April 23, 2024 • 19 mins
In this episode, we talk to Greg Williams, VP at Western Computer, about the evolving role of systems integrators in the tech landscape. Greg shares insights on the shift from traditional software roles to modern integrations that demand a new breed of IT professionals. We discuss the impact of AI and machine learning on everyday business operations and explore how companies can navigate the transition to digital-first operations. Greg emphasizes the importance of adopting new technologies like AI to stay competitive, highlighting the motto "automate or die" as essential for business survival in the digital age.
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Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to Tectastic, where we navigate theintersection of technology and business,
uncovering innovations that redefine our world.
Greg, how are you?
Hello.
Good afternoon.
You're currently the VP at western computer,what what role do you play in the industry?
(00:21):
Yeah.
So we are a systems integrator, but focused,business applications.
Like ERP, accounting, inventory control, ecommerce, all the back end office systems.
It's actually interesting that we're talking mycompany, Volley AI, works with a lot of
solution systems integrators, because whatwe're trying to do is solve the the tech debt
(00:43):
accumulation problem we have a we built out aplatform that's really robust and, quite
capable, but we built our first product on topof it, which is basically just a I think the
easiest way to describe it is it your PR buddyor your code review, assistant that goes
through and looks at your overall architectureand makes for improving your patterns, like the
(01:03):
things that you're doing in your pull request.
That's cool.
It makes me think of the quote a couple weeksago from the NVIDIA CEO.
I don't know if he saw it, but he said our jobis to make the coding easy enough that anyone
can do it that we don't need trained developersanymore, and I thought that
was interesting.
Yeah.
So this is actually what I set out to do.
So I've been in AIML for, jeez, 20 years, atleast, in one former another.
(01:28):
Yeah.
But chat, GPT, when it hit, was a big eyeopener.
We were doing predictive systems for, like,when's your package gonna arrive?
That type
of thing.
But to all of a sudden, have this tool, anybodycan be a programmer now.
Right?
Right.
And that was the eye opener for me with chat iswhen it came out.
I went, oh my god.
This is actually that moment because now thecomputer's talking to me in the way that I
(01:52):
understand.
I don't have to talk to it in a way that itunderstands.
Yes.
That opens up every door for automation, fordoing all the fun stuff us wizards of the
technology world, you know, that our keenknowledge that we Hammer.
Now everybody's got access.
That's what it thought.
Yeah.
We're not there yet.
Right.
And that big gap is what Valla actually set outto do.
(02:12):
My original thing that I wrote a year ago wastrying to fill that gap to say it's not
actually true yet.
You say you wanna build something.
You're, like, my the person I always use is mywife.
Multiple advanced degrees, lots of professionalcertifications, all that kind of fun stuff.
But when she gets hired by a company to takeall that experience and knowledge and put it to
practice, what does she end up doing?
(02:33):
She ends up managing technology systems thatdon't do a very job solving the problem.
Right.
And she always needs IT tech support to make itdo those things.
Yes.
So how do you fill that gap?
That's what I tried to build and ended up beingthat there's a lot of a lot of reasons why that
doesn't work.
There's a reason that SIs exist.
Right.
Right?
And it's about that complexity of that ERP andthat CMS and the the all the WMS and all the
(02:57):
systems,
right,
that you've gotta be able to work in thatspace.
I might be a little jaded, but sometimes Ithink technology just keeps repackaging itself
into the latest solution.
So it was interesting to hear you say thatwe've had AINML for 20 years because we have.
Yeah.
For guys like us, we could use it, but itwasn't accessible to everybody else.
(03:17):
And it still isn't, but I remember, you know,15, 20 years ago, the big thing was workflow.
Yeah.
And you would go do a software demo, andeverybody all the executives would be like, can
I workflow that?
Can I workflow that?
Can I re and be sure you can workflow it allyou want?
And then you get in the project, And, ofcourse, the workflow wouldn't do it.
You'd have to have a developer come in andextend the workflow.
(03:38):
And the developer would be looking at mesaying, don't I just write this the way you
need it instead of using this workflow?
You know, it's funny.
The you're describing exactly how I think of ittoo.
I've gone full circle on the open sourcecommunity and componentization of everything,
but it goes back to, like, when I sit down andwrite something myself, I don't use any
(03:59):
external packages.
I never do.
I hate them because I spend more time figuringout how to implement it with their little
library than just sitting on a writing myself.
Right.
As we sort of building out this company and,like, looking at those similar problems, every
time you use an off the shelf solution forsomething.
If it's your ERP or your CMS or whatever,you're pulling forward a bunch of past
(04:19):
decisions that have been made.
And a lot of those decisions were made toabstract away some concepts so that, like,
theoretically, you could integrate with it.
That's what most of solutions, systemsintegration solutions integration is is making
folks talk to each other.
Yeah.
And any conversation with external vendors orother software companies that you're trying to
(04:39):
integrate with, the first few meetings are allagreeing on terminology.
What is your depth of the word container,right?
Is it a box or is it a shipping container?
Cause it's different in in the MicrosoftDynamics software that we integrate all the
time.
They use that word container very directly.
It could be in cardboard box, or it could be apallet, or it could be anything.
It's just a word for them.
But then sometimes if you tell a developer weneed to do something with the container,
(05:02):
they're thinking something entirely different
K.
Yeah.
They're thinking about.
Yeah.
Right.
Exactly.
So all these meetings come down to let's agreeon the terminology first, and then let's then
let's go from there.
Yeah.
I gave a talk a long time ago on the definitionof done.
Because I think that's the first thing you haveto define.
Right?
When we say we're agreeing to deliver thisthing, what are we delivering?
(05:23):
Fully.
Everybody's expectations put all on the table.
We need to know the full definition of done.
And people get angry with you when you try tostart at that point because they're like, well,
everybody knows what that means.
Like, you and you just gave differentdefinitions for what we say when we mean done.
When I say done, I mean, it's fully test.
It's fully deployed.
It's fully that customers can use it, then it'sdone.
Right.
And as a systems integrator in the ERP world,it's never done.
(05:47):
You're constantly evolving that system.
And we get customers, you know, we, we buildthe code, we build the system, we get them
live.
We do 2 weeks of training.
The team thinks they're done.
And then the accounting people say, oh, no.
We're not done.
We gotta close our 1st month and finalize that.
Then we're done.
And then we get backed operations well.
There's all these things you told us we'regonna be phase 2 that we couldn't get to in the
(06:10):
implementation.
Now we gotta do those, or we're not done.
So we do and in our world, actually, it feelslike we're never done.
We're constantly optimizing these systems.
But I I wonder, isn't that the business model,isn't that the whole point of being in that
space?
Is that there's always more automation that thecompany needs and wants.
And that's a good thing.
Yes.
It is.
It's a great thing.
(06:31):
Yeah.
And, you know, we're looking for 10 to 5 teenyear or longer relationships with our
customers.
And we have those.
And we're there to advise them.
We're there to guide them on, you know, whattechnology trends are coming out.
So for example, a lot of them are coming to usright now and saying, hey.
What's you know, how should I use this AI?
And most of the times, well, you're not quiteready for it.
You're still figuring out this whole, like,cloud migration that you should have done 10
(06:54):
years ago.
Yeah.
Exactly.
Yeah.
That's true.
I I got to know that the SI space pretty well,you know, my last 15 years roles because it was
kind of my secret weapon.
I get pulled in by, like, a Nike to increasetheir rate of digital innovation And you have
the same problems at every company.
If you're not Google, Facebook, Amazon,Netflix, or a couple others, where all the best
(07:15):
engineers are gonna be drawn boards.
Yes.
It is very difficult to get critical mass, andyou have to have it.
So you build up these big teams with, you know,maybe you've got 10% of just amazing people in
your team, but that other 90% dragging on itand making it very difficult to proceed.
So you've got the people You've got a culturalproblem because you're not a digital first
(07:36):
company.
You're, you know, you're you sell shoes, nottechnology.
Right.
And so I would bring in these hired guns thathad critical mass.
That's what the that that was a whole business,right?
Right?
You've gotten great people.
So I'd bring them in and say, okay.
We are going to migrate from on prem to in thecloud, we're gonna migrate from x to y because
I'm trying to pay down this colossal amount oftechnical debt that's been built up over time.
(07:59):
And I know and you know that this is just thebeginning of that process because that
technical debt also stopped all the otherthings that the business wanted.
You know, I'm in sales.
I need to know whatever.
I'm in marketing.
I need to know something specific.
I'm in inventory management.
I need to have predictive, etcetera.
Right?
(08:20):
All those wants, they don't even ask anymore.
And the instant you plug that bottleneck.
And all of a sudden, the technology unlocksopportunity within the business, which is the
whole point of doing soft are.
We're automating
Yes.
All these things.
Yes.
And automation is where it's at.
I mean, that's where every company eats more ofthat if they're gonna survive.
You either More
(08:40):
automation faster.
Yeah.
It's it's it's automator die, really.
I mean, that's what it comes down to.
Years ago, I did a go live of a warehousemanagement system.
This is when I was still doing projects myself,and it was rough go live.
Inventory wasn't correct.
Long story short, we had to stop the go live,count the whole warehouse, we're there till 4
Hammer, back at 8 AM and everything workssmoothly after that.
(09:03):
And at the end of the 3 or 4 days on-sitethere, The owner of this manufacturing company
asked to meet with us, call us on the carpet.
And he said, in World War 2, we built theB-fifty 2 bomber with the big chief pencil and
a pad of paper.
Why do we need all these computer systems?
And I gotta give a CFO credit because with astraight face, he said, well, in 1985, you had
(09:24):
25 people in accounting, and now you have 5.
Do you wanna go back and hire all those people?
Well, here, I'll give the counterargument,though.
How many software engineers do you have on theteam now?
Right.
Yeah.
He's got 4 IT guys.
There there is a counterargument there.
But we are getting more efficient over time.
Absolutely true.
Yeah.
And the the long arc of history, like, moreautomation, less and less human intervention,
(09:48):
especially where we're not good.
Like, accounting is it's not something thatpeople wake up at night and go, oh, I can't
wait to get pen and paper and figure out wherethe books have gone wrong.
Like, nobody want, well, not nobody.
There are some people like that.
Christian.
Very few
people like this.
Right?
I have never worked with some of them, so Ihave to defend them.
(10:09):
I I do too.
As I said, I was like, no, there's a lot ofthem.
I'm not as many as it has been needed, but Ithink that we're actually It's very telling in
the moment in time that we're in.
I said that there's a a lack of critical massin most companies to meet the needs of their
technology wants and desires.
That's been true for a while.
And for the first time, that barriers droppedto the floor with this, you know, set of
(10:31):
generative AI tools that are coming into theworld, The problem, though, is it's still that
gap between what I have and what I desire, andI can't fill it without having some software
development teams get involved to British.
So you might have an AI tool that allows you todo, like, Hey.
I can automatically generate a bunch ofspreadsheets and all that.
That's fun, but it doesn't connect into my ERP.
(10:54):
Right.
But what we're seeing is that desired statecoming, like, it's getting really high, really
fast, but we still have this huge gap betweenhow many soft engineers in the world are
capable of building into those systems and thedesires of the business and the people in the
business to do something with it, but we'restarting to also see price pressure on, that
(11:17):
top line, like, hourly billable rate that SIScan charge is down, like, 20% in the last year.
Because there's this perception that, like, oh,no.
I just have my own teams do it with this AItool, which isn't there yet.
Right.
Oh, yeah.
We tend to deal with companies in the small andmid market.
So less than 500,000,000 revenue for the mostpart, let's say.
(11:38):
So they don't have especially at the lower endof that, they don't have big IT teams.
They depend on SIs for everything.
Maybe they have a few guys in IT but we'reseeing a number of challenges to that market.
One of them is, as they transition to thecloud, they need a different skill set from
their IT team.
Yeah.
Big time.
They have IT guys that are used to patchingservers and interacting with SQL and stored
(12:02):
procedures and stuff like that.
And now it's like, you're gonna write codeagainst an API, or, you know, it's entirely
different skill set.
Yeah.
So that's that's the major shift we're seeingas as these small to midsize businesses
digitally transform into the cloud, they need adifferent, level of staffing internally.
So part of a transition when you're coming in,you're doing these these and you're trying to
(12:24):
help them modernize.
Part of it is getting the staff that's there upto that skill level.
I imagine part of it's also like, no.
We're gonna help you hire somebody that has thenecessary knowledge because you've got too much
resistance and not enough there there.
Yeah.
How do you engage with that, especially theseSMBs, the small and medium businesses?
We usually educate them upfront that it isgonna be at the leadership level.
(12:46):
Hey, this is a different IT skill set.
It's more business analyst and less hardwareguy.
And that's the way we explain it at the SMBlevel.
They need to be comfortable working with dataand workflows and maybe a little bit of code
here and there, they don't need to knowanything about hardware anymore.
They don't need to know how to patch a server.
They don't need to know the firmware of theirrate controller, which are old problems that we
(13:06):
had, And so we explain it that way, and then wetell them, hey.
If we can help you get your people up to speed,or we can help you find someone to augment them
if necessary.
This is related because I wanted to touch onthe people piece of it.
Yeah.
A lot of the people listening to this havetheir own startup.
They might be early in their startup.
That's generally common audience.
Right?
And one of the hardest parts of any leader intheir first company that running when you're
(13:30):
the the buck stops your person trying to figureout how to get the most out of the team that
you've got knowing full well that they aregoing to be missing a lot of the skills and
experience necessary to effectively do the jobthat they're in today.
Everybody in your startup is in the biggestrole of their lives.
This is the biggest opportunity they've takesfull of overhead.
So you've gotta get the maximum amount of themand help them learn what they don't know fast.
(13:52):
Like, speed is the only thing that Hammer.
Right?
Right.
What advice do you give to people in thatsituation?
I think as a manager, a couple things, youknow, failure is okay.
Failure without an explanation or any guidancethat you may fail is is not okay.
So make it a safe space for them.
Provide them with the tools to ramp on thingsas much as you can.
(14:15):
But I think, generally, it's all aboutcommunication and saying, Hey, it's it's okay
if you if you don't miss this deadline, butgive me a few days notice ahead of time and let
me know you might need some help.
So what what you don't wanna hear is theengineer that goes heads down on an issue for 5
days and doesn't make any headway on it.
Mhmm.
You want them after one day to raise his handand say, hey.
I need some help here.
Please please help.
(14:36):
Yeah.
Working with younger engineers that's been thebiggest thing I've seen them do is put heads
down trying to solve something and not getanywhere on it.
And then come to me 3, 5 days later and say,well, I wanted to bang my head up against this
because I wanted to learn something new.
And I wanted to expand my skill set in like,well, we could have gotten you some help after
day 1, and you would have learned it and youstill would have expanded your skill set.
(14:56):
Heads down at it for 5 days didn't helpanybody.
So the, the real time business data ones isreally important on the start up too.
Oh, yeah.
I mean, profiles looking at going, yeah, that'sa really important one too.
A lot of people screw up with, like, OKRs andtheir KPIs and all that kind of stuff because
they're focused on the wrong thing.
So knowing what good data is to make gooddecisions is a difficult thing to do.
(15:21):
It is.
It's very hard to get to relevant data.
Yeah.
You have any, like, high level guidingprinciples that help you determine if it is
good data to guide you?
We just went through as a company.
And it was an intensive workshop at theleadership level
Mhmm.
To align on those and then come up with themand then come back a week or 2 later and
(15:43):
challenge them again.
And that's what works.
And that's what worked for us.
And again, make it safe, no judgment,brainstorm, agree on things, and then come back
and tweak it again.
That's the best way that we found to align onOKRs and KPIs.
The guidance I've I try to get people on thisis very similar to that.
Like, you're gonna make a mistake.
(16:05):
Your measurements are supposed to be the, youknow, you formed a hypothesis of your business,
and you're gonna form an experiment that'sgonna be your product or service that you're
putting in market, the data you want back isconfirmation of the success or failure of that
experiment.
That's what you need to know.
Yep.
Right?
So what does that look like in your specificcase, well, it might be.
(16:25):
I had a lot more customers today than I didyesterday.
Maybe that's the data you needed.
Right.
Or might have a lot more engagement product Ihad, but it's going to be unique to you, more
than likely.
Your experiment is unique to you, but you'reprobably gonna have to change it if you change
the
Yeah.
If you pivot or whatever, you know, that you'reyou're changing something, you probably got to
change it.
So you can't be wholly grayish about your KPIsbecause in a good situation, you're learning
(16:48):
and gonna learn that they were the wrongmeasurement.
Yeah.
It was a it was fun exercise for me because Ihave 20 years of tribal knowledge in this
business.
And then we had other people that didn't havetribal knowledge.
But they Hammer different way of looking atthings, and they had more experience with
formal KPIs and OKRs.
So to get those people in a room in a line wasreally the best way to do it.
(17:09):
That mixture of tribal knowledge with overallbest practices really hit it for us.
And that's that's exactly right.
Combination of people that can challengeassumptions because maybe they're naive, and I
I use that in a nice way.
I don't mean, like, they're No.
I mean, I getcha.
Yeah.
But mixing that with lots of an experiencebecause the problem of experience is you're
(17:32):
blind to different ways of looking at it.
Yeah.
And, yeah, that's a good mix.
So we're we're actually over the time we hadallotted for recording, but I wanna give you a
chance to say it, like, if you wanted to givethe audience anything, to take away I know that
I wanna send them to westerncomputer.com ifthey wanna find out more about, daily business
operations, how to improve it, especially ifthey're a small to medium business with
(17:53):
profoundly large technology offering?
Yeah.
So we're a, western computer.
We've been doing this for 35 years.
We're a 100% Microsoft shop a systemsintegrator that focuses on delivering solid ERP
solutions and CRM solutions for small andmidsize businesses.
And that is a big area that they all have aneed and they often, don't recognize how many
(18:16):
workarounds they've created for their workflow.
Yeah.
Put this data in this spreadsheet then go overhere and send this email and then save this
document to SharePoint.
And and that's the first step of the process.
Yeah.
Then send an email to Bob, and Bob will, like,transcribe it into something else.
Yeah.
Exactly.
Well, Greg William, Western Computer.
(18:37):
It was wonderful having you on.
It's fantastic.
Thank you for being here.
Thanks, Christian.
Nice to meet you today, and, and I enjoyed ourpodcast.
And that's a wrap for this episode ofTectastic.
Wanna thank you personally for joining us, andwe'll see you next time.
Until then, keep exploring, and stay curious.
(18:58):
Thank you for listening.
If you are new here and enjoyed the content,please subscribe.
It really helps us out.
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Welcome to Tectastic, where we navigate theintersection of technology and business,
uncovering innovations that redefine our world.
Greg, how are you?
Hello.
Good afternoon.
You're currently the VP at western computer,what what role do you play in the industry?
(00:21):
Yeah.
So we are a systems integrator, but focused,business applications.
Like ERP, accounting, inventory control, ecommerce, all the back end office systems.
It's actually interesting that we're talking mycompany, Volley AI, works with a lot of
solution systems integrators, because whatwe're trying to do is solve the the tech debt
(00:43):
accumulation problem we have a we built out aplatform that's really robust and, quite
capable, but we built our first product on topof it, which is basically just a I think the
easiest way to describe it is it your PR buddyor your code review, assistant that goes
through and looks at your overall architectureand makes for improving your patterns, like the
(01:03):
things that you're doing in your pull request.
That's cool.
It makes me think of the quote a couple weeksago from the NVIDIA CEO.
I don't know if he saw it, but he said our jobis to make the coding easy enough that anyone
can do it that we don't need trained developersanymore, and I thought that
was interesting.
Yeah.
So this is actually what I set out to do.
So I've been in AIML for, jeez, 20 years, atleast, in one former another.
(01:28):
Yeah.
But chat, GPT, when it hit, was a big eyeopener.
We were doing predictive systems for, like,when's your package gonna arrive?
That type
of thing.
But to all of a sudden, have this tool, anybodycan be a programmer now.
Right?
Right.
And that was the eye opener for me with chat iswhen it came out.
I went, oh my god.
This is actually that moment because now thecomputer's talking to me in the way that I
(01:52):
understand.
I don't have to talk to it in a way that itunderstands.
Yes.
That opens up every door for automation, fordoing all the fun stuff us wizards of the
technology world, you know, that our keenknowledge that we Hammer.
Now everybody's got access.
That's what it thought.
Yeah.
We're not there yet.
Right.
And that big gap is what Valla actually set outto do.
(02:12):
My original thing that I wrote a year ago wastrying to fill that gap to say it's not
actually true yet.
You say you wanna build something.
You're, like, my the person I always use is mywife.
Multiple advanced degrees, lots of professionalcertifications, all that kind of fun stuff.
But when she gets hired by a company to takeall that experience and knowledge and put it to
practice, what does she end up doing?
(02:33):
She ends up managing technology systems thatdon't do a very job solving the problem.
Right.
And she always needs IT tech support to make itdo those things.
Yes.
So how do you fill that gap?
That's what I tried to build and ended up beingthat there's a lot of a lot of reasons why that
doesn't work.
There's a reason that SIs exist.
Right.
Right?
And it's about that complexity of that ERP andthat CMS and the the all the WMS and all the
(02:57):
systems,
right,
that you've gotta be able to work in thatspace.
I might be a little jaded, but sometimes Ithink technology just keeps repackaging itself
into the latest solution.
So it was interesting to hear you say thatwe've had AINML for 20 years because we have.
Yeah.
For guys like us, we could use it, but itwasn't accessible to everybody else.
(03:17):
And it still isn't, but I remember, you know,15, 20 years ago, the big thing was workflow.
Yeah.
And you would go do a software demo, andeverybody all the executives would be like, can
I workflow that?
Can I workflow that?
Can I re and be sure you can workflow it allyou want?
And then you get in the project, And, ofcourse, the workflow wouldn't do it.
You'd have to have a developer come in andextend the workflow.
(03:38):
And the developer would be looking at mesaying, don't I just write this the way you
need it instead of using this workflow?
You know, it's funny.
The you're describing exactly how I think of ittoo.
I've gone full circle on the open sourcecommunity and componentization of everything,
but it goes back to, like, when I sit down andwrite something myself, I don't use any
(03:59):
external packages.
I never do.
I hate them because I spend more time figuringout how to implement it with their little
library than just sitting on a writing myself.
Right.
As we sort of building out this company and,like, looking at those similar problems, every
time you use an off the shelf solution forsomething.
If it's your ERP or your CMS or whatever,you're pulling forward a bunch of past
(04:19):
decisions that have been made.
And a lot of those decisions were made toabstract away some concepts so that, like,
theoretically, you could integrate with it.
That's what most of solutions, systemsintegration solutions integration is is making
folks talk to each other.
Yeah.
And any conversation with external vendors orother software companies that you're trying to
(04:39):
integrate with, the first few meetings are allagreeing on terminology.
What is your depth of the word container,right?
Is it a box or is it a shipping container?
Cause it's different in in the MicrosoftDynamics software that we integrate all the
time.
They use that word container very directly.
It could be in cardboard box, or it could be apallet, or it could be anything.
It's just a word for them.
But then sometimes if you tell a developer weneed to do something with the container,
(05:02):
they're thinking something entirely different
K.
Yeah.
They're thinking about.
Yeah.
Right.
Exactly.
So all these meetings come down to let's agreeon the terminology first, and then let's then
let's go from there.
Yeah.
I gave a talk a long time ago on the definitionof done.
Because I think that's the first thing you haveto define.
Right?
When we say we're agreeing to deliver thisthing, what are we delivering?
(05:23):
Fully.
Everybody's expectations put all on the table.
We need to know the full definition of done.
And people get angry with you when you try tostart at that point because they're like, well,
everybody knows what that means.
Like, you and you just gave differentdefinitions for what we say when we mean done.
When I say done, I mean, it's fully test.
It's fully deployed.
It's fully that customers can use it, then it'sdone.
Right.
And as a systems integrator in the ERP world,it's never done.
(05:47):
You're constantly evolving that system.
And we get customers, you know, we, we buildthe code, we build the system, we get them
live.
We do 2 weeks of training.
The team thinks they're done.
And then the accounting people say, oh, no.
We're not done.
We gotta close our 1st month and finalize that.
Then we're done.
And then we get backed operations well.
There's all these things you told us we'regonna be phase 2 that we couldn't get to in the
(06:10):
implementation.
Now we gotta do those, or we're not done.
So we do and in our world, actually, it feelslike we're never done.
We're constantly optimizing these systems.
But I I wonder, isn't that the business model,isn't that the whole point of being in that
space?
Is that there's always more automation that thecompany needs and wants.
And that's a good thing.
Yes.
It is.
It's a great thing.
(06:31):
Yeah.
And, you know, we're looking for 10 to 5 teenyear or longer relationships with our
customers.
And we have those.
And we're there to advise them.
We're there to guide them on, you know, whattechnology trends are coming out.
So for example, a lot of them are coming to usright now and saying, hey.
What's you know, how should I use this AI?
And most of the times, well, you're not quiteready for it.
You're still figuring out this whole, like,cloud migration that you should have done 10
(06:54):
years ago.
Yeah.
Exactly.
Yeah.
That's true.
I I got to know that the SI space pretty well,you know, my last 15 years roles because it was
kind of my secret weapon.
I get pulled in by, like, a Nike to increasetheir rate of digital innovation And you have
the same problems at every company.
If you're not Google, Facebook, Amazon,Netflix, or a couple others, where all the best
(07:15):
engineers are gonna be drawn boards.
Yes.
It is very difficult to get critical mass, andyou have to have it.
So you build up these big teams with, you know,maybe you've got 10% of just amazing people in
your team, but that other 90% dragging on itand making it very difficult to proceed.
So you've got the people You've got a culturalproblem because you're not a digital first
(07:36):
company.
You're, you know, you're you sell shoes, nottechnology.
Right.
And so I would bring in these hired guns thathad critical mass.
That's what the that that was a whole business,right?
Right?
You've gotten great people.
So I'd bring them in and say, okay.
We are going to migrate from on prem to in thecloud, we're gonna migrate from x to y because
I'm trying to pay down this colossal amount oftechnical debt that's been built up over time.
(07:59):
And I know and you know that this is just thebeginning of that process because that
technical debt also stopped all the otherthings that the business wanted.
You know, I'm in sales.
I need to know whatever.
I'm in marketing.
I need to know something specific.
I'm in inventory management.
I need to have predictive, etcetera.
Right?
(08:20):
All those wants, they don't even ask anymore.
And the instant you plug that bottleneck.
And all of a sudden, the technology unlocksopportunity within the business, which is the
whole point of doing soft are.
We're automating
Yes.
All these things.
Yes.
And automation is where it's at.
I mean, that's where every company eats more ofthat if they're gonna survive.
You either More
(08:40):
automation faster.
Yeah.
It's it's it's automator die, really.
I mean, that's what it comes down to.
Years ago, I did a go live of a warehousemanagement system.
This is when I was still doing projects myself,and it was rough go live.
Inventory wasn't correct.
Long story short, we had to stop the go live,count the whole warehouse, we're there till 4
Hammer, back at 8 AM and everything workssmoothly after that.
(09:03):
And at the end of the 3 or 4 days on-sitethere, The owner of this manufacturing company
asked to meet with us, call us on the carpet.
And he said, in World War 2, we built theB-fifty 2 bomber with the big chief pencil and
a pad of paper.
Why do we need all these computer systems?
And I gotta give a CFO credit because with astraight face, he said, well, in 1985, you had
(09:24):
25 people in accounting, and now you have 5.
Do you wanna go back and hire all those people?
Well, here, I'll give the counterargument,though.
How many software engineers do you have on theteam now?
Right.
Yeah.
He's got 4 IT guys.
There there is a counterargument there.
But we are getting more efficient over time.
Absolutely true.
Yeah.
And the the long arc of history, like, moreautomation, less and less human intervention,
(09:48):
especially where we're not good.
Like, accounting is it's not something thatpeople wake up at night and go, oh, I can't
wait to get pen and paper and figure out wherethe books have gone wrong.
Like, nobody want, well, not nobody.
There are some people like that.
Christian.
Very few
people like this.
Right?
I have never worked with some of them, so Ihave to defend them.
(10:09):
I I do too.
As I said, I was like, no, there's a lot ofthem.
I'm not as many as it has been needed, but Ithink that we're actually It's very telling in
the moment in time that we're in.
I said that there's a a lack of critical massin most companies to meet the needs of their
technology wants and desires.
That's been true for a while.
And for the first time, that barriers droppedto the floor with this, you know, set of
(10:31):
generative AI tools that are coming into theworld, The problem, though, is it's still that
gap between what I have and what I desire, andI can't fill it without having some software
development teams get involved to British.
So you might have an AI tool that allows you todo, like, Hey.
I can automatically generate a bunch ofspreadsheets and all that.
That's fun, but it doesn't connect into my ERP.
(10:54):
Right.
But what we're seeing is that desired statecoming, like, it's getting really high, really
fast, but we still have this huge gap betweenhow many soft engineers in the world are
capable of building into those systems and thedesires of the business and the people in the
business to do something with it, but we'restarting to also see price pressure on, that
(11:17):
top line, like, hourly billable rate that SIScan charge is down, like, 20% in the last year.
Because there's this perception that, like, oh,no.
I just have my own teams do it with this AItool, which isn't there yet.
Right.
Oh, yeah.
We tend to deal with companies in the small andmid market.
So less than 500,000,000 revenue for the mostpart, let's say.
(11:38):
So they don't have especially at the lower endof that, they don't have big IT teams.
They depend on SIs for everything.
Maybe they have a few guys in IT but we'reseeing a number of challenges to that market.
One of them is, as they transition to thecloud, they need a different skill set from
their IT team.
Yeah.
Big time.
They have IT guys that are used to patchingservers and interacting with SQL and stored
(12:02):
procedures and stuff like that.
And now it's like, you're gonna write codeagainst an API, or, you know, it's entirely
different skill set.
Yeah.
So that's that's the major shift we're seeingas as these small to midsize businesses
digitally transform into the cloud, they need adifferent, level of staffing internally.
So part of a transition when you're coming in,you're doing these these and you're trying to
(12:24):
help them modernize.
Part of it is getting the staff that's there upto that skill level.
I imagine part of it's also like, no.
We're gonna help you hire somebody that has thenecessary knowledge because you've got too much
resistance and not enough there there.
Yeah.
How do you engage with that, especially theseSMBs, the small and medium businesses?
We usually educate them upfront that it isgonna be at the leadership level.
(12:46):
Hey, this is a different IT skill set.
It's more business analyst and less hardwareguy.
And that's the way we explain it at the SMBlevel.
They need to be comfortable working with dataand workflows and maybe a little bit of code
here and there, they don't need to knowanything about hardware anymore.
They don't need to know how to patch a server.
They don't need to know the firmware of theirrate controller, which are old problems that we
(13:06):
had, And so we explain it that way, and then wetell them, hey.
If we can help you get your people up to speed,or we can help you find someone to augment them
if necessary.
This is related because I wanted to touch onthe people piece of it.
Yeah.
A lot of the people listening to this havetheir own startup.
They might be early in their startup.
That's generally common audience.
Right?
And one of the hardest parts of any leader intheir first company that running when you're
(13:30):
the the buck stops your person trying to figureout how to get the most out of the team that
you've got knowing full well that they aregoing to be missing a lot of the skills and
experience necessary to effectively do the jobthat they're in today.
Everybody in your startup is in the biggestrole of their lives.
This is the biggest opportunity they've takesfull of overhead.
So you've gotta get the maximum amount of themand help them learn what they don't know fast.
(13:52):
Like, speed is the only thing that Hammer.
Right?
Right.
What advice do you give to people in thatsituation?
I think as a manager, a couple things, youknow, failure is okay.
Failure without an explanation or any guidancethat you may fail is is not okay.
So make it a safe space for them.
Provide them with the tools to ramp on thingsas much as you can.
(14:15):
But I think, generally, it's all aboutcommunication and saying, Hey, it's it's okay
if you if you don't miss this deadline, butgive me a few days notice ahead of time and let
me know you might need some help.
So what what you don't wanna hear is theengineer that goes heads down on an issue for 5
days and doesn't make any headway on it.
Mhmm.
You want them after one day to raise his handand say, hey.
I need some help here.
Please please help.
(14:36):
Yeah.
Working with younger engineers that's been thebiggest thing I've seen them do is put heads
down trying to solve something and not getanywhere on it.
And then come to me 3, 5 days later and say,well, I wanted to bang my head up against this
because I wanted to learn something new.
And I wanted to expand my skill set in like,well, we could have gotten you some help after
day 1, and you would have learned it and youstill would have expanded your skill set.
(14:56):
Heads down at it for 5 days didn't helpanybody.
So the, the real time business data ones isreally important on the start up too.
Oh, yeah.
I mean, profiles looking at going, yeah, that'sa really important one too.
A lot of people screw up with, like, OKRs andtheir KPIs and all that kind of stuff because
they're focused on the wrong thing.
So knowing what good data is to make gooddecisions is a difficult thing to do.
(15:21):
It is.
It's very hard to get to relevant data.
Yeah.
You have any, like, high level guidingprinciples that help you determine if it is
good data to guide you?
We just went through as a company.
And it was an intensive workshop at theleadership level
Mhmm.
To align on those and then come up with themand then come back a week or 2 later and
(15:43):
challenge them again.
And that's what works.
And that's what worked for us.
And again, make it safe, no judgment,brainstorm, agree on things, and then come back
and tweak it again.
That's the best way that we found to align onOKRs and KPIs.
The guidance I've I try to get people on thisis very similar to that.
Like, you're gonna make a mistake.
(16:05):
Your measurements are supposed to be the, youknow, you formed a hypothesis of your business,
and you're gonna form an experiment that'sgonna be your product or service that you're
putting in market, the data you want back isconfirmation of the success or failure of that
experiment.
That's what you need to know.
Yep.
Right?
So what does that look like in your specificcase, well, it might be.
(16:25):
I had a lot more customers today than I didyesterday.
Maybe that's the data you needed.
Right.
Or might have a lot more engagement product Ihad, but it's going to be unique to you, more
than likely.
Your experiment is unique to you, but you'reprobably gonna have to change it if you change
the
Yeah.
If you pivot or whatever, you know, that you'reyou're changing something, you probably got to
change it.
So you can't be wholly grayish about your KPIsbecause in a good situation, you're learning
(16:48):
and gonna learn that they were the wrongmeasurement.
Yeah.
It was a it was fun exercise for me because Ihave 20 years of tribal knowledge in this
business.
And then we had other people that didn't havetribal knowledge.
But they Hammer different way of looking atthings, and they had more experience with
formal KPIs and OKRs.
So to get those people in a room in a line wasreally the best way to do it.
(17:09):
That mixture of tribal knowledge with overallbest practices really hit it for us.
And that's that's exactly right.
Combination of people that can challengeassumptions because maybe they're naive, and I
I use that in a nice way.
I don't mean, like, they're No.
I mean, I getcha.
Yeah.
But mixing that with lots of an experiencebecause the problem of experience is you're
(17:32):
blind to different ways of looking at it.
Yeah.
And, yeah, that's a good mix.
So we're we're actually over the time we hadallotted for recording, but I wanna give you a
chance to say it, like, if you wanted to givethe audience anything, to take away I know that
I wanna send them to westerncomputer.com ifthey wanna find out more about, daily business
operations, how to improve it, especially ifthey're a small to medium business with
(17:53):
profoundly large technology offering?
Yeah.
So we're a, western computer.
We've been doing this for 35 years.
We're a 100% Microsoft shop a systemsintegrator that focuses on delivering solid ERP
solutions and CRM solutions for small andmidsize businesses.
And that is a big area that they all have aneed and they often, don't recognize how many
(18:16):
workarounds they've created for their workflow.
Yeah.
Put this data in this spreadsheet then go overhere and send this email and then save this
document to SharePoint.
And and that's the first step of the process.
Yeah.
Then send an email to Bob, and Bob will, like,transcribe it into something else.
Yeah.
Exactly.
Well, Greg William, Western Computer.
(18:37):
It was wonderful having you on.
It's fantastic.
Thank you for being here.
Thanks, Christian.
Nice to meet you today, and, and I enjoyed ourpodcast.
And that's a wrap for this episode ofTectastic.
Wanna thank you personally for joining us, andwe'll see you next time.
Until then, keep exploring, and stay curious.
(18:58):
Thank you for listening.
If you are new here and enjoyed the content,please subscribe.
It really helps us out.
And if you are a regular listener, thanks somuch for your continued support.
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