Transcript
WEBVTT
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Conversations from the front lines and marketing. This is B two, B growth.
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Welcome in to be to be growth, and today I am thrilled to
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have John Literalc with me. He
is the global account executive at easy projects,
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the creators of the bird view professional
services automation platform, and he's also
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the host of when spreadsheets hit the
fan. And today I'm actually thrilled because
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not only do we have John with
us, but we're gonna feature one of
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his episodes here in a couple of
minutes. John, welcome to B to
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be growth. Yeah, Benji,
thanks for having me. I'm excited to
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be here, for sure. Congratulations
on the show. I know still in
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the early days, but exciting to
to see this this happening and getting off
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the ground. Tell us a little
bit of the premise of when spreadsheets hit
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the fan? I'd love to hear
about it. Yeah, absolutely. I
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think the title kind of gives a
hint at it. It's a show for
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senior operational leaders and sea level executives
who, you know, do lots on
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spreadsheets and, you know, do
business decisions and some of the troubles and
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what was they've had. And Yeah, really what we're trying to do is
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collect create a community of listeners and
guests around best practices around, you know,
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running your business, whether that's from, you know, a human resources
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point of view or from an operational
point of view. You know, how
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can you run your your business better, really targeting like people, like chief
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operating officers, chief marketing officers.
Yeah, it's been pretty exciting. And
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how many episodes do you have so
far? Yeah, we launched in May
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and by the end of August will
have about eight. It's been good.
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We're trying to do about, you
know, two a month right now.
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Fantastic. I wonder, as you've
gotten into this, John, what's your
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favorite episode so far? What what
stands out to you? Well, I
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know it's gonna sound but they're all
my favorite. But if I had to
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think about one that I think would
be relevant to your audience, it would
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actually be the first one. It's
titled Digging Out the Data Case for measurement
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as a core company value. The
reason why I think it would be interesting
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to your audience is, uh,
the gentleman Shawn Collier, is the chief
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operating officer for Creative Agency, Marketing
Agency, and a lot of what he
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talks about is really really targeted for, you know, marketing firms. So
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that's one I would pick for the
show, but I love them all.
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Fantastic. Well, I'm excited to
get to share that episode then, right
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now with our audience here on B
two, b growth, and we love
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getting to do these cross promotions of
sorts. We get to learn from other
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shows and so for everybody listening,
enjoy this one. If you want to
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connect with John or myself over on
Linkedin, you can do that and you
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can also check out easy projects and
bird view online. Be Sure to do
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that. John, is there anyway
that? What's the best way to to
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check out easy projects and what bird
views up to? Yeah, we have
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a really simple Internet address. Easy
projects, all one word projects within s
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and then dot net, not dot
com, and once you're there there's you
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know, tab right to the bird
view website. Fantastic. All right.
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Well, let's jump into today's full
conversation. Digging out of the data a
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case for measurement as a core company
value. Here we go. Welcome to
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when spreadsheets hit the fan, a
bird view podcast. This is a show
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for leaders and fast growing professional service
organizations looking for the latest conversations around service
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delivery best practices. Let's get into
the show. Welcome to when spreadsheets the
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fan. I'm your host, John
Lyric. In today's episode I talked to
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Sean Collier. Sean is the CEO
of Etna Interactive, a digital marketing company
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that helps elective healthcare providers across North
America attract their ideal patient audience so they
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can build the practice of their dreams. With expertise and online marketing and systems
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engineering at an interactive helps both private
practices in large groups expertly deployed custom online
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marketing strategies. Sean turns business limitations
into competitive edges for maturing companies, using
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data concealed in the organization to release
time and generate profits. Sean and I
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are going to talk about the importance
of making a data driven decision, what
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happens if you don't and sort of
why a lot of companies still don't make
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data driven decisions. Let's jump right
into it. Well, you know,
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Sean, I've been really excited.
You know talk to you, you know
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you do something really incredible work as
a creative agency, and you know you've
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been doing this for a long time. You've been around the block a lot
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on a lot of different companies.
Uh. So, when you look out
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there in the business world, you
know, either in your industry or just
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in business in general, with your
experience, what do you think is the
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biggest mistake organizations are making and they
should stop? You know right away.
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What's what's your pet peeve? My
pet peeve? Well, the first one
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that comes to mind is probably not
the question you're looking for, but people
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taking zoom calls without an appropriate headset
and microphone. I don't know how many
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things. It can lead to a
lot of things, but you know,
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probably the less flippant answer to your
question is what I would coin is making
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decisions about the direction of a product
of business a team without the underlying data
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to support it. And it's something
that I talked to my team about a
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lot. I'm a very data centric
guy. So even though the you know,
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the title of your podcast is when
the spreadsheets hit the fan, I
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am a big fan of spreadsheets right. I use all the time and mostly
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because I love that underlying data and
it's important to me to use data to
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make a decision and track it in
its resolution and did it make an improvement
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and stuff like that. But a
lot of organizations don't do that. You
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know, myself included, my organization
included, there are times at which we
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don't use the underlying data to make
a better decision or arguably the right decision.
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Yeah, that resonates with me and
I mean I think nobody would disagree
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with you that making decision based on
data and in fact is important. But
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people still do right. So can
you give me an example in your experience
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where you've seen someone make a business
decision they didn't have the right data or
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they had the wrong data, and
can you quantify for anyone listening to this?
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What would you know have been the
impact, you know, like intangible
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things like, you know, revenue, and intangible things like maybe brandon that
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you know we always are listening.
Honest, I only hear those kind of
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war stories from you know, someone's
been out there like yourself. So I've
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run product teams in a number of
organizations and in my court organization, which
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were a digital marketing agency. We
help clients, you know, across North
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America, to promote their brand and
drive leads into their practices. And people
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don't usually think of product in the
sense of this repeatable, unitized thing,
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as something creative agency is really attached
to but we do, and it is
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a practice that's very important because repeatability
of processes, controlling pricing, being able
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to ramp up resources to do this
repeatable, qualified thing is really important.
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However, in the product world one
of the biggest challenges that you can run
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into is if you build a thing, is this really what your customers want?
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Can you really sell it and will
they really pay for it? And
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you know a number of I'll speak
from from experience inside of of Atna,
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you know, a twenty year old
organization. There are times where we build
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to a client need. Right,
you've got some really excited salesperson I know
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you work in sales, some really
excited salespersons out there talking to a client
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like I really want they want this
thing. Know, we can do this
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thing there. Like okay, that's
cool. I like, I see where
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you're going. I think the product
can do these things. We can twist
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it, shape it, build it, whatever the case may be, and
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it might satisfy that one client.
But if you don't do the LEGWORK,
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homework to understand does that thing that
you want to build, that product extension
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Um the product shape? Is it
scalable to other people. What is the
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market for this? One of the
market opportunity for it? Right. That's
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something that I think, uh,
product organizations fail at a lot, unfortunately,
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because you know, somewhere inside the
product organizations someone's got that great idea
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and again, it might be a
really, really good idea, but if
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you can't sell it to someone who's
willing to spend money for it at the
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scale that it took you to recoup
your initial investment to build it and,
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you know, the five x that
you wanted to make on that investment of
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time and effort and so forth,
then you've really done your business. That
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its service by not looking at the
addressable market, at the existing clients who
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want that thing, find some way
to test and understand the impact of this
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product that you want to bring to
bear. So that's that's something I see
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happen a lot because people get really
excited about building new stuff. Right.
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It's it's fun, it's interesting to
build new product. Um, it's exciting
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to market new product, but if
you can't sell it, if people aren't
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going to buy it, then you've
wasted a lot of organization time. So
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it's one of the things that I've
seen. Um, build a lot of
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excitement and then, unfortunately, a
lot of depression in the teams that build
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that product and bring it to market
and then they realize, well, it's
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not selling, it's not moving,
it's too complicated to sell, it's priced
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wrong, it doesn't fit the real
need of the market, whatever the reasons.
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Maybe you know it doesn't. Instead
of those product teams to develop something
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new next time. Yeah, you're
right. What comes to mind is the
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term perpetual pioneering, right. Yeah, you're never getting into like being able
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to, you know, get out
of that mode. So, yeah,
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that's that really resonated with me.
I think, Um, you know,
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a lot of our listening audience,
being business leaders and senior operational practitioners,
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are gonna are going to resonate with
that. Right, building a product,
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uh, you know, it's a
gamble and you want to be making the
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right gamble right decisions. So that
that was great advice. Okay. So
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if we stop making decisions without data, okay, then is it as simple
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as saying, you know, we
start making decisions with data, or do
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we start doing it with a certain
type of data? Yeah, I think
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there's a sliding scale of some sort. There are clearly some decisions that I
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don't need data for. What kind
of Sandwich am I gonna need for lunch?
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Right? You know, there are
things that it would be overkilling.
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Will be able to spreadsheet hold on
Um, but there are things where it
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can matter. Right, I'll use
another story as an example. Pricing changes,
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right, so Etna did, probably
lots of companies around this time or
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making pricing changes. You know underlying
markets and costs of delivery for goods is
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changing. But when you make a
pricing change out in the marketplace, that's
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an important and impactful decision that you
need to understand and it's hard, it
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could be very hard, to make
that judgment call of is this the right
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one to do? Should I make
this change, you know, for margin
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purposes, for how it will sell
in the marketplace? Doesn't allow my customers
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to still buy this product that I'm
still doing, doesn't change my market.
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So when I make this change,
how much data do I really need?
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Do I need a lot, do
I need little? Do I need to
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analyze a ton, or do I
not? And any one decision that we
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make. You know, I definitely
won't say you always have to have data,
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but I will say that when you
make that decision, you should understand
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what are the what's the data that
you're going to change? Am I going
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to change how fast step gets done? So I need to be tracking time
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on task or something like that for
a process. Am I going to change
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my adoption rate for product sales?
Am I going to change contract timelines?
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Like, what am I expecting to
change with this thing and make sure I'm
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measuring that so I can see the
impact of my decision. So maybe if
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I didn't have all the data up
front, I should at least be knowing
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what am I going to change with
this and let's make sure I measure it
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after the fact so I can know
I did. I did make the right
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decision, that was a good decision
or, you know, it was mostly
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right. I didn't get it right
and now I need to make another pivot
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of some sort. Oh yeah,
and and so that heuristic constant learning,
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just you're just going to be constantly
improving as well, right as you as
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you have that data and analyzing it
as the new data come in, because
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you're right, you can't get all
the data sometimes up at the front right
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well, and a lot of times
organizations haven't been tracking that thing that you're
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thinking you're gonna make a change to, like, Oh, we don't look
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at the data that way. I
don't. You know, I can make
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a guess at it. I can
use some other data that approximated Um this
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this elements that I'm looking at,
but we haven't been trackeding it. Well,
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we probably should be tracking it now
because we're we are making an organizational
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change to impact that thing. So
we should know what the change is when
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we make it. Great, Oh, that's awesome. So one of the
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things that we want to do here
on what spreadsheets at the fan is we
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always want to challenge our guests to
try and take their wisdom of what they
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would stop doing and start doing and
turn into a simple maxim. What would
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you start? which would just stop, Dake, do you think you could
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do that here? A SIMPLE MAXIM? Write something that can be applied.
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Uh, you know, spoken in
short term, but applied by everyone you
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know in their day. Right exactly. You're in the boardroom and you just,
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you know, stop doing this start
doing that. That's exactly right.
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When looking at a decision that you
need to make, can you see how
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did I say this? Can you
quickly estimate the impact of your change on
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your team, on your clients and
on your business at large, and if
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any of those get out of a
you know from a small, medium large
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perspective that the impact is large on
any three of those things, then you
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should probably stop and get more data. Okay, good, we'll see.
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Yeah, it's good and I think, Um, you know, because anyone
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that's obviously just kind of, you
know, listening to this while they're driving
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now that that's what's gonna stick with
them and resonate with them. So,
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you know, that's great. Okay, let's talk about some of the theory.
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Right, obviously it's so, so
common sense that you should make decisions
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with data and you know, we
we hear this all the time, right,
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data driven decisions. So why are
so many organizations still not doing it?
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What do you think is the reason
why they're not doing it? I
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want to say urgency. I think
that there are a lot of organizations are
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moving very quickly, right, you
know, leaders and executives companies all the
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way down the line to everyone who's
working on any individual project. They have
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to make hundreds of decisions a day
and they know that if they deliberate on
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one too long, it might have
an impact, or maybe they just don't
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want to deliberate on it too long. I don't want to have to think
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about this because I don't understand the
urgency or the or, sorry, I
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don't understand the impact of it.
I can make a decision and move on.
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So that volume of things and the
speed with which we have to move
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in any given day is driving us
to want to get to a decision.
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We don't want to deliberate, we
don't want to Dili Dally, we don't
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want to hold up the client,
we don't want to hold up our teams.
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Whatever that impact is, we want
to we want to get there,
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not not from the standpoint of I'm
gonna make a snap judgment. Let's hope,
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let's hope not, because those are
probably not good for you. They're
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more emotionally driven than logically driven.
But speed adders in our businesses. It
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matters for our clients and because we
want to make a decision fast, we
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don't necessarily want to go dig out
the data, and that really probably brings
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the other side of the coin.
Is it's often harder than it should be
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to pull out the data about things. So when you think about the systems
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and processes that you use to keep
tracking your finances, keep track of your
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workflow, keep track of your contracts, you know, your client support,
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whatever the case may be. You
need to be able to get that data
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out of those systems to ask and
answer the question of this decision that you're
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trying to make. So I gotta
go fast, but it's hard for me
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to get the data. So I'M
NOT gonna go get the data, I'm
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just going to make a decision.
Oh yeah, that makes so much sense.
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Uh, I would agree with you. In my experience it's urgency right.
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Um, you know in the back
of your head, as a business
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leader, you know I should get
more data on this and really think this
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through and you know, test it
a b testing and all that. But
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again, that urgency right to get
things done. You know, to to
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move Um, you take shortcuts.
So, Um, you know. Can
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you give us some examples of when
you've seen someone, even yourself, who's
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taking the time to slow down,
you know, not a bow to the
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tyranny of the urgent and has taken
the time to get the data, even
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if if it took a little longer
than expected, and how how that made
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a better decision. Can give an
example? Yeah, definitely. Um,
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we went through a process recently of
selecting a new crm provider. Right.
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It's a you know, new systems
software to help run our business we've been
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running for fifteen plus years on effectively
kind of a homegrown solution, you know,
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as as engineers world do, uh, as we talked about in the
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pre show, like engineers will solve
problems by creating software themselves often and we
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did that right. We we built
in, ran a system for a very
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long time and Um, we ultimately
the debt that was created, the technical
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debt that was created with that system
is outweighed by the effort required to move
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to a new system. So we
get into this process of evaluating serum systems,
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looking at your you know, all
the litany of everyone that could be
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involved in it. And I ran
that part of the process and probably took
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about an initial three months to do
a requirements gather and look at the usual
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suspects and get down to the demonstrations
and start drilling into it. And I
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could have gotten to a solution,
a decision at the end of that relatively
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quickly. And then my CEO Ryan
through a curve at me and said,
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Um, well, what other things
are we do we want to solve for
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in this and what else can we
solve for having to do with some finance
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questions right that the intersect with our
CFO and maybe pause for a second and
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go huh, yeah, I should
probably take a step back and gather a
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little bit more and wind up unpacking
a process that our finance team uses,
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because I was thinking very operationally,
as a CEO probably should and does,
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and didn't think about the finance side
of this question that Ryan was asking of
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me, and we wound up arriving
at a whole new UH. It's a
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revenue booking process that really changes the
game for us and automates a ton of
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steps that were very manual for my
cfo, grace and her team, and
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we were able to remove work that
didn't need to exist or won't won't need
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to exist when we have it deployed
and give more time to the teams to
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actually create value in their organization versus
doing all the Colete to click and by
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the simple ask of saying, well, what more could we do with this?
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Where else should we go? A
gave me. It gave me,
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I guess, a little bit of
latitude to say, like, I'm done
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with a decision, let's move on, to say, okay, well,
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I'm freed up now. You know, my boss is saying it's okay for
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me to take a minute and think
further about this and uncover a section,
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uh, that's going to create a
huge benefit for a company when we roll
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it out. Yeah, that's that's
amazing. So it's an amazing story and
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just because you took the time to
do it right and and I think that
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maybe the impetus there was, you
know, I was challenged with the question
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which had the implication behind it,
like take the time to think about this
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question right, so as leaders we
can go to our teams and say,
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I have this problem, I need
you to solve this problem, and they
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might hear it as organizational dictate,
like Oh, I gotta go now,
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move a move, like no,
no, no, no, I need
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a solution. Here are the parameters
that I'm thinking of. I need these
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things solved, but I need you
to take this I need you to think
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about it and come back to me
with how you think you want to solve
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it. And you know the data
under buying that and so on. So
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to take the time to do it
right. Um, as long as we
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agree upon the when and I'll tell
you if it's an urgent thing. This
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is on fire because my client is
screaming at me versus. This needs to
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be done right, this needs to
be done complete, this needs this has
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a huge impact of the organization.
I needed thought through this as a small
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impact the organization. Just giving your
best judgment. Okay, that's great.
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Um, I love the stories.
They're just, you know, you're showing,
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like, the benefits and and the
costs of not, you know,
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making a proper data driven decision.
I love that you have said, you
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know, it's the tyranny of the
urgent. I think you're you're right on
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that. That just that resonates with
me. That feels right. But if
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I want to get started and I
want to help my organization, whether I'm
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a consultant or I'm a chief operating
officer, I'm the owner of the CEO,
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how do I get started? What
step one, step two? To
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make my organization culture of, you
know, making decisions by, you know,
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having the right facts, the right
data. What do I need to
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do? The first one is,
I think, modeling from the top.
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You've gotta have leaders in the organization
that believe in not making knee jerk decisions,
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even though they might have the experience
to say this is the right thing
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to do, I've been through this
thirty times, I can do this Um
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at least to back those decisions up
with. Here's the data that I know,
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because I'm looking at the P and
l monthly, I'm looking at the
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incoming Um Saturation. You know,
whatever those elements are that you get as
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a leader, right, you get
a lot of data kind of shoved at
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you as a leader, hopefully Um, and you're digesting it and your understanding
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it and you've wrapped your head and
your fingers around that data and you can
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use and expose that to team members
that you're asking to solve problems for you
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and say I need to solve here's
some data that I think impacts that and
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I think this is and this should
be part of your decision process. So
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you model it, model that behavior. The second part of that is asking
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questions of them to say hey,
you came up with this process change,
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you came up with this decision to
do x, Y Z. can you
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show me how you arrived at that? Can you show me the data that
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influenced your decision here and by asking
for the data. It should be evidence,
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like I need to see and understand, not to second guess them,
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because clearly that that conversation could take
a left turn there and go into a
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wrong place. So I'm not trying
to second guess your decision, but I'm
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trying to understand how you arrived at
it and what was the data that was
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evidenced by that process. So the
modeling and asking the questions, I think,
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are key elements to help the organization
get there. That the last one
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that I'll offer, Um, is
how you know we do this as of
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one of the core values of Etna, which is make it measurable. So,
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Um, that's something that needs to
be at a mission statement. You
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know, company values level, and
this is are always hard things to do
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for a leadership and executive team.
It's kind of recast the values for the
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organization. But we chose when we
did this, the last time we did
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this like six years ago or so, when we cast value statements, we
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put data and we put measurability specifically, not just data, because uh,
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data is kind of metamorphous word,
but put measurement as a core value.
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And that should bring to mind and
give you the opportunity to talk about how
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are you going to measure that change? What were the measures you use to
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do this? What was your measures
of success? Right, so it becomes
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part of the of the vernacular.
Wow, great advice and really easy to
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follow. I mean someone can fall
that like tomorrow right. They can get
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started on that tomorrow right. Model
the behavior, start asking questions that elicit
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the person that's making the decision to
show that they've gotten. They've gotten the
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data and, you know, put
it into your core values, it right
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into your your your guidelines for your
company. Really easy to implement. Um,
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let's talk about, though, as
easy it is to implement. We
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know things go wrong, right,
something always happens, Murphy's law. So
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tell me where you've seen someone try
to do this and they had some kind
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of resistance and how did they overcome
that challenge, that obstacle to making their
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organization more data driven? Yeah,
it's, Um, my head kind of
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split in two directions. They are
thinking about two ways things could go wrong.
357
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One is that you create an opportunity
for a decision paralysis and that I
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haven't collected enough data. I'm struggling
to go get the data I'm scrubbing from
359
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multiple systems to compile things down.
So there's and this is very common when
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you have a lot of legacy systems
right. For Your Company has been around
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for twenty years, guaranteed you've got
some legacy systems right, and pulling the
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data out of those systems and mashing
it up together can be hard, Um,
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and people will spend a lot.
Can't a lot, meaning more than
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probably should be for the level of
decision right. A small, medium,
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large impact again and people will kind
of get wound around the axle of saying
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I have this data, I'm not
sure what it tells me, I don't
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think it's enough, I don't think
I'm prepared to make this decision, or
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I can't even get at the thing
I'm trying to approximate. You know,
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there's a fun story about this one. So in the digital marketing, marketing
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space, things change all the time. Google is when it's changing its rules
371
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for how it does it's search engine
rankings. Right, so when you get
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the actual search results up on a
page, it's using all kinds of algorithms
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and the logic and obviously, as
agency we want to get our clients at
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the top of the page for the
keywords and phrases and locations that they really
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care about. And so there was
a change that Google made last year called
376
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the UH Google Web Cor vitals update, which is basically Google saying speed matters.
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Make things fast all the time.
And they came out with three primary
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measurements of how they study fast on
a website. And so we responded with,
379
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oh well, we need to refactor
how our clients websites that we build
380
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reflect on those three measures of performance
that Google will use to then influence the
381
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search in ranking, so our clients
pages will be faster on those three metrics
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and appear higher in the search engine
results. And then we did it.
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We rolled it out, we rolled
it across a whole bunch of clients and
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it's done good things. It is
absolutely measurably better performance on the site.
385
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But Google didn't do exactly what they
said they would go in to do,
386
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and the results of what is it
Um measurably better for our clients sites and
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the consumers that are going to them. Yes, does that change the behavior
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of the ranking on the search engine
results page? I don't know, and
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that's the problem I get stuck in. My teams gets stuck in analyzing the
390
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impact of this very sizeable, very
effort, high effort, heavy change,
391
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and I can't give you an answer. We decided to make the change because
392
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it made sense to make the change, but now that I've deployed it,
393
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I can't easily say did it do, from a Google perspective, what we
394
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wanted it to do? And so
I'm stuck in this paralysis mode of not
395
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being able to answer as good or
bad, or maybe maybe I don't want
396
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to say it's bad because we spent
so much effort at it and and so
397
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that's something that teams can get stuck
on and get wound around the actual delivering
398
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data day to day to data before
they can make the decision and say it's
399
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okay to lose, it's okay to
get it wrong, it's okay to let
400
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the data not be there, because
ultimately you have to set a boundary for
401
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your decision. When are we going
to say this easy to get done and
402
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here's where we're gonna go, or
at least how far are we going to
403
00:28:49.519 --> 00:28:56.799
go before we have more data and
and complete this decision set? Yeah,
404
00:28:56.839 --> 00:29:00.240
that's that's awesome. Uh, you
don't want to out to the tyranny of
405
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the urgency, like what urgent,
what you said at the start, but
406
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at the same time you don't want
to shift over into the other ditch and
407
00:29:07.720 --> 00:29:11.240
have paralysis by analysis. And I
think you've navigated for us kind of a
408
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good middle of the road, right, so that decisions you know will be
409
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well to the best of an organization's
ability at any level. You know they'll
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start making decisions based on the right
level of data that they can acquire and
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understand and and it evaluated that against
the impact, the impact to your team,
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00:29:27.720 --> 00:29:30.960
to your customer and to your organization. If any one of those is
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00:29:32.000 --> 00:29:34.319
a this could have a big impact
onto any of those three, then it's
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00:29:34.319 --> 00:29:37.960
okay to take the time, Um, and ask for help. Right.
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I hope that everyone gets the opportunity
to work in an organization as as fun
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00:29:42.359 --> 00:29:47.079
as as my team is, because
I can ask for help, even as
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00:29:47.079 --> 00:29:49.480
a leader in the organization. If
I am running into a wall, I
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00:29:49.519 --> 00:29:53.200
can grab one or more of my
reports my team and say, Hey,
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00:29:53.200 --> 00:29:56.720
look, this is what I'm seeing
and I don't understand it. Can you
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00:29:56.720 --> 00:30:00.000
help me make heads or tails at
this, because I don't feel comfortable with
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00:30:00.119 --> 00:30:03.519
and forward by decision until I can
understand this. And so by saying that,
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00:30:03.799 --> 00:30:07.079
by giving space to it and letting
other people come help you with it,
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you can often, you know,
move yourself off the marker that you're
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stuck on because it is a big
impact thing and you don't feel comfortable with
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00:30:14.960 --> 00:30:22.920
making that final decision because the data
is inconclusive. Excellent. I know every
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00:30:22.920 --> 00:30:26.319
business leader out there is doing a
gut check right now and asking themselves,
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00:30:26.720 --> 00:30:32.079
have I created a proper culture Um, you know, to make data driven
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00:30:32.119 --> 00:30:36.880
decisions? Am I modeling out the
behavior for everyone myself? Am I asking
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those right questions? This was high
value. Sean. I Really wanna thank
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00:30:41.079 --> 00:30:45.240
you get great stories. They really
resonated with us and, uh, you
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00:30:45.279 --> 00:30:49.599
know, thank you for joining when
spreadsheets at the fan. It was great
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00:30:49.640 --> 00:30:53.920
to be with you here, John. I really appreciate it. Projects,
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00:30:55.119 --> 00:31:00.039
resources, finances a single source of
truth for service delivery teams. Birdview P
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00:31:00.279 --> 00:31:07.440
s a helps increase profitability by automating
and optimizing the entire service delivery cycle.
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00:31:07.960 --> 00:31:11.640
To learn more, visit easy projects
dot net slash bird view, Dash P
436
00:31:11.920 --> 00:31:18.359
S A. You've been listening to
when spreadsheets hit the fan a bird view
437
00:31:18.440 --> 00:31:23.039
podcast. Keep connected with us by
subscribing to the show in your favorite podcast
438
00:31:23.039 --> 00:31:26.599
player. If you like what you've
heard, please rate the show. That
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00:31:26.759 --> 00:31:32.880
helps us to keep delivering the latest
and Best Practices for professional service teams.
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00:31:33.440 --> 00:31:33.359
Until next time,