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of the ¬rm depends on the outcome of a sequence of four events which
will impact the decision. This came from an actual valuation assignment.
Part 3 consists of a mathematical technique to streamline the process
of forecasting sales for a startup. We call the technique the exponentially
declining sales growth model. This model enables the user to generate a
realistic, exponentially declining sales pattern over the life of the product/
service with ease and greatly simpli¬es and facilitates sensitivity analysis,
as it eliminates or at least greatly reduces the need to manually insert
sales growth percentages in spreadsheets.


3
Two more sophisticated approaches are using Monte Carlo simulation and real options, which
are excellent solutions but beyond the scope of this chapter.




CHAPTER 12 Valuing Startups 409
FIRST CHICAGO APPROACH
Startups are much riskier ventures than mature businesses. Because of a
lack of sales history and often a lack of market information, a number of
widely varying scenarios are plausible, and the range of outcomes is
much wider and more unpredictable than that of mature businesses.
In a DCF analysis the forecast cash ¬‚ows are supposed to be the
weighted average cash ¬‚ows, with the appraiser having considered the
full range of possible outcomes. However, it is dif¬cult to do this with
such a wide range of possible outcomes. Instead, typically the appraiser,
investment banker, or venture capitalist uses the usually optimistic fore-
cast of the client”perhaps downplayed somewhat”and discounts that
to present value at a very high rate, around 50“75%.
Thus, a more traditional single-scenario DCF analysis to calculate fair
market value is not only more dif¬cult to perform, but it is also far more
subject to criticism by parties with different interests. Short of using
Monte Carlo simulation”a complex approach requiring specialized soft-
ware that is warranted only in a limited number of assignments with
very sophisticated clients”it is virtually impossible to portray the cash
¬‚ows accurately in a single scenario. Instead, the best solution is to use
a multi-scenario approach known as the First Chicago approach. I name
the typical scenarios: very optimistic (the grand slam home run), opti-
mistic (the home run), conservative (the single), and pessimistic (the
strikeout).
According to James Plummer (Plummer 1987), Stanley C. Golder
(Golder 1986) was the originator of the First Chicago approach, named
after First Chicago Ventures, a spinoff of First Chicago Bank™s Equity
Group. In 1980 he founded the venture ¬rm Golder, Thoma, and Cressey.
James Plummer actually gave the name to the First Chicago approach.
Bradley Fowler wrote the original literature on the First Chicago approach
(Fowler 1989, 1990, 1996).

Discounting Cash Flow Is Preferable to Net Income
While discounting forecast cash ¬‚ow is always preferable to discounting
forecast net income, it is even more important to use cash ¬‚ow in valuing
startups than it is in mature ¬rms. This is because cash is far more likely
to run out in a startup than in a mature ¬rm. When that happens, the
¬rm is forced either to take on new investment, which dilutes existing
shareholders™ ownership in the company, or go out of business. In both
cases, using a discounted future net income approach will lead to a se-
rious overvaluation.
When budget is a consideration, it is possible to discount forecast
net income instead of cash ¬‚ow. However, it is critical that the appraiser
at least do some due diligence to ascertain that the subject company will
not run out of cash.

Capital Structure Changes
Startups tend to have somewhat frequent changes in capital structure.
Investment often occurs in several traunches. These changes can involve



PART 5 Special Topics
410
replacing debt with common or preferred equity and new investment in
equity. This complicates the value calculations because one must be very
careful about whose equity he or she is measuring. Each round of in-
vestment dilutes existing equity, and it is easy to measure the wrong
equity portion if one is not careful.



Venture Capital Rates of Return
Venture capitalists price companies by determining the present value of
cash ¬‚ow or future earnings. One method of valuation is to discount an
optimistic forecast of FMV at the required rate of return. Required rates
of return for VC vary directly with the stage of the company, with star-
tups being the riskiest, hence requiring rates of return of 50“75% (Plum-
mer 1987).
Fowler cites (Fowler 1990) a survey published by Venture Economics
covering 200 companies which indicated that 40% of VC investments lost
money, 30% proceeded sideways or were classi¬ed as ˜˜the living dead,™™
20% returned 2“5 times invested capital, 8% returned 5“10 times, and 2%
returned greater than 10 times the investment. In a follow-up article
(Fowler 1996) he refers to comments made by Professor Stewart Myers
of MIT in his November 1995 address to the American Society of Ap-
praisers con¬rming that 70“80% of VC investments are failures, whereas
20“30% are big winners. In addition, Professor Myers observed that the
overall IRR for successful VC partnerships was approximately 25%.4
The 25% rate of return is consistent with a more recent Wall Street
Journal article (Pacelle 1999) which cites Venture Economics as a source
that venture capital ¬rms returned an average 27.4% over the past 5 years,
although they returned only 15.1% over the past 20 years. From this, we
can calculate the ¬rst 15 years™ (roughly 1979“1993) compound average
return as 11.27%.5 That is a very low return for VC ¬rms. It is comparable
to NYSE decile #1 ¬rm long-run returns. I would attribute that low return
to two factors. That period:
1. Was the infancy of the VC industry, and the early entrants faced
a steep learning curve.
2. Included two severe recessions.
It is not reasonable to expect VC investors to be happy with a 15% return
long run. The ¬ve-year average of 27.4% is more in line with the risk
undertaken.
As to batting averages, a reasonable synthesis of this information is
that 2% of VC investments are grand slams, 8% are home runs, 20% are
moderately successful, and 70% are worthless or close to it.


4
He also mentioned that the average VC project return was 1%. He said the difference in returns
is due to the skewness in the distribution that comes from the venture capitalists quickly
identifying and pulling the plug on the losers, i.e., they do not continue to fund the bad
projects. Thus, the bad projects have the least investment.
5
r15)(1.274)5 1.15120, which solves to r15
The equation is: (1 11.27%.




CHAPTER 12 Valuing Startups 411
Table 12-1: Example of the First Chicago Approach
In Table 12-1 we use these percentages for weighting the four different
scenarios, very optimistic, optimistic, conservative, and pessimistic, re-
spectively.
Initially we perform discounted cash ¬‚ow calculations to determine
the conditional FMV of the subject company under the different scenarios.
Typical venture capital rates of return include the discount for lack of
marketability (DLOM) and discount for lack of control (DLOC). This
tends to obscure the discount rate, DLOM, and DLOC. The appropriate
discount rate using the First Chicago approach begins with the average
success rate of approximately 25% reported by Professor Myers.
The 25%, however, is a geometric average rate of return. We should
estimate an increment to add in order to estimate the arithmetic rate of
return.6 In Table 5-4 we show arithmetic and geometric mean rates of
return from log size model regressions of the 1938“1997 New York Stock
Exchange data for different size ¬rms.
For a ¬rm of $1 million FMV, the regression forecast arithmetic and
geometric returns, rounded to the nearest percent, are 25% and 18%, re-
spectively, for a differential of 7%. For a ¬rm of $25 million FMV, the
regression forecast arithmetic and geometric returns, rounded to the near-
est percent, are 21% and 16%, respectively, for a differential of 5%. We
can add the size-based differential to estimate the arithmetic average rate
of return to use for our discount rate. For most size ranges the result
comes to approximately 30%.7
Column B of Table 12-1 lists the conditional FMVs obtained from
discounted cash ¬‚ow analyses using different sets of assumptions. In the
very optimistic scenario we forecast outstanding performance of the com-
pany, with a resulting FMV of $130,000,000 (B6). Cells B7 and B8 display
the FMVs arising from optimistic and conservative forecasts, respectively.
In the pessimistic scenario we assume the company fails completely, re-
sulting in zero value. When valuing a general partnership interest, which


T A B L E 12-1

First Chicago Method


A B C D

5 Conditional FMV [1] Probability [2] Wtd FMV

6 Very optimistic scenario $130,000,000 2% $2,600,000
7 Optimistic scenario 50,000,000 8% 4,000,000
8 Conservative scenario 10,000,000 20% 2,000,000
9 Pessimistic scenario [1] 0 70% ”
10 Weighted average FMV 100% $8,600,000

Notes:
[1] Individual discounted cash ¬‚ow analyses are the source for the numbers in this column
[2] Based on the VC rates discussed in the chapter




6
I con¬rmed this in a telephone conversation with Professor Myers.
7
Fowler™s article did not address this adjustment.


PART 5 Special Topics
412
has unlimited liability, the appraiser should consider the possibility of
negative value.
Column C lists the probability associated with each scenario. These
are derived directly from the empirical probabilities of VC success dis-
cussed above. We calculate the weighted FMV in column D by multiply-
ing the conditional FMV in column B by its associated probability in
column C and summing the results. Thus, in this example the weighted
average FMV is $8,600,000 (D10).


Advantages of the First Chicago Approach
The major advantages of the First Chicago approach are:
1. It reduces the uncertainty associated with a single FMV by
allowing for several scenarios representing differing levels of
success of the company.
2. It breaks down the huge range of potential outcomes into ˜˜bite-
size™™ chunks, i.e., the individual scenarios, that are credible and
plausible when performed carefully.
3. It makes the appraiser™s probability distribution of outcomes
explicit. In doing so, it has two additional advantages: (a) If the
client agrees with the conditional FMVs of each scenario but for
some reason feels the probabilities are not representative of the
subject company™s chances, it is an easy exercise for the client to
weight the probabilities differently and adjust the valuation him
or herself. This is particularly important when the assignment is
to provide existing shareholders with information to negotiate
with funding sources. If both sides accept the scenario
valuations, it is usually easy for them to come to terms by
agreeing on the probabilities of the outcomes, which they can
easily do without the appraiser; and (b) it protects the appraiser.
When the appraiser shows a ¬nal weighting of the conditional
FMVs multiplied by their probabilities to calculate the FMV and
the appraiser shows the probability of total failure as, say, 70%,
it can protect the appraiser from a disgruntled investor in the
event the company fails. The appraiser has clearly
communicated the high probability of investors losing all their
money, despite the fact that the FMV may be very high”and,
we hope, is”due to the large values in the upper 30% of
probable outcomes.
Therefore, the First Chicago approach is normally the preferred
method of valuation of startups. It is also useful in valuing existing ¬rms
that are facing radically different outcomes that are hard to forecast. For
example, I used it recently to assist warring shareholders who wanted
one side to buy out the other in a four-year-old company. The ¬rm was
pro¬table and had grown rapidly, but there were several major uncer-
tainties that were impossible to credibly consider with accuracy in a single
DCF scenario. The uncertainties were as follows:
1. There was much customer turnover in the prior year, despite
healthy growth.

CHAPTER 12 Valuing Startups 413
2. If one of the shareholders left, sales might suffer greatly for two
or three years and even endanger the company.
3. There were regulatory issues that could have had a dramatic
impact on the company.
4. Pro¬t margins were highly variable in the past four years and
could have been affected by regulation.
Collectively, these uncertainties made a single scenario forecast of
sales growth and pro¬tability very dif¬cult. Despite considerable parti-
sanship by the shareholders, who often actively lobbied for changes in
the DCF analyses, the First Chicago approach enabled us to credibly
model the different paths the Company could take and quantify the val-
uation implications of that. Ultimately, we presented them with the val-
uation of the different scenarios and our estimates of the probabilities,
and the weighted average of the product of the two constituted our es-
timate of FMV. We also explained that they could change their subjective
weighting of probabilities of outcomes, thus changing the FMV. Ulti-
mately, they worked out an arrangement without any further need for
our help.


Discounts for Lack of Marketability and Control
Finally, venture capitalists typically have more control and possibly mar-
ketability than most other investors. When valuing the interests of other
investors, the appraiser must add the incremental discounts for lack of
control and marketability that apply to the speci¬c interests, i.e., an arm™s-
length investor would typically require a higher rate of return on smaller
interests than the 30% that the VC expects.

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