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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