Scott Meadow

- [Lisa Koengeter] All right,
we are going to get started.

Thank you all again for joining us...

this evening, this morning,

for those of you who are
joining us from Asia.

My name is Lisa Koengeter

and I am the director of Admissions

for the Executive MBA Program.

It's my pleasure to welcome
you on behalf of our full-time,

our evening, our weekend,

and our executive MBA programs

to this MBA Masterclass
Series on "I Love Cash Flow:

Building Intellectual Proof of Concept"

with Professor Scott Meadow.

So in this Masterclass series,

we feature our world-renowned faculty

giving you a glimpse
inside of the classroom

and our very distinct approach
to business education.

It's what we call the Chicago Approach.

And today you are gonna
experience that live,

and there's two key
features of that approach

I want to call your attention to.

One is our data-driven, our
evidence-based teaching,

which will give you tools

to be able to ask better questions,

to think more strategically,

and to solve really big problems.

You'll have a sample
of that evidence-based,

data-driven approach tonight

as you hear from Professor Meadow.

The second component of the
Chicago Booth experience

that I want to call your attention to

is our very collaborative community.

Here at Booth, you'll join

a supportive network of
students, faculty, staff, alumni,

who will all be your champion
each and every step of the way

through your journey as an MBA student.

Professor Meadows'
participation in tonight's event

I think is a great example
of that collaborative spirit

here at Booth.

His generosity to help not only students

in the classroom, alumni,

but also all of you this evening

who are joining us as
prospective students.

So in true Booth style of this
collaborative environment,

we encourage questions.

We encourage you to use the Q&A box

and send us your questions

throughout the class this evening.

We will save a few minutes at
the end of the presentation

to answer your questions live.

All right, with that,

let's meet your professor
for this Masterclass:

Scott Meadow.

Professor Meadow is a Clinical
Professor of Entrepreneurship

at Chicago Booth.

And he is also a partner
at the Edgewater Funds

and Maroon Partners.

Over the course of his career,

Scott has approved hundreds
of equity financings

and he's personally led
more than 60 investments --

including two dozen
healthcare services companies,

over a dozen consumer
services and retail companies,

as well as many biotech companies.

In December of 2011, Scott's
activities were recognized

by the State of Illinois

when he received the
Richard J. Daley medal.

Each year, this medal is
awarded to one single individual

who has been an advocate
of venture capital

and private equity in the state.

In addition to all of
these accomplishments,

Scott is a dynamic
teacher in the classroom.

He's taught over 10,000
students at Chicago Booth

in entrepreneurial
finance, private equity,

commercializing innovation,
introduction to venture capital

and our new venture challenge program.

He was awarded the Phoenix
Prize for Excellence in Teaching

four times: the first person to do so.

Professor Meadow earned
his AB Magna Cum Laude

from Harvard College

and his MBA from Harvard Business School.

And with that,

please join me in welcoming
professor Scott Meadow.

Scott, I turned the mic over to you.

- [Prof. Meadow] Thank
you, Lisa, thanks so much.

And if anything happens
to me in the next hour

and I should keel over dead or something,

make sure Lisa is speaking at my funeral.

That was such a beautiful introduction.

Thank you, Lisa.

OK, well, let's get started.

And we've got this fun, this
fun kind of cartoon to look at.

And we have here really Sisyphus.

And Sisyphus, for those
of you that don't know,

got in an argument with Zeus

back in the time of Greek mythology.

And he was basically
doomed to push that rock

that he's carrying up a hill
only to have it roll down.

And that curse was for the end of time.

And so our Sisyphus here is,

as you can see, staring at this rock,

and what does the rock represent?

The rock represents his customers,

his employees, his competitors,

his suppliers, all there --

his lawyers, his investment bankers:

all the people that
he, as an entrepreneur,

has to think about as he's
leading this adventure

into a disruptive concept.

Now you see this over
here, this banana peel.

That's supposed to be funny.

But let me just tell you
that as an instructor

in the entrepreneurial world,

a person that's got that
many things on his mind

has 100 percent probability
of slipping and falling

on that banana peel.

So the issue is not so
much that you slip and fall

on the banana peel -- 'cause
there's 100 percent probability

that's gonna happen --

the real issue is, you know,

have you done enough so
that you can get yourself up

and keep pushing forward?

So that's what we're gonna
talk about a little bit

over the next hour.

So we're gonna talk about the entrepreneur

and the investor, and issues
impairing that partnership.

And so some of those things are,

there's a lack of efficiency
in deploying capital

to private equity projects.

Sometimes, people put too much in,

sometimes they don't put enough in --

and it tends to create problems.

There's sort of limited joint
development of the projects

underlying profit formula.

So an entrepreneur will show
up with the profit formula;

the investor doesn't know
where that came from.

There's no systematic
methodology for forecasting fixed

and variable cost structure
of the enterprise.

And think about it:

If you're starting something
up, the riskiest time

in the venture's life is at the beginning.

And if you can substitute
variable cost for fixed,

that's gonna give you a much
better chance of succeeding.

There's difficulty in
predicting meaningful milestones

for the project.

So we would like to put money in,

but put that money in against milestones

and move the economic formula forward.

And then there's a general
lack of transparency

in the company's forecast.

So the investor oftentimes doesn't know

where those numbers come from.

And then finally, there's
limited analytical support

for the long-term
trajectory of the business.

So what do I mean by this one?

So I think everybody's
probably heard of the concept

of hockey-stick projections, right?

And that was considered to
be, you know, kind of ...

It's kind of joke.

If you say somebody has
hockey-stick projections,

that means that they're not
really realistic projections.

But think about it this way:

If you're starting a
company that's disruptive

to its base concept,

wouldn't you expect
hockey-stick projections?

So the issue is not so much
the hockey-stick projections,

but what kind of analytical
modules have you developed,

and what kind of systematic
support do you have

for those projections?

And that's very, very important.

So if you've thought
about these six things

as variances occur, there's no foundation

for editing the business concept

unless you put that foundation in place.

And that's what we're
gonna talk about a bit.

So just in the way of background.

Venture capital, private equity investors

only invest in novel sectors
that they understand.

So what does that mean?

So here's some technology, healthcare,

financial institutions,
industrial, aerospace,

infrastructure, et cetera,
are all sector-specific niches

in the entrepreneurial market that people

in the venture business as
investors tend to focus on.

So for an investment in a new
sector or disruptive concept

to be palatable to a
private equity investor,

that private equity
investor has to be confident

that the idea is novel,
that the entrepreneur

has the centrality to execute --

which means strategic
sector-specific knowledge --

and some kind of operational
access to the people

that are gonna make
the project successful.

And most importantly,
that the entrepreneur

has the capacity to
communicate the concept:

i.e., smoothing out information
assymmetries that exist

and that are inherent in such
an early-stage investment.

So effective entrepreneurs
reduce information asymmetry

so that they can attract
the kind of investor

that can make them successful.

And how can they tell if that investor

can make them successful?

If the investor can help
them recruit executives;

provide access to potential
and investors and acquirers;

provide introductions
to the right customers;

coach senior managers;
provide industry expertise

and strategic perspective;

and help editing the business model

based on new information.

But investors can only
add value to the project

if they understand the
economics and the profit formula

and trust the centrality
of the entrepreneur.

So entrepreneurs must
effectively communicate

the economics of the business,

the profit formula and
capital gain opportunity

to potential investors.

So this is something
that probably everybody

has seen before.

This is a set of forecasts
for a new business, OK?

Now let's say Lisa and I are partners

and we're getting ready to
fly out to the West Coast

and meet with Kleiner Perkins
about our new project, OK?

And Lisa thought we ought
to show Kleiner Perkins

five-year projections

that grow from roughly $2
million to roughly $50 million.

But I on the other hand

thought we ought to show
them something that grew

from $10 million to $100 million.

And we went back and forth,
and back and forth on this

for quite a while -- and
we ultimately settled

on these numbers.

We go out to 3000 Sand Hill Road,

or maybe 4000 Sand Hill Road,

and we sit in front of four
associates at Kleiner Perkins

with our business concept.

And we think we're gonna
get a lot of questions

about numbers but instead,
they ask us three questions.

Question number one is, you
know: Is your project something

that you two have
experience in, in the past?

And we say, yes, that's the case.

And then they start to
think to themselves,

"Geez, have we invested in
this sector in the past?

Do we have a group of potential executives

that could either help Scott and Lisa

or potentially join their
board and make them better?"

And lastly, will Scott and Lisa play ball

with our modus operandi

in terms of how we want
to manage a project?

So assuming that we had
a pretty good meeting,

the team at Kleiner
Perkins is gonna go back

and they're gonna talk to a partner.

And if the partner feels

that they can potentially help us

and help us in the right way

based on the kind of
sector-specific expertise

that they have -- and the
experience that they have

in the sector that we're in --

they're likely to come back and
ask us for a second meeting.

Now when Lisa and I fly out
for our second meeting, OK,

they're gonna give us a set of projections

that are very different than
the ones you see before.

In fact, they're gonna take
out a giant meat cleaver

and they're gonna cut
through our projections

and slice 20 percent off the top.

And you know what?

There's not a word we can say about it.

Because they're not -- they
just don't trust our ability

to come up with referenceable,
credible projections.

So what we're gonna
talk about a little bit

is how we can come up with
referenceable projections

that hopefully help us, as entrepreneurs,

hold on to as much of the
company as we possibly can.

So part of that process has to do

with something that I call analogs, OK?

And an analog is a company
or group of companies derived

from secondary market research

and confirmed by personal interviews

that mirror the economics,
operating characteristics,

investment requirements,
and customer profile

of our new projects.

Among other things, analog should allow us

to model and communicate project economics

for our concept, or target
a company, using components

that reflect the economics
of similar businesses.

They help us forecast
revenue and its key drivers,

things like unit volume
and average sales growth

or sales price.

They help us understand the
growth at the unit level

and from addition, and
the addition of units.

They help us predict the cost
structure and hypothesize

about investment requirements.

So selecting analogs requires
a little bit of creativity.

We aim to find referenceable
data about the economic drivers

of the project.

So what we're looking for are companies

with similar revenue models

and comparable payment terms
in the same line of business;

with similar cost structures
that pursue the same customers;

that follow the same
business and economic cycles;

that require a similar
level of initial investment;

require the same type of human capital;

and have similar working
capital characteristics;

and require operational
access to similar resources

that are out there.

So if you're scratching
your head and saying,

"Geez, what is an analog?"

I think most of us have
heard of the company Staples

that sells office products.

Well, I was fortunate to be
involved in the startup of that.

And if we were thinking about

what are the appropriate
economic variables

that go into the Staples profit formula,

we would look at an analog like Home Depot

or something like that.

So Home Depot would be
an analog for Staples.

If we look at the economic
variables associated

with making Home Depot
successful, similar,

those economic variables will be helpful

in helping us understand Staples.

So that's what an analog is all about.

So in coming up with
the appropriate analogs,

we have to do some marketing research.

And the first kind of marketing research

that I'm gonna talk to
you about is something

that you're all familiar about --

and that's secondary marketing research.

So if you Google something,
that would be an example

of pursuing secondary marketing research.

Secondary marketing research is something

that was written by
somebody else about a topic

that we are interested in.

And we access that to learn
from a secondary source

information that will
make us knowledgeable,

a little more knowledgeable
about the business.

So this is an example of
secondary marketing research, OK?

So this is a -- an equity research report

developed by J.P. Morgan.

So this is secondary marketing research

because it's a report written
by this group of people

about a company called Bad Bath & Beyond.

But I'm gonna use this as an example

of conducting something

that I'm gonna call personal research,

which helps you fall back on --

which asks you to fall back

on your own personal social capital.

So imagine that we are
starting, that Lisa and I,

the business that we wanna talk about

is a high-end bath and towel company.

So we're selling very
expensive bath and towels

in a 5,000-square foot store.

And so we thought it would
be a good idea to get,

to not only read this report --

which is accessing secondary
marketing research --

but also call up the people
that wrote this report

and conduct personal research
to help us understand

more about the business.

So we place 100 emails to
Christopher Horvers, CFA.

And he does not answer.

You know why?

Because he's Christopher Horvers, CFA.

Then we call him 20 or 30 times.

And he doesn't pay any attention.

You know why?

Because he's Christopher Horvers, CFA.

Well, if he's Christopher Horvers, CFA,

that means he's not
Christopher Horvers, partner;

Christopher Horvers, managing director;

Christopher Horvers, vice president;

So Christopher Horvers is hanging on

to the bottom rung of the ladder,

trying to climb up that ladder.

So he's not going to take the
time to talk to Lisa and I

about our idea because his base business

is writing equity research
for institutional sales people

at J.P. Morgan who sell
stock to big companies

like Ford Motor Company,

CalPERS, CalSTRS, and people of that sort.

So he's not gonna take
any time talking to us.

But that's OK

'cause we look down here and
we see Garrett Castellani.

Now Garrett Castellani went to Duke,

which is a school in the
Southern United States,

it's a pretty fine institution.

He played lacrosse.

He was in a national fraternity.

He then went to Booth, got his MBA,

and now is working at J.P. Morgan.

And so we reach out to Garrett

and we ask him if he'd
be willing to talk to us

about Bed Bath & Beyond.

And the thing about Garrett

is that nobody talks to Garrett, OK?

So Garrett, you know, on Saturday nights

he'll go to a cocktail party.

He'll hand out his business card.

It'll say Garrett Castellani,
you know, Associate,

J.P. Morgan.

And he can thump his chest

and say that he's an investment banker.

But then, on Monday morning,

he's gonna return to the office:
into a four-by-four office

with no windows and with just
enough space under the door

so people can shove pizza and Red Bull

to keep him going 120
hours a week, you know,

cranking out information.

A matter of fact:

Many of you probably understand
that it's Garrett Castellani

who wrote 70 or maybe 80
percent of this report

and everybody else was proofreading.

So if we can reach out and
get Garrett to talk to us,

then he's probably gonna provide us

with a lot of very important information.

And so if we go back and we
look on LinkedIn or Facebook

or some other social media vehicle,

there's probably going to be
seven degrees of separation

between ourselves and Garrett.

And if we pick up the
phone and in a very nice

and very calm way, say,

"Garrett, hello, my name's Scott Meadow.

I heard wonderful things about
you as a lacrosse player.

We were in the same fraternity.

I went to Colgate, you went to Duke.

I wonder if you would have
a few minutes to answer

some of our questions about
a bath and towel concept

that we're trying to start,

that Lisa and I trying to start."

And guess what?

Garrett is happy to do so
because nobody talks to Garrett.

So Lisa and I ask our first question;

15 minutes later, he answers our question.

We ask our second question;
15 minutes after that,

he answers that question.

We asked our third question;

15 minutes after that, he answers that.

And we're tempted to go
to a fourth question,

but we don't wanna push our luck.

So he answers all those questions.

We ask Garrett, "Is it all
right if we call you back

if we have any more questions?"

He says, "Absolutely, no problem.

Call me back any time."

Think about it.

From his standpoint, by talking to us

he feels a little better about himself.

And he walks out the door of J.P. Morgan

at 12:15 in the morning as
opposed to 11:30 at night,

just because he spent a
few minutes talking to us.

So once we've been able
to find a series of people

like Garrett, then we put together

sort of a list of people that
we're going to interview.

And let's take somebody like Alex Tang.

We set this up in such a
manner so that we have --

we have background here
so that we could talk

about, you know -- kind of
grease the wheels a little bit

to ask him the really tough questions.

And then we have over here,

the kinds of topics that we
hope to address with Alex

and with all the other
people that we've been able

to reach out to.

So personal research
should address key aspects

that we think are linchpin variables

in terms of making our concept successful.

So how do we go about that?

Well, first of all,

there are quantitative factors
that we need to understand.

So some of those had to
do with the operations

of the business; the income
statement; the balance sheet;

the cash flow; growth;
and things of that sort.

So these, what we've listed,
are factors that we need --

that we need to be informed about,

and that we think are important

in terms of understanding our new concept.

And then we list the
rationale for why we think

those particular issues are important.

For example, advertising
and marketing expense.

We need to understand the amount spent

to produce given revenue
in this particular project.

So we want to highlight the factors

that we need to be informed
about and then look for analogs,

which I've listed on the
right hand side of the sheet.

These quantitative analogs will inform us

about the factors that
we have across the top.

So this information, these factors,

we've flipped and we've
put on the horizontal

and we've used analog
companies -- like the ones

that I've listed here -- to
inform us about these factors.

Now ... hey Lisa,

can you read that particular
number for me right there?

I'm joking, Lisa.

You don't have to do
anything. (Lisa laughs)

The point is that you're
probably wondering, "Scott,

why are you showing us such messy slides?"

Because I'm going to
talk to you distinctively

about the red boxes.

Because those are the
areas, those are the things

that I think are the most important.

That being said: Since we're partners

and we're joint and several
-- which is a legal term

that means, that if I do 10 bad deals

and you do 10 good deals,

and my bad deals cancel
out your good deals,

then you don't make any money. OK?

So therefore, you are going to be inclined

to look at the information that,

that my team and I have been looking at

and see if there's something
there that you catch

that will help make
the project successful.

So I'm talking about the red boxes

but I'm leaving the rest of this available

because your economic
self-interest is such

that it's highly likely
that you'll take a good look

at what I've got here,

and hopefully find something
that Lisa and I missed,

and point it out to us in the future.

So once we've come up with
the appropriate analogs,

the next step is to develop
what is known as a unit model.

Now there's lots of
conversation about unit models

and a lot of flapping about it.

But a unit model emerges from the analogs.

And a unit model seeks to
explain the profit formula

based on a rational economic
segmentation of the business:

like a single location and an account

for something like a
enterprise software investment;

a tribe, a region, a specific new drug.

So analogs provide information
on the individual unit.

They help us build up the
economics of a concept

that has never existed before.

And so we construct a
unit model to evaluate

the profit formula of the
business in microcosm.

So another way of saying that
is we construct a unit model

to evaluate the profit formula,

using the least amount
of capital possible.

And the reason is,

is because the most expensive money

that we're going to acquire
to fund this project

happens at the beginning.

And so therefore, what
we're trying to do is prove

that this works using the
least amount of money.

Easier to get funded from
the venture capital community

and probably easier for us to execute.

So in constructing a unit model,

we use analogs as the building
blocks of revenue cost,

working capital and unit level investment,

as well as direct costs like
normalized SG&A and CAPEX.

So let's go through some
simple, simple terms

that I think everybody's familiar with.

Revenues minus cost of good sold,

minus operating expenses, equals something

that I call "unit level
profit contribution."

And then if we take unit
level profit contribution,

I'm suggesting we subtract out

something called "normalized SG&A" --

which equals earnings
before interest, taxes,

depreciation and amortization.

So what is normalized SG&A?

So what we're trying to
prove with this unit model

is that the unit we're trying to evaluate,

the profit formula.

And in evaluating the profit formula,

we have to look at the unit model

under normal sort of circumstances.

And so let's say it may cost us a million

or a million and a half dollars

of overhead to get our business started.

But if we are opening a
single unit and we allocated

all that money to the single unit,

it would come out with a
negative profit formula

and we would probably never
invest in the company again.

So instead, we look for
an analog that represents

what the SG&A of the company

is likely to be when it is more mature.

So, we might,

if we were looking at setting
up something like Staples,

we might go back and look
at Home Depot and see

that they're spending
normalized SG&A of 2.5 percent.

We may borrow that 2.5
percent from Home Depot

and apply it so that what we're getting

is a true measure of an
evaluation of the profit formula.

So: EBITDA minus depreciation
and amortization --

and all the other things
that we generally see

as part of the P&L and
cashflow statement --

take us down to unit level cashflow.

Which brings us down to
the bottom of the page.

And the bottom of the page is a mechanism

for evaluating the unit model.

And this is a unit model, OK?

And we basically take it out for 10 years.

There's no terminal value or value

that we would sell the business for, OK?

And this is the investment
that we're going to make

in the unit model at time zero.

And we're discounting
these cash flows back

against this unit level cashflow.

And that gives us a 10-year
internal rate of return

of 38 percent.

And you probably say, "OK, well, Scott,

what's so special about 38 percent?"

Or what's so special about 30 percent?

Well, when I first got to
Booth about 20 years ago,

I took all the projects
that I had written up.

And I think it was about 60.

And I was able to get another
50 from friends of mine

in the industry, and colleagues of mine,

or teaching assistants of mine;

looked at each one of those companies;

and put them each in a unit model form.

And what we found is that
a business that had a,

an internal rate of return at
the unit level of 30 percent

had a 80 percent chance
of being successful.

And a business that had

a 10-year unit model IRR of 25 percent

had a 40 percent chance
of being successful.

So that made 30 percent
very important to us

and we always seek to look for concepts

that can generate at least 30 percent.

But the question I've gotta
ask everybody is, what grade

would you give the student

that put this particular
analysis together?

I mean, it's a pretty fancy
little piece of analysis.

It looks like a nice job of
Excel spreadsheeting here.

Well, I would give this
student a D-minus. OK?

Why a D-minus?

Because just like when Lisa and I walked

into Kleiner Perkins' office,

there is no references

as to where any of these
numbers come from, came from.

So therefore, we can expect

that nobody is gonna take them seriously

as a result of us not providing background

as to where these number came from.

So a better example of what
things should look like

are what we have here.

And what you see in every row

for this particular unit model,

we have individual
footnotes that talk about

where each one of these numbers came from

and what our assumptions
are associated with that.

So we clearly state the
assumptions and sources.

We include references
to complex calculations

that might have come up, and
we give the reader a basis

to make adjustments in
case one of our colleagues

looks at this and says, "You
know what? I don't think --

I don't think that it's
reasonable for service revenue

in this year to be at this number.

I wonder where he got that from.

Oh, I see. Well...

It's still wrong --

but at least I know where it came from.

I can sit down with Scott.

We can together come up with a number

that we think is more appropriate
and make an adjustment."

Remember we live in an Excel world.

And what we are looking
for is a set of numbers

that is transparent, that
everybody understands,

and that everybody has contributed to --

so that everybody's singing
from the same hymnal.

So this is a unit model
that I would give an A to.

So: How do we determine
whether or not a unit model

is a good business model or not?

Well, let me suggest two
very important features.

One is how much cash is required
to invest in the unit model

with zero being fantastic -- right? --

and $3.5 million being a lot of money

to put into the unit model, OK?

So how much we put into the
unit model is important.

The other dimension is
how long does it take

for the unit model to be
cash-flow positive? OK?

Well, the best is zero.

It's cash-flow positive right away.

Not so good is six years.

So what you see in the red box

in the upper right-hand
corner is a pretty good model:

a model that gets to cash-flow
positive in about a year

and is in probably the $200,000

or $300,000 investment dimension.

So at this point,

let's take a second and talk

about the four different
types of unit models.

So the first one is a
physical location or a store.

So what would be an example of that?

Well, a retail store, a lab
facility, a production plant,

a geriatric community, a
hospital, et cetera. OK?

And as we're trying to understand that,

if I gave you a set of numbers,

talking about the total initial investment

at the unit level, OK? And
you see these dots here

and all this information over here?

Pretend that there's nothing there

and all you have is the numbers.

And let's say that this
is a sporting goods store

that has never existed before.

And the initial inventory is $2.3 million.

And you look at that and you
say, "That's interesting."

And then your eye goes
down the page and you say,

"Geez, accounts payable."

So Scott's saying to me that the trade,

since this is a sporting goods store --

Wilson's Sporting Goods,
Nike, et cetera --

those kind of vendors
are willing to finance

half the inventory.

Wow.

And this is a concept
that has never existed.

I don't believe that that's gonna happen.

That doesn't make any sense to me.

And you fold it up,

and you put it away, and you
go work on something else.

But now pretend that everything
on the right is visible --

and you can look at analogs

like Best Buy, Oshman's et cetera --

and you can see that the
number and the accounts payable

that I talked about, we
actually observed in analogs

that we were able to use to research

the investment associated
with this particular company.

So I think everybody's pretty familiar

with what a facility-based
model would look like.

An individual McDonald's.

An individual Staples.

A healthcare facility like
Sunrise Assisted Living.

And we end up getting a 10-year IRR here

that's pretty, pretty attractive.

So that's a facility-based unit model.

A geographic-based unit
model is a little different.

So let's say that Lisa and
I were starting a business

that, well the business
that we're starting

is the Dove Bar business.

And I think everybody's
familiar with a Dove Bar, right?

It's that delicious ice cream treat.

It's got about 6 percent
butterfat and, you know,

this much delicious
chocolate around the outside.

You take one bite and you
go into diabetic shock, OK?

Everybody know what I'm talking about?

OK.

So let's pretend that Lisa and I --

the company actually started

in a small town between
Chicago and Milwaukee.

And let's say that Lisa
and I go up to Milwaukee,

and we go in to see the frozen
confection buyer at 7-Eleven.

And we're trying to make
our case about how fantastic

our Dove Bar is.

And, you know, the buyer,
whose name is Jane Wilson --

Jane just, you know, she
didn't really get it.

So Lisa rips open one of the Dove Bars,

sticks it Jane's mouth:

Jane takes a bite.

She's sold. OK?

And she asks us to wait
in the waiting room.

And so Lisa and I go
out in the waiting room.

She calls some of her colleagues --

the frozen confection buyer at 7-Eleven

that's out in the Phoenix area,

in the Atlanta area, et cetera --

and she calls us back in and she says,

"Listen, Lisa and Scott,

we are so excited about your Dove Bar

that we wanna put it in every 7-Eleven

in the United States." Right?

And Lisa and I are so excited
that we're already picking out

what color metallic paint
we're gonna get on our new BMWs

after we sell our stock in
this fantastic investment.

But before we walk out the door,

we sort of think to ourselves,

"Geez, if we are just supplying 7-Eleven,

then fundamentally we become
a house brand for 7-Eleven

and 7-Eleven controls us
in every possible way."

So Lisa and I go back in and we say,

"Jane, listen, what we
would like you to do:

We're just a small company, OK?

And what we would like you to consider

is just letting us supply 7-Eleven stores

in the Milwaukee area.

Now we know that that's a big
hassle logistically for you.

But if you allow us to test our product

in your stores in the Milwaukee area,

we will give you an exclusive

in the convenience store
vertical for 18 months."

Well, Jane likes that and she says yes.

Lisa and I we've got something good going.

So we go over to Kroger

and we have the same
conversation with Kroger, OK?

Lisa has to shove the ice
cream bar in the mouth

of the person that we're talking about.

And we tell Kroger,

"Listen, if you let us just
service the Kroger stores

in the Milwaukee area, we
will give you an exclusive

for the grocery chain
vertical for 18 months."

When we're done there, we go to Walgreens.

Same conversation, just
Milwaukee, 18 months exclusive.

And then lastly, we go
to Costco and same thing.

Just Milwaukee, 18 months and exclusive.

Now think about what
we've got in Milwaukee.

We are doing business

with four national
distribution channels, OK?

And in addition to that,

when we're trying to sell a
product like the Dove Bar,

we have to advertise that product on TV

or people aren't gonna know
what we're talking about.

We can't do banner ads
effectively on the Dove Bar.

But that's OK because
we can buy advertising

on a regional basis --

which means that we can
hit Jane in the head

with as many advertisements in Milwaukee

about the Dove Bar as Coca-Cola

can hit Jane in the head with.

So what do we have in Milwaukee?

We have a geographic regional unit model.

In essence, we have a
national business in microcosm

because what you can see is
complete proof of concept

in the Milwaukee market. So that's what,

that's what a geographic
unit model looks like.

Least amount of money going
in to prove the model.

Now all of these models
are a little different.

So if I was a venture
capitalist and I was to walk in

to a partner meeting with
everybody that I'm talking to,

and I was to say to you,

"We need a million and a half
dollars to finance Dove Bar

and $500,000 is going for advertising,"

you're not gonna be very
impressed with that --

but because I haven't told
you how we're gonna spend

the money on the advertising.

So therefore, we're gonna
use an analog like this,

which is the marketing program

for a consumer services concept.

And what I'm going to show
to you is how much money

is being spent and how we
intend to spend it by media.

And on top of that,

we're going to monitor the
concept on a weekly basis,

which should allow us to fine
tune this as we go forward.

So it's very important
that we provide data

at every step of the way
for an emerging concept.

Let's talk a little bit about
a technology-based concept.

And a technology-based concept is,

is structured around the
amount of money that it takes

to develop the technology and
introduce it to the market

divided by the number of
accounts we're likely to get

with our first version of
the technology. So let me,

let me just see if I can
show you an example here.

So here we are building up
the cost of generating --

and this, by the way, is a real project.

Venture capitalists spent $35 million

on this particular project.

And this is their homework, OK?

So let's take a look.

So the first thing they did --

and the product that they invested in

is enterprise software --

so they built this up.

This is, as you can see,

the estimated lines of code,

lines of code per programmer,
et cetera, et cetera.

Which gives way to the
number of programmers

they're going to need, et cetera.

And that comes out to about $483,000,

and about $100,000 of hardware.

And you could see, we
have references over here

where every single number came from.

And if you were thinking, "Geez,

if I'm going to adhere to his method,

am I going to have to make
40 or 50 phone calls?"

Well, if you're a sector-specific expert,

you'll probably be able
to get the work done

with three or four phone calls.

But the people that were
putting this forward assumed

that our $583,000 R&D investment
is divided by 50 accounts.

OK? Now this is enterprise software.

So when we say enterprise,
we're talking about,

you know, Ford Motor Company,

or United Healthcare,
or something like that.

So what's the likelihood -- OK? --

what's the likelihood that a company

like Ford Motor Company
or United Healthcare,

that there's gonna be 50 of
those that are going to buy

enterprise software from a company

that's never existed before?

You see my problem?

That's a problem.

So we come over here.

But if the initial investment
of 583 is allocated

over 50 units, then at the unit level,

we're only investing $12,000

and we get a tremendous outcome.

A 66 percent, 10-year
internal rate of return.

Now I'm sure everybody that's
tuned in knows pretty clearly

that there's no way we're
going to be able to sell

50 enterprise customers in our first year.

In fact, it would be amazing
if we could sell three of them.

But just to be polite,

let's say one of my partners
sticks their hand up and says,

"You know, Scott, just for the
fun of it, run these numbers,

but just put in 10 units
instead of 50 units."

And when we do that,

looking at dividing the 583 by 10 units,

it drags the 10-year
IRR down to 15 percent.

Now, the unfortunate thing
that I've gotta tell you

is this is as far as my
venture capital colleagues went

and then lost all $35
million of their investment.

When in fact, had they
just thought about things

in a little bit more rational basis,

this would've been a turn
down from the beginning.

So the last unit model that
I'm going to talk about

is something called a specialized asset.

And this is predominantly
used for biotech.

Now since we're moving
up towards the hour,

this is a very interesting model,

and it also goes out for 10 years,

But it's a little different
because we have to get through

a process that's for a biotech company

that is overseen by the FDA.

And that's why you see pre-clinical,

phase one, phase two, phase three.

And then over here,

you see an infusion schedule of money

that is put in without equity
by large pharma companies,

hoping to get something
that I call episodic drugs

launched, financed by venture capitalists.

And then over here,

we see that ultimately, this business

makes nothing, makes no
money throughout its life.

You see all those negative numbers?

But right here in year five,

somebody comes in and buys the business,

and that's the positive,
that's the positive cash flow

that gives us a very
attractive unit model.

Now, what you need to understand

is that a specialized asset unit model

that's coming up with a
new kind of antibiotic

called Cethromycin

is really interesting thing to talk about.

But you can't hear the end of the story

until you take my class,
Commercializing Innovation,

which I hope you will when
you come to Chicago Booth.

Thank you all for sitting
through my discussion.

And I think we have
time for some questions.

- [Lisa] Professor
Meadows, this was amazing.

Thank you for the time.

We have a number of
questions that have come in.

If you have time to take a few live,

I would love to pose a few questions

and I'm gonna have my
colleague Zach help me as well.

So Professor Meadows, the
first question I have for you:

"What are common missteps or oversights

in constructing unit models?

Which of these can literally
more costly than the others?"

- [Prof. Meadows] Well, I think the most,

the most critical item is segmentation.

And what I mean by that
was the technology venture

that we were looking at.

If we go through the process
of coming up with the amount

that it costs not only
to develop the product,

but also to market it --

because you've gotta remember
that technology companies

don't fail because of the technology;

they fail because of the marketing.

So once we've accumulated all those costs

in the denominator,

then misjudging how many
customers we are likely to get

and what the sales cycle is likely to be

for a new and emerging company,
that can destroy a business.

Particularly in the very
important technology sector

that we're all pursuing
in various ways today.

- [Lisa] All right another
one for you, from Gillan:

"How does the need for
valid unit models change

with funding rounds?

Should the models change
across funding rounds:

say, between Series A versus D,

where concept objectives have changed

and the business model has
proved to be more believable

with each round?

Thoughts on that?

- [Prof. Meadows] So that's a
thoughtful question, Gillan.

I hope you're an admitted
student. (Lisa laughs)

No, I think the important thing about this

is, we are going to be constantly
refining this unit model.

Right?

Every week, every month,
constantly refining it.

And when we fund a venture like this,

we're hoping that the money
that goes into the company

in the first round of investing
is really enough money

to take us through the
proof-of-concept stage.

And so during that period of time,

we basically have been
able to learn a lot more

about the analogs that we've used,

and whether or not they're
appropriate or not appropriate.

And then, how this is
likely to look in the future

as it moves to a stage in its development

that's more mature.

So the unit model is absolutely essential,

whether you're doing making
a venture capital investment

or you're spending a billion dollars

to do a leveraged buyout.

Because the unit model applied
in the leveraged buyout

is equally important
because if the unit model

is not running effectively,

you'll go bankrupt and lose all your money

in that leveraged buyout.

So you're constantly refining,

constantly updating, and getting a better

and better understanding
of the true economics

of the business the
longer you live with it.

- [Lisa] Excellent.

And a question here from Roland:

"How do you find an analog if the company

is a totally new concept,
maybe like a SpaceX?"

- [Prof. Meadows] Well, because we're not,

we're not looking for an analog

for the whole company. OK?

That's very important.

Since I was just giving a short talk,

I did use a company to
illustrate what an analog means.

And so I used, I used Home
Depot as an analog for Staples.

But that's what not what
we're going to to do

if we're working together
on stuff like this.

We're gonna break the unit model down

into really four pieces:

Revenue, cost, working
capital and investment.

And then the factors
that go into revenue --

that go from revenue to total revenue,

from cost to total cost --

those are each going to
be individual analogs.

So the way we can effectively
research the concept

is to basically go in and
get a good understanding

of those individual
factors, and find analogs

for those factors.

We can't, we obviously
can't find an analog

like the Home Depot analog for a concept

that's never existed before.

But the individual components that make up

the microeconomics of
the concept have existed

in one form or another in the past.

I don't know enough about the
company that you referenced

to use it as an example in
our short amount of time.

So I hope you forgive me

for answering the question that way.

- [Lisa] That was perfect.

Thank you.

Aperva would like to know:

"Can you have more than
one type of model?"

- [Prof. Meadows] Great question, Aperva.

I hope to see you in
Commercializing Innovation also.

(Lisa laughs)

Can you have more than
one kind of unit model?

Well, let's take something --

let's take something relatively easy,

like Burrito Beach.

Burrito Beach is a
fast-casual restaurant chain

that locates in office buildings,

and you can just run down
and grab yourself a taco

and go up to your desk.

So the food on a one-to-10
scale with Chipotle being a 10

is like an 8 1/2 but the
convenience is an 11.

So now I did that big explanation, Lisa

and I forgot -- now I
remember the question.

- [Lisa] More than one type of model.

- [Prof. Meadows] More
than one type of model, OK.

So in that particular example,

we would have to understand
the unit level economics

at the individual restaurant level.

So that's one unit model that
we would need to understand.

But we're not gonna open
up one Burrito Beach.

We are going to saturate a
geography with Burrito Beaches.

So in that case,

we would have to understand
the unit economics

at the individual restaurant level

and the economics at the geographic level

because that's how we're
rolling the concept out.

And then in addition,

we're probably going to have
to develop software that helps

the customer interface as well
as helps us prepare the food

for the customer as well.

So in that one example of some, you know,

of a fast-food restaurant chain,

we're gonna use three
different kinds of models

to understand it.

- [Lisa] Excellent, thank you.

Catherine has a question:

"When is it viable to
transition from using analogs

to create supportable forecasts,
into using actual data

from the company itself?

If a company differs
significantly from its analogs,

how do you determine if this is a red flag

or a potential differentiator?"

- [Prof. Meadows] Well, if it's different

from the intellectual proof of concept

that we have on paper,

then we are constantly going to revise

our intellectual proof of
concept that we have on paper.

So we have our model on paper.

We have the concept being
actualized in the economy.

And as we see, as we experience

the actual history of the business

as it unfolds, we're going
to continue to change

our unit model to reflect reality.

Now, at some point, Catherine,

we may decide that after
being in business for a while,

we were really off on
a couple of very key,

what I call linchpin variables
or factors in the unit model.

And that in fact, the
unit model is generating

a rate of return based on our
changes of 20 or 25 percent.

If that's the case,

then we're gonna look at each other,

entrepreneur and investor
and say, "Listen.

I think you did your
absolute best on this.

I committed $15 million to
this particular project.

We've invested a million and a half,

and it doesn't look as
though this is going to work

based on the factors that have appeared

as we tried to actualize the
concept in the marketplace

and let's close this project down.

And look, I'm not mad at my friend, Zach,

because he lost a million and
a half dollars of my money.

Thank goodness he didn't
lose $15 million of my money.

So I'm gonna invite Zach in and say,

"Zach, you are a great entrepreneur.

You're data-driven.

We preserved my capital.

Why don't you take a seat in my office,

come up with something else

and I'll fund you on
that project as well."

- [Lisa] Great.

I wanna be mindful of
your time, professor.

So I'll ask one more question
from our audience from Dipdy.

She would like to know: "What
is a good margin of error

to consider in these forecasts?"

- [Prof. Meadows] Well,
there is no margin of error.

We're always working
within 100 percent outcome.

And what I mean by that is
we've done enough research

such that the numbers
that we're putting forward

in our projections are numbers
that we truly believe in

until they're proven wrong --

at which point we will
replace what is wrong

with what is right and we will continue,

continue to go forward.

Now that, what I wasn't able
to really talk about here

is how we're monitoring a
project as it gets actualized

in the economy.

I mean, we're sitting there
having a conversation:

if Zach is the CEO of the company,

and I'm the venture capitalist,

I'm gonna be calling Zach
every Friday and talking to him

about a series of issues

that I think are particularly important,

and that he thinks are
important -- every Friday.

I'm never gonna call Zach up and say,

"Hey, Zach, you were 20
percent off this week

in this particular cost component.

Why?"

I mean, that's malpractice on my part.

I'm supposed to already know
the economics of this business.

And so I call Zach up and I say,

"Zach, it looks like we got a problem

with this particular issue.

I mean, is this a one-time occurrence

or do you think this is
likely to be an indicator

of what the long-term economic model

is likely to look like?"

And based on that, we
make an adjustment and we,

we go forward. If he says,

"I think this is what's
permanently gonna be like" --

If he says,

"This is what I think it's
prominently going to look like,"

then we're likely to change the number,

have a new unit model and
continue to go forward

until it indicates that
we either shouldn't,

or we should go faster.

- [Lisa] Outstanding.

I'm gonna ask you one more
question around a favorite book.

Anything that you recommend to the folks

that are on the call
tonight, considering Booth,

wanting to learn more about this topic,

what's a favorite book
that you would recommend?

- [Prof. Meadows] Well since, you know,

I'm an entrepreneurial ... I'm
an entrepreneurial educator.

But I'm also an English major.

So let me see if I can
put two of them together.

- [Lisa] Great.

- So try "Moby-Dick" as
a book I'm recommending.

And everybody scratch -- why Moby Dick?

Well, so ... Captain Ahab,

who's the protagonist in "Moby-Dick,"

is an example of an entrepreneur

who literally does
absolutely everything wrong.

So if you read the book and
you watch everything Ahab does,

you'll have a good idea of all the things

that you shouldn't do.

What do I mean?

Well first of all, he loses
all of his investors' money.

Second of all, he is an
egomaniac and is chasing, chasing

after a market that he's never
gonna be able to penetrate.

And he gets all of his, all
of his employees killed.

So, you know, all in all
you'll have a fantastic read

and you'll also see a
whole bunch of things

that you never wanna do

if you're lucky enough to get
funded as an entrepreneur.

- [Lisa] Outstanding.

That's fantastic.

This has been really thought-provoking

based on all of the questions in the chat.

I wish we had more time.

Join us at Chicago Booth

and you can have more time
with Professor Meadow.

Professor Meadow,

just a few things I'm seeing in the chat

in terms of thanking you and
how fantastic this session was.

Rashida said,

"Thank you, Professor Meadow
for being here tonight.

Your initial overview at
the onset of this class

was a perfect summation and explanation

for how the show 'Shark Tank' works."

Caitlin, "This was fantastic.

Thoroughly enjoyed this.

Thank you very much."

Gillan who asked one of our questions.

He responded to say,
he's applying this fall;

this was a great session and thank you.

So thank you for the time,

the insights and your thought leadership.

And with that, we are
out of time this evening.

And thank you to all of
you who have joined us.

Keep an eye on our Masterclass
series, our website.

We have a number of faculty who

we are featuring throughout
the spring quarter.

And you can tune in to more sessions

like the one you heard today,

and you can also review the
recordings from past sessions.

So with that, Professor Meadow, thank you.

Zach, thank you for
helping with the Q&A box.

And to all of our attendees,
stay healthy, be well,

and we hope to see you here at Booth.

Take care.

- [Prof. Meadow] Thanks again.

Thank you, everybody.

- [Lisa] Bye-bye.

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