October 3, 2023 • 48 mins
Here are suggested show notes for this Bootcamp on developing a single source of truth (SSOT) in media and event organizations:
Title: Developing a Single Source of Revenue Truth in Complex Data Environments
Key Topics Covered:
- Introduction to the concept of a single source of truth (SSOT) for revenue data
- Value creation and tracking through SSOT implementation
- Steps for developing SSOT tools and technology
- Common pitfalls to avoid when implementing an SSOT strategy
- Importance of "right data in, right data out" approach
Main Points:
1. Definition of SSOT: A centralized platform containing trustworthy, clean, and meaningful data from across the organization.
2. Benefits of implementing an SSOT:
- Improved operational efficiency
- Increased revenues and customer retention
- Enhanced employee satisfaction
- Better cost predictability
3. Key components of a successful SSOT strategy:
- Cross-functional team involvement
- Focus on quick wins and iterative implementation
- Clear communication across the organization
- Agreement on definitions and success metrics
4. Technology considerations:
- Data warehouse
- Data extraction and cleansing tools
- Data access and management layer
- Visualization tools
- Predictive ML/AI capabilities
5. Common pitfalls to avoid:
- Starting too big or trying to tackle everything at once
- Letting IT own the strategy instead of business leaders
- Disagreement on data definitions
- "Once and done" mentality
6. Importance of aligning SSOT with stakeholder goals:
- Mapping data needs for investors, C-suite executives, and functional teams
- Prioritizing based on current business needs and urgency
7. "Right data in, right data out" concept:
- Focus on meaningful, actionable data
- Avoid tracking everything, which can jeopardize long-term value
Presenters:
- Heather Holst-Knudsen, CEO of H2K Labs
- Chad Rose, CEO of InsightOut and Treehouse Technology
Key Takeaway: Implementing a single source of truth for revenue data can drive significant value creation across media and event organizations, but requires careful planning, stakeholder alignment, and an iterative approach to be successful.
Interested in joining Revenue Room™ Connect, the first C-Suite network for CEOs and their revenue-critical C-Suite teams in media, events, data/information,
About Heather Holst-Knudsen
Heather Holst-Knudsen is the founder and CEO of H2K Labs and Revenue Room™ Connect. She is a seasoned executive with extensive experience in digital transformation, data, and revenue growth. She is a recognized leader and operator in media, marketplaces, events, and adjacent technologies. Heather has a proven track record of leading organizations to achieve customer-centric innovation, revenue growth, and enterprise value creation. As a thought leader, Heather shares her insights on multisided business models under The Revenue Room™. Connect with Heather on LinkedIn.
ABOUT H2K LABS
H2K Labs is a tech-enabled value creation specialist that helps media, data/information, event, and marketplace businesses accelerate revenue, drive profitability, and fuel enterprise value using data, digital, and AI. We host The Revenue Room™ Podcast, curate Revenue Room™ Connect, a professional network for CEO and their revenue-critical C-Suite teams, and produce events including RevvedUP 2025. For more information, please visit https://www.h2klabs.com
To join Revenue Room™ Connect, please visit https://www.revenuero
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Transcript
Episode Transcript
Available transcripts are automatically generated. Complete accuracy is not guaranteed.
(00:00):
Welcome to the Revenue Room,presented by H2K Labs.
(00:05):
Here's your host, HeatherHolst-Knudsen.
Well, welcome everyone.
This is the first of ourbootcamps focused on the concept
of data driven revenue growth.
Today we're going to talk aboutdeveloping a single source of
(00:25):
revenue truth in complex dataenvironments.
We'll cover a few things today.
We'll introduce the wholeconcept to you how an SSOT works
in a revenue type capacity.
Because it's part of anoverarching strategy, the way to
create value and track andmeasure, steps to developing
tools and tech, landmines toavoid.
(00:47):
We've seen many and this wholeconcept of write data in, write
data out.
I'm Heather Roltz Knudsen, theCEO of H2K labs.
I have been in media events,digital information for over 30
years.
And my bent is data and revenue.
So I am very passionate aboutthe subject and our business
partner.
(01:07):
Is Chad Rose, the CEO ofInsightOut and a software
development and data companycalled Treehouse Technology.
Chad, you want to say hi?
Hello everyone.
Great to be here.
I'm looking forward to thediscussion and answering any
questions you all might have.
My background is largely in dataanalytics engineering, more on
the technical side.
So.
(01:27):
We can get into the details asneeded and happy to entertain
any questions.
So what we're trying to do todayis we're going to review the
fundamentals of developing asingle source of truth in your
revenue organization, thebenchmarks for value creation.
and understanding and reallytrying to help you with the
opportunity in the landmineidentification.
(01:48):
This is meant to be interactiveby the way, so there'll be
points in time where I'll stop,ask questions.
If you do have questions youwant us to answer and you want
to put it in the chat, pleasefeel free to do so.
You'll get a copy of the deck,and we're in the process of
building a detailed playbookthat'll have more action
oriented type of tools thatyou'll also receive.
(02:10):
And if you would like to set upa time with us, both Chad and
myself, from both the businessand the data tech perspective,
To consult where you are withyour SSOT strategy.
That also is something we weredoing for the people who
participate.
All right.
So I think everyone knows this,but data driven organizations
are far more profitable thantheir counterparts.
And this is a study that wasjust done at the behest of
(02:31):
Google through Harvard BusinessReview.
Operational efficiency,revenues, customer retention,
employee satisfaction, costpredictability across the board
being data driven is a hallmarkof leadership and profitability.
91 percent of those respondents,by the way, agree that
democratizing access to the dataand analytics is important to
(02:54):
the success of theorganizations.
And that democratizing access toAI to drive predictive insights
is crucial.
And the reason why I bring upthis democratization is it is a
critical part of becoming datadriven.
Many times we'll see companiesthat invest in the SSOT
strategy, but yet they're givingit to leadership or functional
(03:15):
leaders, but they're notbringing it down to the whole
business.
The democratization aspect iscritical to become truly, fully
data driven.
I recently took a course withMIT on data monetization, which
is.
Really when they say datamonetization, they look at it
from three areas.
It's an improved strategy, awrap strategy, and a sell
(03:37):
strategy.
The improved side is really whatyou're doing internally to add
cash to the bottom line.
Improving operations, improvinghow you're acquiring, retaining
and growing revenue, improvingprocesses, standardization, all
those things.
But it all starts with your dataasset.
But if you go through thisjourney, you'll be able to drive
(03:59):
excellence across all differentareas of the business.
But today we're really going tofocus on the one core thing that
has to be done right in orderfor you to go through these
capabilities of data asset.
That is your master data, howit's integrated, how it's
curated, right?
When you go up to curation andyou have the right platforms.
(04:20):
And you have the right datascience, you can then actually
drive predictive andprescriptive insights.
But one of the key things alsoto realize is that as you go
through this process, thesecapability building is
iterative.
It happens over time and it'sevolutionary and it's part of
your journey.
I think sometimes I find whentalking to customers and clients
(04:44):
that.
Bigness of doing something likethis is almost like a like a
game stopper.
And then making that dataavailable to up and down across
the organization is really a keycriteria for success.
So we're going to do a quickpoll here, just so I know where
everyone is on this SSOTjourney.
It's confidential.
(05:04):
I'm not going to show theresults.
I'll speak to them.
So feel free to answer.
I think this is going to be avery interesting conversation.
I think people are in the sameboat and starting the journey or
on it and a little bit worriedabout where you are.
I'm going to end the poll andlet's move on.
Okay.
(05:24):
So single source of revenuetruth in complex data
environments.
First of all, let's talk aboutwhat an SSOT is.
Some people call it a singlepoint of truth.
I've actually never heard that,but thought I'd put it up here.
Essentially, what it's doing isgetting your data into a state
where it can be found in asingle spot.
(05:45):
It's trustworthy, it's clean,and it's meaningful, right?
Centralized platform.
Yeah.
I mean, one way to think aboutit is if you have a question as
to the performance of a certainpart of the business.
Is there a place that you can goto get that answer with data?
Right.
If you have to go to a thousanddifferent places or go to Excel
(06:06):
or otherwise, you probably don'thave that, but it's one way to
think about it.
Chad, I don't know if you readmy blog on LinkedIn the other
day, but the forecast was deadon arrival because it took a
hundred hours across sevendifferent divisions.
And two weeks per division todevelop.
I mean, it was unbelievable.
Like they definitely do not havea single source of truth.
(06:27):
So, and then, and the reason whyI like to add the word revenue
in when it comes to thisparticular arena is I find that
it's very important to reallytruly define what the revenue
truth is in terms of where thedata lies.
And it's not just about what'sin your CRM.
It's way more than that.
(06:48):
It is what anything yourcustomer is touching that you're
selling to their behaviors, theway you're engaging with them
post sale, what they're doing onyour website post sale, all of
these things are really criticaland important and should be able
to be referenced in a centralplatform in media and events
where marketing services arebeing sold and the delivery is
(07:11):
about bringing value to them, i.
e.
you're bringing an audience tothem You're looking at data on
the product side because yourproduct performance is about
what's happening on the audienceside and how that curation is
happening and how that meets thedelivery of contracts.
That is such a fundamental,profound impact.
(07:31):
On your analytics, yourforecasting and everything,
especially with existingcustomers, which is your most
profitable base, making thatconnection is critical.
So in the complex dataenvironment, which I just
touched on, which is differentthan what I call a one sided
business model or businessmodels that sell hard goods.
Or software, for example, whereyou are selling this SaaS
(07:54):
solution, here's what you'regetting, and we can track and
see usage.
Complex data environments do nothave it that easy.
And it's not just the two sidedbusiness model, it's multiple
channels and formats.
It is, a lot of these businesseshave had acquisition activity,
so M& A activity.
(08:14):
You're bringing in businessesthat are working off different
platforms or different markets.
It's very complex.
And so we put this together toaddress the complexity part, but
Chad and I work together on alot of client calls and things
like that.
And I think one of the thingsI'd love Chad to talk about is
working with one sided, morestandard type business models
(08:37):
versus This complex dataecosystem, tell me what your
insights are and the things thatyou see.
Yeah, absolutely.
You know, I think with regardsthis segment of the market, you
have almost within eachbusiness, you have almost
multiple different businessunits that act and behave very
differently, almost separatePNLs and probably are in some
(08:59):
cases, typically, like youmentioned, Heather, you know, if
you have a software company,they have a recurring revenue
model and that's how they lookat their business, that's the
most important metric.
And so the data model and theanalytics all revolve around
that.
There's an element of that here,but then there's also an element
of delivering goods andservices.
There's an element within theevent space of having to manage
(09:22):
this unusual sort of sales cycleand trying to hit your targets
and predict where you're goingto land.
And so each one of thoseindependently.
It is typically within ourexperience, a single project, so
to speak, to develop a singlesource of truth.
It's a, as I mentioned, it's acertain data model.
It's a certain system thatthey're inputting the data into,
(09:43):
but here you have all of themcombined, all of them at once,
and so there's a real level ofadditional complexity if you
want to get the full picture onthe entire business.
Not necessarily important to goabout it from the start to say,
you know, we're going to tackleit all at once.
You know, if you do want to getthe full picture, there are a
(10:03):
lot more variables than youwould usually see with a more
simplified business model.
Absolutely.
And I think, you know, from thefinance side, it's very
complicated and you touched onit, which I bring up here under
the business model, a lot ofthese business models are now.
under pressure or see theopportunity to move into data
monetization and move into thatrecurring predictable revenue
(10:26):
stream strategy.
So you'll have an old businessmodel going on the advertising,
the lead gen, the sponsorship insync with new.
Types of business model, therecurring revenue.
And so you're actually nowdealing with all different types
of revenue recognition,waterfall forecasting.
The levers are different interms of driving the predictive
(10:47):
analytics.
So again, it's complex.
I think what that means too, isthat if you have the ability to
put this together.
And achieve that single sourceof truth and you can really
differentiate or at least use itas a competitive advantage
within your market.
I 100 percent agree.
One of the things I always liketo say is if you go down this
(11:08):
path, your sellers are going tosell a thousand times better.
Your customer understanding isgoing to skyrocket.
You're going to outsell thecompetition over and over again.
It absolutely will be acompetitive advantage.
100%.
This is my view of, I used torun media and digital
information businesses.
So I would say when I wasputting together those awful
(11:30):
spreadsheets every month for myboard meetings, I would do my
best to pull data together fromsome of these areas that where
it was possible to really try togive some realistic
understanding of.
What did we believe was going tohappen predictively with
customer renewals, expansion,upselling, the new business
(11:50):
acquisition?
How was that being impacted bythe marketing funnel?
How was that being impacted bythe product delivery?
How was that, or are theretrends that we were seeing on
our website that were happeningthat would show up or down
movement?
You know, we talked a lot, wewere in the manufacturing and
the tech connecting tech withmanufacturing.
So.
(12:10):
This is the whole event side,but there's a lot of data
sitting around and the largeryou are and the more portfolios
and brands you have and the morebusinesses you've acquired, this
is this ecosystem, this.
Data ecosystem on the revenueside gets quite significant.
But the good news is you don'thave to include everything.
(12:30):
It's really important to look atthe data that's meaningful, and
we'll talk about that later, anddo not include data you don't
need.
Someone may say, well, you'reputting HR on there, but we need
to know headcount and payrolland things like that.
Finance has that on their side.
Right.
Chad, you, and you have a strongopinion about this.
Yeah, I do think it's just asimportant to consider what not
(12:53):
to put in, what not to includein the single source of truth.
I think there's a lot that wehave here.
And the important point to noteis if you had all of this
combined and you had all thesesources, you would be in really
great shape to get there.
You don't want to tackle themall at once.
And you really shouldn't, butwe'll get into that a little bit
more, but we also try to callout things that just really are
(13:14):
necessary when it comes to.
A revenue, single source oftruth and wasted effort that you
would put it into trying tobring that data together.
Right.
How do you know you need asingle source of revenue?
Truth Heather, real quick, givenwhere everyone is, if you don't
mind me jumping in, I'd becurious to understand or hear a
little bit, if anyone has anopinion, like if they're on the
(13:36):
path, why did they start Why areyou trying to develop one?
What pain points or where didthe priority come from?
If anyone has an opinion onthat, it'd be great to hear.
It's all of those things.
Yeah.
And we've been kind of, it's nota secret.
It's not like an aha.
Oh my God.
(13:56):
All these things exist now.
We've known a long time.
It comes down to then theinvestment, meaning people
spending the time to do theassessment and then migrate to
whatever the SSOT is going tobe.
Was there any finally made thepush over the edge there to get
started?
In my opinion, I'm Intel.
(14:16):
I feel like the shift in economyover the last couple of years
and our lack of ability topredict our revenue and count on
our historical retention rate,and then to figure out why and
what to do about it kind of cameto a head in the last, I would
say 24 months.
And if I can add to this too,it's not only these bullet
(14:38):
points, but even in ourbusiness, we had a problem.
Different teams would givedifferent answers.
Like they didn't know who toask.
They may go to one part of ourfinance or accounting function.
They may go to rev ops.
They may go to some Salesforceadmin and like everyone then had
a different approach as totrying to answer the question
and the requester has to bedifferent answers.
So it wasn't even just the datasources who in the organization
(14:59):
is responsible for reporting onsome of these key business
questions, which were maybe isthe easier one to sort out
versus.
Some of the data and techissues.
Good afternoon, everyone in ourcase, I had a chat with Heather
about this a few months ago,where we knew what was coming.
The pandemic certainly through alittle bit of a wrench in that
from a, from an end point, butwe ended up.
(15:21):
Buying 3 companies during overzoom during the pandemic, so
2022 was like.
We didn't even know what we had.
Now the dump truck has backed upto my house and dumped all the
information on the driveway.
And I'm like, great.
I need to get my teams to sortall that out.
And so it's all those things,but a different arrival path.
(15:43):
That's pretty common too.
Just the M and a route ends upbeing unmanageable unless you
can get it all together.
We're able to introduce certainshared services, but I know this
exists within these bulletpoints.
Right.
But it's like.
Just the tech stacks and thevarious legacy tech alone can
certainly make this.
Like from the top, somethingthat we could do better, but
(16:05):
then we will still need tochange some of the other
logistics.
Anyway, I'm not going to take upother people's time.
No, that's a good, it's a fairpoint.
It's a good point.
And that's another way oflooking at it.
Generally, it's an added benefitof doing this, but yeah,
absolutely.
Yeah.
And you'll see, I use the sametime last year on this third to
last bullet point.
Life is not the same anymore dueto a lot of different reasons.
Buying patterns have changed andyour demographic is changing and
(16:30):
expectations have changed.
So.
The one, the historical backview does need to be
complimented with real timetrending data, where the machine
learning and the AI comes in,where that actually allows you
to pressure test.
What people are telling you,right?
And that's why, and I'll justback up here really quickly.
So the unstructured sources atthe bottom, the, there's what's
(16:55):
being put in manually into yourCRM, for example, versus what's
happening actually.
So if you have customerinsights, I talk about this all
the time.
If you sold something and thereis a contract with product
performance metrics that need tobe met, and those aren't being
met or they're delayed.
(17:15):
That does have an impact.
That's something that is data.
You need to know that most timesdoes not get surfaced when you
talk to your sales team.
They think the deal's in there.
It's going to close on this dateand for this amount.
But yet, because they're notreally connecting like, Oh, we
haven't delivered yet.
It's going to be delayed.
So that's going to push my dealout to here.
Or we're noticing that while wemay have the same amount coming
(17:39):
in on a renewal, We're gettingless traction, you know, at
events, but there are otherthings that are happening
outside the CRM that help withnot getting caught, not knowing
what's going to happen.
So again, I'm just underscoringthat this is part of the SSOT
strategy that's really criticalto keep in mind when you are
going through it.
(18:01):
So let's go forward.
I think we already asked thatthis question was going to come
after this list of how you knowyou need a single source of
truth.
But I'll say that if you'respending a lot of money on
manual labor, additionalheadcount, and spreadsheets to
generate forecast reports, thatforecast dead on arrival example
I used before.
All of these are signals youneed it.
(18:21):
So we already kind of opened upthe discussion, but Mintel is
there.
You do research, right?
And, or you're giving insightsand intelligence for improving
marketing outcomes forcustomers.
If I am understanding what I sawon your website, correct?
Yeah, that's the gist of it.
All right.
Are these customized typeprograms or is it like a, is it
(18:42):
productized and standardized?
About 80 percent of the money wemake is in the form of a
subscription, like asubscription license to our
platform.
And then we've got aprofessional services arm that
does kind of customize one offdeliveries.
Okay.
And the subscription, I'massuming at the large ticket
item subscription that renewsannually.
(19:03):
Okay.
When you look at customeradoption and usage with your
platform, how do you definethat?
We have usage stats to be ableto say like number of active
users on our platform.
We can look at their downloads.
We can look at what they'relooking at.
So it's one of the client healthscore metrics that we then
provide to the client successmanager or the account manager
(19:25):
to be able to assess like thehealth of the account and as we
get closer to it, the risk orlack thereof and renewing that
account into the next year.
Okay.
And is that data applied toforecasting and pipeline and
things like that to adjust basedon the customer health score?
Nope, all of the forecastingright now is subjectively
categorized into different salesstages by the account manager.
(19:48):
So we give some training andguidance to say like, okay, if
this has happened, this stage,if this has happened, you're in
this stage, but they still havekind of the ultimate call day
and their manager, there's kindof a review of it, but they, it
doesn't factor in usage data orthings like that, at least
systematically, like the accountmanager may know it in their
heads.
Like, Ooh, this is a risk.
I blow usage here at thisaccount.
So I'm going to categorize it atthis stage, but it's not
(20:10):
systematically built into theforecast.
No.
Okay, got it.
So, anyone else want to talkabout the complexity at your
business that we may have missedor may add color to our
conversation?
All right.
Well, I will then move on.
So let's talk about value.
One of the biggest complaintsthat I hear is we've invested
(20:32):
all of this money and time andeffort into building, you know,
this data driven culture andstrategy, and we're not seeing
value.
Well, that's a result ofactually not defining it and
making a part of the strategy,but let's go into what value can
look like.
So there's tons of value with anSSOT, everything from, you know,
(20:53):
making it easier to discoverinformation, reducing the cost
to create those reports,including headcount that you
won't need anymore, or theheadcount can be reallocated to
value creation and added valueactivities.
It helps with data governance.
It helps across the board.
But the real big thing here, themessage I always like to say is
that if you are going to moveforward with an SSOT strategy.
(21:16):
You need to look at it as acontinuous creation of value
across multiple areas of thebusiness.
And you want to track and lookat those and have that top of
mind as you put your plantogether, track the progress of
the plan and evaluate outcomesof your plan as it goes through
milestones.
Yeah.
And actually just real quickHeather on that prior slide.
(21:38):
So a lot of our customers, thebest when they're using the
analytics and the single sourceof truth.
I mean, the means that it wasreally meant to be, they are
able to deploy new marketingefforts or change certain
tactics in their sales process.
And then simultaneously in realtime, kind of see how that is
impacting their business.
(21:58):
Right.
So again, as it relates, like,do I have a proper single source
of truth, am I doing thiscorrectly?
You should really be able to trynew strategies within the
business, adjacent to that, seethe performance with little
effort to develop like that.
To develop that insight or todevelop that visibility into how
(22:20):
that is performing within themarket.
And that...
It enables people to try thingsand then turn them off or turn
them back on depending on howthey work.
It really goes to Heather'spoint of enabling that value
creation going forwardcontinuously.
So the way that I look at it isthis.
The first part isstandardization.
Regardless of whether, where youstart on the SSOT strategy, you
(22:41):
need to look at things in yourbusiness.
And how you can use this processto standardize them.
I look at it that the SSOTstrategy comes first, by the
way, because you want to knowwhat to standardize, what makes
sense, and test it out versusdoing that first, then driving
(23:02):
SSOT side.
But it's everything fromprocesses, how you measure
things.
What does conversion mean tosales versus a conversion act
mean to sales versus marketing,for example, it's the platform
standardized as much as you canon them and it's also products.
This is more towards a mediacompany, for example, or events
organization, but you should nothave 100 different newsletters
(23:25):
that you're selling with alldifferent ad formats.
You'll never be able to tracktrue performance of your
newsletter channel.
And add types and things likethat.
If you are deploying alldifferent kinds of
normalization, standardizationneeds to take place, you should
have a customer engagementprocess that's standardized, but
this data strategy could helpyou do that and do it with low
(23:46):
risk and low destruction ordisruption to the business.
If I talked about the valuesthrough data and systems,
revenue excellence is an areathat this strategy can truly
drive everything from.
I use the word the revenue room,I trademarked it.
It really is a mindset, it's aculture shift, but it is an
actual organizational constructwhere you're using data to
(24:08):
connect all of what the revenuecritical functions in the
business and have them in someway or another jointly
accountable for outcomes, right?
Revenue customer outcomes.
I'll use an event example, butI've seen this a thousand times
where sales sells a sponsor, youknow, very large sponsor
promises all of these outcomes.
(24:30):
The contract comes in and bothmarketing and the enablement
team are looking at this andsay, there's no way we can do
this.
And it was over, it wasoversold.
They didn't deliver, everyone'spointing fingers.
But if you use data now toactually co sell, co deliver, co
create with the customer.
And data's at the ready to saywhat you can do and what you
(24:51):
can't do.
You can really optimize revenueperformance in that way.
Product excellence, if, again,if you're standardizing around
product sets, and you canactually see what's working,
what's not, you can thenleverage that across all of
those solutions regionally, forexample, or across portfolios.
to really drive better outcomes.
And then organizationally,everyone talks about data driven
(25:13):
skills.
You are not going to be able toacquire data science and data
skills across yourorganizations.
It's impossible.
What you have to do is you haveto build them.
So if you're utilizing an SSOTstrategy, you're making that
data available, you've got theright governance, so the right
people are seeing the rightdata, you're actually going to
embed.
(25:34):
data capabilities in the dailyflow of work, because if they've
got the right dashboard that'sgoing to help them do their job,
it's going to see how they'reperforming.
It's going to help them makebetter decisions.
They're going to learn a lotabout data and then business
value.
I mean, up and down across theboard, it helps with risk
identification in time toactually activate it or mitigate
(25:54):
it.
Identify new customeropportunities in terms of
revenue, and it allows you tolead the business versus the
situation leading you.
And if you are looking to sellyour business, then we'll build
value evaluation multiples themore data driven you are.
So before I move into steps, anythoughts or comments on the
(26:14):
value equation?
Did we miss something you wantus to answer, or did you want to
share how you look at value atyour business?
Not on that one, but just apoint of clarification is a
single source of truth always aplace we're talking about, i.
e.
This is going to be somesoftware or ERP system
somewhere.
And it's a matter of choosingthe right ones and properly, or
is the solution now in 2025,you're always, it is a system
(26:36):
that will be that and it's justsetting up the system correctly.
And I'll let you answer that onefirst.
Generally it is like, if it's anapplication you're logging into,
right.
And that can take a couple ofdifferent forms of how you want
to do it, but.
Ultimately, yeah, it's one placeversus going to your CRM to get
the revenue or to get the salesnumbers and your finance system
to get the profitability andmarketing to get the leads and
(27:00):
so on.
So it's cutting that all out andhow you get to that, how you
implement that technically, youcan take a variety of different
approaches, but the goal is toget to one place where you see
it all together.
Okay.
I have a question.
Should I post it in the chat orcan I say it now?
Is there a sweet spot of size oforganization that you have found
(27:25):
this really can be the mosteffective, you know, plus or
minus one iteration on the size?
In my experience, and then I'lllet Chad weigh in.
I actually am pretty astoundedat this.
Large companies, enterpriselevel companies that the
forecast is dead on arrival,that came from one of the
largest event organizers in theworld.
(27:45):
Okay.
Billion dollar company.
So I think that the data issuemoving in this direction is it's
for large enterprise, but alsofor a midsize company, like if
you want to compete and you arecompeting for dollars, you may
be competing against part of abrand portfolio within that
large company.
It's for everybody.
(28:05):
We worked with companies thatare a couple of million in
revenue, all the way up tofortune 500 to Heather's point.
You want to be mindful of ROIhere and like how much you're
investing in this technology andwhat you're expecting to get
out.
So for the smaller companies,there might be significant pain
points within certain parts ofthe business that can be solved
through the single source oftruth or through a certain slice
of it.
So as long as you're mindful ofthat, depending on your size,
(28:28):
and you're not going as a smallorganization, going and grabbing
all the data that really won'tdrive much of a difference in
terms of the business.
If you're considering that inthe process, then you're
probably doing it the right way.
As the business gets bigger thansmall tweaks in the marketing or
operations can make.
Big differences in the dollars.
And so the ROI is there to bringthose systems and those
(28:50):
datasets.
Absolutely.
And two other points.
And the reason why I brought upthis slide is, which Chad said
is totally spot on.
It's like, where in the businesscan data, a single source of
truth really help youaccelerate, right?
And especially if you're smallerand you have limited resources,
but you have to make big games,this could be a very
significant, profitableinvestment for you to make.
But it's very important to focusin on that area that you want.
(29:13):
You may not need the predictivewaterfall forecasting for your
CFO to deliver to your board.
So you won't need to connectinto all of those other systems,
but focus in, it can delivervalue.
Absolutely.
I also think it's important tounderstand how you approach it.
And here is a standard layupthat we see successful.
(29:37):
Which is one you do need tocreate a cross functional team.
Whether it's three people or tenpeople, it's the functional
roles who are going to benefitfrom the data outcomes to
activate them to drive the ROIwho need to be on this team.
It's important to, once you haveyour team to discuss, document,
connect, and prioritize thebusiness outcomes that you feel
(29:59):
are being thwarted due to thesedata issues.
And when I say connect andprioritize, certain issues are
connected to the other and haveto be solved first, right?
So identify what thoseconnections are.
But second is always focus onthe quick win, right?
When I say quick win is, it'sgoing to be the one that can be
implemented With the leastdisruption to your business
(30:22):
first.
As well as we'll have the bestoutcome and you'll see in our
landmines, a lot of people missthis step.
They go full boat and thatactually, especially for a small
business is not recommended.
It's very important tocommunicate up and down the
organization, what you're doingand what to expect, you know, as
(30:44):
you're going through thisprocess.
Not just that you're doing it,but how things are going to
start changing.
The adoption cycle, all of thosethings and start preparing for
that.
And then everyone needs to agreeon success.
And the agreement part isactually interesting.
It's also, you'll see in ourlandmines is getting agreement
on what things mean is actuallyreally challenging.
(31:06):
And it's, I think Chad's seen afew situations where that has
really impacted the outcomes.
And then you need the commitmentand then obviously finding
partners to help you.
Because it's important that yourbusiness keeps moving forward
while you're doing this versusstopping it, right?
So you need to fill anycapabilities gaps that you may
(31:26):
not have in order to get itdone.
So quick win approach, and wethoroughly believe in this.
Is once you've identified yourquick win and you have your
partners, you then go back intothe current future state, you
define your goals, you do thearchitecture.
Chad, I know you have, you're onthe tech side.
I don't know if you want to talka little bit about this wave
here of architect, validate anddevelop.
(31:47):
Yeah, absolutely.
Going back to Mike's question, Ithink the technology you need
also depends a little bit basedon the size of the business
number of systems you have, thetypes of where your data is
residing.
If you're in more modernsolutions and CRM and finance
systems, it's a little easier todeal with, but sometimes
organizations have outdatedsystems that are much more
(32:08):
difficult to pull data out of,but regardless in the quick
winter approach, you try toimplement as little as you can
just to get to the outcome.
And then continue to add on asyou take down priorities one at
a time.
So it's in this cycle here isreally just an iterative cycle,
right?
You're starting, you'reidentifying the priority,
defining it and going aboutgetting it done and then moving
(32:31):
on to the next one.
Once people see how it can workand see, it can believe in the
outcomes.
Yeah.
And I'll, during that MITcourse, they use Microsoft as an
example and how Nadellabasically went from very old
school sales practices, sellingsolutions on the Microsoft
Dynamics side, and then theymoved to the 365, which was the
subscription based.
And basically, they did theirsingle source of truths, they
(32:57):
launched dashboards and theystarted out with three areas
they were going to measurefirst, then added the next one
on and so on.
And it was like a flywheeleffect, but iteration scale and
leading from the top andensuring adoption because
leaders are using this is verycritical to also this quick win
approach.
All right.
Landmines.
So we talked a little bit aboutthis, but starting too big,
(33:19):
biting off more than you canchew.
This is something I, Chad, Ithink you've seen this just many
times, and maybe you could talka little bit about your
experience with the starting toobig.
Yeah, we've mentioned it.
I don't know if.
Folks have questions on whatwe're referring to here, but I
think generally what we mean isthat most of you have decided
(33:40):
that you're going to go downthis path, there was something
that initiated that some sort ofvisibility or issues that you
had trying to tackle all tacklethem all at once and getting a
handle on how marketing isperforming, how sales and then
finance all together performingat the same time is challenging
approach.
And that's what we're trying toadvise against is.
(34:00):
You know, really take a singlesystem or a single metric, get
that going and build on top ofthat over time.
I'll talk to a few more here.
I think the IT owning thestrategy is another one we see.
The strategy really needs to beowned by the CFO or the COO or
the finance team.
(34:21):
That's what we see due to whatthe outcomes are, but that's
another landmine to avoid.
Yeah.
What you'll potentially end upwith is a more overly technical
solution.
That may not meet the needs ofthe business.
And so it's really important tohave the business side
represented and delivering anddetermining what's the priority,
(34:41):
what the investment is managingto that investment and so on.
Exactly.
We talked about the disagreementon definitions and there's a way
to solve that.
I also see the once and donementality.
It's, this is an ongoingcommitment to data integrity and
data driven culture and mindset.
So it's, you don't do it onceand then you're done.
You need to have the datagovernments and rules set to
(35:03):
ensure that you're keepingconsistent and that you're
taking it to the next level whenthe business is ready.
Heather, one thing I wanted toadd here too, just given that
you guys, a lot of you arealready in the process.
You typically do need atechnical representation to
actually make it happen, to getthe right pieces in place, to
create the solution or thedashboard.
If those people that you havedoing that are.
Coming from a background thatdoes not involve data analytics,
(35:26):
that's a big red flag.
So if they're more of a websitedeveloper or an application
developer or some other internalIT resource, transitioning over
to be a data analyst or datascientist, whatever you want to
call it is a pretty big changein mentality and approach.
And so if you're leveraginginternal team that you're moving
(35:47):
over from one technology toanother, this technology being
analytics, that can be a very.
Risky move.
So I just wanted to throw thatout there and make sure that
folks had that in mind as well.
And another one that's not onhere is that, but I think it has
a lot to do with the wrong datain wrong data out is to get
right data in right data out.
It's not just what you want toreport on.
(36:09):
It's what you want the data totell you for the future.
Right.
And that may require.
additional data sets that you'renot considering.
So it's really critical topressure test that or else
you'll just get very nicelooking reports.
Right.
And you're looking for, you wantyour single source of truth to
drive prescriptive andpredictive insights.
(36:30):
The next slide is really aquestion related to landmines.
Are there any landmines you'vealready encountered or you want
to share that either you wouldlike to brainstorm about or you
found a solution?
So one of the things that Iencountered throughout my career
was the disagreement ondefinitions.
I once worked on a project wherewe were trying to revamp an
(36:51):
internal system and I rememberworking on this for about two
years based on definitions.
So how does that process workwhere you sort of get everybody
together to hop on board andagree on a definition?
What is one strategy?
(37:11):
I'll tackle that quickly andthen Chad, I'm sure you've got
perspective, but there actuallyis a strategy which probably was
not available to you during thetime you were doing this.
That is, if you, people getthreatened when you're going to
start messing around with theiractual system.
Let's say you're using a CRM.
Maybe you're all on Salesforce,but it's partitioned off by this
division, that division, orthere's a way to agree to make
(37:35):
it a lighter lift, wherebyyou're actually agreeing at what
these things mean, but you'redoing it at a level at the data
platform that you're using forthe SSOT and the analytics and
the visualization.
And you're mapping so thatyou're actually not disrupting
what's happening in the actualsource of the data.
So that's one, one solution.
(37:57):
Should I do anything to add tothat?
Yeah, we did add a couple noteson the prior slides.
But one thing that's reallyimportant in that process for
us.
Single owner, preferably anexecutive that is sponsoring
initiative and has the ultimatediscretionary power to say yes
or no to the definition theyneed to be a very, they need to
(38:18):
be very committed to the processand to the, and to what you're
trying to achieve and they needto help generate the buy in.
I think if you don't have asingle person who is owning
this, that's much more difficultto get consensus.
And then secondly, I think itgoes back to our start small
process approach.
If you want to define everymetric and every definition
across the company, all at once,it might take two years, but if
(38:41):
you start with a couple and thenyou go through and you actually
deliver, you know, a unifiedversion of revenue for everyone
across the company, that theycan slice and dice how they
want, they might be able tofilter it by certain areas or
otherwise, or adjust it based ontheir preference, but if you
give them that end result, thenthey'll see the benefit of
agreeing to a consensusdefinition.
(39:02):
Thank you.
And what that would lead to, andthen you can add on to that
going forward.
And I'll add a third thing in,tie back to what Chad said, but
taking a step further.
If you're, and I'll use revenueas a revenue org.
If you're actually aligningoutcomes across the revenue
critical functions now, andpeople are jointly accountable
in, in unique ways, but haveaccountability for revenue
(39:24):
outcomes.
And you're providing them thedata set to allow them to see
how they're doing, but it has tobe unified.
You're actually creating abenefit.
There's a need for it and abenefit above and beyond just
saying we're doing a singlesource of truth.
There's value for the end useras well as the functional
leaders, so there's, there wouldbe a way to get better buy in.
(39:45):
But eventually the business willsay, this is how we're
measuring, right?
And this is how you're going tobe tied to success.
Utilizing the way we're doingthis.
We're just, I want to do a timecheck cause there's actually a
little bit more to go through,about eight minutes.
Chad, why don't you go quicklythrough the tools and tech and
considerations, and then we'llmove into the write data in
write data out.
(40:06):
So just a few components thatyou probably need to consider or
at least have for developingthis and putting this together.
First one's data warehouse,which is really somewhere that
stores.
All of the data that you'veaggregated or collected from all
the different systems.
Typically in the cloud nowadays,there are a variety of providers
out there who offer very goodsolutions.
(40:26):
Second is more of a dataextraction and data cleansing
capability or tool.
Oftentimes this is also soldindependently within the market.
So there it's basically what itmeans is it's a tool to bring
the data out of your CRM or outof your source systems and then
to transform it or to clean itup and get it ready for report.
(40:47):
The third is a data access anddata management layer or tool,
which is a means to make surethat only the right people are
seeing the data that they needto see and also a means to
adjust the data as needed.
You want as a business user, asa business in general, you want
to enable the end users tomanage that information that's
(41:09):
in the single source of truth tothe best of their ability
without technical intervention.
And that's what we were callingout there with that capability.
Force something to display it.
So a way to look at the results,look at the data period or dive
into it, so to speak.
And then lastly, a predictive MLAI capability, which can sit on
(41:32):
top of all this information andhopefully give you more advanced
insight into the business.
And generally these can.
Either sold and purchasedindependently in the market or
unified within a singleplatform.
And what is ETL, RETL?
I don't know what that standsfor.
So that's extract, transform,load, and then R is reverse.
(41:55):
And that's a little bit newertechnology.
What that is being able to takethe data that you've aggregated
and push it back into yoursource systems, grab data from
finance and Salesforce and theCRM, potentially being able to
push that.
I mean, it's back into theSalesforce or CRM, which is
funny.
Is this a picture of likecomprehensively what you would
(42:18):
need?
Eat all of those elements inyour, you generally need at
least data warehouse, dataextraction, or ETL, and then a
display.
If you don't have those three,it's tough to get by.
You really want a data accessand data management to do it
properly.
And then the predictive is moresomething you can add at the
end.
If you want to, once you'vegotten the data combined, we're
(42:39):
trying to keep it as simple aspossible in terms of achieving
them.
Thank you.
So just quick key factors, we'llrun through these, I want to
make sure we get to the lastpart is obviously the
consideration, do you have thestaff to do it or do you need to
outsource it?
When, you know, your time tovalue is really important.
You don't want to be spendingtwo years defining things,
right.
And agreeing you like you wantto go, your investment goes out
(43:00):
and you want to start activatingit, enabling it and iterating
it.
There's the complexitycalculation, like how much and
again, that's why the quick winpart is really important is what
we're being pitched or what arewe looking at?
Is it adding complexity that wedon't need and it's going to
stop us from getting to the timeto market.
And.
How disruptive will this be onthe business to go forward or
(43:21):
non disruptive?
It's important that whoeveryou're working with understand
your business and organizationalmodel and how are you going to
calculate your investment andthen the payback period, right?
How will this investment payitself back plus?
And the real biggie also is makesure it's built for business
users.
And then, so, write data in,write data out is a very
(43:45):
important concept.
Not everything needs to bemeasured.
It's not all meaningful.
Tracking everything willjeopardize the long term value
that an SSOT strategy delivers.
The next slide.
And it really needs to be mappedto stakeholder goals.
So the next slide we'll gothrough the stakeholders and how
you need to understand whoyou're addressing.
And Steven, this may go to yourquestion also is, you know,
(44:08):
which part of the organizationare you trying to drive value
through data?
But the first stakeholder aregonna be your investors.
And no particular order, by theway, the second stakeholder is
clearly the C E O.
The C F O is right there.
C r O.
The C m O.
The c o o.
(44:28):
The chief product officer, andthen your functional teams,
right?
All underneath those layers.
And again, you'll add yours, butbuild your map of stakeholders.
And then the next slide we'll,let's focus on investors.
So investors, if you are eitherPE owned, or you are looking to
be PE owned, or maybe you are aprivate equity, oh, and you own.
(44:51):
The map, the goals, right?
They're looking for duediligence for new investments,
operational oversight of currentportfolio companies, proof of
investment thesis,identification of hidden
opportunities, and examples oftypes of data they need go cut
across.
Pretty much.
I would say all of the executivedashboard, if we wanted to look
at the CFO, which is the nextstakeholder.
(45:15):
Your CFO is a critical person inthe organization, and there's a
huge plate to, of things thatthey need to do.
Everything of reportingfinancials to board and
shareholders, to maximizingassets and resources, managing
EBITDA and EBITDA growth.
Their data requirements are, Iwould say probably the most
extensive and probably tap intothe majority of the data out
(45:41):
there because they're looking atcosts.
They're looking at margin,they're looking at growth,
revenue, they're looking atcustomer lifetime value, and
they're looking at revenue peremployee profitability.
And then the next one examplethat we'll share is the CRO, who
is driving the revenue andmapping their goals like we'll
(46:02):
include in our deck, a littleblank slates of this, but you
would map your, what are thegoals, the data required to hit
those goals and some examples ofhow you measure for those
stakeholders.
And then that goes into howyou're going to build your
strategy and how you'llprioritize.
Right.
Maybe the investor.
(46:22):
Data isn't as important as theCRO data because revenue right
now is your most critical,urgent issue.
You would start with revenue.
Or it could be that you'respending hundreds of hours
building forecasts that are deadon arrival, and your board's
really sick of it, so the CFO isgoing to come first.
And it'll dictate the data thatyou're going to attack first.
(46:48):
Because we're over by a minute.
We had opened up for morequestions.
If you'd like to set up a callwith us to dive into this
deeper, we're offering an hourtime, like office hours.
So just email myself and I willget that set up.
You'll get this deck.
We have another bootcamp forSeptember 21st.
This is all about the actualpredictive analytics side.
(47:10):
And once you get a single sourceof truth going, how can you use
predictive analytics to drive?
Top and bottom line growth andmanage risk and capture
opportunity.
So the registration link for the21st is in the chat, whether you
want to just copy it for lateror we can also email it to you.
I hope everyone found thishelpful.
Thank you, Heather.
(47:31):
Yes, thank you.
Thanks, Chad.
I think we have our work cut outfor us because we are really
just in the early stage.
And this was very useful,especially at like a summary
level of things that we can talka little bit more about
internally and give us some sortof path to go by.
(47:55):
Terrific.
We really appreciate you joiningus and hope we'll see you on the
21st.
I'll also reach out to see ifthere you need any help in
between now and then.
For sure.
Thanks everyone.
Thank you everyone.
Heather Holst-Knudsen (48:05):
You can find us@2klabs.com.
Thank you.
Thank you for listening to TheRevenue Room by H2K Labs.
Subscribe to our channel today.
Welcome to the Revenue Room,presented by H2K Labs.
(00:05):
Here's your host, HeatherHolst-Knudsen.
Well, welcome everyone.
This is the first of ourbootcamps focused on the concept
of data driven revenue growth.
Today we're going to talk aboutdeveloping a single source of
(00:25):
revenue truth in complex dataenvironments.
We'll cover a few things today.
We'll introduce the wholeconcept to you how an SSOT works
in a revenue type capacity.
Because it's part of anoverarching strategy, the way to
create value and track andmeasure, steps to developing
tools and tech, landmines toavoid.
(00:47):
We've seen many and this wholeconcept of write data in, write
data out.
I'm Heather Roltz Knudsen, theCEO of H2K labs.
I have been in media events,digital information for over 30
years.
And my bent is data and revenue.
So I am very passionate aboutthe subject and our business
partner.
(01:07):
Is Chad Rose, the CEO ofInsightOut and a software
development and data companycalled Treehouse Technology.
Chad, you want to say hi?
Hello everyone.
Great to be here.
I'm looking forward to thediscussion and answering any
questions you all might have.
My background is largely in dataanalytics engineering, more on
the technical side.
So.
(01:27):
We can get into the details asneeded and happy to entertain
any questions.
So what we're trying to do todayis we're going to review the
fundamentals of developing asingle source of truth in your
revenue organization, thebenchmarks for value creation.
and understanding and reallytrying to help you with the
opportunity in the landmineidentification.
(01:48):
This is meant to be interactiveby the way, so there'll be
points in time where I'll stop,ask questions.
If you do have questions youwant us to answer and you want
to put it in the chat, pleasefeel free to do so.
You'll get a copy of the deck,and we're in the process of
building a detailed playbookthat'll have more action
oriented type of tools thatyou'll also receive.
(02:10):
And if you would like to set upa time with us, both Chad and
myself, from both the businessand the data tech perspective,
To consult where you are withyour SSOT strategy.
That also is something we weredoing for the people who
participate.
All right.
So I think everyone knows this,but data driven organizations
are far more profitable thantheir counterparts.
And this is a study that wasjust done at the behest of
(02:31):
Google through Harvard BusinessReview.
Operational efficiency,revenues, customer retention,
employee satisfaction, costpredictability across the board
being data driven is a hallmarkof leadership and profitability.
91 percent of those respondents,by the way, agree that
democratizing access to the dataand analytics is important to
(02:54):
the success of theorganizations.
And that democratizing access toAI to drive predictive insights
is crucial.
And the reason why I bring upthis democratization is it is a
critical part of becoming datadriven.
Many times we'll see companiesthat invest in the SSOT
strategy, but yet they're givingit to leadership or functional
(03:15):
leaders, but they're notbringing it down to the whole
business.
The democratization aspect iscritical to become truly, fully
data driven.
I recently took a course withMIT on data monetization, which
is.
Really when they say datamonetization, they look at it
from three areas.
It's an improved strategy, awrap strategy, and a sell
(03:37):
strategy.
The improved side is really whatyou're doing internally to add
cash to the bottom line.
Improving operations, improvinghow you're acquiring, retaining
and growing revenue, improvingprocesses, standardization, all
those things.
But it all starts with your dataasset.
But if you go through thisjourney, you'll be able to drive
(03:59):
excellence across all differentareas of the business.
But today we're really going tofocus on the one core thing that
has to be done right in orderfor you to go through these
capabilities of data asset.
That is your master data, howit's integrated, how it's
curated, right?
When you go up to curation andyou have the right platforms.
(04:20):
And you have the right datascience, you can then actually
drive predictive andprescriptive insights.
But one of the key things alsoto realize is that as you go
through this process, thesecapability building is
iterative.
It happens over time and it'sevolutionary and it's part of
your journey.
I think sometimes I find whentalking to customers and clients
(04:44):
that.
Bigness of doing something likethis is almost like a like a
game stopper.
And then making that dataavailable to up and down across
the organization is really a keycriteria for success.
So we're going to do a quickpoll here, just so I know where
everyone is on this SSOTjourney.
It's confidential.
(05:04):
I'm not going to show theresults.
I'll speak to them.
So feel free to answer.
I think this is going to be avery interesting conversation.
I think people are in the sameboat and starting the journey or
on it and a little bit worriedabout where you are.
I'm going to end the poll andlet's move on.
Okay.
(05:24):
So single source of revenuetruth in complex data
environments.
First of all, let's talk aboutwhat an SSOT is.
Some people call it a singlepoint of truth.
I've actually never heard that,but thought I'd put it up here.
Essentially, what it's doing isgetting your data into a state
where it can be found in asingle spot.
(05:45):
It's trustworthy, it's clean,and it's meaningful, right?
Centralized platform.
Yeah.
I mean, one way to think aboutit is if you have a question as
to the performance of a certainpart of the business.
Is there a place that you can goto get that answer with data?
Right.
If you have to go to a thousanddifferent places or go to Excel
(06:06):
or otherwise, you probably don'thave that, but it's one way to
think about it.
Chad, I don't know if you readmy blog on LinkedIn the other
day, but the forecast was deadon arrival because it took a
hundred hours across sevendifferent divisions.
And two weeks per division todevelop.
I mean, it was unbelievable.
Like they definitely do not havea single source of truth.
(06:27):
So, and then, and the reason whyI like to add the word revenue
in when it comes to thisparticular arena is I find that
it's very important to reallytruly define what the revenue
truth is in terms of where thedata lies.
And it's not just about what'sin your CRM.
It's way more than that.
(06:48):
It is what anything yourcustomer is touching that you're
selling to their behaviors, theway you're engaging with them
post sale, what they're doing onyour website post sale, all of
these things are really criticaland important and should be able
to be referenced in a centralplatform in media and events
where marketing services arebeing sold and the delivery is
(07:11):
about bringing value to them, i.
e.
you're bringing an audience tothem You're looking at data on
the product side because yourproduct performance is about
what's happening on the audienceside and how that curation is
happening and how that meets thedelivery of contracts.
That is such a fundamental,profound impact.
(07:31):
On your analytics, yourforecasting and everything,
especially with existingcustomers, which is your most
profitable base, making thatconnection is critical.
So in the complex dataenvironment, which I just
touched on, which is differentthan what I call a one sided
business model or businessmodels that sell hard goods.
Or software, for example, whereyou are selling this SaaS
(07:54):
solution, here's what you'regetting, and we can track and
see usage.
Complex data environments do nothave it that easy.
And it's not just the two sidedbusiness model, it's multiple
channels and formats.
It is, a lot of these businesseshave had acquisition activity,
so M& A activity.
(08:14):
You're bringing in businessesthat are working off different
platforms or different markets.
It's very complex.
And so we put this together toaddress the complexity part, but
Chad and I work together on alot of client calls and things
like that.
And I think one of the thingsI'd love Chad to talk about is
working with one sided, morestandard type business models
(08:37):
versus This complex dataecosystem, tell me what your
insights are and the things thatyou see.
Yeah, absolutely.
You know, I think with regardsthis segment of the market, you
have almost within eachbusiness, you have almost
multiple different businessunits that act and behave very
differently, almost separatePNLs and probably are in some
(08:59):
cases, typically, like youmentioned, Heather, you know, if
you have a software company,they have a recurring revenue
model and that's how they lookat their business, that's the
most important metric.
And so the data model and theanalytics all revolve around
that.
There's an element of that here,but then there's also an element
of delivering goods andservices.
There's an element within theevent space of having to manage
(09:22):
this unusual sort of sales cycleand trying to hit your targets
and predict where you're goingto land.
And so each one of thoseindependently.
It is typically within ourexperience, a single project, so
to speak, to develop a singlesource of truth.
It's a, as I mentioned, it's acertain data model.
It's a certain system thatthey're inputting the data into,
(09:43):
but here you have all of themcombined, all of them at once,
and so there's a real level ofadditional complexity if you
want to get the full picture onthe entire business.
Not necessarily important to goabout it from the start to say,
you know, we're going to tackleit all at once.
You know, if you do want to getthe full picture, there are a
(10:03):
lot more variables than youwould usually see with a more
simplified business model.
Absolutely.
And I think, you know, from thefinance side, it's very
complicated and you touched onit, which I bring up here under
the business model, a lot ofthese business models are now.
under pressure or see theopportunity to move into data
monetization and move into thatrecurring predictable revenue
(10:26):
stream strategy.
So you'll have an old businessmodel going on the advertising,
the lead gen, the sponsorship insync with new.
Types of business model, therecurring revenue.
And so you're actually nowdealing with all different types
of revenue recognition,waterfall forecasting.
The levers are different interms of driving the predictive
(10:47):
analytics.
So again, it's complex.
I think what that means too, isthat if you have the ability to
put this together.
And achieve that single sourceof truth and you can really
differentiate or at least use itas a competitive advantage
within your market.
I 100 percent agree.
One of the things I always liketo say is if you go down this
(11:08):
path, your sellers are going tosell a thousand times better.
Your customer understanding isgoing to skyrocket.
You're going to outsell thecompetition over and over again.
It absolutely will be acompetitive advantage.
100%.
This is my view of, I used torun media and digital
information businesses.
So I would say when I wasputting together those awful
(11:30):
spreadsheets every month for myboard meetings, I would do my
best to pull data together fromsome of these areas that where
it was possible to really try togive some realistic
understanding of.
What did we believe was going tohappen predictively with
customer renewals, expansion,upselling, the new business
(11:50):
acquisition?
How was that being impacted bythe marketing funnel?
How was that being impacted bythe product delivery?
How was that, or are theretrends that we were seeing on
our website that were happeningthat would show up or down
movement?
You know, we talked a lot, wewere in the manufacturing and
the tech connecting tech withmanufacturing.
So.
(12:10):
This is the whole event side,but there's a lot of data
sitting around and the largeryou are and the more portfolios
and brands you have and the morebusinesses you've acquired, this
is this ecosystem, this.
Data ecosystem on the revenueside gets quite significant.
But the good news is you don'thave to include everything.
(12:30):
It's really important to look atthe data that's meaningful, and
we'll talk about that later, anddo not include data you don't
need.
Someone may say, well, you'reputting HR on there, but we need
to know headcount and payrolland things like that.
Finance has that on their side.
Right.
Chad, you, and you have a strongopinion about this.
Yeah, I do think it's just asimportant to consider what not
(12:53):
to put in, what not to includein the single source of truth.
I think there's a lot that wehave here.
And the important point to noteis if you had all of this
combined and you had all thesesources, you would be in really
great shape to get there.
You don't want to tackle themall at once.
And you really shouldn't, butwe'll get into that a little bit
more, but we also try to callout things that just really are
(13:14):
necessary when it comes to.
A revenue, single source oftruth and wasted effort that you
would put it into trying tobring that data together.
Right.
How do you know you need asingle source of revenue?
Truth Heather, real quick, givenwhere everyone is, if you don't
mind me jumping in, I'd becurious to understand or hear a
little bit, if anyone has anopinion, like if they're on the
(13:36):
path, why did they start Why areyou trying to develop one?
What pain points or where didthe priority come from?
If anyone has an opinion onthat, it'd be great to hear.
It's all of those things.
Yeah.
And we've been kind of, it's nota secret.
It's not like an aha.
Oh my God.
(13:56):
All these things exist now.
We've known a long time.
It comes down to then theinvestment, meaning people
spending the time to do theassessment and then migrate to
whatever the SSOT is going tobe.
Was there any finally made thepush over the edge there to get
started?
In my opinion, I'm Intel.
(14:16):
I feel like the shift in economyover the last couple of years
and our lack of ability topredict our revenue and count on
our historical retention rate,and then to figure out why and
what to do about it kind of cameto a head in the last, I would
say 24 months.
And if I can add to this too,it's not only these bullet
(14:38):
points, but even in ourbusiness, we had a problem.
Different teams would givedifferent answers.
Like they didn't know who toask.
They may go to one part of ourfinance or accounting function.
They may go to rev ops.
They may go to some Salesforceadmin and like everyone then had
a different approach as totrying to answer the question
and the requester has to bedifferent answers.
So it wasn't even just the datasources who in the organization
(14:59):
is responsible for reporting onsome of these key business
questions, which were maybe isthe easier one to sort out
versus.
Some of the data and techissues.
Good afternoon, everyone in ourcase, I had a chat with Heather
about this a few months ago,where we knew what was coming.
The pandemic certainly through alittle bit of a wrench in that
from a, from an end point, butwe ended up.
(15:21):
Buying 3 companies during overzoom during the pandemic, so
2022 was like.
We didn't even know what we had.
Now the dump truck has backed upto my house and dumped all the
information on the driveway.
And I'm like, great.
I need to get my teams to sortall that out.
And so it's all those things,but a different arrival path.
(15:43):
That's pretty common too.
Just the M and a route ends upbeing unmanageable unless you
can get it all together.
We're able to introduce certainshared services, but I know this
exists within these bulletpoints.
Right.
But it's like.
Just the tech stacks and thevarious legacy tech alone can
certainly make this.
Like from the top, somethingthat we could do better, but
(16:05):
then we will still need tochange some of the other
logistics.
Anyway, I'm not going to take upother people's time.
No, that's a good, it's a fairpoint.
It's a good point.
And that's another way oflooking at it.
Generally, it's an added benefitof doing this, but yeah,
absolutely.
Yeah.
And you'll see, I use the sametime last year on this third to
last bullet point.
Life is not the same anymore dueto a lot of different reasons.
Buying patterns have changed andyour demographic is changing and
(16:30):
expectations have changed.
So.
The one, the historical backview does need to be
complimented with real timetrending data, where the machine
learning and the AI comes in,where that actually allows you
to pressure test.
What people are telling you,right?
And that's why, and I'll justback up here really quickly.
So the unstructured sources atthe bottom, the, there's what's
(16:55):
being put in manually into yourCRM, for example, versus what's
happening actually.
So if you have customerinsights, I talk about this all
the time.
If you sold something and thereis a contract with product
performance metrics that need tobe met, and those aren't being
met or they're delayed.
(17:15):
That does have an impact.
That's something that is data.
You need to know that most timesdoes not get surfaced when you
talk to your sales team.
They think the deal's in there.
It's going to close on this dateand for this amount.
But yet, because they're notreally connecting like, Oh, we
haven't delivered yet.
It's going to be delayed.
So that's going to push my dealout to here.
Or we're noticing that while wemay have the same amount coming
(17:39):
in on a renewal, We're gettingless traction, you know, at
events, but there are otherthings that are happening
outside the CRM that help withnot getting caught, not knowing
what's going to happen.
So again, I'm just underscoringthat this is part of the SSOT
strategy that's really criticalto keep in mind when you are
going through it.
(18:01):
So let's go forward.
I think we already asked thatthis question was going to come
after this list of how you knowyou need a single source of
truth.
But I'll say that if you'respending a lot of money on
manual labor, additionalheadcount, and spreadsheets to
generate forecast reports, thatforecast dead on arrival example
I used before.
All of these are signals youneed it.
(18:21):
So we already kind of opened upthe discussion, but Mintel is
there.
You do research, right?
And, or you're giving insightsand intelligence for improving
marketing outcomes forcustomers.
If I am understanding what I sawon your website, correct?
Yeah, that's the gist of it.
All right.
Are these customized typeprograms or is it like a, is it
(18:42):
productized and standardized?
About 80 percent of the money wemake is in the form of a
subscription, like asubscription license to our
platform.
And then we've got aprofessional services arm that
does kind of customize one offdeliveries.
Okay.
And the subscription, I'massuming at the large ticket
item subscription that renewsannually.
(19:03):
Okay.
When you look at customeradoption and usage with your
platform, how do you definethat?
We have usage stats to be ableto say like number of active
users on our platform.
We can look at their downloads.
We can look at what they'relooking at.
So it's one of the client healthscore metrics that we then
provide to the client successmanager or the account manager
(19:25):
to be able to assess like thehealth of the account and as we
get closer to it, the risk orlack thereof and renewing that
account into the next year.
Okay.
And is that data applied toforecasting and pipeline and
things like that to adjust basedon the customer health score?
Nope, all of the forecastingright now is subjectively
categorized into different salesstages by the account manager.
(19:48):
So we give some training andguidance to say like, okay, if
this has happened, this stage,if this has happened, you're in
this stage, but they still havekind of the ultimate call day
and their manager, there's kindof a review of it, but they, it
doesn't factor in usage data orthings like that, at least
systematically, like the accountmanager may know it in their
heads.
Like, Ooh, this is a risk.
I blow usage here at thisaccount.
So I'm going to categorize it atthis stage, but it's not
(20:10):
systematically built into theforecast.
No.
Okay, got it.
So, anyone else want to talkabout the complexity at your
business that we may have missedor may add color to our
conversation?
All right.
Well, I will then move on.
So let's talk about value.
One of the biggest complaintsthat I hear is we've invested
(20:32):
all of this money and time andeffort into building, you know,
this data driven culture andstrategy, and we're not seeing
value.
Well, that's a result ofactually not defining it and
making a part of the strategy,but let's go into what value can
look like.
So there's tons of value with anSSOT, everything from, you know,
(20:53):
making it easier to discoverinformation, reducing the cost
to create those reports,including headcount that you
won't need anymore, or theheadcount can be reallocated to
value creation and added valueactivities.
It helps with data governance.
It helps across the board.
But the real big thing here, themessage I always like to say is
that if you are going to moveforward with an SSOT strategy.
(21:16):
You need to look at it as acontinuous creation of value
across multiple areas of thebusiness.
And you want to track and lookat those and have that top of
mind as you put your plantogether, track the progress of
the plan and evaluate outcomesof your plan as it goes through
milestones.
Yeah.
And actually just real quickHeather on that prior slide.
(21:38):
So a lot of our customers, thebest when they're using the
analytics and the single sourceof truth.
I mean, the means that it wasreally meant to be, they are
able to deploy new marketingefforts or change certain
tactics in their sales process.
And then simultaneously in realtime, kind of see how that is
impacting their business.
(21:58):
Right.
So again, as it relates, like,do I have a proper single source
of truth, am I doing thiscorrectly?
You should really be able to trynew strategies within the
business, adjacent to that, seethe performance with little
effort to develop like that.
To develop that insight or todevelop that visibility into how
(22:20):
that is performing within themarket.
And that...
It enables people to try thingsand then turn them off or turn
them back on depending on howthey work.
It really goes to Heather'spoint of enabling that value
creation going forwardcontinuously.
So the way that I look at it isthis.
The first part isstandardization.
Regardless of whether, where youstart on the SSOT strategy, you
(22:41):
need to look at things in yourbusiness.
And how you can use this processto standardize them.
I look at it that the SSOTstrategy comes first, by the
way, because you want to knowwhat to standardize, what makes
sense, and test it out versusdoing that first, then driving
(23:02):
SSOT side.
But it's everything fromprocesses, how you measure
things.
What does conversion mean tosales versus a conversion act
mean to sales versus marketing,for example, it's the platform
standardized as much as you canon them and it's also products.
This is more towards a mediacompany, for example, or events
organization, but you should nothave 100 different newsletters
(23:25):
that you're selling with alldifferent ad formats.
You'll never be able to tracktrue performance of your
newsletter channel.
And add types and things likethat.
If you are deploying alldifferent kinds of
normalization, standardizationneeds to take place, you should
have a customer engagementprocess that's standardized, but
this data strategy could helpyou do that and do it with low
(23:46):
risk and low destruction ordisruption to the business.
If I talked about the valuesthrough data and systems,
revenue excellence is an areathat this strategy can truly
drive everything from.
I use the word the revenue room,I trademarked it.
It really is a mindset, it's aculture shift, but it is an
actual organizational constructwhere you're using data to
(24:08):
connect all of what the revenuecritical functions in the
business and have them in someway or another jointly
accountable for outcomes, right?
Revenue customer outcomes.
I'll use an event example, butI've seen this a thousand times
where sales sells a sponsor, youknow, very large sponsor
promises all of these outcomes.
(24:30):
The contract comes in and bothmarketing and the enablement
team are looking at this andsay, there's no way we can do
this.
And it was over, it wasoversold.
They didn't deliver, everyone'spointing fingers.
But if you use data now toactually co sell, co deliver, co
create with the customer.
And data's at the ready to saywhat you can do and what you
(24:51):
can't do.
You can really optimize revenueperformance in that way.
Product excellence, if, again,if you're standardizing around
product sets, and you canactually see what's working,
what's not, you can thenleverage that across all of
those solutions regionally, forexample, or across portfolios.
to really drive better outcomes.
And then organizationally,everyone talks about data driven
(25:13):
skills.
You are not going to be able toacquire data science and data
skills across yourorganizations.
It's impossible.
What you have to do is you haveto build them.
So if you're utilizing an SSOTstrategy, you're making that
data available, you've got theright governance, so the right
people are seeing the rightdata, you're actually going to
embed.
(25:34):
data capabilities in the dailyflow of work, because if they've
got the right dashboard that'sgoing to help them do their job,
it's going to see how they'reperforming.
It's going to help them makebetter decisions.
They're going to learn a lotabout data and then business
value.
I mean, up and down across theboard, it helps with risk
identification in time toactually activate it or mitigate
(25:54):
it.
Identify new customeropportunities in terms of
revenue, and it allows you tolead the business versus the
situation leading you.
And if you are looking to sellyour business, then we'll build
value evaluation multiples themore data driven you are.
So before I move into steps, anythoughts or comments on the
(26:14):
value equation?
Did we miss something you wantus to answer, or did you want to
share how you look at value atyour business?
Not on that one, but just apoint of clarification is a
single source of truth always aplace we're talking about, i.
e.
This is going to be somesoftware or ERP system
somewhere.
And it's a matter of choosingthe right ones and properly, or
is the solution now in 2025,you're always, it is a system
(26:36):
that will be that and it's justsetting up the system correctly.
And I'll let you answer that onefirst.
Generally it is like, if it's anapplication you're logging into,
right.
And that can take a couple ofdifferent forms of how you want
to do it, but.
Ultimately, yeah, it's one placeversus going to your CRM to get
the revenue or to get the salesnumbers and your finance system
to get the profitability andmarketing to get the leads and
(27:00):
so on.
So it's cutting that all out andhow you get to that, how you
implement that technically, youcan take a variety of different
approaches, but the goal is toget to one place where you see
it all together.
Okay.
I have a question.
Should I post it in the chat orcan I say it now?
Is there a sweet spot of size oforganization that you have found
(27:25):
this really can be the mosteffective, you know, plus or
minus one iteration on the size?
In my experience, and then I'lllet Chad weigh in.
I actually am pretty astoundedat this.
Large companies, enterpriselevel companies that the
forecast is dead on arrival,that came from one of the
largest event organizers in theworld.
(27:45):
Okay.
Billion dollar company.
So I think that the data issuemoving in this direction is it's
for large enterprise, but alsofor a midsize company, like if
you want to compete and you arecompeting for dollars, you may
be competing against part of abrand portfolio within that
large company.
It's for everybody.
(28:05):
We worked with companies thatare a couple of million in
revenue, all the way up tofortune 500 to Heather's point.
You want to be mindful of ROIhere and like how much you're
investing in this technology andwhat you're expecting to get
out.
So for the smaller companies,there might be significant pain
points within certain parts ofthe business that can be solved
through the single source oftruth or through a certain slice
of it.
So as long as you're mindful ofthat, depending on your size,
(28:28):
and you're not going as a smallorganization, going and grabbing
all the data that really won'tdrive much of a difference in
terms of the business.
If you're considering that inthe process, then you're
probably doing it the right way.
As the business gets bigger thansmall tweaks in the marketing or
operations can make.
Big differences in the dollars.
And so the ROI is there to bringthose systems and those
(28:50):
datasets.
Absolutely.
And two other points.
And the reason why I brought upthis slide is, which Chad said
is totally spot on.
It's like, where in the businesscan data, a single source of
truth really help youaccelerate, right?
And especially if you're smallerand you have limited resources,
but you have to make big games,this could be a very
significant, profitableinvestment for you to make.
But it's very important to focusin on that area that you want.
(29:13):
You may not need the predictivewaterfall forecasting for your
CFO to deliver to your board.
So you won't need to connectinto all of those other systems,
but focus in, it can delivervalue.
Absolutely.
I also think it's important tounderstand how you approach it.
And here is a standard layupthat we see successful.
(29:37):
Which is one you do need tocreate a cross functional team.
Whether it's three people or tenpeople, it's the functional
roles who are going to benefitfrom the data outcomes to
activate them to drive the ROIwho need to be on this team.
It's important to, once you haveyour team to discuss, document,
connect, and prioritize thebusiness outcomes that you feel
(29:59):
are being thwarted due to thesedata issues.
And when I say connect andprioritize, certain issues are
connected to the other and haveto be solved first, right?
So identify what thoseconnections are.
But second is always focus onthe quick win, right?
When I say quick win is, it'sgoing to be the one that can be
implemented With the leastdisruption to your business
(30:22):
first.
As well as we'll have the bestoutcome and you'll see in our
landmines, a lot of people missthis step.
They go full boat and thatactually, especially for a small
business is not recommended.
It's very important tocommunicate up and down the
organization, what you're doingand what to expect, you know, as
(30:44):
you're going through thisprocess.
Not just that you're doing it,but how things are going to
start changing.
The adoption cycle, all of thosethings and start preparing for
that.
And then everyone needs to agreeon success.
And the agreement part isactually interesting.
It's also, you'll see in ourlandmines is getting agreement
on what things mean is actuallyreally challenging.
(31:06):
And it's, I think Chad's seen afew situations where that has
really impacted the outcomes.
And then you need the commitmentand then obviously finding
partners to help you.
Because it's important that yourbusiness keeps moving forward
while you're doing this versusstopping it, right?
So you need to fill anycapabilities gaps that you may
(31:26):
not have in order to get itdone.
So quick win approach, and wethoroughly believe in this.
Is once you've identified yourquick win and you have your
partners, you then go back intothe current future state, you
define your goals, you do thearchitecture.
Chad, I know you have, you're onthe tech side.
I don't know if you want to talka little bit about this wave
here of architect, validate anddevelop.
(31:47):
Yeah, absolutely.
Going back to Mike's question, Ithink the technology you need
also depends a little bit basedon the size of the business
number of systems you have, thetypes of where your data is
residing.
If you're in more modernsolutions and CRM and finance
systems, it's a little easier todeal with, but sometimes
organizations have outdatedsystems that are much more
(32:08):
difficult to pull data out of,but regardless in the quick
winter approach, you try toimplement as little as you can
just to get to the outcome.
And then continue to add on asyou take down priorities one at
a time.
So it's in this cycle here isreally just an iterative cycle,
right?
You're starting, you'reidentifying the priority,
defining it and going aboutgetting it done and then moving
(32:31):
on to the next one.
Once people see how it can workand see, it can believe in the
outcomes.
Yeah.
And I'll, during that MITcourse, they use Microsoft as an
example and how Nadellabasically went from very old
school sales practices, sellingsolutions on the Microsoft
Dynamics side, and then theymoved to the 365, which was the
subscription based.
And basically, they did theirsingle source of truths, they
(32:57):
launched dashboards and theystarted out with three areas
they were going to measurefirst, then added the next one
on and so on.
And it was like a flywheeleffect, but iteration scale and
leading from the top andensuring adoption because
leaders are using this is verycritical to also this quick win
approach.
All right.
Landmines.
So we talked a little bit aboutthis, but starting too big,
(33:19):
biting off more than you canchew.
This is something I, Chad, Ithink you've seen this just many
times, and maybe you could talka little bit about your
experience with the starting toobig.
Yeah, we've mentioned it.
I don't know if.
Folks have questions on whatwe're referring to here, but I
think generally what we mean isthat most of you have decided
(33:40):
that you're going to go downthis path, there was something
that initiated that some sort ofvisibility or issues that you
had trying to tackle all tacklethem all at once and getting a
handle on how marketing isperforming, how sales and then
finance all together performingat the same time is challenging
approach.
And that's what we're trying toadvise against is.
(34:00):
You know, really take a singlesystem or a single metric, get
that going and build on top ofthat over time.
I'll talk to a few more here.
I think the IT owning thestrategy is another one we see.
The strategy really needs to beowned by the CFO or the COO or
the finance team.
(34:21):
That's what we see due to whatthe outcomes are, but that's
another landmine to avoid.
Yeah.
What you'll potentially end upwith is a more overly technical
solution.
That may not meet the needs ofthe business.
And so it's really important tohave the business side
represented and delivering anddetermining what's the priority,
(34:41):
what the investment is managingto that investment and so on.
Exactly.
We talked about the disagreementon definitions and there's a way
to solve that.
I also see the once and donementality.
It's, this is an ongoingcommitment to data integrity and
data driven culture and mindset.
So it's, you don't do it onceand then you're done.
You need to have the datagovernments and rules set to
(35:03):
ensure that you're keepingconsistent and that you're
taking it to the next level whenthe business is ready.
Heather, one thing I wanted toadd here too, just given that
you guys, a lot of you arealready in the process.
You typically do need atechnical representation to
actually make it happen, to getthe right pieces in place, to
create the solution or thedashboard.
If those people that you havedoing that are.
Coming from a background thatdoes not involve data analytics,
(35:26):
that's a big red flag.
So if they're more of a websitedeveloper or an application
developer or some other internalIT resource, transitioning over
to be a data analyst or datascientist, whatever you want to
call it is a pretty big changein mentality and approach.
And so if you're leveraginginternal team that you're moving
(35:47):
over from one technology toanother, this technology being
analytics, that can be a very.
Risky move.
So I just wanted to throw thatout there and make sure that
folks had that in mind as well.
And another one that's not onhere is that, but I think it has
a lot to do with the wrong datain wrong data out is to get
right data in right data out.
It's not just what you want toreport on.
(36:09):
It's what you want the data totell you for the future.
Right.
And that may require.
additional data sets that you'renot considering.
So it's really critical topressure test that or else
you'll just get very nicelooking reports.
Right.
And you're looking for, you wantyour single source of truth to
drive prescriptive andpredictive insights.
(36:30):
The next slide is really aquestion related to landmines.
Are there any landmines you'vealready encountered or you want
to share that either you wouldlike to brainstorm about or you
found a solution?
So one of the things that Iencountered throughout my career
was the disagreement ondefinitions.
I once worked on a project wherewe were trying to revamp an
(36:51):
internal system and I rememberworking on this for about two
years based on definitions.
So how does that process workwhere you sort of get everybody
together to hop on board andagree on a definition?
What is one strategy?
(37:11):
I'll tackle that quickly andthen Chad, I'm sure you've got
perspective, but there actuallyis a strategy which probably was
not available to you during thetime you were doing this.
That is, if you, people getthreatened when you're going to
start messing around with theiractual system.
Let's say you're using a CRM.
Maybe you're all on Salesforce,but it's partitioned off by this
division, that division, orthere's a way to agree to make
(37:35):
it a lighter lift, wherebyyou're actually agreeing at what
these things mean, but you'redoing it at a level at the data
platform that you're using forthe SSOT and the analytics and
the visualization.
And you're mapping so thatyou're actually not disrupting
what's happening in the actualsource of the data.
So that's one, one solution.
(37:57):
Should I do anything to add tothat?
Yeah, we did add a couple noteson the prior slides.
But one thing that's reallyimportant in that process for
us.
Single owner, preferably anexecutive that is sponsoring
initiative and has the ultimatediscretionary power to say yes
or no to the definition theyneed to be a very, they need to
(38:18):
be very committed to the processand to the, and to what you're
trying to achieve and they needto help generate the buy in.
I think if you don't have asingle person who is owning
this, that's much more difficultto get consensus.
And then secondly, I think itgoes back to our start small
process approach.
If you want to define everymetric and every definition
across the company, all at once,it might take two years, but if
(38:41):
you start with a couple and thenyou go through and you actually
deliver, you know, a unifiedversion of revenue for everyone
across the company, that theycan slice and dice how they
want, they might be able tofilter it by certain areas or
otherwise, or adjust it based ontheir preference, but if you
give them that end result, thenthey'll see the benefit of
agreeing to a consensusdefinition.
(39:02):
Thank you.
And what that would lead to, andthen you can add on to that
going forward.
And I'll add a third thing in,tie back to what Chad said, but
taking a step further.
If you're, and I'll use revenueas a revenue org.
If you're actually aligningoutcomes across the revenue
critical functions now, andpeople are jointly accountable
in, in unique ways, but haveaccountability for revenue
(39:24):
outcomes.
And you're providing them thedata set to allow them to see
how they're doing, but it has tobe unified.
You're actually creating abenefit.
There's a need for it and abenefit above and beyond just
saying we're doing a singlesource of truth.
There's value for the end useras well as the functional
leaders, so there's, there wouldbe a way to get better buy in.
(39:45):
But eventually the business willsay, this is how we're
measuring, right?
And this is how you're going tobe tied to success.
Utilizing the way we're doingthis.
We're just, I want to do a timecheck cause there's actually a
little bit more to go through,about eight minutes.
Chad, why don't you go quicklythrough the tools and tech and
considerations, and then we'llmove into the write data in
write data out.
(40:06):
So just a few components thatyou probably need to consider or
at least have for developingthis and putting this together.
First one's data warehouse,which is really somewhere that
stores.
All of the data that you'veaggregated or collected from all
the different systems.
Typically in the cloud nowadays,there are a variety of providers
out there who offer very goodsolutions.
(40:26):
Second is more of a dataextraction and data cleansing
capability or tool.
Oftentimes this is also soldindependently within the market.
So there it's basically what itmeans is it's a tool to bring
the data out of your CRM or outof your source systems and then
to transform it or to clean itup and get it ready for report.
(40:47):
The third is a data access anddata management layer or tool,
which is a means to make surethat only the right people are
seeing the data that they needto see and also a means to
adjust the data as needed.
You want as a business user, asa business in general, you want
to enable the end users tomanage that information that's
(41:09):
in the single source of truth tothe best of their ability
without technical intervention.
And that's what we were callingout there with that capability.
Force something to display it.
So a way to look at the results,look at the data period or dive
into it, so to speak.
And then lastly, a predictive MLAI capability, which can sit on
(41:32):
top of all this information andhopefully give you more advanced
insight into the business.
And generally these can.
Either sold and purchasedindependently in the market or
unified within a singleplatform.
And what is ETL, RETL?
I don't know what that standsfor.
So that's extract, transform,load, and then R is reverse.
(41:55):
And that's a little bit newertechnology.
What that is being able to takethe data that you've aggregated
and push it back into yoursource systems, grab data from
finance and Salesforce and theCRM, potentially being able to
push that.
I mean, it's back into theSalesforce or CRM, which is
funny.
Is this a picture of likecomprehensively what you would
(42:18):
need?
Eat all of those elements inyour, you generally need at
least data warehouse, dataextraction, or ETL, and then a
display.
If you don't have those three,it's tough to get by.
You really want a data accessand data management to do it
properly.
And then the predictive is moresomething you can add at the
end.
If you want to, once you'vegotten the data combined, we're
(42:39):
trying to keep it as simple aspossible in terms of achieving
them.
Thank you.
So just quick key factors, we'llrun through these, I want to
make sure we get to the lastpart is obviously the
consideration, do you have thestaff to do it or do you need to
outsource it?
When, you know, your time tovalue is really important.
You don't want to be spendingtwo years defining things,
right.
And agreeing you like you wantto go, your investment goes out
(43:00):
and you want to start activatingit, enabling it and iterating
it.
There's the complexitycalculation, like how much and
again, that's why the quick winpart is really important is what
we're being pitched or what arewe looking at?
Is it adding complexity that wedon't need and it's going to
stop us from getting to the timeto market.
And.
How disruptive will this be onthe business to go forward or
(43:21):
non disruptive?
It's important that whoeveryou're working with understand
your business and organizationalmodel and how are you going to
calculate your investment andthen the payback period, right?
How will this investment payitself back plus?
And the real biggie also is makesure it's built for business
users.
And then, so, write data in,write data out is a very
(43:45):
important concept.
Not everything needs to bemeasured.
It's not all meaningful.
Tracking everything willjeopardize the long term value
that an SSOT strategy delivers.
The next slide.
And it really needs to be mappedto stakeholder goals.
So the next slide we'll gothrough the stakeholders and how
you need to understand whoyou're addressing.
And Steven, this may go to yourquestion also is, you know,
(44:08):
which part of the organizationare you trying to drive value
through data?
But the first stakeholder aregonna be your investors.
And no particular order, by theway, the second stakeholder is
clearly the C E O.
The C F O is right there.
C r O.
The C m O.
The c o o.
(44:28):
The chief product officer, andthen your functional teams,
right?
All underneath those layers.
And again, you'll add yours, butbuild your map of stakeholders.
And then the next slide we'll,let's focus on investors.
So investors, if you are eitherPE owned, or you are looking to
be PE owned, or maybe you are aprivate equity, oh, and you own.
(44:51):
The map, the goals, right?
They're looking for duediligence for new investments,
operational oversight of currentportfolio companies, proof of
investment thesis,identification of hidden
opportunities, and examples oftypes of data they need go cut
across.
Pretty much.
I would say all of the executivedashboard, if we wanted to look
at the CFO, which is the nextstakeholder.
(45:15):
Your CFO is a critical person inthe organization, and there's a
huge plate to, of things thatthey need to do.
Everything of reportingfinancials to board and
shareholders, to maximizingassets and resources, managing
EBITDA and EBITDA growth.
Their data requirements are, Iwould say probably the most
extensive and probably tap intothe majority of the data out
(45:41):
there because they're looking atcosts.
They're looking at margin,they're looking at growth,
revenue, they're looking atcustomer lifetime value, and
they're looking at revenue peremployee profitability.
And then the next one examplethat we'll share is the CRO, who
is driving the revenue andmapping their goals like we'll
(46:02):
include in our deck, a littleblank slates of this, but you
would map your, what are thegoals, the data required to hit
those goals and some examples ofhow you measure for those
stakeholders.
And then that goes into howyou're going to build your
strategy and how you'llprioritize.
Right.
Maybe the investor.
(46:22):
Data isn't as important as theCRO data because revenue right
now is your most critical,urgent issue.
You would start with revenue.
Or it could be that you'respending hundreds of hours
building forecasts that are deadon arrival, and your board's
really sick of it, so the CFO isgoing to come first.
And it'll dictate the data thatyou're going to attack first.
(46:48):
Because we're over by a minute.
We had opened up for morequestions.
If you'd like to set up a callwith us to dive into this
deeper, we're offering an hourtime, like office hours.
So just email myself and I willget that set up.
You'll get this deck.
We have another bootcamp forSeptember 21st.
This is all about the actualpredictive analytics side.
(47:10):
And once you get a single sourceof truth going, how can you use
predictive analytics to drive?
Top and bottom line growth andmanage risk and capture
opportunity.
So the registration link for the21st is in the chat, whether you
want to just copy it for lateror we can also email it to you.
I hope everyone found thishelpful.
Thank you, Heather.
(47:31):
Yes, thank you.
Thanks, Chad.
I think we have our work cut outfor us because we are really
just in the early stage.
And this was very useful,especially at like a summary
level of things that we can talka little bit more about
internally and give us some sortof path to go by.
(47:55):
Terrific.
We really appreciate you joiningus and hope we'll see you on the
21st.
I'll also reach out to see ifthere you need any help in
between now and then.
For sure.
Thanks everyone.
Thank you everyone.
Heather Holst-Knudsen (48:05):
You can find us@2klabs.com.
Thank you.
Thank you for listening to TheRevenue Room by H2K Labs.
Subscribe to our channel today.
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