Real Options and Real Engineering ProjectsTed Eschenbach, PE, TGE ConsultingNeal Lewis, University of Bridgeport

Morgan Henrie, MHCElisha Baker, IV University of Alaska Anchorage

Joseph C. Hartman, PE, University of Florida

Abstract: Real options ana]ysis is a tool that has not fullyjustified itself in the face of real world complexity. It isintended lo value flexibility in future choices; however, muchof the literature focuses on the mathematical details of howlo perform real options analyses, without taking the timeto ask whether key characteristics of engineering projectshave been properly recognized. In addition, many paperscontrast real options analysis with a simple NPV analysiswith deterministic data and no options. Because engineeringeconomic analysis has long included decision trees, sensitivityanalysis, simulation and other tools, the key question is, whatdoes real options analysis add lo this toolbox? A comparisonof real and financial options and case studies of engineeringprojects led us to conclude that the value of real options ismore limited than many .suggest. Different recommendationsdue to the use of real options may be limited to near-zero NPVprojects where the future benefit stream can be well forecastedand where uncertainly can be identified. This can lead to greatdifficulty in applying options to real engineering projects.

Keywords: Real Options, Engineering Economy, SensitivityAnalysis, Decision Trees, Risk Analysis, Simulation

EMJ Focus Area: Program and Project Management, SystemsEngineering, Economics of Engineering

The theoretical foundation for real options or options onreal assets begins with options on financial securities. Forexample, a call {put) option gives the holder the right to

buy (sell) a certain number of shares at a specified price withina specified period. The option premium is the price paid forthe option. Financial options can be used to increase leverageand potential gains, but their principal use is for hedging toreduce risk.

This article stems from the authors' uneasiness with thedirection of much of the work on real options and the claimsby some proponents that NPV analysis is inadequate andthat real options must be used to evaluate all strategicallyimportant questions.

Without question there is real value in the work on realtiptions. Many examples of significant bottom-line monetaryimpacts from the consideration of real options have beengenerated; however, the decision-making environments forfinancial and real options differ substantially, and engineeringprojects have characteristics that limit the applicability ofreal options.

This article is organized into a literature review, acomparison of financial options with real options for engineeringprojects, a series of case studies, and implications for practiceand research.

Literature ReviewThere are several good books on real options (Bossaerts, 2002;Brach, 2003; Brennan and Trigeorgis, 2000; Copeland andAntikarov, 2001/2003; Mun, 2006; Trigeorgis, 1996). In ouropinion, the easiest to follow introduction can be found in Park(2007, Chapter 13). These introductions typically begin with thevaluation of financial options and include the Black-Scholes andbinomial lattice models. Park and Herath (2000) also provided astraightforward introduction and Miller and Park (2002) providea good literature review (through 2001).

Both the Black-Scholes equation and the binomial latticemethod require five parameters for calculating tbe option value.For real options, these parameters include the present ViUue offuture cash flows, the investment cost, the interest rate, the timehorizon, and the project volatility. The first four variables areexactly the same as those required to determine the net presentvalue. Volatility is the only added variable, although it is themost difficult to determine and the most complex of the inputparameters.

The mathematical details may be challenging; for exampleestimating volatility for projects is not straightforward (Lewis andSpurlock, 2004). Nevertheless, there are many examples of the useof real options; Nichols (1994). Heratb and Park (1999), Enke(2003), Lewis et al. (2004), Miller and Park (2004), Sarkis andTamarkin (2005), and Lozada (2005). In fact, real options havebeen incorporated into other evaluation approaches such as scorecards (Mufioz and Rabelo, 2005), game theory (Shil and Allada,2005; Cottrell and Sick, 2002), and decision analysis (Smith andNau, 1995; Heratb and Park, 2001); however, the penetration ofreal options analysis into practice is somewhat limited. A surveyof usage by Fortune 1000 firms found that only 14.3% were usingreal options (Block, 2007). For a specific example, petroleumexploration and development is clearly an area with highlyvolatile product values wbere real options analysis is likely to bemost useful; yet, a survey of project selection practices (Razakand Kocaoglu, 2001) has no mention of it at all.

Wlietherthelimiteduseisdue to the mathematical challengesof real options, an implicit recognition of this article's focus onthe characteristics of real engineering projects, or another cause,we do not want to even conjecture.

This limited use may also be attributed to the fact that therecommendations are not significantly different than traditionaldecision analysis (i.e., decision tree and utility theory) methods(Smith and McCardle, 1999). In fact, the authors state that they

Refereed management tool manuscript. Accepted by Associate Editor Marino.

Engineering Management Journal Vol. 19 No, 4 December 2007 11

are uneasy with strictly applying real options analysis to oil andgas investment decisions.

Otbers share tbis uneasiness. For example, McGrath (1997)proposes that traditional financial options models cannot be appliedto technology positioningprojocts, because"...their core assumptionsdo not hold. For instance, the price of an underlying tecbnology assetis not known, and it may not be continuously tradable."

Position of this Article Relative to the LiteratureIn any case, a good starting point for the relationship between realoptions and engineering projects is Equation I for the extendedNPV or ENPV (Trigeorgis 1996, Lewis and Spurlock, 2004).

ENPV = NPV + Option Value (1)

This expression reminds us that considering real options willchange recommended decisions only for projects with an NPVthat is negative, but not so negative as to exceed the option value.

This relationship is also a good way to establish theperspective to dismiss more extreme claims that real optionsanalysis should replace misleading financial measures such asNPV analysis (e.g., Brydon, 2006). A representative quote fi-omLeslie and Michaels (1997) is a top listing from Google Scholar:"Real options are important in strategic and financial analysisbecause traditional valuation tools such as NPV ignore the valueof flexibility."

This article also provides a fine example of using real optionsto force consideration of the value of keeping leases for potentialNorth Sea development to allow for the increase in recoverablereserves due to new drilling and production techniques;however, we question why these possibilities couldn't be analyzedwith NPV

Exhibit 1 . Financial vs. Real Options

Equation 1, however, may be in conflict with anotherintuitively appealing result that says using a higher hurdle rate for"risky" projects captures much of the "option value" (McDonald,2000). For example, using a higher hurdle rate of say 20% or aprofitability index of 1.5 forces projects to wait until profitabilityis high. On the other hand, it is difficult at best to translaterisk into a hurdle rate; the translation is always subjective andoften arbitrary.

To the extent that real options analysis is interpreted asrequiring consideration of future potential changes and otheroptions, then it is clear that such consideration must become partof economic evaluation of potential projects.

Real options analysis has little or no role in the manyapplications of engineering economic analysis to mutuallyexclusive design choices. This is in contrast to the analysis offinancial options such as hedging fuel costs that may be part ofroutine operational decision-making. In contrast, real optionswill have some role in the selection of projects with strategicimplications; however, we suggest that the sweeping claims thatreal options must replace the antiquated tools of NPV analysis,such as decision trees and simulation, are wrong. In fact, webelieve the next two sections clearly explain why real optionscan add value to the decision-making process for only a smallpercentage of engineering projects.

Methodology of Financial vs. Real OptionsSince the theoretical roots of real options lie in financialoptions, a comparison as summarized in Exhibit I is useful.There are two major conclusions that we suggest based onthis exhibit.I. The many differences and additional complications for real

options for engineering projects imply that the extension of

Characteristic Financial Options Real Options for Engineering Projects

Market

Complexity

Active and weil-studied

Low. stock price is the one uncontrolled variable

Need for options in this Medium to High: often used for hedging, high payoutcontext potential

Statistical validity

Transaction costs

Information

Variable whoseuncertainty is key

Interest rates andinflation

H/g/i:huge historical databases & statistical analyses

toiv: active market with very low transaction costs

Lots on few items, publicly available

Stock price

Calculations done with nominal dollars & nominal ormarket interest rates

Uncertainty described by Volatility coefficient from one proven method

None

H/g/i;many uncontrolled parameters, all based onforecasts

Low: not needed for high NPV projects, not helpful forlow NPV (significantly negative) projects, and best usewhere NPV near zero

Low to non-existent: all parameters are estimates withunknown variability and accuracy

High: firm must formulate alternatives, createinformation, analyze, decide. Requires time andspecialized skills.

Little on many items, must forecast and research,information is limited,expensive,and its validity isoften time-limited

Investment cost, revenue, time-to-market, projectlifetime, future market share, future volatility, potentialviable alternatives

Calculations often done v ith constant-value dollars,real interest rates must be used

Volatility coefficient variations with different results

Engineering Management Journal Vol. 19 No. 4 December 2007

option theory to real options may not be valid in some casesand it will be a challenging effort in most cases.

2. The existence of an open market for financial options testsand proves the validity of financial option valuation andpricing. The lack of a market for real options for engineeringprojects implies that proving the validity of the optionvaluation is difficult and may be impossible. Audits thatmatch the financial results of approved projects againstexpectations are rare; audits that generate post-projectestimates of probability distributions (Was this really the25% probability case?) are even rarer, and audits of projectsthat are not accepted simply don't happen.

Most of the comparisons in Exhibit 1 are clear—once statedin this way; however, there are two that merit further discussion,[he conclusion that the need for real options is low for engineeringjirojects is due to the observation that most major engineeringprojects are subject to large uncertainties, and, consequently,marginal projects or payoffs are avoided. It is for these marginal[irojects where Equation 1 can show that the option to do "xxx" isbetter than a project witb a negative present worth.

Because financial options are generally relatively short-termand part of an active market using nominal prices, analyses aredone in nominal dollars and at market or nominal interest rates;however, engineering projects are long-term and inflation isclearly an issue. These projects are often analyzed using constant-value dollars. Note that an easy test for the underlying assumptionis whether or not any costs or revenues are stated, for example, as$450,000 per year for 10 years. Because the chance that inflationwill exactly balance changes in volume is small, the uniform cashHow is usually a reliable indicator of constant-value dollars. Ifconstant-value dollars are used, then interest rates must be real,not nominal. The approximate real rate equals the market rateminus the inflation rate.

Characteristics of Real Engineering ProjectsOne of the defining characteristics of engineering projects is thecontinuous accumulation of knowledge during a project. For ahigh tech R&D project, this may tbcuson the technical limits of aprocess and the details of how to achieve the limits. For a buildingproject, the knowledge may be represented in a growing set ofdesign documents. And for a resource development project, theknowledge may come from drilling holes and extracting cores. Insome cases, the knowledge comes from non-engineering activitiessuch as market surveys, customer focus groups, and the actions ofcompetitors, suppliers, and customers.

A second defining characteristic of real engineeringprojects is that they are accomplished by teams of people,often representing different organizations. Wiiile much of theknowledge being accumulated is represented in reports, processes,;md objects, a significant share of the knowledge is tacit—not explicit.

The tacit knowledge may concern the details of a process,but it also includes the understanding of which team membergives optimistic estimates and who is pessimistic, who over-performs and who does not, what the real agendas of some teammembers and organizations are, and how stable the project'sexpected outcomes are.

The knowledge in an engineering project is a capitalinvestment, but unlike a building, it cannot sit empty, waiting(or use. Knowledge is better thought of as having a half-life thatdescribes how it decays over time. Tbis decay may come from the

memory of a team member, new technology, or new regulations,but it means that the knowledge becomes less valuableover time.

Unfortunately, the dynamic character of knowledgeaccumulation does not integrate well with the uncertaintyanalysis of any of our available tools, whether decision trees,simulations, or real options. First, the continuously arrivingnew knowledge may differ from predictions. Analyses may haveto be redone or scrapped. For example, in the SCADA projectdescribed next as Case 1, no one would have predicted thereason and need to shut down the project. Because it was notpredicted, it could not have been incorporated into the project'sforecasts for any tool. Second, the time and resources for redoinganalyses frequently may limit re-analysis efforts to projectionswith new deterministic estimates or to revising the expectedvalue analysis. Simulation is more difficult and real options evenmore difficult.

On tbe other hand, there is another characteristic ofengineering projects that does integrate well (at least theoretically)with real options analysis. This is the staged development thatis characteristic of engineering projects. While the terminologyand details are very different for high tecb and for infrastructureprojects, as engineering projects they go through similar stages.These include conceptual design, preliminary design, detaileddesign, production or construction, operation, and shutdown.

The stage-gate nature of this process is shown through termssuch as feasibility study, proof of concept, go/no-go decisions,and decision gates. At each stage tbere is a conscious evaluationof whether the project should be terminated, expanded, shrunk,revised, delayed or accelerated. These options to change theproject's scope, budget and timing can only increase the project'svalue. This is the concrete application of Equation I.

Exhibit 2 summarizes the four detailed case examplespresented in this article.

Exhibit 2. Cbaracteristic of Real Engineering Project Highlighted

Case Characteristic

1. SCADA Delay costs include total redesign vi ith newteam

2. Leak detection Stage-gate nature of decision-making

3. Classroom Multiple alternatives with little informationbuilding on uncertainty (single value may be mode

or average) and undefined benefit stream

4. Drug product Cost of waiting due to lost sales

Case Example 1: OeIay/Termination of SCADA ProjectIn l-ebruary 2000 tbe following project communication wasreceived:

Your project has been suspended as of this date.Suspension means tbat the project is to stop work;however, the project should have an orderly shutdownsuch that it could be restarted again on short notice(Project manager working notes, 2000).The suspended project was a supervisory control and data

acquisition (SCADA) replacement project. The fijll scope of workincluded design, detailed engineering, material procurement,

Engineering Management Journal Vol. 19 No. 4 December 2007 13

installation, and final testing and certification. The estimatedproject cost was approximately $i2M with an expected durationof approximately 24 months.

At notification of suspension, the project was still inthe design and engineering phase, involving both hardwareand software activities. The hardware engineering effortswere approximately 40% complete and software engineeringwork was approximately 30% complete. Minimal materialprocurement activities had provided a small set of test bedequipment. Overall tbe project was indicating 16% completewith accumulated expenditures of $1.9M over seven months ofactivity. In general the project was within project schedule andbudget plans.

So why shut down a project that was trending towardcompleting on lime and within budget? The answer lies withinthe company's sudden and unexpected discovery of a regulatorycompliance problem. The required new higher priority projectwas not within the firm's project funding plans or personnelassignments. Approximately $ 1OM had to be allocated to this newproject, and key personnel had to be reallocated from in-processefforts. Faced with this new challenge, the fastest response wasto suspend the SCADA project, reallocate the remaining $10Mto the new project, and reassign critical human resources lo tberegulatory issue project.

While the need to address tbe regulatory item is a higherpriority, suspension of the SCADA project did not come withouta cost. These costs can be generally classified as actual suspensioncosts and restart costs.

The SCADA project actual suspension costs were primarilydriven by the directive to have a "...shutdown such thai [theproject] could be restarted again on short notice." In order toaccomplish this, the project team performed the major tasksof boxing up all project files, making electronic copies of alldocumentation, and transferring the documentation and projecthardware to storage. The project team was given one week toachieve this. At the conclusion of these efforts, approximately 450labor hours were expended for an estimated cost of $51,000. This$51,000 equates to 0.5% of remaining project funding or 2.7%of ihe work completed. While not a significant percentage of iheproject budget, the actual funds spent does not show the humanfactors cost or subsequent restart costs.

As a human factors cost, this project lost tbe project team. Eachteam member was either reassigned to other projects within theircompanies (like many large projects,subcontractors were involved),or in a few cases, they were forced to find new employment at otherlocations. The fiill institutional tacit project knowledge was lost.This certainly impacts the firm's desire for a potential quick restart,since a new project team would be required.

The final restart costs have not been determined. While theneed for the project has not diminished, subsequent events haveprevented the project from restarting. Effectively, the project spentapproximately $2M with no return on investment. Any effort tostart the project at this lime will require a complete restart. Allprevious information is outdated and of minimal value.

We expect, however, that wben the project is restarted, timeand effort will be spent trying to use the previous work (Whittaker,2006). This shows respect for the previous work and project team,and validates the orderly shutdown. We also expect, however, thatthe marginal value of the previous work will at most equal theeffort expended trying to use it.

This example has had a longer shutdown than may betypical. Even so, tbe dispersal of the project's human capital and

the marginal value of previous work at restart are consistent withour experience in a broad array of engineering environments.

In addition, we believe that engineering project managerswill certainly not be surprised that delay often really translatesinto "terminate and re-start from scratch." Nevertheless, we havenot seen this connection made in any of the literature on realoptions. Finally, this example is one of many where the time, data,and expertise to analyze tbe delay/terminate decision as a realoption is simply unavailable.

Case Example 2: Pipeline Leak Detection ProjectAs an example of the stage-gate process, consider a pipeline leakdetection project. From a technology perspective, each pipeline isunique. Differences include physical and environmental factors,fluid characteristics such as corrosion potential, and availablefield instrumentation data. These variables require a customizedleak detection system tbat is specifically configured, maintained,and operated within the specific pipeline system.

Due to ihe technological risk factors, each leak detectionsystem implementation faces financial risk. The financial risk isnot only related to the historically low probability of success forsoftware implementation projects, but the correlated financialrisk of a unique pipeline system operating environment.

To address the technology and financial risk, it is common touse a very stringent staged project method. The major go/no-godecision points include competitive bidding lo a strict technicalrequirement document, proof of concept on a limited sectionof pipeline, expansion of the limited application to a broaderpipeline segment, full pipeline implementation, and, finally, a setof enhancements. Contractually, each stage is set up with a knownfinancial risk tied to meeting technical requirements within anagreed timeframe. At each of these go/no go points, the companyhas a clearly defined technical objective with known maximumfinancial risk.

It is clear, however, that the data for decision-makingcontinually evolves. At each stage gate, there is detailed data on theresults of the past stage, much better quality estimates for the nextstage, and some effort has been made to refine the estimates forfuture stages. At each stage gate there needs to be a new analysisof the economics of each alternative.

The stage-gate decisions mesh weD with real options;however, the complexities and data requirements for sequentialcompound options are even more pronounced than for thesimple delay option described as Case 4.

Case Example 3: Minimal Now, Staged, or All-at-OnceConstructionsA common situation for a new facility is the decision to size itto meet immediate needs, to meet planned future needs, or toinclude some features to facilitate later expansion. For example,a classroom building could be built (1) to match current needs{= minimahiow) for$13M with another $ 12M required wheneveran e.xpanded or second building is built; (2) to meet future needs(= all now) for $21M; or (3) in stages (= staged) for $15M nowand $7M later (Eschenbach, 2003}. This choice is so commonthat the advantages and disadvantages of each approach can beidentified (Eschenbacb).

This is a classic case of tbe choices or t)ptions involved withengineering projects. Larger foundations, larger capacity powerlines, water mains, and road and sewage connections may costvery little up front, while disrupting operations to expand theinfrastructure can be very expensive. This can be modeled very

14 Engineering Management Journal Vol. 19 No. 4 December 2007

clearly with decision trees, and calculating the economic value ofeach choice is straightforward.

In a present value analysis, doing it all now often appears tohe advantageous; however, the key value of the staged or minimaloption only shows up when these alternatives are examined witha stochastic set of potential futures. Linking ftiture constructioncosts to future needs ensures that those costs are incurredonly when and if they are needed. This dramatically reducesdie standard deviation or risk that is maximized by buildingeverything now (Eschenbach, Case 23, 1989).

This example exhibits the mix of options and uncertaintiesihat engineering decision-making must address, which even ina very simple case rapidly become complex as we better modelreality. This case also highlights one challenge of using realoptions analysis—a benefit stream is required. Since the benefit ofthe classroom building is undefined, the benefit stream is definedthrough incremental analysis comparing each of the three pairsof alternatives.

Case Example 4: Construction of Production Facilities for aNew Drug Not Yet Approved by FDALewis, Eschenbach, and Hartman (2007) detailed the analysisusing these methodological tools of a build-now vs. a wait-and-see strategy for a facility for a new drug that is in the Food andDrug Administration (FDA) approval process.

This is a common problem for drug companies, and it fitsin the framework of the delay option. The drug has 12 yearsremaining of its 20 years of patent protection, and the EDAapproval process will take two more years. There is a 90% chancethat the FDA will approve the new drug.

The facility to produce the new drug will take twoyears to build, cost $38M, and have a salvage value of $9M ifthe FDA does not approve the drug. If facility constructionbegins now, it will be available to produce the drug upon FDAapproval. Net revenue is expected to be $20M in first-year sales,$28M in second-year sales, and $35M in all remaining years,rhe question facing the firm is whether the facility shouldbe built now (expected PW of $25M, standard deviationof $I9M, and P(Ioss) = .1) or should they wait until afterFDA approval.

If the facility is built after FDA approval, there is less risk, butpositive cash flows are delayed for two years, and the expirationof patent protection means the positive cash flows still ends 12years from now. The expected PW is $15M, the PW's standarddeviation is $5M, and the P(loss) - 0. Real options are mostuseful in the analysis of this last case.

Real Options and Engineering ProjectsRather than focusing on types of engineering projects, this sectionis organized by the activity that the option represents.

Delay OptionFor most engineering projects the only realistic point for aj)lanned delay is after the conceptual or preliminary design stages.1 he knowledge at this stage is at a level of detail where it maybe useful later, and in fact this knowledge is often the reason forchoosing to delay a project.

For example, current technology may simply not provide theperformance that the project needs, but projected trends may indicatethat a delay of nine months will provide the needed performance.

Once construction has started, the costs of delay are farlarger. For example, consider a nuclear power plant where the

government mandated several delays for regulatory review andapproval. There were 250 welders working on stainle.ss steel fora specification unique to the nuclear power industry. Each delayimplied layoffs, and new hiring, training, and learning curvesfor each start-up. The contractor won the court case, as the verylarge cost overruns were the fault of the government owner formandating the delays.

It is more typical, however, for delay not to be a realisticeconomic option. Delay may simply be a euphemism forterminating a project. In a competitive market, delay is likelyto mean loss of potential markets. In a building project, delaywill often lead to new regulatory requirements for addedparking, energy efficiency, signage, handicap access, burricaneor earthquake resistance, environmental assessment, etc. in thesecases delaying the project is better interpreted as terminating aproject that may be restarted later.

When matched with the first two defining characteristics ofengineering projects, delay causes the decay of the knowledge base,and more importantly, delay often fragments the project team—only some team members may return at restart, if any do.

There are two classes of projects where delay is a morecommon strategic option. Resource development projects tendto happen when prices are high and demand is near capacity. Afeasibility analysis may be used to identify the breakeven priceat which (iirther development should be considered. Thus, theremay be a significant delay between the initial study and furtherstages of development.

The second class of project tends to be more locally drivenand less global—that is real estate development projects. Whatis the demand for class A office space or for a research park?Usually the land sits idle and detailed engineering designwaits until the decisions of what and when are indicated bymarket factors.

Termination or AbandonmentPilot plants and prototypes are often built for the express purposeof determining whether the project should be continued orterminated. Thus, an economic analysis with this option shouldinclude a decision tree. This is a real options analysis, but withthe tools of traditional economic analysis and not in a frameworklinked to volatility, binomial lattices, or Black-Scholes models.

While not based on a comprehensive survey, ourexperience suggests that organizations often over-estimatethe value of previous work and under-estimate the difficultyof starting over with a changed project team for the option toterminate and restart later; however, it is also common to omitconsideration of this "shut-it-down" option, which can be veryeconomically attractive, as it represents the value of "cuttingyour losses."

Expand, Shrink, Accelerate, and ReviseSome engineering projects can be designed for modularexecution. Building projects can be completed in phases, softwaredevelopments can be staged as releases, and new, improvedmodels can foOow later. This allows time for technology andmarket development, but it also requires consideration of thecosts in time, money, and scope of changing the project team tomatch the new requirements.

Economic analysis is required at each decision point,but the key perspective of real options is that the flexibilityrepresented by tbe options is of economic value. Thisperspective also applies to the decisions made at the stage gates

Engineering Management Journal Vol, 19 No, 4 December 2007 15

of conceptual, preliminary, and detailed design, and productionor construction.

Sometimes the flexibility built into the original design isused for other purposes. For example, an Arizona State Universitylibrary was designed to support another two floors. Whenstandards for resistance to earthquakes were changed, it was nolonger possible to add the floors, but the existing structure wascertainly safer.

Other times the tlexibility built into the design is neverused. The Trans-Alaska Pipeline System (TAPS) was designedfor three phases of construction that would add pump stationsa.s North Slope production increased. Technology advancementseliminated the need to expand into the third project phase. Dragreducing agents were developed that provided a much cheapertechnological solution, which also meant some of the initialinvestment for expansion capabilities was wasted.

Methodological ToolsBelore di.'icussiiig the tools to be used in evaluating the optionslinked to engineering projects, let us first consider the datatypically available for pricing financial options and that availablefor engineering projects. Financial options are relatively straight-forward, as summarized in Exhibit 1: there are histories withstatistical validity, and there are well established markets toestablish values.

Unfortunately, as summarized in Exhibit I, engineeringprojects are full of complex choices—some of the future estimatesare better characterized as guesses, and there is no market tohelp establish option values. There are markets for the productsof engineering projects (a new DVD player, a building or a newdrug), but this is not the same as a market for an option on theengineering project. Your customers buy your products, yourcompetitors would be the market for options on your projects.

So the question is, "What tools are most likely to be of valuein analyzing these possibilities?" Exhibit 3 summarizes the levelsof economic evaluation. Our experience on many engineeringprojects suggests that decision trees and simulation are the bestpossible tools. Tbe key problem is that if no one has a modelof tbe potential futures, then tbere is no basis for a real optionsanalysis. Real options are complicated, which implies that mostmanagers don't know, like, or trust the tool. Thus, most economicevaluation is at a simpler level.

Exhibit 3. Levels of Economic Evaluation

Gut feel

Single-value estimates

Estimates from expected value of probability distributions

Decision trees

Simulation

Real options

The major decision points and options are developed ina decision tree. This typically includes representative optionsthat are discrete choices in a continuous world. For example theexpansion option might be modeled as a 50% expansion in 3 years,where in reality the expansion could be any percentage between25% and 100% at any point in a window of 2 to 10 years.

Significant projects will have numerous options. Earlychoices may include termination during preliminary design dueto lack of competitive strengths, or after the prototype phase, for

inability to meet cost targets. The initial analysis must recognizethat the detailed design may be of radically different size. Manyinfrastructure projects face periodic efforts to renew, redesign,and change existing projects—all of which can be recognized andplanned for from the beginning. The complexity of multiple optionsat multiple points in time implies that developing, describing, andcommunicating the options requires decision trees.

Each of these options requires the development of a modelof system performance, in each case, what are the potential futuredemands, costs, capabilities, and requirements? The knowledgetbat is generated by constructing the model(s), and tbe insightsgenerated by using the model are wbat support quality decision-making. The process of building the model that requiresdeveloping the data and understanding tbe relationships can beso illuminating that the model's results are secondary.

Generating the simulation model is a big step in recognizingand quantifying an uncertain future. It allows the consideration ofoptions for future decisions. Moreover, the nature of simulationmeans that managers and engineers who may not understandthe details of model construction can still be confident inthe results.

We suggest that sucb a simulation model is, tor mostengineering projects, the only realistic method to develop a modelof outcomes over 5 to 50 years witb data and estimated relationshipsprovided by many people with distinct competencies. It makes theassumptions explicit and thus open to discussion and debate.

We suggest that for most engineering projects, sucha simulation model is the only realistic way to estimate thevolatility of a project, which is required for real options analysis(Lewis and Spurlock, 2004). Thus, the simulation model is arequirement, and the question concerns whether further analysisis appropriate. In some cases, ftirther analysis by more financiallysophisticated analysis using the tools of real options may providefurther payoffs.

Applying Real Options Analysis to the Case ExamplesExhibit 4 summarizes the challenges in applying real optionsto these cases. Only in case 4, the drug product, is it realisticallypossible to use real options, since missing information means thatreal options cannot be applied in the other cases. Note: In Case 3,incremental analysis of investment costs could be used instead ofevaluating the three alternatives individually; bowever, this stilldoes not address the key uncertainties in "when" the expansionwill truly be needed.

Exhibit 4. Challenge in Using Option Models

Case Challenge

1. SCADA Delay costs unknown and unknowable,since iength of delay is unknown

2. Leak detection Requires sequential compound option &binomiai lattice solutions

3. Classroom building Undefined benefit stream makes optiondetermination impossible

4. Drug product Cost of waiting often ignored, and asin tbis case, it often dramatically lovi/ersvalue of option

As detailed in Lewis, Eschenbach, and Hartman (2007) realoptions were applied to analyze Case 4. As described in the initial

16 Engineering Management Journal Vol. 19 No. 4 December 2007

summary of this case, waiting is less risky, but the mucb largerPW for acting now suggests that the firm should proceed. Thislevel of risk is typical for new drugs.

This analysis compares the alternatives considering theprincipal uncertainty of the FDA approval; however, all ofthe data in the prohlem is estimated and therefore subjectto uncertainty. Thus, the data were analyzed using upperand lower limits for all variables to produce spider plots andtornado diagrams. In a real world analysis, this would be thepoint where some effort would be made to better define thekey parameters.

These limits were used to define triangular distributions foreach variable. Simulation was done assuming independence ofthe variables. The expected PW for the build-now option was$I8M, its standard deviation was $21M, and the P(loss) ^ 11%.The wait-and-see alternative when simulated had an expected PWof $13M, a standard deviation of $9M, and a P(loss) = 2%. Thus,assumptions of asymmetry for some variables (more bad thangood} has reduced variable means below their modal base case, sothat simulation shows reduced economic attractiveness of bothalternatives, with a somewhat larger increase in the indicated riskof the wait-and-see option.

When analyzed as a real delay option using the basic Black-Scholes model, the wait option is valued at $29M (whicb ishigher than the expected values for both alternatives under PWanalysis). Similar values are calculated with a binomial lattice.These calculations assume that the project's volatility is typicalfor the firm, so that the firm's financial volatility parameter of .4can be used. {Note that this is one of several ways used to establishtbe volatility parameter.)

The option value of $29M is misleading, however, andshould be ignored. Like many of the published examples usingreal options, this basic delay option ignores the cost of waiting. Infinancial options, tbe cost of waiting comes from stock dividendsthat are not received by the owner of an option. Here ihere islost revenue by not being in the market. In other examplescompetitors migbt market a similar product first, whichwould imply lost revenue and continuing lost market share.The deferral option needs to consider the cost of not makinga decision.

Unfortunately, the cost of waiting is usually dealt with indetail only in those books that treat real options in detail. Articlesand book chapters may simply mention it or pass it by altogether.In reality, the cost of waiting can kill the option value of a realoption. When dealing wiib any deferral option, the advantage ofwaiting needs to be offset by the cost of waiting.

For this example, the cost of waiting may be determined byfinding the PW of tbe incremental value between tbe alternatives,which is the value of tbe cash flow differences in years 3, 4, 5,and 6. Under the delay option, there are no revenues in years 3and 4, and years 5 and 6 are ramping up to full sales. Discountingthese differences using tbe hurdle rate provides a total cost ofwaiting of $28M. Because the cost of waiting is part of the optionvalue calculation, it cannot simply he subtracted from the $29Moption value without waiting.

The option value including the cost of waiting is $8M, whichis far smaller than the value of proceeding immediately. Becausethe build-now alternative has the largest PW, il is the best decisionbased on the predicted information. Exhibit 5 summarizes thedependence of the option value on the volatility coefficient. Thisexhibit illustrates one of the counter-intuitive results associatedwith real options—increasing variability or volatility increasesthe value of the option.

Exhibit 5. Cost of Waiting, Dementia Drug

SO

40-

30-

20-

10

Option w/o cost ofwaiting

PW, build now

Optionwith cost of waiting

20 40 60 80

Volatility, %

100 120

ConclusionsReal options analysis has earned a place in the toolbox used toeconomically evaluate engineering projects; however, since itstarts with the premise that options can only add value, it is onlyneeded for those projects whose economic value appears to bemarginal or negative. Real engineering projects, however, haveinvestment costs and returns that are significant and usually go/no-go is clear. Because uncertainties are large, marginal projectsor payoffs are avoided. Because real options matter most for thesemarginal projects, it implies that real options don't matter oftento engineering managers.

Note; real options analysis does no better than deterministicnet present value analysis in accounting for uncertainty in theparameters. In both cases a separate sensitivity analysis is required.What real options analysis can do is force us to recognize the valueof flexibility in our decision options.

In our experience numerous economic evaluations are"no-brainers" once the preliminary data has been developed.The project is usually clearly acceptable or not acceptable. Thus,evaluations witb weak tools such as payback period or weakmodels tbat ignore uncertainty are often good enough to supporthigh quality decision-making.

In more cases, good decisions are the result of in-depthinvestigations into the data of a project. That is, uncertaintiesin a project can often be resolved (to some extent) throughresearch. This is typical to most real projects that progress instages. While real options can play a role in evaluating thesestaged investments, it is unclear if they provide better insight tbanpreviously developed tools that evaluate options (decision trees)under uncertainty (simulation).

Real options, however, can play a valuable role if it forcesthe decision-maker to consider multiple options at time zerothat may otherwise be ignored. This comes with the requirementthat any real options analysis consider the cost of waiting,as well as focusing on the value of waiting. Unfortunately,as real options are designed to evaluate single projects(Trigeorgis, 2005), their role in capital budgeting decisions maybe limited.

The payoff comes from doing good projects—nol fromdoing better-than-needed analysis. Thus, we suggest that realoptions should be taughl by academics and understood bypractitioners; but it should nol be used all that often. Also, whenreal options analysis is used, the characteristics of the engineeringprojects must be considered in defining the costs and outcomesof the options.

Engineering Management Journal Vol. 19 No. 4 December 2007 17

We suggest the following as potential topics for fijtureresearch;

Which {if any) of the methods for establishing a volatilitycoefficient for real options is correct?What level of project detail and uiformation on uncertaintiesis required to support real options?How common is the use of real options, and what industry,firm, and project characteristics promote or inhibit the useof real options?

• What is the role of real options in public sector engineeringeconomic analysis?

We suggest the following as implications for the engineeringmanager:

Real options can help decision-making under the right,limited circumstances (NPV near zero) and the otherlimitations discussed above.Decision trees and simulation provide tools that areoverlooked and under-appreciated. In many ca.ses, theyprovide more information than options and assist theengineering manager in more circumstances than optionswill(NPV>0).If you can't describe your possible futures with decision treesand future uncertainties with probability distributions, thenyou can't build a reliable model for real options.

• Value comes from action not analysis; thus, stop the analysisas soon as the answer is clear. The stages of analysis are:

Preliminary base case analysisUse decision trees and sensitivity analysis to defineproblem and data

• Calculate expected values, standard deviations, andP(loss) to evaluate the tradeoffs between risk andreturnAdd probability distributions and simulationAdd real options analysis, including the cost of waiting

ReferencesBossaerts, The Paradox of Asset Pricing, Princeton University Press

(2002).Block, Stanley, "Are 'Real Options' Actually Used in tbe

Real World?" The Engineering Economist, 52:3 (2007),pp. 255-267.

Brach, Marion A., Real Options in Practice, )ohn Wiley & Sons(2003).

Brydon, Michael, "Evaluating Strategic Options Using Decision-Theoretic Planning" Ififorniation Technology & Management.,7:1 (lanuary, 2006), pp. 35-49.

Copeland, Tom, and Vladimir Antikarov, Real Options: APractitioner's Guide,Texere LLC (2001 & 2003 reprinting).

Coltrell, Tom, and Gordon Sick, "Real Options and FollowerStrategies: The Loss of Real Option Value to First-MoverAdvantage," The Engineering Economist, 47:3 (2002),pp. 232-263.

Enke, David, "Real Options for Deregulated Electricity Markets,"Proceedings of 24"' AnnualASEM Conference (October 2003),pp. 505-514.

Fschenbach, Ted, Cases in Engineering Economy, John Wiley(1989).

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Economist, 44-A (1999a), pp. 1-38.Herath, Hemantha S.B.,and Chan S. Park,"Real Options Valuation

and Its Relationship to Bayesian Decision-Making Methods,"The Engineering Economist, 44:1 (1999b), pp. 1-38.

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Lewis, Neal, and David Spurlock, "Volatility Estimation ofForecasted Project Returns for Real Options Analysis,"Proceedings of 25"' Annual ASEM Conference (October 2004),pp. 583-592.

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McDonald, Robert L.,"Real Options & Rules of Thumb in CapitalBudgeting," Project Elexibility, Agency, and Competition, Eds.Michael J. Brennan and Leno Trigeorgis, Oxford UniversityPress (2000).

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18 Engineering Management Journal Vol. 19 No. 4 December 2007

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About the AuthorsE.R. "Bear" Baker, IV, PhD, received his doctorate in systemsengineering and his masters and baccalaureate degrees inphysics from Clemson University. He is a profes.sor in theCollege of Business and Public Policy at the University ofAlaska Anchorage. He has served as dean of engineeringat the Oregon Institute of Technology, and on the facultiesof UAA, UAF, and Clemson. His industrial experience withFluor Daniel, Simons Technology, and others includes projectand management consulting primarily in manufacturing,supply chain management, and resource extraction. He hasheld numerous leadership positions, most recently as VP oftbe technology division for Amec (world's second largestengineering firm).

Ted Eschenbach, PE, PhD, received the MCE degree in1998 from the University of Alaska Anchorage. His mastersin operations research and his doctorate in industrialengineering are from Stanford University. He is the principalof TGE Consulting, an emeritus professor of engineeringmanagement at UAA, and the founding editor emeritus of

the Engineering Management journal. He is the author or co-author of engineering economy texts currently published byOxford University Press.

Foseph C. Hartman, PE, PhD, received his PhD in 1996and MS in 1994 in industrial engineering from the GeorgiaInstitute of Technology and his BS in general engineeringfrom the University of Illinois at Urbana-Champaign in1992- He is a professor in tbe Department oi" Industrial andSystems Engineering at the University of Florida and servesas department chair. His research interests are in economicdecisions analysis and dynamic programming. He is editor ofThe Engineering Economist,

Morgan Henrie, PMP, PhD, received his doctorate inengineering management from Old Dominion Universityand his master of science in project management fromThe George Washington University. He also holds BSEEand BA in technology management degrees. Mostrecently, as the principal to MH Consulting, Inc., he hasprovided project management services both nationallyand internationally to the oil and gas industry and thetelecommunication industry.

Neal Lewis, PhD, received his doctorate in engineeringmanagement in 2004 and BS in chemical engineering in1974 from the University of Missouri-Rolla, and his MBA in2000 from the University of New Haven. He is an associateprofessor in the School of Engineering at the University ofBridgeport. He has over 25 years of industrial experience,having worked at Procter & Gamble and Bayer. Prior to UB,he taught at UMR, UNH, and Marshall University.

Contact: Ted Eschenbach, TGE Consulting, 4376Rendezvous Circle, Anchorage, AK 99504; ph: 907-333-7817;fax: 907-337-2928; tedel@ak.net

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