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Chapter 10
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Increasing the Value of the
Organization
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Multiple Approaches to
Valuation are Illustrated by
Case Examples
• Mergers in oil industry in the 1980s
(Chevron-Gulf)
• Mergers in oil industry of the 1990s
(Exxon-Mobil)
• Firm valuation through the stages in the
life cycle
• Valuations in the Internet industry
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Oil Mergers of the Early 1980s
(Chevron/Gulf)
• Transaction terms
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Chevron won auction in March 1984
Cash bid of $80 per share
Pretakeover activity price of Gulf was $39
Premium was $41 or 105%
Gulf had 165.3 million shares, total price was
$13.2 billion — a gain of $6.8 billion
– Transaction was taxable and treated as a
purchase
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Valuation and Merger Analysis
General Framework
• Nature of the industry
• Industry characteristics that drive
mergers and potential synergies
• Historical value drivers
• Business economic analysis of the
future for the industry and firms
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• Projections of the value drivers for
valuation firms
• Effects of the merger or rival
competitive structure and strategies
• Antitrust and other regulatory aspects
• Implementation
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Exxon-Mobil Merger
• Characteristics of the oil industry
– Basic characteristics
• Oil is a global market
• Strategically important for industrial, political,
and military reasons
• Large costs required for environmental
protection
• Impact of OPEC
• High degree of price instability
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– Setting for oil industry mergers in 19971999
• Price fluctuations — from $25 per barrel in 1996
to $9 per barrel by early 1999 to $24 per barrel
in September 1999; $35 in early 2000; $26 in
May 2000
• Restructuring, investment in technology, and
cost reduction
– Oil industry characterized by cash flows in excess of
positive NPV investment opportunities
– Oil companies tried diversification in 1980s which
resulted in declines in shareholder values
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• Reasons for the Exxon-Mobil merger
– Would extend presence in regions of the
world with highest potential for future oil and
gas discoveries and production
– Stronger position to invest in large outlay
programs with high prospective returns and
risk
– Complementary exploration and production
operations in South America, Russia,
Eastern Canada, Asia, and Africa
– Near-term operating synergies in the amount
of $2.8 billion
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• Event analysis
– Event date 0 was announcement date on
12/1/98
– Excess returns with respect to AMEX Oil Index
– CAR for event window [-10,0]
• Mobil = 16.2%
• Exxon = 0.97%
– CAR for event window [-10,+10]
• Mobil = 23.7%
• Exxon = 6.3%
– Positive CARs consistent with calculation of
$32 billion added value from the merger
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• Antitrust issues
– Herfindahl-Hirschman Index (H Index)
measure
• H index for petroleum industry
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1975, H index = 410
1979, H index = 416
1984, H index = 377
1990, H index = 362
1995, H index = 407
1996, H index = 415
• H index well under critical 1,000 level specified
in regulatory Guidelines
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– Effects of major oil mergers on H index
• Major oil combinations
– Total/Petrofina: increase index by 6.13 points to 395.48
– Total Fina/Elf Aquitane: increase index by 22.01 points to
417.49
– BP/Amoco: increase index by 29.18 points to 446.67
– Exxon/Mobil: increase index by 83.07 points to 529.74
– BP Amoco/ARCO: increase index by 51.1 points to
580.84
– If a Chevron/Texaco took place: increase index by 17.94
points to 598.78
• Six mergers among top 23 petroleum companies in
the world would result in a rise of H index from 389
to 599, well short of 1,000 critical level
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– Overall industry concentration measures are
far below 1,000 threshold
– Antitrust issues are not raised from an
aggregate industry standpoint
– Although individual oil companies are large,
oil industry is also large ($1.5 trillion
revenues)
– Federal Trade Commission required ExxonMobil to sell off some wholesale distribution
and retail marketing entities
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The Internet and Online
Technologies
• Background
– Revolutionary distribution vehicle
– Global market
– High growth rates
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– Financial characteristics
• High volatility in stock prices
• High stock prices relative to revenues because of
high prospective growth rates
• Internet retailers can earn returns on invested
capital comparable to traditional retailers with
gross operating margins in the 5 to 10% range vs.
20 to 30% because of lower investment
requirements
– Use of M&As
• Proceeds and stocks from new Internet IPOs used
for rapid series of acquisitions
• Aim is to achieve critical mass, market leadership,
and name recognition
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• Valuation approaches
– Comparable companies approach
• Ratio of market to EBITDA may not work
because of low or negative EBITDAs
• Ratio of market to book may be distorted
because losses depress size of book values
• Ratio most widely used is market to revenues
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– DCF valuation
• Standard DCF methodology with multiple
stages of revenue growth can explain valuation
relationships observed for Internet companies
• Illustration of a 4-stage DCF valuation model
– Stage 1
• Losses in early years
• High revenue growth rate above 50%
• Negative operating margins
• Zero tax rate
• High cost of capital of 15%, reflecting high beta
risks
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– Stage 2
• Company has matured sufficiently to achieve
profitability
• Period of favorable growth and high margins
• Growth rate drops to around 33%
• Operating margins rise to 30%
• Tax rate around 20% to reflect benefit of
carryforward of tax losses in Stage 1
• Cost of capital remains relatively high
– Stage 3
• Revenue growth decays until it reaches 3%
• Operating margin declines to 15%
• Combined corporate tax (federal and state) of
40%
• Cost of capital remains relatively high
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– Stage 4
• Constant or no growth rate
• Operating margins decline further to 10%
• Tax rate and cost of capital at same level as in
Stage 3
• Variations in the value drivers can be made to
reflect different scenarios
• High multiples of market to revenues observed
in Internet companies reflect high growth and
high profit margins achievable in early stages of
new industries
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Calculating Growth Rates
• Discrete compound annual growth rate (d)
– Geometric average based on the end points of the
time series
– Found by dividing the final year number (Xn) by the
initial year figure (X1), then taking the n-th root (for n
number of years between initial and final number)
1/ n
 Xn 

d  
 X1 
 1
– May be seriously flawed if end values are not
representative of fluctuations in the time series of the
variable
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