Creating and Valuing Flexibility in SystemsArchitecting: Transforming Uncertaintiesinto Opportunities Using

Real Options Analysis

ABSTRACT

Flexibility is one of the strategies to ensure the value delivery

of a System of Systems (SoS) during its life cycle in light of the

changing external environment. This article discusses the notion

of ‘Real Options Thinking’ to create flexibility and ‘Real Options

Valuation’ to value flexibility when designing an SoS to manage

significant uncertainties. We propose a ‘Real Options Analysis’

framework consisting of the dual parts of ‘Real Options

Thinking’ (akin to good management intuition) and ‘Real

Options Valuation’ (akin to stochastic optimisation) to promote

a common ‘options language', enrich vocabulary, sharpen our

thinking and guide quantitative analysis when managing

technical projects. Adopting ‘Real Options Thinking’ and ‘Real

Options Valuation’ will increase our capacity to identify, create

and secure both technical and managerial options through

deliberate choice, in a cost-effective and timely manner. It will

also increase our tolerance of uncertainties and empower us

to actively manage uncertainties to create opportunities and

reduce risks.

Angela Ho Wei Ling

Ng Chu Ngah

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Creating and Valuing Flexibility inSystems Architecting: Transforming Uncertaintiesinto Opportunities Using

Real Options Analysis

“Uncertainties are a source of risks andopportunities” (de Neufville, 2004).

Traditionally, for large-scale complex systems,uncertainties are treated as risks and aretherefore undesirable. The approach towardsuncertainties is consequently to manage themthrough risk mitigation. However, ‘Real OptionsThinking’ introduces a paradigm shift in lookingat uncertainties as sources of opportunities aswell. This paradigm shift in thinking isessentially the act of capitalising on theopportunities embedded in uncertainties whilelimiting the extent of risks involved. Thisviewpoint is critical as most current engineeringpractices are conservative and may not exploitthe potential upsides of uncertainty. We wouldbe able to perform better if we can develop adynamic strategy in anticipation ofuncertainties arising from external factors.Through an SoS architecture that can evolveand adapt to a changing environment, we willincrease our potential and ability to capitaliseon emerging opportunities throughuncertainties. Real Options Analysis is thus anActive Uncertainty Management technique asopposed to Passive Uncertainty Managementtechniques like risk management.

FLEXIBILITY IN SOS ARCHITECTING AS A STRATEGY TO ENSURE SOS VALUE DELIVERY

Systems architecting is an approach to designand build effective and efficient SoS. The SoSarchitecture "provides the structure or skeletonof the system, as well as the principles, rulesand guidelines governing the system design,creation and evolution. It also provides thebroad framework, system level constraints aswell as the relationship for the substructuresand modules of the system. It determines theoption available for future development." (Tan,Yeoh, Pang & Sim, 2006). In order to preservevalue over its life cycle, an SoS has to be ableto handle dynamic complexity and a changingoperational environment.

INTRODUCTION –UNCERTAINTIES ASBOTH RISKS AND OPPORTUNITIES

In the context of Singapore defence, our reallife complex systems are invariably Systems ofSystems (SoS) which always operate in uncertainand dynamic environments. Typically, whilesystems architects design an SoS, programmemanagers develop an SoS that will operate inan uncertain and dynamic environment. Thedrivers of uncertainties can be both externaland internal. External factors such as emergentthreats, new operational concepts, disruptivetechnologies and shifts in supplier industrystructure are largely beyond our control. Onthe other hand, internal factors come fromuncertainties in the programme delivery andare generally well managed by current projectmanagement practices. The approaches andmethods to deal with uncertainties arisingfrom external factors are not well understoodtoday. In addition, there is an increasing needto design and deliver SoS in fast-changingenvironments. Thus, it is essential to anticipatethese known unknowns and, as far as possible,prepare for this class of uncertainties.

History shows that we are poor forecasters ofexact trends. Over-confident forecasts like“640kb ought to be enough for anyone” fromBill Gates underestimated the uncertainty indemand and technology. Designing an SoS tospecific trends may turn out to be costly as asingle ‘unknown unknown’ can throw off ourpredictions and ability to react in the future.We would be better off predicting a range ofscenarios and developing the feasible solutionspace containing all flexible on-demandresponses that we can choose to adapt as newinformation becomes available with time,rather than designing our SoS to forecastedtrends.

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Flexibility is one of the key strategies to copewith environmental changes and dynamiccomplexity, and Real Options Analysis is oneway to tangibly create and value flexibility inSoS. A working definition of ‘flexibility’ is asfollows:

An SoS is flexible if we have the freedom tomake our choices during life cycle operationto cope with the large external changes.Flexibility can be created and valued in systemsarchitecting and designed using the RealOptions Analysis framework.

Breakthrough engineering solutions have acommon thread of incorporating flexibledesigns to cater to wide-ranging scenarios.These flexible designs are also known as‘options’ and people have been practising ‘realoptions thinking’ even though the languageof options may not be as ubiquitous. A goodexample is the flagship UndergroundAmmunition Facility (UAF) project, managedby DSTA, for high-density ammunition storage.DSTA has invested in the research anddevelopment (R&D) on protective infrastructureand related technologies for years to createoptions for MINDEF to address various defenceneeds. When the new challenge of creatingnew ammunition storage for the SAF arose inthe face of tremendous pressure to free upland for national development, DSTA was readyto exercise the option and embark on thebuilding of our first UAF. Apart from derivingdirect value from the options created throughR&D, this effort also generated emergentbenefits by allowing DSTA specialists to setnew safety standards, including obtaining theNorth Atlantic Treaty Organisation’s acceptanceand becoming a leader in the field.

Flexibility is the life cycle propertythat allows an SoS to endure sets ofchanges with ease. It is an active andlargely external approach to managingchange (adapted from Moses, 2003).

DEFINING REAL OPTIONS

The science of options analysis began withfinancial options. A financial option gives onethe right but not the obligation to buy an assetlater at a pre-determined price. This meansone can be better off during good times andhave a fallback position during bad times.Should the value of the asset increase, one canprofit from it. Should the value of the assetdrop, one’s losses are limited to the optionpremium. Black and Scholes (1973) developedthe theory of pricing financial optionswhile/and considering uncertainty, decisionspaces and time in the equation. Option pricinghas led to flexible financial structures, createda market of options transactions and reducedthe volatility of the commodities.

A real option is the extension of the idea tovalue the flexibility of management decisionson a real or tangible asset. Asset owners needto know the price of their productive asset todetermine its economic value. Since an assetcan be put into creative use in multiple waysand the management has the flexibility tocontrol how much resources to invest orwithhold from it in the future, depending onthe future demand – the value of the assetdepends on their own possible courses ofaction. This viewpoint changed the perspectiveof asset valuation from historical cost valuationto prospective contingent valuation. The valueis contingent on the future possible actions ofthe management. Today, real options analysisis being accepted as a conceptual and analyticaltool to support strategic decision making underuncertainty by extending existing techniquesof Net Present Value valuation. It is a bridgingtool for strategic and financial decision makers.

It is important to distinguish an ’option’ fromour common understanding of it as an‘alternative’ or a ‘choice’. An ‘option’ is notanother ‘alternative’ or ’choice’. Instead, itrefers to our right, and not the obligation, to

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take an action (i.e. exercise it) at some pointin time with an upfront cost. An option is asecured choice that makes it available ondemand.

A simple example of a real option inengineering design is the option to ‘expand’(the action) in the design of the bridge acrossthe Tagus River in Lisbon, Portugal. In the1970s, the first bridge was designed forvehicular traffic when there was no demandfor commuter railway system. However, thegovernment insisted that the bridge structurebe strong enough to carry rail traffic. Twentyyears later, there were changes in technologiesand in rail demand (pre-determined time toexercise options) and the government was ableto exercise its option (option to expand) andextend rail service on the bridge. There wasan upfront cost for this option – the bridgehad to be reinforced when it was built (pre-determined cost). However, when theenvironment changed in the 1990s, Portugalwas able to take advantage of this opportunityto exercise the option that it had built into thetechnical design of the bridge 20 years earlier(Gesner & Jardim, 1998).

At face value, we may view such an exampleas simplistic. We caution readers to checkagainst having any hindsight bias. We shouldreflect on the uncertainties and constraintsthat the decision makers would have faced inthe context of their time. Additionally, thedecision equation will be more complicatedwhen there are several sources of uncertaintyand only a few options for judgement.

A real option is a technical or managementchoice that we secure today at a

pre-determined cost for a pre-determinedtime to have the right to exercise when

needed without any obligation(de Neufville, 2001).

REAL OPTIONS TYPES

A flexible SoS must have both technical andmanagerial options built into the architecturethat can be exercised when needed. Both ofthese options are classified as ‘Real Options’in our engineering SoS and are different fromthe Acquisition Options in procurement thatwe are more familiar with.

Technical Options are options that are createdin the design of the technical SoS itself.Technical Options are called Real Options inSoS (de Neufville, 2002) as they are embeddedin the technical design of the SoS architecture.Identifying technical options within the SoSwould require a good understanding of theSoS and modular architecture. A classic technicaloption is the design of a dual operating mode.For example, straight stretches of roads canbe designed and built so that we can use themas runways for aircraft. However, this meanswe have to design the roads with somelimitations for transport use while ensuringheavier load requirements and removablebarriers.

Managerial Options are options that arecreated to manage the process of SoSdevelopment and operation. They treattechnology as a ‘black box’ and are essentiallyfinancial options taken on technical projectsand SoS. Managerial options are the RealOptions on SoS and are enabled by thetechnical options, contractual obligations ofsuppliers as well as financial and resourcecontrol over the process of SoS developmentand operations. Classic managerial optionsinclude options to defer a decision, alter theoperating scale of the SoS or abandon somesub-initiatives. Back to the road-runwayexample, the management has the option touse roads as aircraft launch pads if enabled bybuilt-in technical options.

Real Options allow the SoS to adapt tochanging scenarios over time. This flexibilityincreases our ability to capitalise on upside

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opportunities and to limit our exposure todownside risks. Flexibility that is embedded inthe technical design and management of SoSis important to improve the operational andtechnical effectiveness. The greater theuncertainty, the higher the value of each realoption.

Both technical and managerial options comeat a cost known as the ‘option premium’. Theoption premium can be seen in two ways: asthe maximum price we should pay to have themanagerial and technical flexibility, or as theprice of our uncertainty. Certainly, we will notpay an option price that is higher than the costof the uncertainty. When we have a bundle ofoptions available across several review pointsin future, we can use a quantitative way todecide how much flexibility to incorporate intothe SoS design and develop the roadmap ofdecisions.

Real options in SoS are thus an additionaltechnique that can be used to value theflexibility of technical choices on SoS design.It is impossible to execute many of themanagement choices to expand capability orswitch operating modes unless the initial design

had the benefit of forethought. Securingtechnical options is costly and is subject tomuch inquiry because they will not be perceivedas required, unless we measure the cost againstthe probable scenarios.

LANGUAGE OF REAL OPTIONS THINKING

Technical and managerial options can bebroadly classified by whether they reducedownside exposure to risks, allow status quoor leverage upside opportunities, dependingon how uncertainties evolve. If uncertaintywas deemed to have a negative impact,exercising real options like the option todownsize or mothball would reduce exposureto risk. On the other hand, if the uncertaintyturned out favourably, exercising real optionsthat increase the exposure to theseopportunities would reap a greater return.Table 1 groups some of the possible options(Trigeorgis, 2001) according to this classification.In the event where more information mightchange the course of action, the option toremain status quo might have to be deliberatelycreated.

Table 1. Types of Real Options

Function Options Description

Option to To alter operating scale and reduce capacity by downsize removing features and resources

Option to To temporarily remove from active service and put mothball into protective storage

Option to To stop and cut losses, typically when projects terminate become unprofitable

Option to defer To postpone starting or initiating an investment

Option to continue To maintain status quo

Option to switch To move to an alternative mode of operationor design

Option to expand To alter operating scale and expand capacity by adding features and resources

Option to grow To invest in an option so it may open new options

Option to restart To restart a temporarily closed operation

Reducerisk

exposure

Status quo

Leverageopportunities

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REAL OPTIONS EXAMPLES

Real Options Thinking can be applied in

different scenarios of uncertainty. In the

example of the bridge in Portugal, the

uncertainty lies in the demand profile. The

Portuguese government decided to create a

real option which would become valuable if

the demand for a commuter railway systemindeed arose. This real option gave them thereadiness to switch quickly, but there wasnaturally an option premium involved whichincluded the cost of the extra load. Table 2provides other case examples where realoptions can be applied and briefly illustratesthe benefit and cost impact of theseconsiderations.

Table 2. Examples of Real Options

No Uncertainty Without With Example Benefit Cost (Option Optionoption option premium) Type

1 Demand Single Dual Roads as Readiness Operator Technical:profile may equipment use of runways to switch training, Switchchange mode equipment quickly cost of

acquiringand operatingboth modes

2 Demand level Right Spare Extra Handle Cost of under Technical:is volatile sizing equipment network small -utilisation Expand

capacity bandwidth demand and cost ofchanges spare

capacity

3 Likelihood of No Redundant Critical Resilience Original and Technical:failure of redundancy equipment equipment and recovery backup cost Switchoperating as backup for 24/7equipment readiness

4 Technical Go (high R&D to Defence R&D Readiness to R&D cost Technical:feasibility; stakes) or investigate to explore develop into GrowDemand No-go feasibility new capability project if

(forgo any and gain feasible, orpotential) subject else exit with

knowledge no furthercost

5 Unknown user Waterfall Spiral Prototype Better risk Management Management: requirements development development development management cost is higher Expand,

and technical life cycle life cycle and customer Downsize,uncertainty satisfaction Terminate,

Continue

6 Future Buy now Lease with Rent capacity Stop or Higher total Management:demand option to with option continue at cost Defer

purchase later to purchase favourableat lock-in price later price

7 Availability of Purchase Purchase with Buy x Fix the price Higher total Management:new suppliers reduced option to platforms today cost than Continue,

set now or buy more with option upfront buy Expandall now at lock-in price to buy y

more later iffavourable

8 Different Customised Standardise Multi-platform Mass Design cost Management:requirements platforms base platform missiles, basic customisation for multiple Switchfrom different and modules interfacesusers software

package

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CHARACTERISTICS AND APPLICATION OF REAL OPTIONS

Real Options has its pros (+) and cons (-).

+ Real Options enable the staging of decisionsin roadmaps. We create flexibility by buildingin decision review points in the future and bydefining the conditions under which theyshould be exercised. For example, an iterativedevelopment life cycle is superior to a waterfalllife cycle when we explore new technicalconcepts. The deferred review points give themanagement the option to scale, hold orterminate the project based on the informationfeedback as uncertainty unfolds. It is theflexibility to stage the decisions that potentiallycreates more value than a waterfall approach.Similarly, a dual-purpose road is quickly usedas a launch pad when an emergency needarises. Instead of formal timed reviews, theoption to switch back and forth always existsduring the life cycle of the project.

+ Real Options increase in value as uncertaintyincreases. The greater the uncertainty in aparticular undertaking, the greater the needto have options, and the higher thecorresponding value of the options we create.For example, the additional investment costof extra capacity in a complex network willbecome viable once the uncertainty in thedemand crosses a certain threshold.

- Real Options increase initial costs. Optionsadd to the baseline configuration of the SoSand increase costs. Options are identified atthe start of the project and hence, a higherinitial upfront cost will need to be factored into acquire the option at the ‘option premium’.For example, suitable civilian transportationresources are requisitioned for military purposeswhen needed. However, there are certain

administrative and periodic trial costs to ensurethat the suppliers and equipment are readyfor the activation. This option premium is theprice we pay for the flexibility to manage theuncertainty.

In view of the essential characteristics of RealOptions, we should realise that:

• Options are derived from the SoS. An optionmay be a logical or physical addition to thebase SoS. This concept is a useful guide whenwe start to identify options and expand ouroption or solution space. For instance, amissile that must have multi-platform launchingcapability or customised software built upona baseline module needs careful designof interfaces.

• Options are choices that are secured today.Unless we invest resources to secure thealternative that we may need later, it remainsan unrealised possibility. This notion is prettyclear for technical options as they have to beincorporated in the initial design. However,this notion can be quite subtle for managementoptions: a procurement option is ‘purchased’today as an option premium so that we canchoose to exercise it later at a pre-agreed price.

• Option investments have to be balanced.Options are secured at a price and we mustinvest in an economical portfolio that balancestheir benefits against their costs. This notionbecomes apparent during front-enddevelopment when there are several sourcesof uncertainty with several types of optionresponses.

REAL OPTIONS ANALYSIS METHODOLOGY

This section walks through the major steps inrealising flexibility in SoS. The Seven-StepMethodology for Systems Architecting shown

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in Figure 1 is an iterative and recursive processthat moves from establishing systemsarchitecting objectives to reviewing of thearchitecture. While flexibility is one of therequirements in painting the big picture, RealOptions Thinking and Real Options Valuationwill enhance the generation of solution spacei.e. Build the Big Picture (Step 3) andIdentify Capability Gaps (Step 4).

Figure 2 is our proposed Real Options AnalysisMethodology which outlines the key steps increating and valuing the real options. Thejoined Red circles are the scenarios atconsecutive time stages (x-axis). The uncertainty

of the future naturally increases over time. Thesmall floating circles are the potential responses(i.e. decisions, secured choices or real options)that management and the technical team cantake for each scenario. Both scenarios andresponses are dependent on preceding choicesand remind us of the legacy effect we maycreate.

1. Determine Evolving Requirements – Thefocus of Step 1 of Real Options Analysis is todetermine evolving requirements that canaddress uncertainties in the future. This requiresa hard look at multi-time stages (e.g. in Figure2, we illustrated it with three time stages on

Figure 1. DSTA Seven-Step Methodology for Systems Architecting(Tan, Yeoh, Pang & Sim, 2006)

Figure 2. Real Options Analysis Methodology for Active Uncertainty Management

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the x-axis) and the probable scenarios at eachtime stage. We consider the technologycapability today vis-à-vis projected uncertainties(i.e. known unknowns) coming from possiblethreat evolutions, key technology trends,changes in our operational concepts, operatingenvironment and stakeholders.

2. Conceptualise Architecture – The art ofsystems architecting is a subject on its own. Itis likely that there are several competingarchitectures proposed to meet the evolvingrequirements. Apart from functional needs,the systems architect has to trade off thevarious strategies for coping with dynamiccomplexity. This develops insights into thephysical and non-physical aspects of the SoS,sources of changes and the dynamic behaviourof the SoS. The architectural descriptions shouldallow for a qualitative understanding and aquantitative inquiry for the valuation ofoptions.

3. Real Options Thinking to expand solutionspace – Real Options present the most flexibilityand value in areas of greatest uncertainties.After projecting where the biggestuncertainties lie (i.e. Step 1), we should explorethe option/solution space and identify wherereal options can be created in the SoS. It isimportant to identify and clarify bothmanagerial (i.e. Real Options on SoS) andtechnical options (i.e., Real Options in SoS).

4. Real Options Valuation – After identifyingand creating the real option space, the realoptions are modelled by varying the designsand consequences. The steps are outlined inFigure 3. Specifically, there are two models tobe developed – the Ops/SoS model and theOptions Valuation model.

a. Ops/SoS model – The Ops/SoS model is anOperational Analysis model that eitherproduces a suitable response for a giventhreat scenario and/or generates the threatscenario that an SoS can handle given aspecific set of constraints. It requires anoperational and systems understanding ofthe specific engagement. At this level, a low

resolution analytical or simulation modelthat transforms the key design inputs tomeasurable outputs is sufficient. We will usethe Ops/SoS model to populate the responsedomain for the set of threat scenarios,and then proceed to compute the transitioncosts between sequential responses.

b. Options Valuation model – Given the set ofthreat scenarios, responses and transitioncosts, we proceed to define a Measureof Effectiveness (MOE) for evaluatingdifferent roadmaps and possible constraintsthat preclude certain roadmaps. Anoptimisation model that considers theuncertainty and time will facilitate anycombinatorial search. A point to highlightis that the solution is a recommendation ofa suitable roadmap for the entire set ofthreat scenarios, and not just a response toa particular threat scenario.

c. Roadmap – In practice, a first look at theroadmap is likely to trigger further inquiryand adjustments of both choices and inputdata. Once refined and stable, the roadmapis a guide for action. The roadmap chosenis the ‘optimal’ roadmap with the highestMOE score that satisfies the given constraints.It is important to note again that theroadmap is not a single path but a set ofpossible paths.

d. Tradespace – The tradespace plots theevolution of the optimal roadmap againstits cost and effectiveness. We can compareother roadmaps that are heuristically chosento understand the differences.

e. Option value – The roadmap is derived froma probability tree. The MOE of a roadmap isan average value based on the responsesfor the given scenario. To have a goodunderstanding of the variability of the MOE,we plot its probability distribution. We canthen compare it with any other heuristicallyderived roadmaps. The difference willcorrespond to the value of the options thatwe have built in.

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5. Invest in Real Options – The managementis presented with the results, starting with theroadmap for the responses to the set ofpostulated scenarios. They will have to decidewhich real options to invest in, in order tosecure the right to respond in the future. In

practice, the roadmap will trigger additionalquestions on new options to be built today sothat we can secure the future we want. Itwould likely be necessary to go back to earlierstages to reiterate the process.

Figure 3. Real Options Valuation Process

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recommend a roadmap that triggers furtherthinking. Together, we call this the Real OptionsAnalysis framework. Adopting Real OptionsThinking and Real Options Valuation willincrease our capacity to identify, create andsecure both technical and managerial optionsthrough deliberate choices in a cost-effectiveand timely manner.

We hope to promote a common ‘optionslanguage', enrich vocabulary, sharpen thinkingand guide quantitative analysis whenmanaging technical projects. Having optionswill always be useful especially if they spreadover space and time and both the managementand the project management team can exercisethem under appropriate circumstances.

Flexibility is a critical consideration that willenable us to deal with uncertainty throughActive Uncertainty Management. It is activebecause we would be engaged in exploringthe real options that can be designed into theSoS. As real options are designed to beexercised in the future, we would also needto think about when these options should beexercised. It is a dynamic strategic planningexercise with the aim of securing the future,whichever way it turns out to be. It is also astrategic decision making tool for SoS architects,the management and project managementteams.

6. Review Real Options – During operations,we will review if the real options investedearlier need to be exercised or deferred. If realoptions were built into the SoS, themanagement can and does have the right toexercise the options when the situation callsfor it. Exercising the correct real options canonly be done after re-evaluating their currentbenefits, and reassessing their impact as moreinformation is revealed with time. Theperceived value of each real option will becomehigher or lower over time as more informationis revealed and uncertainty decreases. We haveto keep reassessing the benefits and impact ofeach option at major decision points in orderto decide which options should be exercised.

CONCLUSION

We will continue to design and build large-scale and complex SoS to face a future that isuncertain. By leveraging the input from pastprogramme experiences and subject matterexperts, we can broadly map out possible futurescenarios. Uncertainty creates both risks andopportunities and our SoS has to remain flexibleso that we can exercise the choices we wantin response to future changes. We need tobuild real options into our technicalengineering SoS that will enable such securedchoices on demand. Real options are bothtechnical and managerial in nature. Whiletechnical options are pre-built into the SoSupfront, managerial options give us themandate to execute the real optionswith time, but without obligation.

A fresh perspective on flexibility is enhancedby Real Options Thinking and Real OptionsValuation. Real Options Thinking is akin togood management intuition and gives focusby listing the canonical management choicesand facilitating the identification and creationof real options. Real Options Valuation is akinto stochastic optimisation which helps us tocompute the maximum economic price thatwe should pay for the uncertainty and

REFERENCES

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Black, F. & Scholes M. (1973). The Pricing ofOptions and Corporate Liabilities. The Journalof Political Economy, Vol. 81, No. 3 (May - June,1973), pp 637-654.

de Neufville, R. (2001). Real Options: DealingWith Uncertainty In Systems Planning AndDesign. 5th International Conference on"Technology Policy and Innovation", paper forpresentation, June 2001.

de Neufville, R. (2002). Class notes for“Engineering Systems Analysis for Design”ESD.71. MIT Engineering School-Wide Electivetaken in Fall 2004. Cambridge, MA.

de Neufvil le, R. (2004). UncertaintyManagement for Engineering Systems Planningand Design. Engineering Systems Monograph,MIT. Retrieved on 10 February 2007 fromh t t p : / / e s d . m i t . e d u / s y m p o s i u m / p d f s /monograph/uncertainty.pdf

Gesner, G. and Jardim, J. (1998). Bridge withina Bridge. Civil Engineering, October, pp 44-47.

Moses, J. (2003). The anatomy of large scalesystems. ESD Internal Symposium. Cambridge,MA.

Tan Y.H., Yeoh L.W., Pang C.K., Sim K.W. (2006).Sy s tems Arch i tec t ing fo r 3G SAFTransformation, DSTA Horizons 2006,pp 36-49.

Trigeorgis, L. (2001). Real Options: An Overview.Chapter 7 of Real Options and InvestmentUnder Uncertainty: Classical Readings andRecent Contributions. Ed. by: Schwartz, E.S. &Trigeorgis, L. MIT Press, pp 103-134.

ACKNOWLEDGEMENTS

We would like to thank Tan Yang How, TeoSiow Hiang, Lim Hang Sheng, Ang Choon Keatand Lee Keen Sing for their ideas andsuggestions during our discussions. We wouldalso like to acknowledge Palvannan RKannapiran, an ex-colleague who had helpedto develop the ideas in this paper. Lastly, wealso acknowledge and reference ProfessorRichard de Neufville of Massachusetts Instituteof Technology for his seminal work in RealOptions Analysis in large-scale system design.

BIOGRAPHY

Ng Chu Ngah is an Analyst (Operational Analysis and Simulation, DMSA). Sheis currently involved in the structuring and modelling of complex systemsand processes through the use of operations research, simulation techniquesand combat models so as to provide an objective basis for decision making.After receiving the DSTA Scholarship in 2003, she attained her Diplômed'Ingénieur from Ecole Nationale des Ponts et Chaussées, as well as herBachelor (First Class Honours) and Master degrees in Industrial and SystemsEngineering from the National University of Singapore.

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Angela Ho Wei Ling is an Engineer with a portfolio spanning across EnterpriseIT and DSTA Masterplanning & Systems Architecting (DMSA). In EnterpriseIT, she has a key role in facilitating the Business Process Transformation andEnterprise Architecture for large-scale, complex Enterprise IT projects of theMinistry of Defence and the Singapore Armed Forces. In DMSA, she is a keydriver in developing Systems Architecting Methodologies. A recipient of theDSTA Overseas Undergraduate Scholarship, she graduated with a Bachelordegree in Computer Science (Honours) with a focus on Human-ComputerInteraction from Carnegie Mellon University. She also earned a Master ofScience in the Technology Policy Programme, with a focus on Aeronauticsand Human Factors, from the Massachusetts Institute of Technology.