):
And I think AI really is anopportunity to pull in all of
those records and all of thosedisparate pieces of information
to provide, a greater insightinto customer sentiment.
and tone.
Don Finley (21:28):
There's this, we basically, all of our companies
are being run on multipleplatforms right now, Like we're
all in the cloud and even ifyou're using Salesforce, you're
likely using Microsoft as well.
And so you've got a split ofsystems that can go on there.
like we have, a few differentsystems that we run this
business on.
But then additionally, we alsohave an aggregate of our own
(21:49):
like data lake, That we pullinformation into that like
stores everything.
And even as a technology firm, Ican tell you There's data that
we're collecting that we're notlooking at yet, So we haven't
made that switch from data toinformation in some capacity.
In most areas we are, Like thecore things that drive the
business, but I feel like everyorganization out there is
(22:10):
sitting on some massive pile ofdata that they know is valuable
to them, but they haven'tfigured out quite how to pull
that into like information andknowledge.
And I feel like that's whatyou're.
sharing here as well, is thatthere's an opportunity to really
understand your business betterfrom a holistic standpoint,
(22:31):
instead of having the disparateconnections that you have
between the, five, 10 systemsthat it takes to run operations.
Ryan Mayes (22:37):
would agree.
what I described as the firstchallenge is where, I'll secure,
where's all your data?
I've got this Excel file.
On my hard drive.
I've got this database overhere.
This system is 10 years old andreally no one's really updating
it.
Okay.
my billing system is way over onthe other side of the company.
that's the first part.
But to your point, the secondchallenge is, and I'm a big
(23:00):
proponent of performancemeasurement.
I cut my teeth on that, early inmy career and it really hasn't
stopped.
Performance measurement is notjust, a skill, it's an art.
And I think in my experience, asI've matured through my
organizational history, not alot of professionals and not a
lot of companies really key inon that.
Yes, they've got theirfinancials.
(23:21):
Yes, there's a P& L and we dosome strategic planning, but to
your point, do you really knowyour business well to the point
where you can turn right aroundand articulate it?
in front of a customer thatsecures a sale or describes
value or really entices them orencourages them.
You know what?
We're the right organization foryou because we can grow, with
(23:43):
you to meet your business needs.
And let me share with you all ofthe great success stories of
what I'm talking about withcustomers who are working with
us right now and performancemeasurement, in my opinion,
extends well beyond an OKR or aKPI.
I think that's a given you,you've got to be able to
measure, there's this adage, youreally can't improve what you
can't measure.
yes, everyone believes in that,but taking it into your point
(24:07):
about transitioning data intoreal information is an art.
And I think many organizationsreally lose on that because.
I can't really talk aboutinformation because my data is
in four different places.
what can you do to maybe connectthose points a little bit more
closely to the point where youcould transition that into more
of an informationalconversation?
And I think that's one of thedifferentiators for growing
(24:28):
agile organizations,particularly as we mentioned,
where problems are becoming muchmore complex and coming at us
quicker is Can you get to aninformation stage much faster?
to really help solve a problemquicker.
Don Finley (24:41):
That's incredible.
Ryan, one last question for you.
for people who are just gettinginto the game, so if you were to
speak to, Ryan from a year ago,what advice would you have for
him in, jumping into the AItransformation?
Ryan Mayes (24:54):
Myself from 12 months ago.
Wow.
I think what I would say is, wetalked about this a little bit
pre show.
I think lifelong problemsolvers.
Learners.
And whether you are in the earlyyears of your career or whether
you're at the midpoint orwhether you're in the back half
of your career, which is whereI'm beginning to find myself.
(25:17):
Continual learning and continualdevelopment is key.
I went into, I found this out alittle bit the hard way.
I've always been a big proponentof continual learning, but I
went through a job transition.
About seven years ago, I couldsee it coming, but I couldn't
get ahead of it.
And I went through a transitionand I started to take an
inventory of, all right, where'smy resume.
(25:39):
And, you go through the steps.
And what I found out was rathersobering was, a lot of my skills
and a lot of my credentials andso forth were somewhat aged.
And I began to talk, throughsome career counselors and some
career coaches, and I wasreceiving great feedback.
That sounded different.
it was because what I found outwas I was behind, I was several
(26:01):
years behind.
So that was the first part.
The second part was I could fixthis, but the sobering part was
I couldn't fix it overnight.
And so from that point, as Iwent through my search and year
subsequent, I made a vow thatI'm, I was going to try as best
as possible not to find myselfin a position where I'm
maniacally focused on my roleand growth of my role, but what
(26:23):
am I doing to learn outside ofmy role to increase my exposure,
to increase my depth of aparticular knowledge topic?
And what am I doing?
Intentionally to continuallydevelop.
And I know we talked about thispre-show, that's where AI came
into me.
I was introduced to it about 12to 15 months ago.
I got an email from anentrepreneur, Hey, I'm having
(26:45):
this product and launch service,program.
And it was a series of livesessions and recorded YouTube
videos.
and one of the YouTube videoswas on ai.
And I thought, well, I'll listenin on this.
This will be very interesting.
And it was one of those 10minute.
At the end of the video, I wasfloored because I saw during the
video how to use chat GPT andwhere taking an idea into
(27:12):
production or an opportunitythat could go to production.
Was fascinating.
And I happened to be sittingdown watching this video.
And at the end of it, I satthere for three or four minutes
and my head was spinning.
What are all of the use casesthat I could use AI for?
And the list is everything.
And so I, it
Don Finley (27:28):
list continues to
Ryan Mayes (27:29):
continues to grow.
And I vowed right then andthere, I'm going to find a way.
To make this a part of what I doin my personal and my
professional life.
And I think that's been one ofthe best decisions that I've
made in the last 12 to 15 years.
So that may be a little bit of along winded response to
continual learning anddevelopment is key.
(27:50):
Don't wait on your boss.
Don't wait on your company.
you are within reason.
the CEO of your career.
So what are you doing tocontinually grow and learn?
It could be a podcast, it couldbe a YouTube video.
I've attended many lectureswith.
Pad a paper and a pen in hand,full well intending to what are
the two or three things that Ican learn out of this 15 minute
(28:12):
talk that I can apply to mywork.
And it's through certifications.
It's through learning.
It's through all kinds ofthings, reading books.
it could be anything andeverything.
And so when you start thinkingof it that way, you are
inundated with boundlessopportunities.
And I think that would be my onepiece of advice that I would
give to myself 12 months ago, 25years ago, and continually
(28:34):
leaning in on that, as I workfor many years to come.
Don Finley (28:38):
I love it.
That's fantastic, Ryan.
And thank you so much for beinghere with us today.
So we all got to stay curiousand continue
Ryan Mayes (28:46):
Don, thank you so much.
I appreciate being a guest onyour podcast and I've had a
great time and thank you somuch.
Don Finley (28:53):
Thank you for tuning into The Human Code, sponsored
by FINdustries, where we harnessAI to elevate your business.
By improving operationalefficiency and accelerating
growth, we turn opportunitiesinto reality.
Let FINdustries be your guide toAI mastery, making success
inevitable.
Explore how at FINdustries.
(29:15):
co.
Welcome to The Human Code, the podcast where
technology meets humanity, andthe future is shaped by the
leaders and innovators of today.
I'm your host, Don Finley,inviting you on a journey
through the fascinating world oftech, leadership, and personal
growth.
Here, we delve into the storiesof visionary minds, Who are not
only driving technologicaladvancement, but also embodying
(00:23):
the personal journeys andinsights that inspire us all.
Each episode, we explore theintersections where human
ingenuity meets the cutting edgeof technology, unpacking the
experiences, challenges, andtriumphs that define our era.
So, whether you are a techenthusiast, an inspiring
entrepreneur, or simply curiousabout the human narratives
(00:44):
behind the digital revolution,you're in the right place.
Welcome to The Human Code.
Today, we're excited to welcomeRyan Mayes, a turnaround
specialist and innovation leaderwith a proven track record of
transforming high riskoperations into thriving
businesses as vice president ofprofessional services and
operations at fleet Corp.
(01:04):
Ryan oversee SAS delivery.
And corporate solutions acrossnorth America, consistently
driving growth, efficiency andcustomer satisfaction.
In today's episode, Ryan shareshis philosophy of focusing on
people, process and technologyto create sustainable change.
We'll explore how he'sleveraging AI to scale
operations, enhance customerexperiences and differentiating
(01:26):
competitive markets.
Ryan also highlights theimportance of lifelong learning.
Staying curious and adapting torapid technological advancements
to remain ahead of the curve.
Join us for an inspiringconversation about leadership
transformation and the practicalapplication of AI and reshaping
businesses for the future.
(01:47):
Ryan, it's a pleasure to haveyou.
And my first question is.
What got you interested in theintersection of humanity and
technology?
Ryan Mayes (01:56):
I think my, philosophy in my professional
roles has been to focus onpeople, process and technology.
When it comes to strategicinitiatives, strategic
roadmapping, I've keyed in onthose three areas.
And I have also believed thatThey're not isolated.
They're very much intertwined.
When you focus on one, you'reimpacting the other two.
(02:18):
And so I've had a lot of successin my career with, developing
plans and developing a visionand strategy with an executable
according to those three, mainthemes.
And so I have always thoughtthat.
People or team members are aidedor enhanced by using technology.
not as a replacement of team,because I think ultimately
whatever solution you're tryingto solve, people in many
(02:42):
organizations are considered tobe, a competitive advantage.
And so as you equip them withtechnology, not only are you
enhancing their ability toproduce or increase their
productivity, but the outcomesor solutions of which they are
providing either to an end useror to a customer are much more.
And so I think in my journeythrough, continual improvements,
(03:03):
Six Sigma and technologies suchas AI, I think there are
opportunities to, to be far moreaggressive with finding new ways
to do work, much more efficientand much more effective.
And I think in my experience,within the last year and a half
with AI, that falls right intomy methodology that I've
employed for many years.
(03:24):
In that AI is not a replacementof a solution per se, but it's a
wonderful tool to come to a moreeffective outcome quicker.
Don Finley (03:36):
and I think it's a nice paradigm to hold that
basically we're looking ataugmenting what people are doing
over the replacement idea And atthe same time it comes back to
this reflective point of whenwe're working on these things,
we're working on them for thesake of ourselves.
And I mean that not as a selfishendeavor, but in the endeavor of
we're doing it to solve problemsthat we have today, or we're
(03:59):
doing it to create somethingthat we've imagined that doesn't
exist today and To have toolslike AI can be really helpful.
in the last year, what have youseen as being the roadblocks to
your own adoption or, the areaswhere you thought it was going
to be super helpful and it, gaveyou pause.
Ryan Mayes (04:16):
I think some of the roadblocks that I've seen is, is
our team using the deliverablesor the output?
That I'm producing and that,that would be across the board
on any initiative.
But on, on this one, it's reallychanging the way that we work.
Instead of allowing a teammember or a salesperson or an
end user on the operations groupto solve the problem on their
(04:38):
own, we're coming alongside ofthem and providing them with.
Templates, articles, tools, newways of working.
And so user adoption, I think,is really key.
I don't think you necessarilyflip the switch overnight.
To say, now we're going througha new paradigm change and we're
going to work this way.
But I think you have to seeincremental change, and progress
(05:00):
and communicate those short termwins.
I've always been a bigproponent.
If you can't acquiretransformational change and then
at least try for incremental asopposed to doing nothing.
I think some of the successesthat I've seen is from a
marketing enablementperspective, providing our team
with far more, intimate anddetailed information on scripts,
(05:22):
playbooks, competitive analysis,landscape definition.
It really enables them to havemuch more one on one intimate
conversations with the customerthat are more targeted and more
pointed based upon who the enduser of the audience really is.
Don Finley (05:35):
And so I think you're using AI to help you to
create some of these artifacts.
Ryan Mayes (05:39):
Yes, because we went from, all right, we don't do
much to now we've gone from, nowwe have a catalog or a library
of content.
And I think it's not to me, thepart a, or the first part is,
okay, now we have content now,what do we want to do with it?
And I think, as I begin to takea look into next year, sort of
the year two, It's reallybringing all of that content
(06:01):
into a framework of, this is howwe work going forward.
This is the strategy or, thereal intent.
In terms of not just what weuse, but how we use it.
And the end result is, a greatervalue proposition, customer
conversation.
it's more targeted, I think,going forward as opposed to,
here's just a data dump.
And I think that's some of thethings that I'll probably key in
(06:24):
on next year.
to really key in on how weincrease our user adoption and
really increase our end resultsas well.
Don Finley (06:31):
it's funny.
So we were talking pre showabout the crawl, walk, run.
Kind of space, And what wasfunny is we were talking about
how you're in the crawl space ofHey, we're going to figure out
how we can utilize this.
It's a lot of trial and error.
It's seeing what sticks, findingthe places where it does add
value and you get morecomfortable with the solutions,
but then what you just describedis you're preparing to get into
(06:53):
that walk phase.
of actually making targetedapproaches and saying, Hey, if
we apply it here's how we knowwe can gain some efficiency.
And it's finding those three Xuse cases that enable you to
grow.
And so in thinking about 2025,what are some of the things that
excite you about this, liketechnology option that is,
coming to play?
what are some of the questionsthat you have there as
Ryan Mayes (07:15):
I think when I begin to consider what's next year,
you mentioned, crawl, walk, andI know we talked about that.
Pre show.
I'm a firm proponent oftransformational change.
I've been in situations in mostof my roles and most of my
career where you don't have theluxury of time to scale an
operation, to develop a visionthat has some type of, of an
(07:36):
aggressive, 18 month roadmap,you've got to, you've got to
move forward and prepare teamsfor.
Significant scale and scope,full well knowing that they're
not prepared for either one.
Because I've worked in manyorganizations in many roles
where there are hyper growth.
Environments, double digitgrowth year over year.
it would be very easy jokinglyto say, you know what?
(07:56):
I'll just shut this departmentdown for two years.
We'll retool and we'll startback up.
No, you have to do that whilethe bus is moving down the road
and the wheels are turning.
Now that's a very daunting,thought.
If you've never been in thatenvironment before, but as I've
matured throughout my career, Ilove those environments because
it's a wonderful opportunity.
You know what?
(08:16):
We're going to develop a plan.
we're going to really improveour team members experience by
focusing on people processingtechnology, like I said, and
within the current company thatI'm in now, I do believe that
using AI going forward as partof who we are and what we do,
that I think is the key goingforward.
It's not just what I'm doing.
(08:37):
Leading a particular corefunction within a business unit.
It's more or less transcendingto, what merchant services as a
real opportunity todifferentiate itself in the
marketplace, not just in termsof its value proposition, but
how we work, in terms ofdeveloping that value and what
we do with it to really provide.
More intimate and moresophisticated solutions to solve
(09:00):
our customer problems.
And I think that's where AIreally comes into allowing us to
scale more into thattransformative effort.
Like I mentioned,
Don Finley (09:08):
and coming into like the merchant services space, as
an industry, there are a lot ofsolutions in the merchant
services space for anybody who'staking payments in any form or
fashion.
And so like to be able to boththe services in new, innovative
ways, but additionally to helpthe customer to understand those
services.
(09:29):
cause it is somewhat daunting.
I spent some time in creditcard.
What's it when you actuallycreate the credit card?
I worked for Barclays for awhile.
we put credit cards on vendingmachines and help build like
Coke's platform as well.
And so I've seen it from numberof angles and the complexity of
the solutions that are availablethrough your business.
And that type of solution can bedaunting for a customer, but
(09:51):
then also understanding it on amonthly
Ryan Mayes (09:53):
it really is.
we're more or less working withthe retailer or the company, the
organization, but there is acustomer front end component.
the customer is I'm purchasingfuel.
I'm purchasing a product, andI'm swiping my card and then I'm
leaving.
But that's not the end of theorganization's responsibility.
There's the entire receiving ofthat payment.
(10:13):
And then there's the, all of thereconciliation and settlement
post transaction, the customeris long gone.
and so what we try to focus onis more of that end to end
customer experience, not justfrom the customer's perspective,
but also from.
the organization's perspectiveas well, and really, to your
point, I agree with you, thepayments industry, regardless of
(10:34):
whether it's fueling industry oranother sister type ancillary
industry is, could be conceivedas very commodity based.
everyone provides a point ofsale piece of hardware.
Everyone provides a paymentsolution.
Everyone wants to provide youwith a similar type experience.
But what I mentioned before is,what does our organization do
differently?
that really separates us fromour competitor base.
(10:55):
Our competitor base is.
It's regional, it's geographic,and it's also a nationwide or
enterprise.
So the way we go to market hasto vary based upon, are we
talking about, a national playor are we talking more of a
geographical or a regional playand I getting back to AI, I
think that's where we get into,much more sophisticated process
(11:16):
in terms of.
Defining our markets, definingour landscapes.
And then from there, how do weoperate within that particular
market or landscape differentlyin the Southeast than we would
say in California or in theWest, because they operate
differently.
In many ways, but you're right.
I think, transitioning a thoughtprocess into a value from a
(11:36):
commoditization type market intomore of a specialty, but also
focusing on scale and scope,because we have to not
necessarily churn throughcustomers.
That's not really who we are,but we have to reach solutions
faster.
And I think that's where AIreally comes into play with how
we operate our businessdifferently next year.
Don Finley (11:58):
it sounds like, you could come up with a, nationwide
plan, but have somehyperlocalization because of
what AI could help you
Ryan Mayes (12:06):
I think you're completely correct, Don.
our, our enterprise customersgenerate a certain percentage of
our revenue.
But when you start taking a lookat the base itself, now you're
starting to run into much more,what we call single or multi
unit owners.
And then what I call mid majors,they're geographically located
and they operate differently.
(12:26):
So we may sell one particularproduct or solution across all
three of those segments.
and most people do as well, theywill use that product
differently.
And I think that's where we getinto much more differentiation,
without, trying to figure out,we'll just go hire five more
people to run our marketingoutfit.
That's not really going tohappen.
And so I think using technologyto augment our current team.
(12:49):
and our base here is really oneof the things that I want to key
in on next year.
Don Finley (12:53):
Are you seeing any change in skills as far as your
base team in regards to how youwant to grow with, these
solutions that we're talking
Ryan Mayes (13:01):
Yes.
back in the day, sales cameeasier, and now they're not.
And I think within the fuelingindustry, it's far more
fragmented.
we have a lot of customers andcompanies that used to work with
us that no longer, becausethey're out of business.
And so the other thing that'shindering that is you see a lot
of new market, Now, they may benational, but they also may be
(13:21):
geographic as well.
So again, getting back to thatmarket landscape definition is
becoming more critical for us.
And then, pre show, we talkedabout within the fueling market,
a lot of our customers want toconsume solutions in the cloud.
So what is your product roadmap?
How are you moving in a way thatmeets customers where they are,
(13:42):
not necessarily where you wantthem to be?
And I think that is one of theother differentiators that I'd
like to key in on next year is,how do we meet customers and how
do we solve their problems wherethey are?
As opposed to, this is ourproduct.
Talking about your product orservice and your features is
always going to be important,but tying it into solving their
problems.
(14:03):
I think that's one of thedifferentiators that really
separates.
a growing company.
Don Finley (14:08):
Yeah.
what is that first order problemthat your customers are having
today?
That a new payment solutionwould help with, I know some of
our, for some of our like,service based businesses, Their
customer satisfaction is likenumber one as far as what's
driving decisions.
for other payment providers thatwe've worked with, like the,
(14:28):
their clients are looking forsomething along the lines of
like how quickly do they haveaccess to their cash?
what are the problems that yourcustomers are facing that you
feel like you could actuallysolve better, with AI
Ryan Mayes (14:42):
I think anyone, and we deal with this in our
personal lives as well.
customer support is usually onpage one, probably towards the
top third of the page.
if I call you, I want you topick up a phone.
If I email you, I want you towrite me back.
customer support is expensive.
in my previous organization, themethodology when I moved into
(15:03):
that new role was When we have acustomer call, we want a team
member picking up a phone.
That's great.
That worked when we were asmaller organization, but if we
want to continue to grow, that'sprobably not going to work.
And then we began to, do somedata analysis.
why are customers calling in?
they want to know where theirlocal store is.
(15:23):
They want to know if the storeis open today or their operating
hours.
Those were easy ones toautomate.
through an IVR.
And for us in the fuelingindustry, it's somewhat similar,
customer support, you can't hireenough people to pick up on
first ring, but what you can dois, what would life look like if
(15:44):
we provided customers with selfhelp?
what if we talked about maybeautomating some of those,
recurring questions that areeasily answerable?
and I think that's one area.
I think the other area iscommunicating to the customer
use cases.
white papers, maybe notnecessarily the documents
themselves, but what are othercustomers doing in working with
(16:08):
us, that are helping them runtheir business more profitable,
more profitably, helping themdrive revenue or increase market
share.
And I think, again, getting intothat, how do we somewhat
automate or provide additional.
AI type based resources toprovide with our sales team and
our sub support team.
really information that getsdown to the root cause of why
(16:29):
customers are even contacting usto begin with.
we're a market leader, we'rewell known, but.
Really getting beyond thecommodity type conversation into
problem solving and reallysolutioning and really growing
with customers as they grow.
I think those are some of thethings that we've had some
marginal success with to start,but I think really with AI
(16:52):
really getting into why wouldcustomers want to work with us?
Why would they not want to workwith a regional competitor who
might offer them a similar typeproduct at.
20 percent off list price thanwhat we could offer.
Now you're getting into not justthe total cost of ownership, but
the value really turning intowhat you do into, we provide
value and really turning thatinto customer speak in terms and
(17:16):
in language that they, clearlyunderstand.
Don Finley (17:18):
and I think that's the added benefit of what we're
seeing with some AI solutionstoday, is that you can have that
personalization, you can havethat connection to where the
client is at and what they'retrying to accomplish.
I know we're constantlyevaluating AI tools and in both
the solutions that we have, thatwe're currently using the
solutions that we're creating.
and one of those spaces thatI've always found interesting is
(17:42):
that inbound calling and ifsomebody is calling us, what are
they calling about?
and there's two areas to look atthis.
One, your IVR system today may,have some of the solutions.
but then additionally, when theydo get to a call, the transcript
is incredibly valuable, but forsomebody to listen in on,
thousands of hours of phonecalls and find the patterns,
(18:03):
it's not very effective.
Yet having an AI do that, youcan have it done in an hour and
it showcases Hey, If you addthis question to your IVR,
you've got a fairly low techsolution in the technology
space.
But then additionally, we canuse those transcripts to train a
customer service agent thatcould actually just be the AI
(18:23):
that answers the questions forthe client.
Helps to, propose solutions orat least identify it.
as well as logging thatinformation into your CRM so
that you can follow up on it
Ryan Mayes (18:34):
Yeah.
I,
Don Finley (18:35):
and so there's like varying levels of how you can
engage with this, both in a hightouch customer position, but
also a, Hey, this is for ourinternal benefit.
And then we'll make the
Ryan Mayes (18:45):
yeah, here within this last year, I can summarize
your call and send out themeeting notes.
the way that we do it at timesis, okay, I'm intensely
listening to you.
I'm typing.
And then after the call, I'mtaking 15 minutes to send a
summary.
that's a way to automate it.
I think you mentioned two usecases.
If I'm a customer calling you,you provide me with a
(19:06):
summarization of that phonecall.
So now you're providing apremium service to a customer
through automation that, priorto that, They would have to take
their own notes or take you attheir word.
And then from a team member oran internal perspective, what
are you using?
What are you doing to use thatinformation to, upscale your
team or to use that for someconstructive analysis in
(19:27):
enabling them to have a bettercall when that type of call
comes back?
I've in my previousorganization, we bolted on a
quality program that looked atkeyword research and, why are
customers calling us?
you've got the ticket count bytype.
that's great.
So you from a categorizationstandpoint, why they're calling
you, but getting into that voiceof customer program that takes
(19:47):
it much, much further in termsof customer sentiment and also,
tone.
And also some of the keywordsthat you can key in online.
Now I know, we've rolled out anew service, we've rolled out a
new program that transcendsticket types.
That voice of customer programthrough automation really comes
in handy and allows you and armsyou with.
(20:07):
Here's how we're going to runour business a little bit
different.
Don Finley (20:09):
Do you ever feel like inundated with information
now?
Ryan Mayes (20:13):
Yes.
I get just as much email asanyone else.
we're somewhat similar, like alot of organizations.
we have data everywhere.
We use more than one system.
And so the challenge of where'sthat one, consolidated database,
or that one customer record.
So, the other thing too is andI'm sure that you're aware of
(20:33):
this too, customers can reach anorganization through multiple
entry points.
They can talk to your salesteam, they can talk to your
operations team, maybe they talkto your product team.
And how would you know that?
and so not only are theremultiple entry points, there are
different types.
Of conversations.
I might talk to the operationsgroup or the customer support
team differently than I would mysales rep or my product,
(20:55):
engineer.
And so pulling all of thatconversation in to, this is
really what's going on with thecustomer.
Is difficult, it's challenging.
It's even more important if thecustomer is, a tier one type
customer.
They're spending a lot of moneywith you.
They're, they are integratedwith you at the hip and you're
going to grow with them.
(21:16):
And I think AI really is anopportunity to pull in all of
those records and all of thosedisparate pieces of information
to provide, a greater insightinto customer sentiment.
and tone.
Don Finley (21:28):
There's this, we basically, all of our companies
are being run on multipleplatforms right now, Like we're
all in the cloud and even ifyou're using Salesforce, you're
likely using Microsoft as well.
And so you've got a split ofsystems that can go on there.
like we have, a few differentsystems that we run this
business on.
But then additionally, we alsohave an aggregate of our own
(21:49):
like data lake, That we pullinformation into that like
stores everything.
And even as a technology firm, Ican tell you There's data that
we're collecting that we're notlooking at yet, So we haven't
made that switch from data toinformation in some capacity.
In most areas we are, Like thecore things that drive the
business, but I feel like everyorganization out there is
(22:10):
sitting on some massive pile ofdata that they know is valuable
to them, but they haven'tfigured out quite how to pull
that into like information andknowledge.
And I feel like that's whatyou're.
sharing here as well, is thatthere's an opportunity to really
understand your business betterfrom a holistic standpoint,
(22:31):
instead of having the disparateconnections that you have
between the, five, 10 systemsthat it takes to run operations.
Ryan Mayes (22:37):
would agree.
what I described as the firstchallenge is where, I'll secure,
where's all your data?
I've got this Excel file.
On my hard drive.
I've got this database overhere.
This system is 10 years old andreally no one's really updating
it.
Okay.
my billing system is way over onthe other side of the company.
that's the first part.
But to your point, the secondchallenge is, and I'm a big
(23:00):
proponent of performancemeasurement.
I cut my teeth on that, early inmy career and it really hasn't
stopped.
Performance measurement is notjust, a skill, it's an art.
And I think in my experience, asI've matured through my
organizational history, not alot of professionals and not a
lot of companies really key inon that.
Yes, they've got theirfinancials.
(23:21):
Yes, there's a P& L and we dosome strategic planning, but to
your point, do you really knowyour business well to the point
where you can turn right aroundand articulate it?
in front of a customer thatsecures a sale or describes
value or really entices them orencourages them.
You know what?
We're the right organization foryou because we can grow, with
(23:43):
you to meet your business needs.
And let me share with you all ofthe great success stories of
what I'm talking about withcustomers who are working with
us right now and performancemeasurement, in my opinion,
extends well beyond an OKR or aKPI.
I think that's a given you,you've got to be able to
measure, there's this adage, youreally can't improve what you
can't measure.
yes, everyone believes in that,but taking it into your point
(24:07):
about transitioning data intoreal information is an art.
And I think many organizationsreally lose on that because.
I can't really talk aboutinformation because my data is
in four different places.
what can you do to maybe connectthose points a little bit more
closely to the point where youcould transition that into more
of an informationalconversation?
And I think that's one of thedifferentiators for growing
(24:28):
agile organizations,particularly as we mentioned,
where problems are becoming muchmore complex and coming at us
quicker is Can you get to aninformation stage much faster?
to really help solve a problemquicker.
Don Finley (24:41):
That's incredible.
Ryan, one last question for you.
for people who are just gettinginto the game, so if you were to
speak to, Ryan from a year ago,what advice would you have for
him in, jumping into the AItransformation?
Ryan Mayes (24:54):
Myself from 12 months ago.
Wow.
I think what I would say is, wetalked about this a little bit
pre show.
I think lifelong problemsolvers.
Learners.
And whether you are in the earlyyears of your career or whether
you're at the midpoint orwhether you're in the back half
of your career, which is whereI'm beginning to find myself.
(25:17):
Continual learning and continualdevelopment is key.
I went into, I found this out alittle bit the hard way.
I've always been a big proponentof continual learning, but I
went through a job transition.
About seven years ago, I couldsee it coming, but I couldn't
get ahead of it.
And I went through a transitionand I started to take an
inventory of, all right, where'smy resume.
(25:39):
And, you go through the steps.
And what I found out was rathersobering was, a lot of my skills
and a lot of my credentials andso forth were somewhat aged.
And I began to talk, throughsome career counselors and some
career coaches, and I wasreceiving great feedback.
That sounded different.
it was because what I found outwas I was behind, I was several
(26:01):
years behind.
So that was the first part.
The second part was I could fixthis, but the sobering part was
I couldn't fix it overnight.
And so from that point, as Iwent through my search and year
subsequent, I made a vow thatI'm, I was going to try as best
as possible not to find myselfin a position where I'm
maniacally focused on my roleand growth of my role, but what
(26:23):
am I doing to learn outside ofmy role to increase my exposure,
to increase my depth of aparticular knowledge topic?
And what am I doing?
Intentionally to continuallydevelop.
And I know we talked about thispre-show, that's where AI came
into me.
I was introduced to it about 12to 15 months ago.
I got an email from anentrepreneur, Hey, I'm having
(26:45):
this product and launch service,program.
And it was a series of livesessions and recorded YouTube
videos.
and one of the YouTube videoswas on ai.
And I thought, well, I'll listenin on this.
This will be very interesting.
And it was one of those 10minute.
At the end of the video, I wasfloored because I saw during the
video how to use chat GPT andwhere taking an idea into
(27:12):
production or an opportunitythat could go to production.
Was fascinating.
And I happened to be sittingdown watching this video.
And at the end of it, I satthere for three or four minutes
and my head was spinning.
What are all of the use casesthat I could use AI for?
And the list is everything.
And so I, it
Don Finley (27:28):
list continues to
Ryan Mayes (27:29):
continues to grow.
And I vowed right then andthere, I'm going to find a way.
To make this a part of what I doin my personal and my
professional life.
And I think that's been one ofthe best decisions that I've
made in the last 12 to 15 years.
So that may be a little bit of along winded response to
continual learning anddevelopment is key.
(27:50):
Don't wait on your boss.
Don't wait on your company.
you are within reason.
the CEO of your career.
So what are you doing tocontinually grow and learn?
It could be a podcast, it couldbe a YouTube video.
I've attended many lectureswith.
Pad a paper and a pen in hand,full well intending to what are
the two or three things that Ican learn out of this 15 minute
(28:12):
talk that I can apply to mywork.
And it's through certifications.
It's through learning.
It's through all kinds ofthings, reading books.
it could be anything andeverything.
And so when you start thinkingof it that way, you are
inundated with boundlessopportunities.
And I think that would be my onepiece of advice that I would
give to myself 12 months ago, 25years ago, and continually
(28:34):
leaning in on that, as I workfor many years to come.
Don Finley (28:38):
I love it.
That's fantastic, Ryan.
And thank you so much for beinghere with us today.
So we all got to stay curiousand continue
Ryan Mayes (28:46):
Don, thank you so much.
I appreciate being a guest onyour podcast and I've had a
great time and thank you somuch.
Don Finley (28:53):
Thank you for tuning into The Human Code, sponsored
by FINdustries, where we harnessAI to elevate your business.
By improving operationalefficiency and accelerating
growth, we turn opportunitiesinto reality.
Let FINdustries be your guide toAI mastery, making success
inevitable.
Explore how at FINdustries.
(29:15):
co.
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