managing risk and uncertainty in complex capital projects

The Quarterly Review of Economics and Finance44 (2004) 751–767

Managing risk and uncertainty in complexcapital projects

Todd M. Alessandria,1, David N. Fordb,2, Diane M. Landerc,3,Karyl B. Leggiod,∗, Marilyn Taylore,4

a Whitman School of Management, Syracuse University, Syracuse, NY 13244, USAb Department of Civil Engineering, Texas A&M University, College Station, TX 77843-3136, USA

c School of Business, Southern New Hampshire University, 2500 North River Road,Manchester, NH 03106-1045, USA

d Henry W. Bloch School of Business and Public Administration, University of Missouri at Kansas City,Kansas City, MO 64110, USA

e Gottlieb/Missouri Chair of Strategic Management, Henry W. Bloch School of Business and PublicAdministration, University of Missouri at Kansas City, Kansas City, MO 64110, USA

Received 3 February 2004; accepted 25 May 2004Available online 12 October 2004

Abstract

In evaluating capital budgeting decisions, quantitative approaches, such as traditional discountedcash flow modeling and real options valuations, are useful when there is a presumed probabilitydistribution for the future forecasted outcomes or for when there are lower levels of uncertainty. Asuncertainty increases and forecasting becomes difficult, the value of financial modeling techniquesdecreases. Borrowing from the strategic management literature, we argue that it may be useful toemploy a qualitative approach to evaluate capital projects when faced with high levels of uncertainty.In order to illustrate our argument, we use a derivative of scenario planning and qualitative real optionsto evaluate non-quantifiable factors in a project for the National Ignition Facility.© 2004 Board of Trustees of the University of Illinois. All rights reserved.

∗ Corresponding author. Tel.: +1 816 235 1573; fax: +1 816 235 6606.E-mail addresses:[email protected] (T.M. Alessandri), [email protected] (D.N. Ford),

[email protected] (D.M. Lander), [email protected] (K.B. Leggio), [email protected] (M. Taylor).1 Tel.: +1 315 443 3674; fax: +1 315 443 5457.2 Tel.: +1 979 845 3759; fax: +1 979 845 6554.3 Tel.: +1 603 668 2211x3325; fax: +1 603 645 9737.4 Tel.: +1 816 235 5774; fax: +1 816 235 2206.

1062-9769/$ – see front matter © 2004 Board of Trustees of the University of Illinois. All rights reserved.doi:10.1016/j.qref.2004.05.010

752 T.M. Alessandri et al. / The Quarterly Review of Economics and Finance 44 (2004) 751–767

JEL classification:D8; D81; G13; G31

Keywords:Qualitative analysis; Scenario planning; Real options; Capital budgeting

1. Introduction

Boards of Directors, executives, and managers need to address the critical nature of riskand uncertainty in the decision-making process. Identification of the risks and uncertain-ties inherent in a proposed action, assessment of their impact on the possible outcomes,and design of contingency plans to manage them are essential for making sound businessdecisions. Without completing these activities, decisions made and undertaken are likelyto be sub-optimal ones, leading to organizations being less competitive in the marketplace.Furthermore, in the wake of the fall of a number of organizations such as Enron, Worldcom,Parmalat, and HealthSouth, the issue of risk management and its implication for corporategovernance has become salient and more critical for decision makers to address.

Determining if investment decisions add value to a firm represents a research focus forboth strategic management and finance scholars. Both disciplines strive to identify pat-terns of decisions that lead to the creation of shareholder wealth (Alessandri, Lander, &Bettis, 2002; Bettis, 1983; Kester, 1984; Myers, 1984). The traditional finance perspectivefocuses on the valuation of risky investment decisions through quantitative frameworkssuch as discounted cash flow (DCF) models and real options analysis (ROA). Strategistsfocus on the qualitative aspects of projects relating to uncertainties or contingencies that canbe identified and evaluated through a framework such as scenario planning. However, thedifferent theoretical lenses and varying empirical approaches in these two academic disci-plines have hindered the understanding of the overall process of strategic decision-making.This research attempts to help narrow this strategic management/finance academic divide,focusing on improving organizational decision-making when evaluating capital projects,whether the issues are traditionally considered primarily from the finance domain or fromthe strategic management domain.

Definitional issues regarding risk and uncertainty have haunted both strategic manage-ment and finance academic disciplines for decades. Oftentimes risk and uncertainty havebeen used interchangeably in the literature, yet they are in fact distinct theoretical constructs(Alessandri, 2003; Knight, 1921; March & Simon, 1958). Given this confusion, it is neces-sary to define how we use the terms risk and uncertainty. For the sake of this research,riskrepresents the “probability distribution of the consequences of each alternative” (March &Simon, 1958, p. 137). This definition is very similar toKnight’s (1921)early work on riskand uncertainty. A probability distribution implies an ability to quantify the consequences ofan alternative. On the other hand,uncertainty, according to March and Simon, is when “theconsequences of each alternative belong to some subset of all possible consequences, butthat the decision maker cannot assign definite probabilities to the occurrence of particularoutcomes” (1958, p. 137).1 This definition also corresponds to the earlier work ofKnight

1 A concrete example of the differentiation between risk and uncertainty is described in Section5, evaluatingthe NIF project.

T.M. Alessandri et al. / The Quarterly Review of Economics and Finance 44 (2004) 751–767753

(1921), and implies a lack of confidence relating to probability estimates or an inability toassign estimates at all, i.e., complete ambiguity. It is important to note that these two con-structs are interrelated and do overlap. Furthermore, agreement on the delineation betweenrisk and uncertainty is not universal.

These definitions suggest that quantifiable factors surrounding a capital project representrisks, whereas qualitative factors that affect decision-makers’ confidence in project estimatesrepresent uncertainties. Given that many investment decisions involve both quantitativeand qualitative analyses, the results from differing methods of project evaluation must bereconciled. The questions then become: given varying degrees of certainty surroundingestimates of the drivers of project value, how do decision-makers evaluate capital projects,especially complex capital projects, and how do they address the outcomes from both astrategic management perspective and a finance perspective.

Varying levels of risk and uncertainty can affect a decision-maker’s choice of models,techniques, and processes used for making the investment decision.Courtney, Kirkland,and Viguerie (1997)suggest that managers employ different analytical tools for differentlevels of uncertainty. As uncertainty increases, these authors propose more qualitative toolsbe used. In support of Courtney et.al.,Alessandri (2003)found that managers tend to useanalytical, quantitative approaches in the face of risk to identify the optimal decision. Yet,on the other hand, as uncertainty increases, managers rely on judgment and experience toa greater extent, employing a more qualitative approach to make the decision, even thoughthey still attempt to go through the process of an analytical, quantitative analysis. Finally,Alessandri’s (2003)results show that when considering risk and uncertainty jointly, theeffect of uncertainty is dominant to that of risk.

The implication here is that analytical, quantitative tools, even ones that can modeldynamic decision-making, are not able to model the more qualitative nature of uncertainty.In our efforts to integrate financial modeling and strategic decision-making, it may be thatwe are asking the wrong question. Instead of trying to quantify strategic management, it maybe that, in certain circumstances, i.e., in the face of high uncertainty, we should be taking amore qualitative approach to the finance side of project analysis. The quantitative modelingframeworks often used for valuation purposes are useful, but their primary function may be tobetter qualitatively define, structure, and understand a project’s uncertainties. For example,the real options approach to capital budgeting is a quantitative valuation framework that canvalue dynamic decision-making. However, its usage has been limited due to implementationchallenges (Lander & Pinches, 1998). Due to implementation problems stemming from alack of data and high uncertainty,Miller and Waller (2003)propose the use of a qualitative,rather than a quantitative, real options approach, in conjunction with scenario planning, todevelop a corporate integrated risk management tool.

This paper demonstrates the role of a qualitative approach to the examination of complexcapital investment projects. The paper discusses the affects of risk and uncertainty on thedecision-making process, and the shortcomings of our current quantitative decision-makingtools in accounting for uncertainty, especially in complex capital projects. Using a majorconstruction project, The National Ignition Facility (NIF) as an example, we first describe theproject and discuss its complexity and uncertainties. We then discuss designing contingencyplans that are generated through a variation of scenario building within an organization.Lastly, we show how using a qualitative, rather than quantitative, real options analysis can


be an alternative for thinking about and better understanding the uncertainty inherent in theNIF capital project.

This paper draws upon multiple perspectives to advance the state of knowledge acrosspractice/academic boundaries and across disciplinary arenas. The goal is to advance currentthinking about the risk and uncertainty concepts as applied to strategic decision-making, andto approach the evaluation of projects from different perspectives, moving from theory intopractice. We use the example of The National Ignition Facility to illustrate how practicingplanners and managers can identify risks and uncertainties in development projects, thenuse and identify flexibility in project analysis, thus increasing their optionality and projectworth.

The paper proceeds as follows: Section2 looks at differentiating risk and uncertainty;Section3discusses scenario building; Section4discusses the real options approach to capitalbudgeting; Section5 introduces the National Ignition Facility project as well as scenariobuilding and a real options analysis application; and Section6 concludes with a discussionof the opportunities for improving our decision-making processes given uncertain businessenvironments.

2. The evaluation of investment projects—theoretical and empirical perspectives

2.1. Contrasting decision-making perspectives

Two primary perspectives relevant to the impact of risk and uncertainty on strategicdecision-making are economic rationality and behavioral theory. The rationality side istraditionally aligned with a finance/economics approach, where analyses are undertakenunder the basic market assumptions of perfect, or close to perfect, information and com-plete markets (Eisenhardt & Zbaracki, 1992; Fisher, 1907, 1930). In fact, the traditionaldiscounted cash flow (DCF) valuation algorithm was originally derived from, and justifiedby, valuing passive investments in bonds and known cash flows. This model assumes theexpected values of the future uncertain cash flows are acceptable proxies for the cash flows’distributions, and that the expected values are given. Additionally, the discount rate is as-sumed known, constant, and a function of only project risk. Under such assumptions, allof the alternatives are economically modeled and analyzed in order to reveal the optimaldecision.2

In recent years, however, more attention has been given to the behavioral literature, suchasKahneman and Tversky (1979, 2000), March and Shapira (1987), Benartzi and Thaler(1995), Thaler, Kahneman, Tversky, and Schwartz (1997), Ordean (1998), Palmer andWiseman (1999), andLeggio and Lien (2002). This literature argues that decision-makersmay not act according to the principles of rationality when faced with risky decisions. Thepresence of uncertainty appears to affect the decision-making process as well, partially dueto the difficulty in gathering and processing information (Maritan, 2001; Sharfman & Dean,1997).

2 We assume the reader is familiar with discounted cash flow analysis. For a primer on DCF, seeBrealey andMyers (2000).


Exhibit 1Summary ofCourtney et al. (1997)proposed residual uncertainty framework

Level Description Suggested analytical tools

1. Clear Enough Future A single forecast precise enoughfor determining strategy

Market research, value chainanalysis, DCF models

2. Alternate Futures A few discrete outcomes that definethe future

Decision analysis, option valuationmodels, game theory

3. Range of Futures A range of possible outcomes, butno natural scenarios

Scenario planning, technologyforecasting

4. True Ambiguity No basis to forecast the future Analogies and pattern recognition,nonlinear models

Existing empirical evidence suggests that higher uncertainty is associated with a morebehavioral approach to decision making (Cyert & March, 1963; Dean & Sharfman, 1993;Maritan, 2001). This finding supportsCourtney et al. (1997), who argue for a multipleprocess, or contingent approach. According toCourtney et al. (1997), the standard practicein strategic planning is to lay out a precise picture of the future, or the most likely out-come, which can then be valued using a DCF model. This approach hides the underlyinguncertainties. These authors suggest a topology of multiple levels of uncertainty:

• Level 1 uncertainty– A Clear-Enough Future – is sufficiently precise for strategy devel-opment, as one can usually determine a single strategic direction.

• Level 2 uncertainty– Alternate Futures – has few discrete scenarios that are possible.The possible outcomes are clear, but it is difficult to predict which one will occur.

• Level 3 uncertainty– A Range of Futures – exists when a range of potential outcomescan be identified and the range is defined by a few key variables. The actual outcome liesalong a continuum.

• Level 4 uncertainty– True Ambiguity – occurs when multiple dimensions of uncertaintyinteract to create an environment that is almost impossible to predict. These environmentstend to migrate toward one of the other three levels over time.

Courtney et al. (1997)go on to suggest that specific decision tools are more appropriateand more useful for some levels of uncertainty but not for others (seeExhibit 1). Forexample, traditional DCF models may be helpful for Level 1, and possibly Level 2, butthey are not appropriate for other levels. In general, as the level of uncertainty increases,managers should employ more qualitative approaches to manage uncertainty in the decisionprocess.

Alessandri (2003)shows that risk and uncertainty are, in fact, considered by managersto be distinct constructs, and these two constructs have different impacts, individually andjointly, on the decision-making process. That is, there exists a difference in managers’ mindsbetween risk and uncertainty and how to respond to each. In terms of individual effects,when managers face risk, they tend to use more analytical, quantitative approaches, andfocus on finding the best decision. This is the typical risk-aversion argument: managersare conspicuously sensitive to risk. Not surprisingly, as the risk levels increase, managersincrease their efforts to both evaluate the risk and find a decision that is going to minimizeor hedge the risk as much as possible. Alternatively, in the presence of uncertainty, man-


Exhibit 2Joint effects of risk and uncertainty on investment decision processes

Low uncertainty High uncertainty

High risk Process: highly analytical Process: qualitative, judgment-orientedObjective: optimal alternative Objective: acceptable alternative

Low risk Process: less analytical Process: qualitative, judgment-orientedObjective: optimal alternative Objective: acceptable alternative

agers employ more judgmental approaches, relying upon intuition or experience in makingtheir decisions. What is interesting here is that managers still went through the motions ofcompleting the standard DCF analyses and had little initial intent to rely on their intuitionor experience.

However, many projects involve elements of both risk and uncertainty, i.e., a joint effect.Analysis of the joint effects of risk and uncertainty reveal that uncertainty effects weredominant (Alessandri, 2003) (seeExhibit 2). Under low uncertainty, the risk decision pro-cess relationships discussed above hold: with higher risk, managers use a more rational oranalytical approach, focusing on the optimal decision. But, when there are high levels ofuncertainty, no matter how high or low the risk level, managers appear to rely on judgmentand experience to justify decisions that have acceptable outcomes. It is important to note thatsome notions of uncertainty represent a lack of information, and the more that was unknownabout a project, the less inclined managers were to rely on either traditional quantitativeor qualitative decision-making tools, and the more inclined managers were to depend uponpast experience and intuition.

Alessandri’s (2003)empirical results suggest managers are not following traditionalfinancial theory in analyzing capital budgeting proposals. The work ofCourtney et al.(1997)andAlessandri (2003)support the notion that traditional quantitative tools need tobe expanded or alternative processes need to be used under conditions of high uncertainty.Yet, we argue that quantitative methods can provide the framework for defining, structuring,and understanding project uncertainties.

2.2. New directions for managing uncertainty

There are a variety of tools managers can use to manage uncertainty. In this paper, ourfocus is on two as suggested byMiller and Waller (2003): scenario planning and ROA. Thefirst qualitative tool comes from the strategy area. Scenario planning provides managers witha structured way to analyze and evaluate uncertainties and contingencies as well. In this pa-per, we differentiate between scenario analysis in the sense of its use in finance/accounting,scenario building in the sense of internal, project based situations which are not readily quan-tifiable, and scenario planning in the sense of external, long-range planning. The processes ofscenario planning and scenario building are similar. The second tool comes from the financearea. The real options approach to capital budgeting is a quantitative tool that allows one tovalue dynamic decision-making. However, it also has potential value as a qualitative tool forhelping managers think in terms of contingency planning, managing flexibility, and design-ing optionality into large capital investment projects. Kester (1994) noted such competitive


advantages and recently, we see the advantages of the real options tool becoming recog-nized as useful in the strategy literature (Abner & Levinthal, 2004; Botteron, 2001; Kogut& Kulatilaka, 2004; Leggio, Taylor, Bodde, & Coates, 2001; Leurhmann, 1998; McGrath,1999; McGrath, Ferrier, & Mendelow, 2004; Zardkoohi, 2004). The second qualitative toolcomes from the strategy area. Scenario planning provides managers with a structured wayto analyze and evaluate uncertainties and contingencies as well.

These two complementary tools – scenario planning, real options – offer managers theability to qualitatively assess risks and uncertainties.Miller and Waller (2003)suggest thatan integration of these two approaches can be used to help a company develop a corporaterisk management program by helping decision makers identify and integrate exposures atthe divisional level. We argue that both approaches can also be used at the project level tohelp manage uncertainty in complex capital projects.

3. Scenario planning

Scenario planning is a qualitative approach to decision-making, used when primaryvariables are not easily quantifiable, and involves the creation of coherent stories aboutpossible futures, with the goal of identifying and evaluating contingencies, uncertainties,trends, and opportunities. It was originally developed during the 1970s by Royal DutchShell. The technique was utilized within firms in the early 1970s to generate alternativeplausible scenarios regarding the longer-term future of the external environment. Scholarsin the strategy realm have pointed out its benefits and problems as a planning tool (Henson,2003; Jennings, 2002; Kennedy, Perrottet, & Thomas, 2003; Mason, 2003; Millet, 2003;More, 2003; Schoemaker, 1993, 1995; Wack, 1985). Today, as organizations have soughtways to manage uncertainty, it has been receiving renewed attention.

Generally, the process involves constructing plausible scenarios of the future environmentand then designing alternative strategies that would be appropriate under those scenarios.Experts in the scenario planning process suggest the creation of three to five scenarios. Theprocess of establishing the scenarios generally involves the following phases:

• Identification of environmental driving forces• Selection of significant forces (or bundles of forces)• Consideration of the forces to establish scenarios• Writing of the “stories” or scripts• Establishing signposts (i.e., leading indicators suggesting that the environment might

indeed be going in the direction of a specific scenario)

Numerous benefits of scenario planning are cited by facilitators, consultants, and ex-ecutives. For example, scenario provides: (a) expanded mutual understanding of potentialenvironmental discontinuities; (b) greater teamsmanship as a result of the process and de-velopment of a common language; and (c) increased nimbleness of the firm that alreadyhas contingent plans articulated. In short, the scenario planning process brings two majorbenefits to our discussion. First it helps in identifying the long-term risks and uncertaintiesthat impact on the firm as a whole, and second, it assists the executives in defining theiralternatives and options, i.e., increasing their optionality. And, in so doing, scenario plan-


ning contributes to the firm’s ability to survive, even under hostile conditions, and to moreproactively exploit more munificent environments. Scenario planning can be limited by thenumber of scenarios proposed, and, although the technique is often used at the firm level,more frequently what is needed is a project-level perspective.

4. Real options analysis: quantitative and qualitative

ROA3 is a controlled means of systematically identifying the interplay between interme-diate outcome states and alternative managerial actions and specifically valuing managerialflexibility. The investment or disinvestment decisions often involve capital assets, and mostdecisions can be viewed as options on real assets. ROA can value asymmetric payoffs, andby doing so can provide a means of valuing managerial flexibility—the ability of managersto intervene proactively to take action during the time frame when the results of previousdecisions are being played out. An option-based approach can incorporate asymmetry intocapital budgeting analyses, and it is a reasonable representation of how managers think. Thetime delayed actions managers might take would be those to enhance the upside effects orto mitigate the downside impact.

ROA can lead to a change in decision-making. The traditional DCF analysis wants allpoint estimates to be as known and certain as possible, and in DCF models, an increase inrisk is accounted for by increasing the discount rate, resulting in lower valuations. Thus,under traditional DCF reasoning, risk hurts. In comparison, option value is most oftena positive function of the volatility of the underlying asset, as, generally, an increase involatility leads to an increase in the range of possible future values for the underlying asset.As this line of reasoning quickly suggests, aggressive firms will seek projects with highervolatility because active management of those projects can create value for the firm. Underreal options thinking, as long as management can control the downside risk of a project,firms should seek risk, at least to some degree. ROA also shows that sometimes negativeNPV projects should be undertaken, given the upside potential embedded in the project.

The question we are concerned with is: how can the real options framework, an in-herently quantitative framework, be used qualitatively to improve the analyses of capitalinvestment projects with moderate to high levels of uncertainty (i.e., Level 3 or Level 4 inCourtney et al., 1997). The answer is that ROA can systematically organize the analysisand identify the uncertainties. Kemna (1993) notes that a real options analysis providesa richer framework for structuring a project and, just as importantly, brings all decisionmakers to the table, as well as providing common terminology for discussing a project.ROA allows us to reformulate the problem resulting in more insight into the project and thepotential sources of value. The primary benefit of a real options analysis may not be projectvaluation, or quantifiability, but the process of describing and understanding the project andthe uncertainty embedded therein. As both Kemna (1993) andLander and Pinches (1998)suggest, a firm can derive a tremendous amount of value from conversations among all of

3 We assume the reader is familiar with the use and valuation techniques of real option analysis. For additionalinformation or background on ROA, seeAmram and Kulatilaka (1999)or Copeland (2002) for a more completediscussion of real options.


the affected managers about project potential and outcomes. The true value of ROA may bethe process of thinking about project flexibility and project design in a more structured way,and not necessarily the resulting valuation. ROA may become unwieldy due to the numberof options embedded in the project, and, although the technique is often used at the projectlevel, what is needed more frequently is a firm-level perspective.

At this point it is important to notice the complementarity of scenario planning andROA, as suggested byMiller and Waller (2003). Although both approaches help to identifycritical exogenous variables by specifically defining and dynamically modeling the project,pushing the boundaries of possible outcomes, and allowing for designing in contingentstrategies or options, they do so in different ways. Scenario planning takes an intentionallyqualitative approach to the analysis of a project and involves the creation of coherent storiesabout possible futures. Real options, on the other hand, takes an intentionally quantitativeapproach to the analysis, now valuing the coherent stories identified. Thus, ROA, in essence,requires the scenario planning process be done and can be thought of as a follow-on pro-cess, adding detailed structuring, and allowing for richer understanding of the scenariosidentified.

We know managers consider flexibility in project valuations and are often willing to spendadditional funds to achieve flexibility. We thus argue that these two approaches – scenarioplanning and real options – can help managers identify potential areas where flexibilitycan be pursued in a project. The following example of the NIF project demonstrates theapplication of scenario planning and a qualitative real options approach to a complex capitalbudgeting problem.

5. Evaluating the National Ignition Facility Project

5.1. Risk and uncertainty

The issue we now turn to is how can practicing planners and managers use scenariobuilding and a qualitative real options approach to manage uncertainty in practice? Weuse the example of The National Ignition Facility (NIF) to illustrate how decision-makersidentify uncertainty and flexibility in project analysis, and by deliberate decision, increaseand use their optionality.

In 1996, the United States signed The Comprehensive Nuclear Test-Ban Treaty whichbanned the testing of nuclear weapons (U.S. Department of State, 2003). Testing had pre-viously been used to verify the operability of the aging stockpile of nuclear weapons and toperform specialized research. The treaty ended the use of tests for these purposes, creatinga need for new means of stockpile testing and research. To fulfill these needs, the U.S. De-partment of Energy is developing the National Ignition Facility (NIF), a nuclear explosionlaboratory. NIF will allow scientists to create what occurs during a nuclear explosion on amuch smaller scale and in controlled laboratory conditions.

NIF is a large, customized planning, design, and construction project valued at over $2.5billion. The conceptual design is to generate and direct 192 individual high-power lasersdown two bays located along each side of the facility. Precision mirrors redirect the lasersinto a target chamber and onto a target that is approximately the size of a grain of rice.


Focusing the enormous energy from the lasers onto the small target will generate nuclearreactions in the target. Auxiliary lasers and other apparatus allow the scientists to observethe impacts of the reactions. When completed, NIF will be at least an order of magnitudemore powerful than previous lasers. At the time of commitment of the Department of Energyto the project, no laboratory laser system the size of NIF had ever been built, and six majorsubsystems had not been invented or developed. Major technical innovations were requiredfor success. In short, there was a great deal of uncertainty in the project.

Project optionality became particularly important in the development of the glass slabsused to amplify the laser beams (one of the six subsystems in the NIF project) becauseof their critical role in project performance and the high uncertainty in their development.Laser glass procurement requires the production of high quality glass slabs called “blanks”,the finishing of the blanks, and the coating of the blanks. The NIF laser would be manytimes larger than existing lasers. Laser development costs increase approximately with thecube of the laser diameter, making a single large laser extremely expensive. A single laseralso concentrates risk in one project component. Therefore, instead of attempting to developa single very large laser, NIF chose a more flexible design, building many smaller lasers.This strategy required far more high quality precision glass blanks than a single laser.

Laser glass blanks used in previous lasers could be produced in batch processes dueto the relatively small size of the lasers. These processes, however, could not produce thequantity and quality of glass needed by NIF in the time available. A new glass productiontechnology had to be developed. There was a great deal of uncertainty and risk concerningwhether or how a process to manufacture laser glass of the required volume and qualitycould be developed, and at what cost since none of the existing glass companies were able tofund the development of this new technology. Therefore the NIF project managers fundedthe development of a new laser glass production technology. The NIF project managementteam’s approach to this development is the basis for our investigation of risk and uncertaintymanagement.

To better understand the distinction between the risk and uncertainty, it may be helpfulto apply these definitions in the context of the NIF project. Using our previously stateddefinition of risk, risk involves the variance in potential outcome values of the specificfactors in the NIF project. From an overall project standpoint, the NIF project faces atleast three risks—performance levels of the completed project, time required to completethe project, and the cost to complete the project. In terms of the first factor, very littlevariance exists due to the mandate of the project. The NIF project must succeed to enablethe U.S. Department of Energy to test the stockpile of nuclear weapons.4 However, the costof the project and the time to completion involve considerable variance in terms of potentialoutcomes. The NIF project had already exceeded the original budget by over $1 billion, andthe estimated time to completion had been extended five additional years. Thus, althoughfor planning purposes a single point estimate of total costs and time to completion wasrequired by Congress for funding, actually a range of potential final total cost estimates andtime to completion estimates existed. These ranges, or distributions, represent forms of risk.

4 Management’s certainty of success stems from the fact that the nuclear arsenal must be tested. Given therestrictions on testing either above or below ground, the alternative is to simulate a test in a lab setting. The project’sultimate success may come at a higher cost or at a delayed time, but the project must ultimately be operational.


The notion of uncertainty in relation to the NIF project refers to how certain/uncertainthe managers feel about the estimates. This degree of certainty varies based upon manyfactors, including the availability of information, the degree to which the project is “newand unknown” versus “similar to existing projects and familiar” to managers in analysisquantity and quality. A lack of information, or a lack of unambiguous information, increasesuncertainty (Galbraith, 1974). Furthermore, projects relating to new capabilities lead to moreuncertainty in managers’ minds than ones that are similar to existing projects (Maritan,2001). Given that the NIF project is unlike any other project, and the six subsystems had tobe developed from scratch, it would seem that uncertainty is high for the NIF project; thatis, the required point estimates of cost and time to completion were likely generated frominformation that included many uncertain factors. Changes to funding requests and timingexpectations sent to Congress support the lack of certainty regarding cost and timing.

The NIF management faced large uncertainties and was equipped with an array of plan-ning and management tools with which to address them. Uncertainty occurs at differentlevels of aggregation in large engineering projects, including the NIF project. Macro-leveluncertainties in the NIF project included the development costs of the six major subsystems,the estimated time to completion for each stage, the likelihood of successful developmentof the six systems, and the annual level of funding provided by Congress. These projectfeatures interact tightly, such as the strong impact of development success and scheduleon cost. Many of these dependencies are bi-directional. For example, reduced funding canslow progress and rates of progress can impact future funding.

Smaller portions of the project, such as the laser glass procurement, also included nu-merous uncertainties. France’s Commissariat a l’Energie Atomique is concurrently de-veloping a similar laboratory and may also need laser glass. But France has not finallyapproved and funded that project. Therefore the total demand for laser glass is risky. Theability of glass firms to develop feasible new glass production technologies and the qual-ity of the glass produced if the production technologies were feasible were uncertain, aswere costs and development schedules. The uncertainties at different levels of aggregationare also interdependent, and again, often in bi-directional ways. For example, slow laserglass production technology development could increase costs in other major systems thatmust wait on laser glass production, which may in turn impact project schedule perfor-mance and funding. Which project and laser glass uncertainties threaten the successfuldevelopment of NIF most? Which should the NIF laser glass procurement managers focustheir limited managerial efforts on? How should the uncertainties, their interdependencies,and their impacts on project behavior and performance be modeled to facilitate decision-making?

5.2. The application of scenario planning to NIF

Scenario planning is not known to have been used explicitly in laser glass technologydevelopment at NIF. However, interviews of NIF project managers reveal clear scenariodescriptions as a basis for planning. The scenario planning process is used here to formalizethe planning practices used on the NIF project, suggest actions if scenario planning had beenformally applied, and elucidate the potential impacts of its use. A set of scenarios for theNIF laser glass subsystem project is depicted inExhibit 3. Once the scenarios are written,


Exhibit 3Scenario building for the NIF decision to fund one versus two glass vendors

Company X: development of the glass manufacturing application and quality of outputSuccessful A. “Bulls eye” (possible, and provides

NIF with future flexibility of choice oflower-cost provider)

B. “X Scores” (likely, but leaves NIFdependent on one supplier)

Unsuccessful C. “Y Scores” (likely, but leaves NIFdependent on one supplier)

D. “Complete Flop” (highly unlikely,but potentially leads to the loss of theNIF project, possible loss of the con-tract to manage the national lab, andsignificant disadvantage to the nationin not being able to test its nuclearweapon supply or undertake nuclearresearch)

Company Y: development ofthe glass manufacturingapplication and quality ofoutput

Successful Unsuccessful

the executive group can then begin the process of creating strategies that are appropriate tothe scenarios. The NIF project team said (in essence), “To invest in one vendor costs $12million. Two things could happen. First the vendor could succeed. The vendor could gothrough all three steps, funded by us, develop a quality production process successfully onbudget and on schedule. Or, the vendor could fail. Vendor failure will delay the project, thedeadlines will not be met, and it is likely the entire project will be cancelled. On the otherhand, if we invest in two vendors, both of them could succeed. If both vendors succeed theproject will be successful and we will have the flexibility of purchasing laser glass fromeither of two vendors down stream. It is also possible that only one of the vendors succeedsor no vendors succeed in a reasonable time frame.” The managers in charge of the projectknew that to proceed with two vendors doubled the cost.

The NIF project managers essentially used scenario building in considering the fourscenarios inExhibit 3. Their intuitive assessment was that Quadrant D was highly unlikely,that B or C was likely, and that A could yield significant value in flexibility on an ongoingbasis. The NIF managers planned for these scenarios. If Quadrant A occurs, NIF has theability to choose the low cost glass provider, thus saving money and it has the abilityto reduce risk by purchasing a portion of laser glass from each of the two glass blankproviders. If either Quadrant B or C develops, the NIF project continues with glass providedfrom one supplier. And by thinking through the possible scenarios up front, the projectmanagers have the ability to think through their future actions to prevent Quadrant D fromoccurring. The managers believed Quadrant D would not occur because they had manytools and opportunities to take evasive action prior to its occurrence, such as increasedfunding for additional research and development to successfully create the technologies orschedule changes to provide additional time for research and development. By discussingpreventive actions, the NIF team has a plan in place to prevent Quadrant D from occurringand to be aware of the danger signs that the firm might be heading towards a Quadrant Dscenario.


5.3. Qualitative real options applied to NIF

NIF managers explicitly used real options (without using real options language) to planlaser glass technology development. For example, having the right to not purchase fromthe high cost vendor is a real option, as is being able to take evasive action to preventQuadrant D from occurring. However, their decision-making practices were far from theformal valuation tools and methods described in the majority of real options literature.This is primarily because of the complexity of the planning environment. The challengesfaced by NIF managers in managing uncertainty in the project and in procuring laser glasswere complicated by the breadth of types of input to their decision-making. NIF’s newand undeveloped glass procurement process lacked history and therefore data for decision-making. Therefore, qualitative factors and approaches had to be used in strategic decision-making. Consider, as an example, the decision whether to use one or more contractorsto develop laser glass production technology. This depends on, among other factors, thelikelihood of success by a single contractor. No data is available to estimate this uncertainty.The NIF project team must assess the performance differentials (e.g., production rates, glassquality) if both vendors succeed and NIF has the ability to purchase the laser glass fromthe low cost provider. Management of uncertainty was made difficult by the multiplicityof strategies and options. If development is staged, NIF holds an option to abandon thatwould be exercised by stopping the funding of a contractor that was forecasted to not besuccessful and continue with funding just the contractor expected to succeed. If multiplecontractors are used in parallel, NIF also holds an option to switch from a less successfulcontractor to a more successful contractor. NIF needed to decide up front if it should stagedevelopment and contract with one, two, or more companies to insure glass of sufficientquality and quantity will be available. If forecasted increases in the probability of success orquality of overall project performance exceeded the cost of staging an additional supplier,the investment would improve the NIF project. How did NIF managers actually make thesedecisions?

NIF managers developed qualitative scenario-strategy-outcome sets, each describing apossible path through the future. Path descriptions often took the form of “If-Then-Else”statements, such as “IF we fund two technology developers and one fails THEN we can usethe other developer, ELSE (if only one is funded and it fails) we have a big problem.” Manypaths overlapped by using the same decisions and sharing dependence on the resolutionof the same uncertainties. Strategies often returned managers to previously-addressed de-cisions. If explicitly and comprehensively described, the paths would aggregately describeand structure the planning environment, alternatives and outcomes in a manner similar toa decision tree. Using their knowledge, experience, and intuition, NIF managers tacitlyestimated probabilities of uncertainty resolution and valued outcomes to identify more andless attractive paths, informally valuing the available strategies and options as formalizedin real options valuation models. Using this approach the managers identified the value oftheir optionality and decided to include both staging and multiple technology developers intheir laser glass strategy.Ford and Ceylan (2002)provide additional details. Perhaps NIFmanagers were aware of this, tacitly and informally estimating the uncertainty in pricesand their impacts on the value of the embedded options, and incorporating them into theirdecision. But structuring the decision as a real option and then proceeding to quantify the


benefits or costs of investing in a second supplier under different assumptions would bedifficult.

6. Conclusion

Large complex capital budgeting projects can be difficult to assess and evaluate. De-cisions and alternatives are often many and complex, as well as difficult to quantify forvaluation purposes. Additionally, there is frequently not enough quantifiable informationavailable to perform a valuation analysis. For example, it is very difficult to put dollars onthe impact of the NIF project not being completed successfully. It is often also problematicto apply financial valuation models due to violations of the underlying assumptions (e.g.,distributional assumptions). Such practical implementation issues cause the DCF and ROAvaluations methods to be ineffective.

Moreover, and an issue for future research, is the issue that the frequent use of realoptions by development project managers, such as those on the NIF project team, violatesthe assumption that the option holder does not influence the behavior of the underlyinguncertain features that drive option value. Real options valuation traditionally and almostuniversally assumes that the option holder does not influence the uncertainties that createoption value. Several researchers extend extant real option valuation models to civil infras-tructure contexts in which this critical assumption applies (Chareonpornpattana, Minato,& Nakahama, 2004; Ho & Liu, 2003; Ng & Bjornsson, 2004; Ng, Chiu, & Bjoornsson,2002; Zhao, Sundararajan, & Tseng, 2004; Zhao & Tseng 2003). However, when productdevelopment managers use real options to control their own projects they purposefully andstrongly contradict the assumption of option holder/uncertainty independence by work-ing to manipulate the uncertainties in their projects through traditional means. Examplesof these uncertainty manipulations in project management abound, including options touse overtime or special equipment to control schedule performance, options to take sub-contracted work in-house, and construction manager at risk contracts that include optionsto change builders. The NIF example used here provides a more detailed description ofanother example, as doWard, Liker, Criatiano, and Sobek (1995)in an automobile devel-opment context. In these cases, real option decisions and project management decisions aretightly linked (seeMiller & Lessard, 2000). Therefore real options valuation models thatassume independence of option holders and underlying uncertainties may not value strate-gies accurately enough to guide planners and managers of product development projects.Improved models will explicitly include the impacts of option holder/asset managementinteractions.

Difficulties, such as those noted above, in applying quantitative real options in practice,suggests that the application of more qualitative processes such as scenario planning orqualitative real options can improve managerial decision-making. Scenario planning canhelp managers better identify the long-term risks and uncertainties that impact on the firmand assist them in defining possible alternatives and contingencies. Real options analysisis helpful in guiding management to consider the non-quantifiable value embedded in aproject by then adding detailed structuring and, thus, allowing for a richer understandingof the scenarios identified.


We found that NIF managers implicitly used a combination of scenario planning andreal options techniques to plan laser glass technology development in their complex strate-gic environment. These practitioners used primarily tacit methods, processes they design,assess, and use to choose among strategies. In short, and as Alessandri (2002) showed, theNIF case study illustrates that there are gaps between what the field of finance advocatesand what managers are actually doing (seeMiller & Lessard, 2000for more descriptions).Finally, there are numerous uncertainties that interact to affect how successful the projectis. We cannot just select one item and say that is the predictor of value. Thinking about howfactors interact to affect the value is important.

To assist the NIF project team and other managers, we need to be able to help them valueand design project optionality. We need to be able to include this multiplicity of uncertaintiesand multiplicity of options in one method to capture all of the what-ifs in a project. We alsoneed to capture realistic behaviors, and thereby capture the practical value of flexibility. Inshort, we need alternative hybrid modeling approaches. We can take our existing modelsand expand them and enrich them and bring in other modeling methodologies that mayhelp us capture some of these uncertainties. If we are to look at options from a managerialperspective, we may need to think about some expansions and different kinds of modelingmethodologies such as scenario building. Then we can use this hybrid method successfullyin finance and strategic management.

Given the information available, managers attempt to make the best decisions possible fora firm. Analysis techniques that work to reduce uncertainty or plan for uncertain outcomesare of benefit to managers. Considering optionality or potential future outcomes when afirm pursues a project helps to capture additional value in the project. It helps to identifywhat management knows, but may not be able to be quantified. Whereas finance focusesvery heavily on how do we quantify this uncertainty, the real discussion is how do we thinkabout all of our potential opportunities. It requires a thorough understanding of the projectto be able to think through all of the opportunities. It takes the best of models from the fieldsof both finance and strategic management to be able to value the quantifiable and recognizeand incorporate the qualitative factors in a project. Taking elements from both disciplinesresults in a process for firm decision makers to improve project assessment and evaluation.

The fields of finance and strategic management have developed tools and processes thathave commonalties and complementarities. The tools we have discussed are ones that usedtogether can assist executives in managing uncertainties, mitigating risks, and exploitingopportunities.

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