Richard de Neufville MIT Technology and Policy Program Slide ...

Richard de Neufville MIT Technology and Policy Program Slide 1 of 23

DYNAMIC STRATEGIC PLANNING

USING REAL OPTIONS

TO IMPROVE

SYSTEMS DESIGN

Richard de Neufville MIT Technology and Policy Program Slide 2 of 23

CONCLUSIONS

“OPTIONS THINKING” WILL DEEPLY CHANGE THE WAY DESIGNERS THINK ABOUT SYSTEMS DESIGN

“OPTIONS ANALYSIS” WILL ENABLE DESIGNERS, REALLY FOR FIRST TIME, TO VALUE FLEXIBILITY CORRECTLY AND THUS IDENTIFY WHAT KINDTO INSERT IN THEIR CREATIONS

Richard de Neufville MIT Technology and Policy Program Slide 3 of 23

ORGANIZATION

PART 1 -- WHAT IS THE POSITION OF OPTIONS ANALYSIS IN SYSTEMS DESIGN?

PART 2 -- WHAT ARE ITS IMPLICATIONS FOR PRACTICE?

Richard de Neufville MIT Technology and Policy Program Slide 4 of 23

A HISTORICAL PERSPECTIVE “SYSTEMS ANALYSIS”, “SYSTEMS

DESIGN” A PHENOMENON SINCE 1950s

DUE TO NEW TOOLS (COMPUTERS) AND METHODS (OPTIMIZATION, ETC...)

EARLIER, SYSTEMS IMPLEMENTED WITHOUT SYSTEMS ANALYSIS

SYSTEM DIVIDED INTO INDEPENDENT BITS BRIDGE JOINTS; HIGHWAY LENGTHS

Richard de Neufville MIT Technology and Policy Program Slide 5 of 23

3 DEVELOPMENT PHASES OF SYSTEMS ANALYSIS / DESIGN

OPTIMIZATION -- PRIMARY TO 1970s

DECISION ANALYSIS -- PRIMARY 1970s TO 1990s

“REAL” OPTIONS ANALYSIS --2000s

Richard de Neufville MIT Technology and Policy Program Slide 6 of 23

OPTIMIZATION POWERFUL ANALYSIS OF

Z = f(aX) Subject to g(cX) < B

EXCELLENT ON IMPORTANT PROBLEMS

BUT: LIMITED SENSITIVITY ANALYSIS -- ASSUMES PARAMETERS KNOWN

UNSUITED FOR UNCERTAIN CONTEXT

Richard de Neufville MIT Technology and Policy Program Slide 7 of 23

UNCERTAINTY IS FUNDAMENTAL

“THE FORECAST IS ALWAYS WRONG” -- AMPLY DOCUMENTED, ALL FIELDS

ANY SYSTEM WILL HAVE TO PERFORM IN BROAD RANGE OF CIRCUMSTANCES

UNCERTAINTIES ARE: TECHNICAL ECONOMIC (PRICES, ECONOMIC CYCLE…) INDUSTRIAL (STRUCTURE OF COMPETITION) POLITICAL (REGULATORY, LEGAL…) ETC...

Richard de Neufville MIT Technology and Policy Program Slide 8 of 23

DECISION ANALYSIS FOCUS ON SEQUENCES OF CHOICES,

FROM PRE-DETERMINED POSSIBILITIES

NOTABLE LESSONS FLEXIBILITY HAS VALUE SECOND-BEST SOLUTIONS OPTIMAL

HOWEVER, NO PROCESS FOR DETERMINING DESIRABLE POSSIBILITIES RISK-ADJUSTED DISCOUNTED CASH FLOW

Richard de Neufville MIT Technology and Policy Program Slide 9 of 23

RISK-ADJUSTED DISCOUNT RATE

HIGHER RATE FOR HIGHER RISK (CAPM CAPITAL ADJUSTED PRICING MODEL REFLECTS RISK AVERSION)

THROUGH TIME, ACCORDING TO EVENTS, RISK LEVEL CHANGES

NO SINGLE DISCOUNT RATE APPLIES

DECISION ANALYSIS WITH CONSTANT DISCOUNT RATE IS INACCURATE

Richard de Neufville MIT Technology and Policy Program Slide 10 of 23

OPTIONS ANALYSIS PROVIDES CANONICAL MEANS TO

ACCOUNT FOR VARYING RISK (BLACK-SCHOLES, WIENER PROCESS)

BOTH TECHNICAL AND MARKET RISK

NOBEL PRIZE WINNING EFFORT

FOCUS ON PRICING OF FLEXIBILITY, OF “OPTIONS”

Richard de Neufville MIT Technology and Policy Program Slide 11 of 23

WHAT IS AN OPTION? A PRECISE MEANING -- NOT “CHOICE”

OPTION IS “RIGHT, NOT OBLIGATION” TO TAKE AN ACTION, A CAPABILITY ACQUIRED AT SOME EFFORT

CALL CONTRACT TO BUY STOCK AT $X CONTRACT TO BUY EXPANSION SITE

“REAL” OPTIONS ARE PHYSICAL R&D TO PERMIT PRODUCT LAUNCH DUAL-FUEL BURNERS FOR POWER PLANTS

Richard de Neufville MIT Technology and Policy Program Slide 12 of 23

“REAL” OPTIONS ANALYSIS IDENTIFIES VALUE OF DESIGN

ELEMENTS PROVIDING FLEXIBILTY

GIVES DESIGNERS ANALYTIC BASIS FOR DESIGN CHOICES

DIFFERS FROM RELIABILITY ANALYSIS -- INCLUDES MARKET RISKS

Richard de Neufville MIT Technology and Policy Program Slide 13 of 23

EXAMPLE: VALUE OF R&D? TRADITIONAL ANALYSIS

WHAT IS EXPECTED VALUE OF EFFORT

OPTIONS ANALYSIS R&D IS AN OPTION CAN BE EXERCISED IF MARKET IS POSITIVE IF MARKET OR TECHNOLOGY POOR, DROP BECAUSE POOR OUTCOMES DROPPED VALUE AS OPTION > EXPECTED VALUE

Richard de Neufville MIT Technology and Policy Program Slide 14 of 23

PRACTICAL IMPLICATIONS GREATER VALUE, THUS EMPHASIS ON

FEATURES NOT TRADITIONALLY CONSIDERED AS OPTIONS

RESEARCH, PRODUCT DEVELOPMENT DESIGN CHOICES (FACILITY SIZE) DESIGN CONFIGURATION (INTERNET) DESIGN OPERATION (SHARED FACILITIES)

OPTIONS “THINKING” EXPLICIT FOCUS ON FLEXIBILITY

Richard de Neufville MIT Technology and Policy Program Slide 15 of 23

EXAMPLE -- PRODUCT DEVELOPMENT AT FORD

R&D INVESTMENTS AS OPTIONS ON THE POSSIBILITY OF A NEW

PRODUCT, NOT PRODUCT DECISIONS, R&D IS AROUND 20% MORE VALUABLE (Neely)

BALLARD, FUEL CELL VEHICLE NESTED OPTIONS, ON MARKETS FOR

VEHICLES AND POWER SOURCES INVESTMENT GOOD -- EVEN IF ON AVERAGE

FC CAR NOT REASONABLE (Oueslati)

Richard de Neufville MIT Technology and Policy Program Slide 16 of 23

EXAMPLE -- FLEXIBLE PRODUCTION

DUAL-FUEL POWER PLANT (Kulatilaka) DEVICES TO PERMIIT OIL/GAS SWITCH COST VALUE IS USE OF CHEAPER FUEL DEPENDS ON FUTURE MARKETS

CAR MANUFACTURE (Toyota, Komatsu) AIRPORT DESIGN (Shared Gates)

ENABLING FLEXIBLE PRODUCTION => TRACKING OF VOLATILE DEMANDS

Richard de Neufville MIT Technology and Policy Program Slide 17 of 23

EXAMPLE -- NATURAL RESOURCE EXTRACTION

OIL PLATFORMS (Hibernia / Smets) TRADITIONAL: DESIGN TO TARGET

PRODUCTION RATE OPTIONS ANALYSIS: LARGER SIZES GIVE

OPTION ON FASTER EXTRACTION

DESIGN OF MINE DEVELOPMENT (Peru) EXPLORATION, INFRASTRUCTURE PROVIDE

OPTION ON EXTRACTION WHAT TO BUILD, WHEN?

Richard de Neufville MIT Technology and Policy Program Slide 18 of 23

EXAMPLE -- COMPUTER ARCHITECTURE

MODULARITY (Baldwin and Clark) HOW MANY MODULES? COST VS. VALUE OF FLEXIBILITY

LOCATION OF NETWORK INTELLIGENCE CENTRALLY -- AS IN TELEPHONE COMPANY AT EDGES -- EXTRA EXPENSE CREATES

OPTION ON INNOVATION -- USERS CAN EASILY CHANGE DISTRIBUTED DEVICES

Richard de Neufville MIT Technology and Policy Program Slide 19 of 23

OPTIONS THINKING… IF OPTIONS ANALYSIS IMPRACTICAL?

MARKETS POORLY UNDERSTOOD HISTORICAL RECORDS ABSENT

OPTIONS THINKING USE DECISION ANALYSIS AS A PROXY EXTENSIVE SPREADSHEET ANALYSIS EXAMPLE -- KODAK (See Faulker)

Richard de Neufville MIT Technology and Policy Program Slide 20 of 23

CONCLUSIONS

“OPTIONS THINKING” WILL DEEPLY CHANGE THE WAY DESIGNERS THINK ABOUT SYSTEMS DESIGN

“OPTIONS ANALYSIS” WILL ENABLE DESIGNERS, REALLY FOR FIRST TIME, TO VALUE FLEXIBILITY CORRECTLY AND THUS IDENTIFY WHAT KINDTO INSERT IN THEIR CREATIONS

Richard de Neufville MIT Technology and Policy Program Slide 21 of 23

REFERENCES -- theory Trigeorgis, L. (1996) Real Options,

Managerial Flexibility and Strategy in Resource Allocation, MIT Press, Cambridge, MA.

McDonald, R. (2000) “Real Options and Rules of Thumb in Capital Budgeting,” in Project Flexibility, Agency and Competition, Brennan and Trigeorgis, Oxford Univ. Press, Oxford, UK, pp. 13-33

Richard de Neufville MIT Technology and Policy Program Slide 22 of 23

REFERENCES -- applications Amran & Kulatilaka (1999) Real Options,

Managing Strategic Investment in an Uncertain World, Harvard Business Sch.

Faulkner T.W. (1996) "Applying Options Thinking to R & D Valuation," Research Technology Management, May, 50-56.

Nichols, N. (1994) "Scientific Management at Merck: An Interview with Judy Lewent," Harvard Business Review, Jan. 89-99.

Baldwin and Clark (2000) Design Rules, the power of modularity, MIT Press.

Richard de Neufville MIT Technology and Policy Program Slide 23 of 23

RECENT THESES NEELY -- Ph.D. -- Practical Method for

Valuing “Real Options” Applied to Research Projects at Ford (with J. Clark, D. Lessard)

OUESLATI -- Method for Valuing Real Options for Multiple Markets

Applied to Ford’s Investment in Fuel Cells SMETS -- Application to Hibernia Platform