February 8, 2023 • 16 mins
In this episode, Brick and Caleb tackle some of the misconceptions around making your organization data-driven, and some of the steps you can take to do it successfully.
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Blue Margin helps private equity owned and mid-market companies organize their data into dashboards to execute on strategy and create a culture of accountability. We call it The Dashboard Effect, the title of our book and podcast.
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
Brick Thompson (00:00):
Welcome to The Dashboard Effect Podcast, I'm
(00:02):
Brick Thompson.
Caleb Ochs (00:03):
I'm Caleb Ochs.
Brick Thompson (00:04):
Hey Caleb.
Caleb Ochs (00:04):
Hey.
Brick Thompson (00:05):
All right. So today we want to talk about
becoming data driven at acompany, and how it's not
necessarily intuitive, how youdo that.
Caleb Ochs (00:16):
What is data driven?
Brick Thompson (00:17):
That's a great place to start. Luckily, I
consulted Chad GPT beforehand.
I'm just kidding. How do youdefine data-driven?
Caleb Ochs (00:28):
Yeah, it's good question. So I would define it
as employees regularly seekingand finding information that
help them do their jobs.
Brick Thompson (00:38):
Yeah. As I think about it, it's that exactly. I
think, maybe to bring it evenmore down to earth for me, it's
that employees regularly usedata to make their decisions and
drive what they're doing. Samething.
Caleb Ochs (00:52):
Sure
Brick Thompson (00:54):
Okay, so with that, what are the benefits of
being data driven? Why doeseverybody talk about, "I want to
become data driven, or make mycompany data driven?" Why?
Caleb Ochs (01:04):
Yeah, so if I've been doing a lot of reading
lately, as you know, and all ofthose books, there's like a
common theme through all ofthem, no matter who the author
is, or what the topic is.
Typically, it's some sort ofbusiness book. I have a very
boring Kindle library. Buteverything has a theme of data
(01:24):
in it, somehow. Whether it's ascorecard that you look at in
your weekly meetings, orwhatever it might be, there's
always that underpinning of,"You've got to look at your
metrics on some sort of regularcadence."
Brick Thompson (01:40):
Yeah, it's almost like you don't have to
ask why. It's just sort of agiven that you need to have data
to optimize your business. Imean, if you look at guys like
Lencioni, you know, The FiveDysfunctions, and other books
guys. He's always coming back todata. Or, The Game of Work,
Chuck Coonradt. It was a bookfrom the 80s, or I think he may
(02:02):
have first written in late 70s,but still applies. You know,
give people the score, give thema scoreboard. They're going to
be happier, they're going to bemore productive, they're going
to feel more fulfilled. And thenI was looking up quotes. And of
course, there's the Druckerquote, "What's measured, is
managed," "What gets measured,gets managed," or sometimes
(02:22):
people say it, "What doesn't getmeasured, doesn't get managed."
It's just so important to abusiness that you almost don't
have to say why.
Caleb Ochs (02:32):
Right, exactly. And I think once you get to a
certain state, a certainmaturity level in your business,
you're gonna be looking at thatstuff anyway. But it's worth
worth repeating.
Brick Thompson (02:42):
For sure. Yeah.
I mean, some of the moretactical things, meetings will
be more useful. Because you knowwhat the score is. Hopefully,
employees will be moresatisfied. You know, all
employees, me and you included,when we know the score, it's way
more fun. You got a handle onhow to dig into a problem, when
you've got the data. And whenyou don't, sometimes you're just
(03:05):
kind of reaching around in thefog a little bit.
Caleb Ochs (03:11):
Yeah. And touching on that meetings are more useful
thing. You know, if you thinkabout what happens in meetings,
people usually discuss things.
There's usually something thatcomes up that needs some data to
figure it out or make adecision, right? And if you've
got that culture, and you havethat data available to you, and
it's readily available, whatcould take some companies who
(03:33):
don't have those things a weekor two, to go find the data,
pull it together, get it to theperson who's asking for it,
might take an hour. You might beable to get that decision made
that day, rather than two weekslater, after you've got the
data.
Brick Thompson (03:50):
That's a really good point. I'm glad you said
that. Because it just makes merealize, every company has data.
Whether it's in a spreadsheet,or fancy data warehouse and
reports, or whatever. But ifyou're not a data driven
company, you may not be good atbeing agile, like you're talking
(04:10):
about. Like, a new problem hascome up, and you need to figure
out how are we going to go afterthis. If you're not data driven,
it might take you weeks ormonths to get the data that
would allow you to get after itright now. Or ever. I mean, if
you're not data driven, you mayhave a company that's just sort
of stuck in status quo and has ahard time adjusting and getting
(04:34):
more agile.
Caleb Ochs (04:35):
You can't make progress, right.
Brick Thompson (04:38):
And I think about, you know, our core
purpose at Blue Margin is tomake great places to work. Make
companies great places to work.
And we do that through dataculture. And really, if you can
give people the score and givethem the tools that they need to
be successful and to optimizewhat they're doing and optimize
the business, it makes it fun atwork.
Caleb Ochs (05:00):
Yeah, right. You know what's going on, you know
what you have to do, you knowwhere you stand currently. It's
like, so many good things comefrom having that data available
to you. I think that's reallyimportant, actually. Because,
when you think about data, it'sso boring. And it's like, it's
just numbers. But it can it hasthat impact that is hard to
(05:23):
quantify, but it's there. Thatpeople become more satisfied
with their jobs. It becomes abetter, funner place to work
when you know what's going on.
And those things should not bediscounted.
Brick Thompson (05:42):
I've experienced that anytime in my career, when
you go from the fog to theclarity, even if the clarity
tells you, "Wow, we're deep init," It's way more fun, because
you can grab on and do somethingabout it.
And you get to see the theresults of your hard work, as
you change that and startclimbing out of it.
Yeah. All right. So everybodytalks about becoming data driven
(06:06):
these days. Most people want tobecome data driven. And yet,
it's hard to do. What makes ithard?
Caleb Ochs (06:13):
So, you know, there's a lot of misconceptions
about how to do it and whatmight work. So one of the common
ones would be, "Let's just buildthis report, and we'll get it to
the users and, be done andthat'll change things. And
that'll start the catalyst, orthat'll catalyze getting us to a
(06:36):
data driven state." When, infact, as in our last podcast
episode, we were talking aboutiteration, that's definitely
more than reality. And anyway,there's a lot more that we'll
get into with that. But youcan't just build a report and
expect people to change.
Brick Thompson (06:51):
Right. Yeah, the one and done. I mean, it
happens, but it's the exception.
You're unlikely to hit it right,exactly, the first time. And
businesses change, and needschange, and requirements change,
and so on.
Caleb Ochs (07:05):
And, now that I'm thinking of this, I think it can
be tricky, because with thesecool tools, like you think take
a Power BI or any of these otherinteractive data visualization
tools, when you get that reportout people are super excited.
It's like, "Oh, this is so cool.
And this is amazing." And itfeels like "Ah, we've totally
done something here." And then,two weeks later, they're like,
(07:28):
"Now it needs to change, and weneed to do this, or we need to
do that." And it's not quitegetting you there. And and then
maybe it just kind of fades inthe distance.
Brick Thompson (07:39):
Yeah. Right.
Well, there's a lot that goesbehind making that not happen.
We'll talk about some of that. Ithink there's also a fallacy, a
misconception, which iscounterintuitive a little bit,
which is, "We'll start bygetting our data perfect. So
we'll corral all the data weneed, and we'll do all of the
data quality cleanup we need todo, let's do all that first. And
(08:03):
then we'll be data driven."You're gonna need to do those
things along the way, butcompanies that set out with this
monolithic waterfall project of,"Let's get our data perfect, and
then we'll start having somereporting and become data
driven." Often, I think thatdoesn't work. Usually, actually.
Because what you think you needwhen you start a data project
(08:26):
often changes, as we talkedabout, and we talked about it a
couple of weeks ago. Once youget reports and data in front of
people, they'll figure out whatthey really need. And so that
old fashioned, old style datawarehouse project of "Let's
define a common data model andspent 18 months building it, and
then we'll be data driven." It'sa it's a huge risk and not the
(08:49):
right way to go.
Caleb Ochs (08:52):
Yeah. Right. It's tough. And especially when you
know that there's data problemsthat you have to solve first, it
can be tempting to say, "We gotto do all this data work first,
and then we can start doing somereporting," when in reality, you
probably should flip thosethings. Start reporting, get
insight into your data, actuallyget a good handle on the on the
(09:15):
problem. Anyway, there's stillplenty more to talk about there
and I could go on and on, but Ithink we've covered it.
Brick Thompson (09:22):
Yeah. Well, and, you know, along that line, I
think we'll come back to thistopic a bunch, because we can't
cover it all. We're trying tokeep our podcasts sort of 10 to
15 minutes, we can't cover allof it, so we'll come back. I
think some of the other problemsthat people have is just people
sort of having resistance tochange, clinging to the status
(09:44):
quo. I mean, I've heard itworking in companies. "Oh, well,
this is how we've done it for 18years. You know, we have this
spreadsheet and we enter thenumber here and then..." It can
be sometimes hard to breakpeople out of that.
Caleb Ochs (09:57):
Right. Yeah, that's definitely big with any change,
and this is no exception. Allright. So, the last thing that I
would like to mention, and thenI think we may have one more
point, is that there's so manytools out there, and there's so
much great marketing, andthere's so much to look at. And
(10:20):
it's almost information overloadwhen you start looking at the
data space. Like, there's justso much stuff out there, and
it's easy to get swarmed by thatmarketing and think, "That's the
answer to my problems." It'snot. The tool is about 10%, of
what you have to do to get youto where you want to be.
Brick Thompson (10:39):
Yeah, it's a really good point. There are a
bunch of good tools out there. Imean, we're Microsoft stack.
Microsoft has great tools.
There's other good tools, too. Ithink what happens to people
sometimes when they're trying tobecome data driven, is they run
into some of these problems thatwe're talking about, and others,
and then they see a goodmarketing piece about a
different tool than the onethey're using. And they think
(10:59):
it's going to be some kind ofmagic solution, sort of the the
easy button to solve myproblems. And really, it doesn't
get to the root of the problem.
Caleb Ochs (11:10):
Right.
Brick Thompson (11:10):
So, that's a really, really good point. All
right. So, with those in mind,what's the right way to approach
becoming data driven? And andI'll just caveat again, we're
not going to get too deep today.
But what are the big pieces thatpeople should be thinking about?
Caleb Ochs (11:27):
Yeah, I think you've got to start with making sure
the company is ready for it. Andwe'll talk a little bit about
exactly what that means. But youhave to make sure that your
culture is ready to embracedata. I remember a few months
ago, I was doing some diligencefor a private equity company
that was looking to buy,actually they had already signed
(11:50):
the LOI, but they were gettingready to take over this company.
And we interviewed the C suiteto see like, "What are your
views on data, where are youat," get an idea of this
company's culture, and more ofthe technical stuff, but really,
a lot of our audits focused onthe culture of the company to
see, is this going to bepossible, if you want to do it?
(12:11):
And one of the guys, you couldtell, he just didn't really want
to get into data. He was more ofa stick the finger in the air
kind of guy. Like, "My gut tellsme we kind of know what's going
on, yeah you can look at thenumbers, but we really know
what's happening." And we raisedthat as a big red flag, like
this could be a real impediment.
You know, I think he was theCEO. That can be a big problem.
Brick Thompson (12:37):
Oh, yeah. So, you're saying starts with
culture, or culture is key. Andwhen you're gonna start with
culture at a company, you've gotto have leadership. Executive
leadership has to be bought inand aligned first, I think. I've
seen projects get derailed, evenwhen you have a lot of the
executive team ready for it, orkey members of it, if you have
(13:00):
one key member who's not, it canderail the whole thing. Because
when you're doing theseprojects, especially at the
beginning, it can be easy topoke holes. If you get a report
that has a incorrect number onit, well, if the team is
culturally aligned, great, yougo back and do an iteration,
revise and fix it and moveforward. If you've got someone
(13:21):
that's looking to not do theproject, then that gives them
something to really hang on to.
Caleb Ochs (13:27):
Yeah, that's a really good point. That can just
torpedo the whole thing.
Brick Thompson (13:32):
It's one of the reasons we're so careful with
our validation and making surethat what we put out is right,
but, things happen. People thatthink they know the business
rules to give a measure, givethe formula for measure, it may
turn out they're missing apiece, and you need to get it
out there in front of the usersbefore you find out. All right.
(13:52):
So after culture, executivesponsorship, I mean, there's a
bunch of stuff you can do aroundexecutive sponsorship. And in
fact, we'll probably go intothat in another podcast, we
won't go to the details here.
What's the next piece that youthink is most important?
Caleb Ochs (14:06):
So there's a concept that is called the Center of
Excellence. So it's basically apanel of people that that are
part of the company that get tomake and are in charge of, not
get to make, they actually areburdened with, making the
decisions around data, andgovernance and those types of
decisions that need to be madeas you start rolling some of
(14:27):
these things out.
Brick Thompson (14:28):
Yeah. So people talk about governance, and BI
Yeah, that alignment piece ishuge. So anything you can do to
and data a lot. And this isreally what we're talking about
when we talk about governance,having some kind of controls,
some kind of body or person, butusually more than one, that's
going to help you define "Okay,what are best practices? What
does a set of data, whatcharacteristics does it need to
(14:50):
have before we'll call itcertified and people can use and
trust it? What are thecharacteristics of data that
we're going to call uncertified.
And then what are the best waysfor you to interact with that
data?" Just because it's notcertified doesn't mean it might
not be useful, but it just maynot be fully mature yet. So that
Center of Excellence concept, Ithink, is really important. And
(15:13):
it can be hard when that doesn'texist at all. But just having
the concept and starting to putthose pieces in place can really
help start pulling thingstogether. And I think Center of
Excellence, then as you getmaturity and become data driven,
can go so much deeper. I mean,it can become sort of the oracle
for the company. So a reallygood Center of Excellence will
(15:37):
have some method for users to beable to ask questions and get
clarification and have anescalation path for when they
see there's an error orsomething should be modified to
make it better. All those typesof things. Another another big
pillar after a Center ofExcellence is something, I think
Microsoft actually has this insome of their white papers
(16:00):
referred to as the ContentDelivery Scope. Sounds kind of
confusing. To me what it what itmeans is basically, what is the
supported data and reporting forthe company and defining that so
that people are clear on "Okay,this is supported, this isn't."
Just because something's notsupported doesn't mean you might
not use it for doing someanalytics and so on. But what's
(16:23):
the stuff that we can trust?
What's the stuff we're reallyrunning the business on? And so
defining that, at least, whereyou're starting, and what the
roadmap of that is going to looklike, can be really important to
getting data driven. It helpsremove ambiguity and confusion
and gets users aligned on whatthey can expect.
(16:50):
to help with that, definitely doit.
Yeah. All right. And thenthere's another concept on the
path to getting data driven,called the Business Algorithm or
Business Objectives andAlgorithm. Do you have a sense
for how to describe that well?
I'll take a stab at it if youdon't.
Caleb Ochs (17:10):
Yeah, I can give it a shot. So really, it tells you,
you know, your businessobjectives, you can think that
you're out there to dosomething, right. Like, I can't
think of a good example rightnow, but you want to do
something out there, you havebusiness objectives that you
want to complete.
Brick Thompson (17:25):
I've got one for you. You want to make your
service delivery guys and womenwho are driving around in
trucks, you want to get theirutilization as high as possible.
So as much of the time thatyou're paying them for, their
billable to a client, so thatmight be an objective.
Caleb Ochs (17:41):
So yeah, that's a good one. So let's say that your
target is 90%. You can say, "10%we're gonna use for training,"
or whatever it is. So that wouldbe one of your business
objectives. And you would havemetrics that support that. Now,
you might think that, "Oh,that's just the utilization,"
maybe, but there's probably fiveother things that support that
(18:03):
as well. And you need to definewhat things and what metrics are
going to support utilization, sothat when somebody has very poor
utilization, you're not justsaying, "That person has poor
utilization,." You're saying,"That person has poor
utilization. Now, let me look atthis, and this and this. Okay,
now I understand what's goingon, and we can actually do
something about it."
Brick Thompson (18:24):
That was great.
All right, really good. Thatcomes up a lot in sales too. The
number you care about for yoursalesperson is how much should
they sell, but when they're nothitting their targets, if all
you have is that end number,it's hard to know where to dig
in. So your algorithm, yourobjectives, upstream of that can
help you get to that. Thatalgorithm, those objectives,
(18:46):
help you know then, what datayou need.
Caleb Ochs (18:51):
And having those things lined up and defined,
helps with that, building agreat place to work, right? You
take that salesperson example,if you're just judging them on
that N number, and you don'tcare about the context around
it, manager could come down hardon somebody. It's like, well,
there's all these othercircumstances that you could
(19:14):
have looked at and seen, "Okay,this is what's going on, let's
actually fix some of the rootissues here and actually work
with this person." And that justmakes a better, better culture.
Brick Thompson (19:23):
Yeah, well, and also, you can take someone that
might have failed based on the Nnumber, and make him successful.
I've seen that many times inmany different situations.
Caleb Ochs (19:31):
Yeah. And that's ultimately what you'd hope for.
Brick Thompson (19:33):
Yeah, of course.
All right. And then there's onemore pillar, which is
establishing a Community ofPractice. What does this mean?
Caleb Ochs (19:41):
So this is, like your analysts and your
developers within the company. Alot of the companies we work
with don't have a staff to dothis. But essentially what it
is, is it's a group of peoplethat you can share ideas with,
share best practices with, getout source from, that type of
(20:01):
thing. So for us, if you don'thave this, or you don't have
people that could participate inthis, you could use like a third
party to be that community ofpractice for you. Somewhere to
give your users support andpeople that are responsible for
this.
Brick Thompson (20:18):
Yeah, that's interesting. We have that just
internally, as we support ourcustomers, we have a huge
Community of Practice here. Sojust because you're not working,
as a Blue Margin employee, justbecause you're not working on a
particular client's project, youmay still get tapped. Because
you've got expertise in aparticular problem that's coming
up.
Caleb Ochs (20:36):
You're right, exactly. And if you can build
that at your own company,fantastic.
Brick Thompson (20:40):
Yeah. All right.
There's so much more to thistopic. We're already 20 minutes
in, so I think we'll wrap fortoday. We'll come back and talk
about some of these pillars inmore detail. There's a lot to
it. But I think that does it fortoday, unless you have anything
else.
Caleb Ochs (20:56):
I'm all good.
Brick Thompson (20:56):
All right.
Thanks, Caleb.
Caleb Ochs (20:57):
Thanks.
Welcome to The Dashboard Effect Podcast, I'm
(00:02):
Brick Thompson.
Caleb Ochs (00:03):
I'm Caleb Ochs.
Brick Thompson (00:04):
Hey Caleb.
Caleb Ochs (00:04):
Hey.
Brick Thompson (00:05):
All right. So today we want to talk about
becoming data driven at acompany, and how it's not
necessarily intuitive, how youdo that.
Caleb Ochs (00:16):
What is data driven?
Brick Thompson (00:17):
That's a great place to start. Luckily, I
consulted Chad GPT beforehand.
I'm just kidding. How do youdefine data-driven?
Caleb Ochs (00:28):
Yeah, it's good question. So I would define it
as employees regularly seekingand finding information that
help them do their jobs.
Brick Thompson (00:38):
Yeah. As I think about it, it's that exactly. I
think, maybe to bring it evenmore down to earth for me, it's
that employees regularly usedata to make their decisions and
drive what they're doing. Samething.
Caleb Ochs (00:52):
Sure
Brick Thompson (00:54):
Okay, so with that, what are the benefits of
being data driven? Why doeseverybody talk about, "I want to
become data driven, or make mycompany data driven?" Why?
Caleb Ochs (01:04):
Yeah, so if I've been doing a lot of reading
lately, as you know, and all ofthose books, there's like a
common theme through all ofthem, no matter who the author
is, or what the topic is.
Typically, it's some sort ofbusiness book. I have a very
boring Kindle library. Buteverything has a theme of data
(01:24):
in it, somehow. Whether it's ascorecard that you look at in
your weekly meetings, orwhatever it might be, there's
always that underpinning of,"You've got to look at your
metrics on some sort of regularcadence."
Brick Thompson (01:40):
Yeah, it's almost like you don't have to
ask why. It's just sort of agiven that you need to have data
to optimize your business. Imean, if you look at guys like
Lencioni, you know, The FiveDysfunctions, and other books
guys. He's always coming back todata. Or, The Game of Work,
Chuck Coonradt. It was a bookfrom the 80s, or I think he may
(02:02):
have first written in late 70s,but still applies. You know,
give people the score, give thema scoreboard. They're going to
be happier, they're going to bemore productive, they're going
to feel more fulfilled. And thenI was looking up quotes. And of
course, there's the Druckerquote, "What's measured, is
managed," "What gets measured,gets managed," or sometimes
(02:22):
people say it, "What doesn't getmeasured, doesn't get managed."
It's just so important to abusiness that you almost don't
have to say why.
Caleb Ochs (02:32):
Right, exactly. And I think once you get to a
certain state, a certainmaturity level in your business,
you're gonna be looking at thatstuff anyway. But it's worth
worth repeating.
Brick Thompson (02:42):
For sure. Yeah.
I mean, some of the moretactical things, meetings will
be more useful. Because you knowwhat the score is. Hopefully,
employees will be moresatisfied. You know, all
employees, me and you included,when we know the score, it's way
more fun. You got a handle onhow to dig into a problem, when
you've got the data. And whenyou don't, sometimes you're just
(03:05):
kind of reaching around in thefog a little bit.
Caleb Ochs (03:11):
Yeah. And touching on that meetings are more useful
thing. You know, if you thinkabout what happens in meetings,
people usually discuss things.
There's usually something thatcomes up that needs some data to
figure it out or make adecision, right? And if you've
got that culture, and you havethat data available to you, and
it's readily available, whatcould take some companies who
(03:33):
don't have those things a weekor two, to go find the data,
pull it together, get it to theperson who's asking for it,
might take an hour. You might beable to get that decision made
that day, rather than two weekslater, after you've got the
data.
Brick Thompson (03:50):
That's a really good point. I'm glad you said
that. Because it just makes merealize, every company has data.
Whether it's in a spreadsheet,or fancy data warehouse and
reports, or whatever. But ifyou're not a data driven
company, you may not be good atbeing agile, like you're talking
(04:10):
about. Like, a new problem hascome up, and you need to figure
out how are we going to go afterthis. If you're not data driven,
it might take you weeks ormonths to get the data that
would allow you to get after itright now. Or ever. I mean, if
you're not data driven, you mayhave a company that's just sort
of stuck in status quo and has ahard time adjusting and getting
(04:34):
more agile.
Caleb Ochs (04:35):
You can't make progress, right.
Brick Thompson (04:38):
And I think about, you know, our core
purpose at Blue Margin is tomake great places to work. Make
companies great places to work.
And we do that through dataculture. And really, if you can
give people the score and givethem the tools that they need to
be successful and to optimizewhat they're doing and optimize
the business, it makes it fun atwork.
Caleb Ochs (05:00):
Yeah, right. You know what's going on, you know
what you have to do, you knowwhere you stand currently. It's
like, so many good things comefrom having that data available
to you. I think that's reallyimportant, actually. Because,
when you think about data, it'sso boring. And it's like, it's
just numbers. But it can it hasthat impact that is hard to
(05:23):
quantify, but it's there. Thatpeople become more satisfied
with their jobs. It becomes abetter, funner place to work
when you know what's going on.
And those things should not bediscounted.
Brick Thompson (05:42):
I've experienced that anytime in my career, when
you go from the fog to theclarity, even if the clarity
tells you, "Wow, we're deep init," It's way more fun, because
you can grab on and do somethingabout it.
And you get to see the theresults of your hard work, as
you change that and startclimbing out of it.
Yeah. All right. So everybodytalks about becoming data driven
(06:06):
these days. Most people want tobecome data driven. And yet,
it's hard to do. What makes ithard?
Caleb Ochs (06:13):
So, you know, there's a lot of misconceptions
about how to do it and whatmight work. So one of the common
ones would be, "Let's just buildthis report, and we'll get it to
the users and, be done andthat'll change things. And
that'll start the catalyst, orthat'll catalyze getting us to a
(06:36):
data driven state." When, infact, as in our last podcast
episode, we were talking aboutiteration, that's definitely
more than reality. And anyway,there's a lot more that we'll
get into with that. But youcan't just build a report and
expect people to change.
Brick Thompson (06:51):
Right. Yeah, the one and done. I mean, it
happens, but it's the exception.
You're unlikely to hit it right,exactly, the first time. And
businesses change, and needschange, and requirements change,
and so on.
Caleb Ochs (07:05):
And, now that I'm thinking of this, I think it can
be tricky, because with thesecool tools, like you think take
a Power BI or any of these otherinteractive data visualization
tools, when you get that reportout people are super excited.
It's like, "Oh, this is so cool.
And this is amazing." And itfeels like "Ah, we've totally
done something here." And then,two weeks later, they're like,
(07:28):
"Now it needs to change, and weneed to do this, or we need to
do that." And it's not quitegetting you there. And and then
maybe it just kind of fades inthe distance.
Brick Thompson (07:39):
Yeah. Right.
Well, there's a lot that goesbehind making that not happen.
We'll talk about some of that. Ithink there's also a fallacy, a
misconception, which iscounterintuitive a little bit,
which is, "We'll start bygetting our data perfect. So
we'll corral all the data weneed, and we'll do all of the
data quality cleanup we need todo, let's do all that first. And
(08:03):
then we'll be data driven."You're gonna need to do those
things along the way, butcompanies that set out with this
monolithic waterfall project of,"Let's get our data perfect, and
then we'll start having somereporting and become data
driven." Often, I think thatdoesn't work. Usually, actually.
Because what you think you needwhen you start a data project
(08:26):
often changes, as we talkedabout, and we talked about it a
couple of weeks ago. Once youget reports and data in front of
people, they'll figure out whatthey really need. And so that
old fashioned, old style datawarehouse project of "Let's
define a common data model andspent 18 months building it, and
then we'll be data driven." It'sa it's a huge risk and not the
(08:49):
right way to go.
Caleb Ochs (08:52):
Yeah. Right. It's tough. And especially when you
know that there's data problemsthat you have to solve first, it
can be tempting to say, "We gotto do all this data work first,
and then we can start doing somereporting," when in reality, you
probably should flip thosethings. Start reporting, get
insight into your data, actuallyget a good handle on the on the
(09:15):
problem. Anyway, there's stillplenty more to talk about there
and I could go on and on, but Ithink we've covered it.
Brick Thompson (09:22):
Yeah. Well, and, you know, along that line, I
think we'll come back to thistopic a bunch, because we can't
cover it all. We're trying tokeep our podcasts sort of 10 to
15 minutes, we can't cover allof it, so we'll come back. I
think some of the other problemsthat people have is just people
sort of having resistance tochange, clinging to the status
(09:44):
quo. I mean, I've heard itworking in companies. "Oh, well,
this is how we've done it for 18years. You know, we have this
spreadsheet and we enter thenumber here and then..." It can
be sometimes hard to breakpeople out of that.
Caleb Ochs (09:57):
Right. Yeah, that's definitely big with any change,
and this is no exception. Allright. So, the last thing that I
would like to mention, and thenI think we may have one more
point, is that there's so manytools out there, and there's so
much great marketing, andthere's so much to look at. And
(10:20):
it's almost information overloadwhen you start looking at the
data space. Like, there's justso much stuff out there, and
it's easy to get swarmed by thatmarketing and think, "That's the
answer to my problems." It'snot. The tool is about 10%, of
what you have to do to get youto where you want to be.
Brick Thompson (10:39):
Yeah, it's a really good point. There are a
bunch of good tools out there. Imean, we're Microsoft stack.
Microsoft has great tools.
There's other good tools, too. Ithink what happens to people
sometimes when they're trying tobecome data driven, is they run
into some of these problems thatwe're talking about, and others,
and then they see a goodmarketing piece about a
different tool than the onethey're using. And they think
(10:59):
it's going to be some kind ofmagic solution, sort of the the
easy button to solve myproblems. And really, it doesn't
get to the root of the problem.
Caleb Ochs (11:10):
Right.
Brick Thompson (11:10):
So, that's a really, really good point. All
right. So, with those in mind,what's the right way to approach
becoming data driven? And andI'll just caveat again, we're
not going to get too deep today.
But what are the big pieces thatpeople should be thinking about?
Caleb Ochs (11:27):
Yeah, I think you've got to start with making sure
the company is ready for it. Andwe'll talk a little bit about
exactly what that means. But youhave to make sure that your
culture is ready to embracedata. I remember a few months
ago, I was doing some diligencefor a private equity company
that was looking to buy,actually they had already signed
(11:50):
the LOI, but they were gettingready to take over this company.
And we interviewed the C suiteto see like, "What are your
views on data, where are youat," get an idea of this
company's culture, and more ofthe technical stuff, but really,
a lot of our audits focused onthe culture of the company to
see, is this going to bepossible, if you want to do it?
(12:11):
And one of the guys, you couldtell, he just didn't really want
to get into data. He was more ofa stick the finger in the air
kind of guy. Like, "My gut tellsme we kind of know what's going
on, yeah you can look at thenumbers, but we really know
what's happening." And we raisedthat as a big red flag, like
this could be a real impediment.
You know, I think he was theCEO. That can be a big problem.
Brick Thompson (12:37):
Oh, yeah. So, you're saying starts with
culture, or culture is key. Andwhen you're gonna start with
culture at a company, you've gotto have leadership. Executive
leadership has to be bought inand aligned first, I think. I've
seen projects get derailed, evenwhen you have a lot of the
executive team ready for it, orkey members of it, if you have
(13:00):
one key member who's not, it canderail the whole thing. Because
when you're doing theseprojects, especially at the
beginning, it can be easy topoke holes. If you get a report
that has a incorrect number onit, well, if the team is
culturally aligned, great, yougo back and do an iteration,
revise and fix it and moveforward. If you've got someone
(13:21):
that's looking to not do theproject, then that gives them
something to really hang on to.
Caleb Ochs (13:27):
Yeah, that's a really good point. That can just
torpedo the whole thing.
Brick Thompson (13:32):
It's one of the reasons we're so careful with
our validation and making surethat what we put out is right,
but, things happen. People thatthink they know the business
rules to give a measure, givethe formula for measure, it may
turn out they're missing apiece, and you need to get it
out there in front of the usersbefore you find out. All right.
(13:52):
So after culture, executivesponsorship, I mean, there's a
bunch of stuff you can do aroundexecutive sponsorship. And in
fact, we'll probably go intothat in another podcast, we
won't go to the details here.
What's the next piece that youthink is most important?
Caleb Ochs (14:06):
So there's a concept that is called the Center of
Excellence. So it's basically apanel of people that that are
part of the company that get tomake and are in charge of, not
get to make, they actually areburdened with, making the
decisions around data, andgovernance and those types of
decisions that need to be madeas you start rolling some of
(14:27):
these things out.
Brick Thompson (14:28):
Yeah. So people talk about governance, and BI
Yeah, that alignment piece ishuge. So anything you can do to
and data a lot. And this isreally what we're talking about
when we talk about governance,having some kind of controls,
some kind of body or person, butusually more than one, that's
going to help you define "Okay,what are best practices? What
does a set of data, whatcharacteristics does it need to
(14:50):
have before we'll call itcertified and people can use and
trust it? What are thecharacteristics of data that
we're going to call uncertified.
And then what are the best waysfor you to interact with that
data?" Just because it's notcertified doesn't mean it might
not be useful, but it just maynot be fully mature yet. So that
Center of Excellence concept, Ithink, is really important. And
(15:13):
it can be hard when that doesn'texist at all. But just having
the concept and starting to putthose pieces in place can really
help start pulling thingstogether. And I think Center of
Excellence, then as you getmaturity and become data driven,
can go so much deeper. I mean,it can become sort of the oracle
for the company. So a reallygood Center of Excellence will
(15:37):
have some method for users to beable to ask questions and get
clarification and have anescalation path for when they
see there's an error orsomething should be modified to
make it better. All those typesof things. Another another big
pillar after a Center ofExcellence is something, I think
Microsoft actually has this insome of their white papers
(16:00):
referred to as the ContentDelivery Scope. Sounds kind of
confusing. To me what it what itmeans is basically, what is the
supported data and reporting forthe company and defining that so
that people are clear on "Okay,this is supported, this isn't."
Just because something's notsupported doesn't mean you might
not use it for doing someanalytics and so on. But what's
(16:23):
the stuff that we can trust?
What's the stuff we're reallyrunning the business on? And so
defining that, at least, whereyou're starting, and what the
roadmap of that is going to looklike, can be really important to
getting data driven. It helpsremove ambiguity and confusion
and gets users aligned on whatthey can expect.
(16:50):
to help with that, definitely doit.
Yeah. All right. And thenthere's another concept on the
path to getting data driven,called the Business Algorithm or
Business Objectives andAlgorithm. Do you have a sense
for how to describe that well?
I'll take a stab at it if youdon't.
Caleb Ochs (17:10):
Yeah, I can give it a shot. So really, it tells you,
you know, your businessobjectives, you can think that
you're out there to dosomething, right. Like, I can't
think of a good example rightnow, but you want to do
something out there, you havebusiness objectives that you
want to complete.
Brick Thompson (17:25):
I've got one for you. You want to make your
service delivery guys and womenwho are driving around in
trucks, you want to get theirutilization as high as possible.
So as much of the time thatyou're paying them for, their
billable to a client, so thatmight be an objective.
Caleb Ochs (17:41):
So yeah, that's a good one. So let's say that your
target is 90%. You can say, "10%we're gonna use for training,"
or whatever it is. So that wouldbe one of your business
objectives. And you would havemetrics that support that. Now,
you might think that, "Oh,that's just the utilization,"
maybe, but there's probably fiveother things that support that
(18:03):
as well. And you need to definewhat things and what metrics are
going to support utilization, sothat when somebody has very poor
utilization, you're not justsaying, "That person has poor
utilization,." You're saying,"That person has poor
utilization. Now, let me look atthis, and this and this. Okay,
now I understand what's goingon, and we can actually do
something about it."
Brick Thompson (18:24):
That was great.
All right, really good. Thatcomes up a lot in sales too. The
number you care about for yoursalesperson is how much should
they sell, but when they're nothitting their targets, if all
you have is that end number,it's hard to know where to dig
in. So your algorithm, yourobjectives, upstream of that can
help you get to that. Thatalgorithm, those objectives,
(18:46):
help you know then, what datayou need.
Caleb Ochs (18:51):
And having those things lined up and defined,
helps with that, building agreat place to work, right? You
take that salesperson example,if you're just judging them on
that N number, and you don'tcare about the context around
it, manager could come down hardon somebody. It's like, well,
there's all these othercircumstances that you could
(19:14):
have looked at and seen, "Okay,this is what's going on, let's
actually fix some of the rootissues here and actually work
with this person." And that justmakes a better, better culture.
Brick Thompson (19:23):
Yeah, well, and also, you can take someone that
might have failed based on the Nnumber, and make him successful.
I've seen that many times inmany different situations.
Caleb Ochs (19:31):
Yeah. And that's ultimately what you'd hope for.
Brick Thompson (19:33):
Yeah, of course.
All right. And then there's onemore pillar, which is
establishing a Community ofPractice. What does this mean?
Caleb Ochs (19:41):
So this is, like your analysts and your
developers within the company. Alot of the companies we work
with don't have a staff to dothis. But essentially what it
is, is it's a group of peoplethat you can share ideas with,
share best practices with, getout source from, that type of
(20:01):
thing. So for us, if you don'thave this, or you don't have
people that could participate inthis, you could use like a third
party to be that community ofpractice for you. Somewhere to
give your users support andpeople that are responsible for
this.
Brick Thompson (20:18):
Yeah, that's interesting. We have that just
internally, as we support ourcustomers, we have a huge
Community of Practice here. Sojust because you're not working,
as a Blue Margin employee, justbecause you're not working on a
particular client's project, youmay still get tapped. Because
you've got expertise in aparticular problem that's coming
up.
Caleb Ochs (20:36):
You're right, exactly. And if you can build
that at your own company,fantastic.
Brick Thompson (20:40):
Yeah. All right.
There's so much more to thistopic. We're already 20 minutes
in, so I think we'll wrap fortoday. We'll come back and talk
about some of these pillars inmore detail. There's a lot to
it. But I think that does it fortoday, unless you have anything
else.
Caleb Ochs (20:56):
I'm all good.
Brick Thompson (20:56):
All right.
Thanks, Caleb.
Caleb Ochs (20:57):
Thanks.
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