Risk Analysis

Some Useful Tools1 10/16/2002 Eastman Kodak Company, 2002

Risk Analysis for Strategic Decisions

Some Useful Tools

Jerry E. Boger

Eastman Kodak Company

October 16, 2002

PMI – Rochester Chapter

Risk Analysis

Some Useful Tools2 10/16/2002 Eastman Kodak Company, 2002

Risks in Projects

Technological / Market Scenario

Competition Analysis

RoughProject

Profitability

Objectives &Constraints

Planning

Project Requirements

Milestone Zero

Organizing The Team

Kickoff Session

Structuring Project

Activities

Objectives &Constraints

Analysis

Activity PathSequencing

ActivityPlanning

MilestonesPlan

Project Costing

ResourceAvailability

Milestone One

Feasibil i ty

Preparat ion

“Strategic” Risk Analysis

“Operational” Risk Analysis

Source: Report of EIRMA Working Group 53

Risk Analysis

Some Useful Tools3 10/16/2002 Eastman Kodak Company, 2002

What is an Influence Diagram?

• A decomposition of a “big uncertainty,” like, “How much money will this project make the company,” into its fundamental uncertainty components

• The outcome of the “influencing” element “Revenue” changes the probability distribution of the “influenced” uncertainty “Earnings” in some significant way

Revenue

Earnings

Costs

Unit Sales

Price

Risk Analysis

Some Useful Tools4 10/16/2002 Eastman Kodak Company, 2002

Example of a Media TechnologyDecision Influence Diagram

NPV

Earnings

Capital

R&D Expenses

PaperUMC

Industry Volume

Paper & Chem Margin

% Kodak Owned

Kodak P/F Earnings

P/FUMC

MarketPotential

MarketShare

Price to Consumer

Performance

Indep. P/F Accept.

Competitive Offerings

P/F Capital Req.

Price to P/F

Manuf'gCapital

P/F Capital

Media Earnings

Advertising

Time toMarket

P/F LaborProcessControl

New Steps

CoatingSpeed

# of Passes

License / Royalty

Risk Analysis

Some Useful Tools5 10/16/2002 Eastman Kodak Company, 2002

Process Steps for Building an Influence Diagram

• Start with the “big uncertainty” on the right side of the page• Work on one uncertainty element at a time; find all the

direct influences for that uncertainty before moving on• Do not show influences that are not uncertainties (knowns)• Define each uncertainty as a question that can be answered

by a number (specify the units), yes or no, or a well-defined multiple choice

• Like peeling an onion, complete one “shell” or level of influencing elements before moving deeper

• Stop when you have enough detail to directly assess the uncertainty elements

Risk Analysis

Some Useful Tools6 10/16/2002 Eastman Kodak Company, 2002

Process Questions

Use the “clairvoyant questions”• To discover the first influence into a target uncertainty,

ask, “What element (uncertainty or decision) would you most want to know to reduce (or eliminate) the uncertainty in the target in question?”

• To discover subsequent influences on that target uncertainty, ask, “If I told you the answer to all the influences identified so far, what other element (if any) would you most want to know to reduce the uncertainty in the target uncertainty?”

Risk Analysis

Some Useful Tools7 10/16/2002 Eastman Kodak Company, 2002

Example from a Technology Decision

• The full tree has a branch for every decision-outcome combination

• Each branch has a probability and an outcome value

This Skeleton Tree

Option Technique Degree of Success

Results in This Full Tree(continued for two more pages)

.

.

.

Risk Analysis

Some Useful Tools8 10/16/2002 Eastman Kodak Company, 2002

Influence Diagram for “Don’t Delay”

Revenue

Cost

Price/Unit

Unit Volume

Feature Setat Launch

Key ComponentPrice Escalation

UMC

CU

U

NPV

Market Share

Market SizeU

COGS

Risk Analysis

Some Useful Tools9 10/16/2002 Eastman Kodak Company, 2002

Example Conceptual Tree for “Commercialization Example”

Payoff is 6 year NPV

Features at launch

Price and share

On Time

Component price

escalationSG&A

Market size

Don’t Delay

Add technical resources

Delay launch 1 year

Abandon program

De-featured

Full

Price and share

1 Year Late

Component price

escalationSG&A

Market size

Risk Analysis

Some Useful Tools10 10/16/2002 Eastman Kodak Company, 2002

F10 F50 F90

• We can characterize uncertainty by estimating three points on the probability distribution: f10, f90, and f50

• The range from f10 to f90 captures 80% of the probability

• By using these points in a sensitivity analysis, the analysis is calibrated for an equal range of probability for each uncertainty

• This is in contrast to a traditional “what-if” analysis using arbitrary ranges of variation

• We can see which uncertainties have the most impact on the uncertainty of the “big uncertainty”

Risk Analysis

Some Useful Tools11 10/16/2002 Eastman Kodak Company, 2002

<== Type Name of 1st Alternative Here

Variable Name

F10 Variable

Value

F50 Variable

Value

F90 Variable

Value F10 Payoff F50 Payoff F90 Payoff Range

1 Features Defeat. Full -6.560951075 1.637795057 1.6378 8.1987510752 Price/Share Poor Anticip Favor -8.264185535 1.637795057 9.895658888 18.159844423 Market Size 80% 100% 130% -0.501100967 1.637795057 4.846139094 5.3472400624 UMC Escal 100% 120% 150% 6.02725387 1.637795057 -4.946393162 10.973647035 SADA 80% 100% 130% 2.165471629 1.637795057 0.846280199 1.319191436

Don't Delay

<== Type Name of 2nd Alternative Here

Variable Name

F10 Variable

Value

F50 Variable

Value

F90 Variable

Value F10 Payoff F50 Payoff F90 Payoff Range

1 Price/Share Poor Anticip Favor -9.082205772 -2.374529692 3.614403533 12.696609312 Market Size 80% 100% 130% -3.704241368 -2.374529692 -0.379962177 3.3242791913 UMC Escal 100% 120% 150% 1.069878092 -2.374529692 -7.541141367 8.6110194594 SADA 80% 100% 130% -1.736758359 -2.374529692 -3.331186691 1.59442833256

Delay 1 Year

Example of data input to a sensitivity analysis spreadsheet• A generic sensitivity analysis workbook can be used• Use a custom model to calculate payoffs then insert the data into this spreadsheet

Risk Analysis

Some Useful Tools12 10/16/2002 Eastman Kodak Company, 2002

Poor FavorPrice/Share-8.3 9.9

1.5 1UMC Escal-4.9 6.0

Defeat. Features -6.6 1.6

0.8 1.3Market Size-0.5 4.8

1.3 0.8SADA0.8 2.2

Poor FavorPrice/Share-9.1 3.6

1.5 1UMC Escal-7.5 1.1

0.8 1.3Market Size-3.7 -0.4

1.3 0.8SADA-3.3 -1.7

Commercialization Quandry

1.63779505733088f50 of Don't Delay

Red indicates Payoff Value

Blue indicates Uncertainty Outcome

-2.37

f50 of Delay 1 Year

Red indicates Payoff Value

Blue indicates Uncertainty Outcome

Don't Delay

Delay 1 Year

After entering the data and running the macros, a “Tornado Diagram” is plotted

Risk Analysis

Some Useful Tools13 10/16/2002 Eastman Kodak Company, 2002

For problems with up to five uncertainties, Gary Brauer at Kodak has written Microsoft Excelsoftware macros for analysis• Each decision alternative must be treated as a separate tree• You choose the appropriate tree structure, input your data, and link a payoff calculation• For problems that don’t fit the structure choices, special software such as DPL may be used, but a large number of cases do fit

Risk Analysis

Some Useful Tools14 10/16/2002 Eastman Kodak Company, 2002

Don't Delay

ScenarioIndexUMC Escalation (% of base) Market Size (% of base) Features At Launch Price / Share Branch Branch

# Outcome Prob Outcome Prob Outcome Prob Outcome Prob Prob Payoff

1 1 0.3 0.8 0.3 Full 0.7 FF-Poor 0.30 0.0189 -7.0180586212 1 0.3 0.8 0.3 Full 0.7 FF-Anticipated 0.40 0.0252 3.0104660833 1 0.3 0.8 0.3 Full 0.7 FF-Favorable 0.30 0.0189 9.9679138524 1 0.3 0.8 0.3 1.00 #N/A5 1 0.3 0.8 0.3 #N/A6 1 0.3 0.8 0.3 #N/A7 1 0.3 0.8 0.3 Defeatured 0.3 De-Poor 0.30 0.0081 -8.5733029888 1 0.3 0.8 0.3 Defeatured 0.3 De-Anticipated 0.40 0.0108 -4.9531576439 1 0.3 0.8 0.3 Defeatured 0.3 De-Favorable 0.30 0.0081 1.148078203

10 1 0.3 1 0.4 Full 0.7 FF-Poor 0.3 0.0252 -6.5084020111 1 0.3 1 0.4 Full 0.7 FF-Anticipated 0.4 0.0336 6.0272538712 1 0.3 1 0.4 Full 0.7 FF-Favorable 0.3 0.0252 14.7240635813 1 0.3 1 0.4 1 #N/A14 1 0.3 1 0.4 #N/A15 1 0.3 1 0.4 #N/A16 1 0.3 1 0.4 Defeatured 0.3 De-Poor 0.3 0.0108 -8.45245746817 1 0.3 1 0.4 Defeatured 0.3 De-Anticipated 0.4 0.0144 -3.92727578718 1 0.3 1 0.4 Defeatured 0.3 De-Favorable 0.3 0.0108 3.69926902119 1 0.3 1.3 0.3 Full 0.7 FF-Poor 0.3 0.0189 -5.74391709320 1 0.3 1.3 0.3 Full 0.7 FF-Anticipated 0.4 0.0252 10.5524355521 1 0.3 1.3 0.3 Full 0.7 FF-Favorable 0.3 0.0189 21.8582881822 1 0.3 1.3 0.3 1 #N/A23 1 0.3 1.3 0.3 #N/A24 1 0.3 1.3 0.3 #N/A25 1 0.3 1.3 0.3 Defeatured 0.3 De-Poor 0.3 0.0081 -8.27118918826 1 0.3 1.3 0.3 Defeatured 0.3 De-Anticipated 0.4 0.0108 -2.38845300327 1 0.3 1.3 0.3 Defeatured 0.3 De-Favorable 0.3 0.0081 7.52605524728 1.2 0.4 0.8 0.3 Full 0.7 FF-Poor 0.3 0.0252 -8.42268544129 1.2 0.4 0.8 0.3 Full 0.7 FF-Anticipated 0.4 0.0336 -0.50110096730 1.2 0.4 0.8 0.3 Full 0.7 FF-Favorable 0.3 0.0252 6.105190097

The Excel software macro creates the full tree behind the problem distribution

Risk Analysis

Some Useful Tools15 10/16/2002 Eastman Kodak Company, 2002

Scenario Inputs and PayoffInput Area

Scenario Scenario Payoff = -6.809UMC Escalation (% of base) Outcome 1.5 1 1.2 1.5

Market Size (% of base) Outcome 1.3 0.8 1 1.3

Features At Launch Outcome Defeatured Full 0 DefeaturedPrice / Share Outcome De-Favorable

Candidate Values

You have to develop a model that can be linked to this spreadsheet and provide a payoff value for each scenario, i.e., for each branch of the tree

Cumulative Probability Plot

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

-15 -10 -5 0 5 10 15 20 25

Payoff Axis

Cu

mu

lati

ve P

rob

abili

ty

Next, a macro runs the model, fills out the tree, and graphs the payoff