Real Options: Teaching Strategy for Uncertain...

Real Options: Teaching Strategy

for Uncertain Environments

Michael Leiblein

Fisher College of Business

The Ohio State University

Three Points: How I incorporate real options concepts

Disequilibrium

Quips, simple examples, humor to create some discomfort

with standard assumptions

An alternative means of thinking

Opinion, model, simulation to illustrate option principles

in a structured, data driven manner

Generate insights

(Case) examples, simulation, & discussion to tie options

to other theories of resource allocation & organization

Disequilibrium An Alternative Insights

Disequilibrium:

Standard Quips & Quotes

―The route to success is to put more money at

risk, not less.‖

J. Lewent, CFO, Merck & Co.

―… the larger the uncertainty, the greater the

opportunity for value creation‖

T.W. Faulkner, Director of Strategic Planning,

Eastman Kodak

Why is that?


Disequilibrium:

Simple stories and examples

Consider a cross-country drive

MapQuest provides a pre-determined route from Boston

to LA, but …

… many value the ―flexibility‖ to change course given

new information. Why?

Consider a Poker Game …

You know the rules and the potential payoffs, but …

… often you don‘t place your final bet before the first (or

even last) card has been dealt? Why?


Disequilibrium: Humor


An alternative means of thinking:

Expert Opinion

―Discounted cash flow is going to look at an average

scenario," comments Triantis. "But if you talk to any

manager, that's not how they think. They think about

contingencies — what's going to happen, how would

we react. And even if they don't think that way, once

it's presented to them that way, they say, 'Yeah, that's

the way we should be thinking.'"

CFO Magazine – ―Will Real Options take roots?‖, July 2003

InsightsDisequilibrium An Alternative


(A quick look at financial options)

―A call option gives its owner the right to buy

stock at a specified exercise or strike price‖

(Brealey & Myers, 1988: 471).

The Black-Scholes option pricing model:

G = f {S, X,, T, r}

The value of a call option increases with project

value (S), uncertainty (), time (T), and the cost

of capital (r).



Simple Example

It is 1982 and you are evaluating entry into the PC business. Entry is now or never. Delay will concede the market to competitors.

The Project NPV for the ‗Mark I‘ appears to be negative … approximately $100 million.

A colleague asks about the importance of ―strategic motives‖ If you enter today, you will have an option to introduce a ‗Mark II‘

micro in a few years as the technology evolves and the market grows.

Your best current information indicates that the Mark II is simply a bigger and riskier project than the Mark I.

Given the tremendous uncertainties in predicting the PC market, you feel the NPV of the Mark II is anyone‘s guess … your point estimate is negative $ 200 Million

Adapted from Brealey, Myers, & Allen (2008).



Simple Example

Absolutely. In three years you have the option to pursue or walk away from the Mark II

The conditional NPV for the Mark II is: $0 if the market flops

$0 if the market is mildly successful

$500 million if the market takes off

With equal probabilities, the Mark II represents a ―lottery ticket‖ on the PC industry with an expected payoff of $167 million.




Simple Example

Suppose a riskier set of market forecasts: ($1 billion) if the market flops,

($200 million) if the market is mildly successful,

$600 million if the market takes off

Expected NPV is still - $200 million.

Conditional on your go-ahead in three years, NPV for the Mark II will be: 0 if the market flops, 0 if the market is mildly successful, $600

million if the market takes off

The expected payoff of your lottery ticket is now $200 M.

The more uncertain the prospects, the more you should be willing to pursue the investment



An alternative mean of thinking: Toy growth example with staged decision making

Case literature

Nucor at a Crossroads, Nucleon, Polaris Energy, …

WSJ examples

Cost of developing a new drug increases to about $1.7 billion (Dec. 8, 2003)

Pfizer ‗Youth Pill‘ Ate Up $71 Million Before It Flopped (May 2, 2002)

Staged Invention

Pharmaceuticals (e.g., Discovery, Preclinical, Clinical trial- phase I, Clinical

trial- phase II, Clinical trial- phase III, FDA filing and review

Sequential Innovation

Industrial Products (e.g., Aircraft and Automobile Frames); Consumer

Products (e.g., Software versions; golf clubs); Manufacturing Processes (e.g.,

semiconductor lithography)

Organization

Equity stakes as options on acquisition


Simulation

Black-Scholes Option Calculator

Calculator inputs Option Analog Black Scholes Calculations

PV of Current Opportunity (S) $6,000,000 PV of StockPresent Value

-$8,000,000

Dividend Yield (q) 0.0% Call Option Value $1,237,684

Required Investment (X) $14,000,000 Strike / Exercise Price d1 -0.1273

Risk-free rate (Rf) 5.50% d2 -1.1273

Time to expiration (T) 4.00 N'(d1) 0.3957

Volatility (Sigma) 50.0%

Some initial (relatively small) investment on a clearly defined underlying asset

whose value changes over time …

Provide payoffs contingent on a specific observable event …

That create advantage due to some restriction on competition in the event of the

contingency (e.g., preferential access)


Generate insights

If real option logic provides a means to consider the evolution

of competitive advantage …

Then it may provide insight into fundamental strategy

questions

How does (sustainable) competitive advantage arise?

How do manager‘s affect the formation of (sustainable)

competitive advantage?

When might resource allocation and organization

decisions facilitate adaptation?


Example: Linking growth & deferal options

logic w/ early and late mover advantages

Early Mover Advantages

Technological leadership

Leaning, Patent, R&D races

Pre-emption of scarce

assets

Key Inputs, Product /

Geographic niches

Switching costs and

Quality risks

Late Mover Advantages

Free Rider effects

Spillovers, educated

consumers

Resolution of technical /

market uncertainty

Industry standards are

established

Incumbent inertia

Pioneer may get bogged

down in bureaucracy

See Lieberman & Montgomery (1988, 1998)


Example: Linking deferral & growth options

logic w/ early and late mover advantages

A simple model of technology

adoption considers two decision

points

Whether and when to adopt a

current technology.

Whether to adopt a future

technology.

Compulsive

Buy & Hold

LaggardInvest in initial opportunity

Time Period 1 Time Period 2

Leapfrog

Investment Strategy

Invest in follow-on

opportunity

Bystander

See Leiblein & Ziedonis (2007);

Grenadier & Weiss (1997)

Generate insights: Deferral & growth

options differ on object of uncertainty

Deferral Option opportunity cost of irreversibly

investing in current project.

Growth Option value of future (linked) projects

Discuss factors that might affect the value of an

embedded deferral or growth option opportunity cost is a function of attractiveness of alternative projects

if under a budget constraint.

Value of future project implies mechanisms are in place (proprietary

learning, contractual agreements) that insure any advantage vis-à-vis

the follow-on opportunity are not competed away when uncertainty is

favorably resolved.


Using Simulation to Generate Insight

Deferral & Growth Option Calculator

Calculator inputs Adjust Values Black Scholes Calculations

PV of Current

Opportunity

(SCurr) $6,000,000

PV of Current

-$4,000,000 d1 0.2092

Required

Investment

(XCurr) $10,000,000

Deferral Option

Value $1,775,477 d2 -0.7908

Risk-free rate

(RfCurr) 5.50% N'(d1) 0.3903

Time to expiration

(TCurr) 4.00

Volatility

(SigmaCurr) 50.0%

Opportunity cost sim (u, sigma, normal)

Model as a random draw of a project w/ NPV x= sigma = . Firms in more

munificent environments get more or better draws; firms with fewer

resources and more constraints.

Preemption

(Kulatilak & Perotti)sim (0,1, uniform)

Number of Rivals (and weaker appropriability regime) diminish SCurr {e.g.,

SCurrAdj=SCurr*(1-Preemption)


Using Simulation to Generate Insight

Deferral & Growth Option Calculator


PV of Future

Opportunity (SFut) $8,000,000PV of Future

-$4,000,000 d1 0.3145

Required

Investment (XFut) $12,000,000

Growth Option

Value $2,613,447 d2 -0.6855

Risk-free rate

(RfFut) 5.50% N'(d1) 0.3797

Time to expiration

(TFut) 4.00

<-- raise to see greater "volatility"

effect

Volatility

(SigmaFut) 50.0%

Claim on Future

Technology sim (0,1, uniform)

Strength of claim (proprietary learning; explicit claim, appropriability

regime) directly affects SFut {e.g., SFutAdj=SFut*Regime)

Holding Costs sim (0,1, uniform)Holding Costs raise XFut (e.g., XFutAdj=XFut*HoldingCost)

Standard Setting Externality (Lin &

Kulatilaka)

Positive externalities may encourage early investment by increasing Sf and

decreasing Sd


Using Simulation to Generate InsightDeferral & Growth Option Calculator


PV of Current

Opportunity

(SCurrComb) $6,000,000

PV of Future

Opportunity

(SFutComb) $8,000,000

Required

Investment …

Risk Free Rate

(RfComb) 5.50%

Sum (Defer,

Growth) $4,388,924

Time to expiration

(TComb) 4.00Max Min(Defer,

Growth) OV $2,102,196 d1comb 1.1214

Corr(SigmaCurr,

SigmaFut) -0.10 Setup Max(Min(Vdef, Vgrowth)-F,0) d2comb -0.9762

Volatility

(SigmaComb) 110.00%Max Max(Defer,

Growth) OV $2,286,728 N(d1comb) 0.8689

Setup Max(Max(Vdef, Vgrowth)-F,0) N(d2comb) 0.1645Covariance Current

& Future

Opportunity sim (-1,0,1, uniform)


A Few Big Picture Points

Disequilibrium & Discomfort to open students

to possibility of different thinking.

Humor to suggest concept & simulation to

illustrate principles

Case examples and illustrations to consider

how joining options with other theory may

generate insight


Any Questions?

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