This week, I continue my deep dive into “knowledge in the contact center”—but this time, we're exploring a crucial aspect: Knowledge Operations. Joining me for the 2nd episode (#119) in this series is my colleague @Greg DeVore, co-founder of @ScreenSteps, who shares his expertise on how we can rethink training and knowledge transfer for contact center agents.
🔗Podcast link here: https://podcasts.apple.com/us/podcast/my-curious-colleague-cpg-cx/id1565590157
Key takeaways:
Reframing the Problem – Instead of focusing on teaching and memorization, Greg suggests we should focus on knowledge transfer, giving agents the tools to access what they need, when they need it.
📉 Cutting Onboarding Time by 10 Months – By shifting to a "Find and Follow" methodology, one company reduced agent proficiency time dramatically!
🤖 AI Needs Better Data – AI is only as good as the knowledge it's fed. The key is structuring and updating that knowledge so AI delivers reliable, actionable insights.
If you're looking for smarter ways to train and support your agents, don’t miss this conversation! 🎧
📖 Want to dive deeper? Check out Greg's book, Find & Follow, available on Amazon.
📌 Connect with Greg: Find him on LinkedIn or visit ScreenSteps.com to learn more.
#contactcenter #knowledgemanagement #ai #traininginnovation #cpgcx
Mark as Played
Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Denise Venneri (00:00):
Welcome to the My Curious Colleague podcast
(00:03):
with me, Denise Venneri. I am atwenty year practitioner in the
consumer engagement space havingworked for two large CPG
organizations. My intent here isreally to share best practices
with particular focus around thespecialist and analyst roles and
to give back to this greatcommunity because CPGCX rocks.
(00:30):
Hello, my curious colleagues. This week, I
continue to be curious aboutlearning more about knowledge in
the contact center. Yes. We'reback again for second in our
series. And today, we're talkinga little bit differently,
specifically more about what'sknown as knowledge operations
according to our guest.
(00:51):
And to help me understand justthat is my colleague, Greg
Devore, cofounder ofScreenSteps. Welcome to the
podcast, Greg.
Greg DeVore (01:00):
Thanks so much for having me. It's great to be
here.
Denise Venneri (01:03):
Of course. My honor. My honor. So let's get
the conversation started, andlet's begin with you telling us
how you got to here.
Greg DeVore (01:14):
Well, we started over twenty years ago, and we
were originally hired to helptrain doctors and sonographers
on three d 40 ultrasoundsystems. They're these $200,000
machines. And as we went intotheir offices, we found that
despite them being flown acrossthe country to be trained in
person and all this training,they were just filled with
(01:36):
sticky notes all over themachine. And we realized we're
really approaching this wrong.We need a better way.
We really just need a bettersticky note than when than than,
you know, super elaboratetraining. And that started us on
a journey where we eventuallybuilt a software platform that's
a knowledge operations platformtoday. But even more
(01:56):
importantly, we started reallystudying how are we training
people in operational knowledge,this this knowledge of how to do
things, how do I answerquestions, how do I solve
problems, and does it makesense, or do we need to kinda
take a step back and rethink ourwhole approach to this problem?
Which eventually led us to writea book and then develop a
(02:17):
methodology called find andfollow, which is a whole
different approach to how are wegonna train, especially agents
in a contact center so thatthey're confident, they're
independent, and they they canhandle all the change and
complexity that gets thrown atthem every day.
Denise Venneri (02:32):
Yes. God bless our agents, seriously. So you
said find and followmethodology. How do you go in
and teach folks about how to usethis find and follow
methodology? And just take methrough a little bit more
specifics on how that'sdifferent.
Greg DeVore (02:50):
Yeah. Well, the the first thing is it's it's a
methodology. It may not be forall contact centers, but contact
centers that deal withcomplexity and change. So if you
have a high level of complexityor a high level of change in the
contact center, which is mostcontact centers. Today.
Training. Yeah. To all the easystuff is kinda being taken away
by automation and AI, butthey're left with these complex
(03:14):
scenarios. If that's the thecase, training or teaching is a
strategy that can't work. It'slike pouring a gallon of water
into a 16 ounce cup.
It's too much information forthe the agents to absorb and
retain. And if you I mean,you've probably had this
experience. You see a new agentin training, and then they're
overwhelmed. It's there's somuch information coming down.
(03:38):
They're furiously taking notes.
And so what we said is there's agreat book. It's called What's
Your Problem? And it's all aboutreframing problems. Says if you
reframe a problem, you're gonnacome up with a radically
different solution because wetend to develop solutions
depending on how we frame theproblem.
Denise Venneri (03:55):
Right.
Greg DeVore (03:55):
So if you're I'm in a contact center and somebody's
not performing well, what's thefirst thing we say? We need
better training. And so traininginvolves teaching and
memorizing. How we reframe thatproblem is we need better
knowledge transfer. How can wetransfer knowledge to that agent
right in the moment they need itso that they can handle any of a
(04:16):
gazillion situations withouthaving to memorize all those
situations.
And when you do that, now wehave a whole different approach.
So I think of it as I have amusic background. I I have a
degree in music. I think of itif you're if you're a musician,
you know what sheet music is.Sheet music is designed so that
(04:37):
you can perform somethingwithout having to have it
memorized.
And if we design that sheetmusic right and I've got the
right skills, I can perform avery complex piece of music
without having to have it all inmy head. And, really, in good
musicians, they can bring it upand they can play right through
it the first time. So we wannathink of that with our agents.
We're enabling a performance forthem. This is like sheet music
(04:58):
for them that it's gonna guidethem through the call, through
the procedure without themhaving to put the caller on hold
or memorize a ton ofinformation.
So if we work there backwards,now we're gonna approach things
very differently. We're gonnadesign recipes, and this find
and follow framework helps us.The first step we do is we
(05:19):
separate out foundational andactual knowledge. So have you
ever seen those procedures thathas, like, well, this is why we
do this. It's because threeyears ago, this happened, and
now we need to make sure we dothat and x y z.
That's all foundationalknowledge that makes it hard for
an agent to follow a procedurein that moment. So what we do is
(05:40):
we pull all that out. We'll say,we'll teach them that
foundational knowledge, thatwhy, the what, you know, what
are the tools we're using, whydo we do this, and then we just
have them practice finding andfollowing actual knowledge,
which are designed like recipesor decision trees. It's kinda
like teaching them to use a GPSinstead of having them memorize
(06:02):
a book of maps.
Denise Venneri (06:03):
Right. So is it sort of like as you're talking
about it in in my world, whichwas CPG, it kinda feels like
consumer facing information,which there's consumer facing
information which you want theagents to understand. And then
there is nonconsumer facing,which is, like, the background
(06:23):
and maybe tips for the agentthat they don't want the
consumer to know about. Am Ithinking about that? Right?
Well, it's Like, it could be
Greg DeVore (06:33):
but but even more specific, it's what does the
agent do? So say somebody'scalling in and they have a
product and somebody ingested itor, you know, they they weren't
supposed to and now you've gotan emergency on your hand.
Right? Right. There's a certainprocedure that that employee
needs to follow.
Okay? You want them followingthe same procedure every time
when that situation comes up.And so they need to know, okay,
(06:56):
what the product is, the factthat this is an emergency. But
that recipe of exactly what theydo, they shouldn't memorize
that. We should bring that up sothey can follow it, and now
they're gonna be consistentevery time.
Or say that there's a productrecall, and now there's a
process that we need to get thatthat thing shipped back to us
and something else shipped outto them. There's a whole
(07:17):
procedure about that. It mightbe different. Are they in The
US? Are they outside of The US?
You know, has it been open? Hasit not? All those different
things, instead of teaching themthat, will give them a decision
tree that will guide them rightthrough the process in real
time. And that has a huge impactnow on if we're onboarding
agents. So we worked with oneorganization.
(07:39):
This was a public utility. Mhmm.It was taking twelve months for
an employee to becomeindependent to or to reach
proficiency. By adopting thissystem, they reduced that from
twelve months to about eight toten weeks.
Denise Venneri (07:53):
Mhmm. Mhmm.
Greg DeVore (07:53):
So you shave ten months off of the time it takes
for an agent to be confident andproficient. That has a big
impact on the contact center.
Denise Venneri (08:02):
Yeah. And to their satisfaction. I I I see
that. Can we can we do anotherexample of how a client may
maybe use this methodology andwhat their results were?
Greg DeVore (08:12):
Yeah. And this would be a good one on to show
the difference. It's it's amindset change. Right? So in
most times, we we think we wantour our agents to learn the
information.
And the more they memorize, themore valuable they are. In our
methodology, the more theymemorize, the less able they are
to change. And if we're dealingwith constant change, that's a
(08:32):
problem. So I'll give you twostories, actually. So we had one
group.
It would take two weeks forchange to go through their
contact center because you can'ttrain everybody at the same
time. You always had to havepeople on the phones. People
would be out. When they switchedto this mode of training, those
two weeks went down to less thana day because now people were
(08:53):
just notified when they cameinto work, x y procedure has
changed. Be aware of that whenyou bring it up.
And and they bring up the call,and it's like Google Maps. You
know, if the road closes, itjust reroutes you around it. So
now they can change instantly.Another good example is a group.
They were doing medical devicetroubleshooting, and they had to
(09:14):
stand up a brand new contactcenter in a hundred and twenty
days from scratch.
They got it out there. They gottheir training time down to two
weeks, and they came out of thegates, and their their quality
scores are 98%, and their SLA is90. So they're killing it.
They're doing great. After aboutthirty days, their stats started
dropping.
(09:34):
Now you would expect agents, themore experienced they are, to
get better, not worse. We wentin and interviewed the agents.
Said, what happened? Well, theysaid, well, in other contact
centers where we worked, it wasfrowned upon if you used the
documentation. It was frownedupon if you use the resources.
They wanted you to know it, andso they stepped away. And we
could see in the analytics inour platform that they had
(09:55):
stopped using it. And somanagement came in and said, oh,
no. We want you. We we don'twant you to memorize.
We want you to rely on this, andthose stats went right back back
up to where they are. So itshows that when we realize we're
not good at working from memory,we can perform much better.
Denise Venneri (10:13):
Interesting. Interesting. Hey. I'd be remiss,
excuse me, if I didn't bring upAI. Yes.
Artificial intelligence. Assomebody who's comes from the
background that I come from,which is two large CPG
organizations, you know, I I'malways like, wait. Are we behind
on AI? What's it gonna do? Whatare the use cases?
(10:34):
So tell me from yourperspective, I believe you're
more in, like, a regulatedregulated industries that you've
given examples on. How is AIused as a facilitator, or isn't
it?
Greg DeVore (10:50):
So AI can be used lots of different ways, and it's
important to understand whichways can you trust. So a lot of
organizations a great place forAI is, you know, quality reports
because that doesn't touch thecustomer at all. Right? It's not
affecting what they're saying.It can automate that the the the
quality measurements there.
Yes. Where people have been morehesitant or they've gotten a bit
(11:13):
burned is when they're a lot ofAI companies, if they're gonna
do agent assist or agentguidance, they'll tell you,
okay. Well, give us your junkdrawer of knowledge. You know,
give us your SharePoint, all thestuff you've got, and we're
gonna feed that to AI, and thenit will get generate answers for
your agents. Important thing tounderstand about AI is it's only
as good as the data you feed it.
Denise Venneri (11:34):
Sure.
Greg DeVore (11:34):
So it if if you're coming to AI, like, it's been
trained on all these generalizedknowledge that's out there, it
doesn't know anything about yourcompany. It doesn't know your
internal procedures. It doesn'tknow your policies unless you
give it to it. So if a lot ofthose things when we work with
organizations, we find a lot ofthat information is stuck in
(11:54):
people's heads.
Denise Venneri (11:56):
Mhmm.
Greg DeVore (11:56):
If it's stuck in people's heads, AI doesn't know
about it. It can't use it. Andwhen AI doesn't know what to do,
it tends to invent things.
Denise Venneri (12:03):
Mhmm.
Greg DeVore (12:04):
So the way we help organizations with AI is saying,
we just need to give it betterdata, and we'll use AI on that
side of things of capturing it.So the biggest challenge is how
do we get that information outof people's heads? And the
barrier to that is actuallywriting the documentation,
getting it out. So we'll use AI.We'll go in and interview them.
They're subject matter experts.We can take those transcripts
(12:26):
and run that through our AI thatthen creates very clear actual
paths and recipes or separatesout that foundational knowledge
that can then be used in oursystem or to feed other AI
systems. And now you can trustthe content that's being
generated or or used in AI.
Denise Venneri (12:45):
Got it. So it's being used very much in the
upfront building, it feels like.
Greg DeVore (12:51):
It's the building and the maintenance because
Mhmm. Yeah. People people don'tunderstand is when they look at
AI, they look at it as a projectof I'm gonna just write all this
documentation, train the AI, andit will work. But any contact
center that I've been a part ofis changing all the time. Sure.
So it's not a project. It's aprocess of continually updating
that AI with relevantinformation so that it can it
(13:14):
can do the right things.
Denise Venneri (13:16):
Got it. Okay. If folks wanted to find out more
about you and what you're up to,what's the next step, Greg?
Greg DeVore (13:25):
If you wanna learn more about the methodology find
and follow, we have a book onthat on Amazon.
You can find
it there. It has lots of contactcenter case studies and really
lays out this framework ofdramatically reducing the amount
of information we have to teachagents for them to perform, you
know, consistently andeffectively. And if they wanna
follow me on LinkedIn or reachout on LinkedIn, I'm there in
(13:47):
Greg Devore. I post a lot there.The company we have is
ScreenSteps.
You can find that atScreenSteps.com.
Denise Venneri (13:54):
Perfect. Perfect. Okay. So we are at the
end, and I really appreciate youtaking time this morning to,
speak with us.
Greg DeVore (14:02):
No. It's great to talk with you. Thanks so much.
You have been listening to theMy Curious Colleague podcast
with Denise Venere. Thank youfor your time.
Welcome to the My Curious Colleague podcast
(00:03):
with me, Denise Venneri. I am atwenty year practitioner in the
consumer engagement space havingworked for two large CPG
organizations. My intent here isreally to share best practices
with particular focus around thespecialist and analyst roles and
to give back to this greatcommunity because CPGCX rocks.
(00:30):
Hello, my curious colleagues. This week, I
continue to be curious aboutlearning more about knowledge in
the contact center. Yes. We'reback again for second in our
series. And today, we're talkinga little bit differently,
specifically more about what'sknown as knowledge operations
according to our guest.
(00:51):
And to help me understand justthat is my colleague, Greg
Devore, cofounder ofScreenSteps. Welcome to the
podcast, Greg.
Greg DeVore (01:00):
Thanks so much for having me. It's great to be
here.
Denise Venneri (01:03):
Of course. My honor. My honor. So let's get
the conversation started, andlet's begin with you telling us
how you got to here.
Greg DeVore (01:14):
Well, we started over twenty years ago, and we
were originally hired to helptrain doctors and sonographers
on three d 40 ultrasoundsystems. They're these $200,000
machines. And as we went intotheir offices, we found that
despite them being flown acrossthe country to be trained in
person and all this training,they were just filled with
(01:36):
sticky notes all over themachine. And we realized we're
really approaching this wrong.We need a better way.
We really just need a bettersticky note than when than than,
you know, super elaboratetraining. And that started us on
a journey where we eventuallybuilt a software platform that's
a knowledge operations platformtoday. But even more
(01:56):
importantly, we started reallystudying how are we training
people in operational knowledge,this this knowledge of how to do
things, how do I answerquestions, how do I solve
problems, and does it makesense, or do we need to kinda
take a step back and rethink ourwhole approach to this problem?
Which eventually led us to writea book and then develop a
(02:17):
methodology called find andfollow, which is a whole
different approach to how are wegonna train, especially agents
in a contact center so thatthey're confident, they're
independent, and they they canhandle all the change and
complexity that gets thrown atthem every day.
Denise Venneri (02:32):
Yes. God bless our agents, seriously. So you
said find and followmethodology. How do you go in
and teach folks about how to usethis find and follow
methodology? And just take methrough a little bit more
specifics on how that'sdifferent.
Greg DeVore (02:50):
Yeah. Well, the the first thing is it's it's a
methodology. It may not be forall contact centers, but contact
centers that deal withcomplexity and change. So if you
have a high level of complexityor a high level of change in the
contact center, which is mostcontact centers. Today.
Training. Yeah. To all the easystuff is kinda being taken away
by automation and AI, butthey're left with these complex
(03:14):
scenarios. If that's the thecase, training or teaching is a
strategy that can't work. It'slike pouring a gallon of water
into a 16 ounce cup.
It's too much information forthe the agents to absorb and
retain. And if you I mean,you've probably had this
experience. You see a new agentin training, and then they're
overwhelmed. It's there's somuch information coming down.
(03:38):
They're furiously taking notes.
And so what we said is there's agreat book. It's called What's
Your Problem? And it's all aboutreframing problems. Says if you
reframe a problem, you're gonnacome up with a radically
different solution because wetend to develop solutions
depending on how we frame theproblem.
Denise Venneri (03:55):
Right.
Greg DeVore (03:55):
So if you're I'm in a contact center and somebody's
not performing well, what's thefirst thing we say? We need
better training. And so traininginvolves teaching and
memorizing. How we reframe thatproblem is we need better
knowledge transfer. How can wetransfer knowledge to that agent
right in the moment they need itso that they can handle any of a
(04:16):
gazillion situations withouthaving to memorize all those
situations.
And when you do that, now wehave a whole different approach.
So I think of it as I have amusic background. I I have a
degree in music. I think of itif you're if you're a musician,
you know what sheet music is.Sheet music is designed so that
(04:37):
you can perform somethingwithout having to have it
memorized.
And if we design that sheetmusic right and I've got the
right skills, I can perform avery complex piece of music
without having to have it all inmy head. And, really, in good
musicians, they can bring it upand they can play right through
it the first time. So we wannathink of that with our agents.
We're enabling a performance forthem. This is like sheet music
(04:58):
for them that it's gonna guidethem through the call, through
the procedure without themhaving to put the caller on hold
or memorize a ton ofinformation.
So if we work there backwards,now we're gonna approach things
very differently. We're gonnadesign recipes, and this find
and follow framework helps us.The first step we do is we
(05:19):
separate out foundational andactual knowledge. So have you
ever seen those procedures thathas, like, well, this is why we
do this. It's because threeyears ago, this happened, and
now we need to make sure we dothat and x y z.
That's all foundationalknowledge that makes it hard for
an agent to follow a procedurein that moment. So what we do is
(05:40):
we pull all that out. We'll say,we'll teach them that
foundational knowledge, thatwhy, the what, you know, what
are the tools we're using, whydo we do this, and then we just
have them practice finding andfollowing actual knowledge,
which are designed like recipesor decision trees. It's kinda
like teaching them to use a GPSinstead of having them memorize
(06:02):
a book of maps.
Denise Venneri (06:03):
Right. So is it sort of like as you're talking
about it in in my world, whichwas CPG, it kinda feels like
consumer facing information,which there's consumer facing
information which you want theagents to understand. And then
there is nonconsumer facing,which is, like, the background
(06:23):
and maybe tips for the agentthat they don't want the
consumer to know about. Am Ithinking about that? Right?
Well, it's Like, it could be
Greg DeVore (06:33):
but but even more specific, it's what does the
agent do? So say somebody'scalling in and they have a
product and somebody ingested itor, you know, they they weren't
supposed to and now you've gotan emergency on your hand.
Right? Right. There's a certainprocedure that that employee
needs to follow.
Okay? You want them followingthe same procedure every time
when that situation comes up.And so they need to know, okay,
(06:56):
what the product is, the factthat this is an emergency. But
that recipe of exactly what theydo, they shouldn't memorize
that. We should bring that up sothey can follow it, and now
they're gonna be consistentevery time.
Or say that there's a productrecall, and now there's a
process that we need to get thatthat thing shipped back to us
and something else shipped outto them. There's a whole
(07:17):
procedure about that. It mightbe different. Are they in The
US? Are they outside of The US?
You know, has it been open? Hasit not? All those different
things, instead of teaching themthat, will give them a decision
tree that will guide them rightthrough the process in real
time. And that has a huge impactnow on if we're onboarding
agents. So we worked with oneorganization.
(07:39):
This was a public utility. Mhmm.It was taking twelve months for
an employee to becomeindependent to or to reach
proficiency. By adopting thissystem, they reduced that from
twelve months to about eight toten weeks.
Denise Venneri (07:53):
Mhmm. Mhmm.
Greg DeVore (07:53):
So you shave ten months off of the time it takes
for an agent to be confident andproficient. That has a big
impact on the contact center.
Denise Venneri (08:02):
Yeah. And to their satisfaction. I I I see
that. Can we can we do anotherexample of how a client may
maybe use this methodology andwhat their results were?
Greg DeVore (08:12):
Yeah. And this would be a good one on to show
the difference. It's it's amindset change. Right? So in
most times, we we think we wantour our agents to learn the
information.
And the more they memorize, themore valuable they are. In our
methodology, the more theymemorize, the less able they are
to change. And if we're dealingwith constant change, that's a
(08:32):
problem. So I'll give you twostories, actually. So we had one
group.
It would take two weeks forchange to go through their
contact center because you can'ttrain everybody at the same
time. You always had to havepeople on the phones. People
would be out. When they switchedto this mode of training, those
two weeks went down to less thana day because now people were
(08:53):
just notified when they cameinto work, x y procedure has
changed. Be aware of that whenyou bring it up.
And and they bring up the call,and it's like Google Maps. You
know, if the road closes, itjust reroutes you around it. So
now they can change instantly.Another good example is a group.
They were doing medical devicetroubleshooting, and they had to
(09:14):
stand up a brand new contactcenter in a hundred and twenty
days from scratch.
They got it out there. They gottheir training time down to two
weeks, and they came out of thegates, and their their quality
scores are 98%, and their SLA is90. So they're killing it.
They're doing great. After aboutthirty days, their stats started
dropping.
(09:34):
Now you would expect agents, themore experienced they are, to
get better, not worse. We wentin and interviewed the agents.
Said, what happened? Well, theysaid, well, in other contact
centers where we worked, it wasfrowned upon if you used the
documentation. It was frownedupon if you use the resources.
They wanted you to know it, andso they stepped away. And we
could see in the analytics inour platform that they had
(09:55):
stopped using it. And somanagement came in and said, oh,
no. We want you. We we don'twant you to memorize.
We want you to rely on this, andthose stats went right back back
up to where they are. So itshows that when we realize we're
not good at working from memory,we can perform much better.
Denise Venneri (10:13):
Interesting. Interesting. Hey. I'd be remiss,
excuse me, if I didn't bring upAI. Yes.
Artificial intelligence. Assomebody who's comes from the
background that I come from,which is two large CPG
organizations, you know, I I'malways like, wait. Are we behind
on AI? What's it gonna do? Whatare the use cases?
(10:34):
So tell me from yourperspective, I believe you're
more in, like, a regulatedregulated industries that you've
given examples on. How is AIused as a facilitator, or isn't
it?
Greg DeVore (10:50):
So AI can be used lots of different ways, and it's
important to understand whichways can you trust. So a lot of
organizations a great place forAI is, you know, quality reports
because that doesn't touch thecustomer at all. Right? It's not
affecting what they're saying.It can automate that the the the
quality measurements there.
Yes. Where people have been morehesitant or they've gotten a bit
(11:13):
burned is when they're a lot ofAI companies, if they're gonna
do agent assist or agentguidance, they'll tell you,
okay. Well, give us your junkdrawer of knowledge. You know,
give us your SharePoint, all thestuff you've got, and we're
gonna feed that to AI, and thenit will get generate answers for
your agents. Important thing tounderstand about AI is it's only
as good as the data you feed it.
Denise Venneri (11:34):
Sure.
Greg DeVore (11:34):
So it if if you're coming to AI, like, it's been
trained on all these generalizedknowledge that's out there, it
doesn't know anything about yourcompany. It doesn't know your
internal procedures. It doesn'tknow your policies unless you
give it to it. So if a lot ofthose things when we work with
organizations, we find a lot ofthat information is stuck in
(11:54):
people's heads.
Denise Venneri (11:56):
Mhmm.
Greg DeVore (11:56):
If it's stuck in people's heads, AI doesn't know
about it. It can't use it. Andwhen AI doesn't know what to do,
it tends to invent things.
Denise Venneri (12:03):
Mhmm.
Greg DeVore (12:04):
So the way we help organizations with AI is saying,
we just need to give it betterdata, and we'll use AI on that
side of things of capturing it.So the biggest challenge is how
do we get that information outof people's heads? And the
barrier to that is actuallywriting the documentation,
getting it out. So we'll use AI.We'll go in and interview them.
They're subject matter experts.We can take those transcripts
(12:26):
and run that through our AI thatthen creates very clear actual
paths and recipes or separatesout that foundational knowledge
that can then be used in oursystem or to feed other AI
systems. And now you can trustthe content that's being
generated or or used in AI.
Denise Venneri (12:45):
Got it. So it's being used very much in the
upfront building, it feels like.
Greg DeVore (12:51):
It's the building and the maintenance because
Mhmm. Yeah. People people don'tunderstand is when they look at
AI, they look at it as a projectof I'm gonna just write all this
documentation, train the AI, andit will work. But any contact
center that I've been a part ofis changing all the time. Sure.
So it's not a project. It's aprocess of continually updating
that AI with relevantinformation so that it can it
(13:14):
can do the right things.
Denise Venneri (13:16):
Got it. Okay. If folks wanted to find out more
about you and what you're up to,what's the next step, Greg?
Greg DeVore (13:25):
If you wanna learn more about the methodology find
and follow, we have a book onthat on Amazon.
You can find
it there. It has lots of contactcenter case studies and really
lays out this framework ofdramatically reducing the amount
of information we have to teachagents for them to perform, you
know, consistently andeffectively. And if they wanna
follow me on LinkedIn or reachout on LinkedIn, I'm there in
(13:47):
Greg Devore. I post a lot there.The company we have is
ScreenSteps.
You can find that atScreenSteps.com.
Denise Venneri (13:54):
Perfect. Perfect. Okay. So we are at the
end, and I really appreciate youtaking time this morning to,
speak with us.
Greg DeVore (14:02):
No. It's great to talk with you. Thanks so much.
You have been listening to theMy Curious Colleague podcast
with Denise Venere. Thank youfor your time.
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