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Project management under risk: Using the real options approach to evaluate flexibility in R&D

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Project management under risk: Using the real options approach to evaluate flexibility in R&D
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  See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/227447363 Project Management Under Risk: Using theReal Options Approach to Evaluate Flexibility in R...D  Article   in  Management Science · January 2001 DOI: 10.1287/mnsc.47.1.85.10661 · Source: RePEc CITATIONS 313 READS 1,096 2 authors: Arnd HuchzermeierWHU Otto Beisheim School of Management 71   PUBLICATIONS   1,348   CITATIONS   SEE PROFILE Christoph H. LochUniversity of Cambridge 109   PUBLICATIONS   4,457   CITATIONS   SEE PROFILE All content following this page was uploaded by Arnd Huchzermeier on 11 January 2017. The user has requested enhancement of the downloaded file. All in-text references underlined in blue are added to the srcinal documentand are linked to publications on ResearchGate, letting you access and read them immediately.  Project Management Under Risk:Using the Real Options Approach toEvaluate Flexibility in R&D Arnd Huchzermeier • Christoph H. Loch WHU–Otto Beisheim Hochschule, Burgplatz, 56179 Vallendar, GermanyINSEAD, Boulevard de Constance, 77305 Fountainbleau, Franceah@whu.edu • christoph.loch@insead.fr M anagerial flexibility has value in the context of uncertain R&D projects, as manage-ment can repeatedly gather information about uncertain project and market charac-teristics and, based on this information, change its course of action. This value is now wellaccepted and referred to as “real option value.” We introduce, in addition to the familiar realoption of abandonment, the option of corrective action that management can take during theproject. The intuition from options pricing theory is that higher uncertainty in project pay-offs increases the real option value of managerial decision flexibility. However, R&D man-agers face uncertainty not only in payoffs, but also from many other sources. We identifyfive example types of R&D uncertainty, in market payoffs, project budgets, product perfor-mance, market requirements, and project schedules. How do they influence the value frommanagerial flexibility? We find that if uncertainty is resolved or costs/revenues occur  after  alldecisions have been made, more variability may “smear out” contingencies and thus reducethe value of flexibility. In addition, variability may reduce the probability of flexibility ever being exercised, which also reduces its value. This result runs counter to established optionpricing theory intuition and contributes to a better risk management in R&D projects. Ourmodel builds intuition for R&D managers as to when it is and when it is not worthwhile todelay commitments—for example, by postponing a design freeze, thus maintaining flexibil-ity in R&D projects.( Real Options; R&D Projects; Project Evaluation; Decision Trees; Stochastic Dynamic Programming; Managerial Flexibility; Project Management ) 1. Introduction andLiterature Overview Most investment decisions (and R&D projects in par-ticular) are characterized by irreversibility and uncer-tainty about their future rewards: Once money isspent, it cannot be recovered if the payoffs hopedfor do not materialize. However, a firm usually hassome leeway in the  timing  of the investment. It hasthe right, but not the obligation, to buy an asset(e.g., access to a profitable market in the case of an R&D project) at some future time of its choos-ing, and, thus, it is holding an option analogous toa financial call option (Dixit and Pindyck 1994). Asnew information arrives and uncertainty about theinvestment’s rewards is gradually resolved, manage-ment often has the flexibility to alter the initial oper-ating strategy adopted for the investment. As withoptions on financial securities, this flexibility to adaptin response to new information enhances the invest-ment opportunity’s value by improving its upsidepotential while limiting downside losses relative to 0025-1909/01/4701/0085$5.001526-5501 electronic ISSN Management Science © 2001 INFORMS Vol. 47, No. 1, January 2001 pp. 85–101  HUCHZERMEIER AND LOCH Project Management Under Risk  the initial expectations (Trigeorgis 1997). Using theanalogy with options on financial assets, such invest-ment flexibility is often called a “real option.” Areal option may significantly enhance the value of aninvestment (Kogut and Kulatilaka 1994).This flexible decision structure of options is validin an R&D context: After an initial investment, man-agement can gather more information about projectprogress and market characteristics and, based on thisinformation, change its course of action (e.g., Dixitand Pindyck 1994, Lint and Pennings 1997). The realoption value of this managerial flexibility enhancesthe R&D project value; a pure net-present value anal-ysis understates the value. Five basic sources of flex-ibility have been identified (e.g., Trigeorgis 1997). A defer option  refers to the possibility of waiting untilmore information has become available. An  abandon-ment option  offers the possibility to make the invest-ment in stages, deciding at each stage, based on thenewest information, whether to proceed further orwhether to stop (this is applied by venture capital-ists). An  expansion  or  contraction option  represents thepossibility to adjust the scale of the investment (e.g.,a production facility) depending on whether marketconditions turn out favorably or not. Finally, a  switch-ing option  allows changing the mode of operation of an asset, depending on factor prices (e.g., switchingthe energy source of a power plant, or switching rawmaterial suppliers).One key insight generated by the real optionsapproach to investment is that  higher uncertainty in the payoffs of the investment increases the value of manage-rial flexibility, or the value of the real option  (Dixit andPindyck 1994, p. 11). This was also shown by Robertsand Weitzman (1981) in a sequential decision modelwithout referring to real options at all. The intuition isclear—with higher payoff uncertainty, flexibility hasa higher potential of enhancing the upside while lim-iting the downside. An important managerial impli-cation of this insight is that the more uncertain theproject payoff is, the more efforts should be madeto delay commitments and maintain the flexibility tochange the course of action. This intuition is appeal-ing. However, there is hardly any evidence of realoptions pricing of R&D projects in practice (see Smithand McCardle 1998; this is confirmed in our conversa-tions with R&D managers) despite reports that Merckuses the method (Sender 1994). Moreover, there isrecent evidence that more uncertainty may  reduce  theoption value if an alternative “safe” project is avail-able (Kandel and Pearson 1998).We view this evidence as a gap between thefinancial payoff variability, as addressed by the realoptions pricing literature, and operational uncertaintyfaced at the level of R&D management. For exam-ple, R&D project managers encounter uncertaintyabout budgets, schedules, product performance, ormarket requirements, in addition to financial pay-offs. The relationship between such operational uncer-tainty and the value of managerial flexibility (optionvalue of the project) is not clear. For example,should the manager respond to increased uncer-tainty about product performance in the same wayas to uncertainty about project payoffs, by delayingcommitments?The first contribution of this article lies in connect-ing these operational sources of uncertainty to thereal option value of managerial flexibility. In a simplemodel, we demonstrate that operational uncertainty(in particular, uncertainty in product performance,market requirements, and schedule adherence) may reduce  the real option value. We interpret this coun-terintuitive result in terms of when the underlyinguncertainty is resolved: If operational uncertainty isresolved  before  decisions are made and costs or rev-enues are incurred, flexibility can be applied to pro-tect the project against a downside. In this case, moreuncertainty enhances the option value of manage-rial flexibility. However, if operational uncertainty isresolved  after  decisions are made, or if it reduces theprobability that flexibility is useful, more variabilityreduces the ability to respond, and thus diminishesthe option value of flexibility.As a second contribution, we extend the usual tax-onomy of types of real options (delay, abandon, con-tract, expand, switch) by “improvement.” Midcourseactions during R&D projects to improve the perfor-mance of the product (or to correct its targeting tomarket needs) are commonly used. The availabilityof such improvement actions represents an additionalsource of option value. 86  Management Science /Vol. 47, No. 1, January 2001  HUCHZERMEIER AND LOCH Project Management Under Risk  The literature on real options is quite extensive—readers are referred to textbooks such as Dixit andPindyck (1994) or Trigeorgis (1997) for overviews.Most applications of real options have been in thearea of commodities (such as oil exploration) becausefinancial markets are well developed in this envi-ronment and allow replication of risks by tradedassets. Recently, research has been carried out on theapplication of real options pricing to R&D projects(e.g., Brennan and Schwartz 1985, Faulkner 1996,McDonald and Siegel 1985, Mitchell and Hamilton1988, Teisberg 1994). 2. Five Types of OperationalUncertainty Figure 1 shows a simple conceptual picture of thedrivers of project value: An R&D project is character-ized by its lead time, its cost over time, and the result-ing product performance. The market is characterized by its payoff from the project (caused by market sizeand attractiveness) and by its performance require-ments, indicating how the payoff increases with prod-uct performance. Project and market characteristicstogether determine the project value. Formally, wecan express this as follows: A project’s value  V   is afunction of five “value drivers” which will be furtherdefined in §3: V   = f  (performance, cost, time, marketrequirement, market payoff). (1)Real options theory has shown that  uncertainty  inthe market payoff enhances the project value  V   if management has the flexibility to respond to con-tingencies. It creates option value in the presence of uncertainty because it can eliminate the payoff down-side while retaining the benefits of the upside. Thisis known to R&D managers, although rarely formallyvalued. When the market potential of a project isunknown, managers strive to  delay  decisions in orderto be able to react to new market information, andthey know that this flexibility has value (e.g., delayingthe specification freeze or the commitment to an engi-neering change, Bhattacharya et al. 1998 or Terwieschet al. 1999).The question we examine in this article is whetherthis insight holds as well for uncertainty in theother value drivers in Equation (1). Each of thefive drivers is typically characterized by uncertainty,which is graphically represented in Figure 1. Uncer-tainty corresponds to  stochastic variability  of param-eter distributions, and in the remainder of thisarticle, we use uncertainty and (stochastic) variabilityinterchangeably.1.  Market Payoff Variability . The market payoff (e.g.,price and sales forecast) depends on uncontrol-lable factors such as competitor moves, demographicchanges, substitute products, etc. It has, therefore, asignificant random (unforeseeable) component.2.  Budget Variability . This refers to the fact thatthe running development costs of the project arenot entirely foreseeable. Budget overruns are com-mon, and less frequently, underbudget completionalso occurs.3.  Performance Variability.  This corresponds touncertainty in the performance of the product beingdeveloped. Initially targeted performance often can-not be fully achieved, as trade-offs must be resolvedamong multiple technical criteria, which togetherdetermine performance in the customer’s eye. Thegreater the technical novelty of a product, the higheris this uncertainty (Roussel et al. 1991).4.  Market Requirement Variability . This correspondsto uncertainty about the performance level required by the market. Performance targets for a product areoften only imperfectly known especially for concep-tually new products (see Chandy and Tellis 1998 orO’Connor 1998).5.  Schedule Variability . The project may finish unpre-dictably ahead of or behind schedule. In the lattercase, reduced market payoffs (in terms of marketshare or prices) may result, as empirical work shows(Datar et al. 1997).The influence of variability in these operationaldrivers (in addition to variability in market payoffs)on the value of managerial flexibility has not beenexamined. It is important to understand the impact of operational drivers because often, different functionalmanagers in an organization are responsible for thedifferent drivers. For example, a project manager may Management Science /Vol. 47, No. 1, January 2001 87  HUCHZERMEIER AND LOCH Project Management Under Risk  Figure 1 Five Types of Operational Variability control project cost, project time, and product per-formance; a marketing manager may be in charge of understanding and influencing performance require-ments; and a finance manager may be responsiblefor the budget approval. It is important for them tounderstand in which cases managerial flexibility cre-ates value. Only then is it worth postponing com-mitments to maintain flexibility. After setting up our basic model in §3, we show in §§4.1 and 4.2 thatincreased variability in market payoffs, as well asin budgets, may indeed enhance the option valueof managerial flexibility, consistent with option pric-ing theory. The other types of operational variability,however, may have the effect of   reducing  the value of flexibility, as we show in §§4.3 to 4.5. 3. The Basic Model 3.1. Contingent Claims Analysis The real option value of managerial flexibility can be evaluated using contingent claims analysis, devel-oped for pricing options in financial markets. Thisapproach, however, requires a complete market of risky assets capable of   exactly 1 replicating the project’s 1 Here, “exactly” means for every sample path of the realization of the uncertainty. risk by the stochastic component of some traded asset(Dixit and Pindyck 1994, p. 121). Such replicabilityoften does not apply in R&D projects, whose risksare typically idiosyncratic and uncorrelated with thefinancial markets. Merton (1998) proposes an approx-imation where a dynamically traded asset portfoliois used to  track   the project value as closely as pos-sible. The approximating portfolio can then be usedto derive an option value from the financial markets.This is complex and beyond the scope of this article,as the key parameter continuously tracked during theproject is product performance (see below), which isa nonfinancial parameter.We therefore revert to an equivalent approach tooption evaluation, dynamic programming (Dixit andPindyck 1994, p. 7; Smith and Nau 1995), which doesnot require asset replication. Thus, we develop in thissection a dynamic programming model of an R&Dinvestment. 2 The drawback of the dynamic programmingapproach is that it does not address the questionof the correct risk-adjusted discount rate. Dynamic 2 Smith and McCardle (1998) propose an “integrated” approach foroil exploration projects, where they use option pricing for risks thatcan be replicated in the market and dynamic programming for risksthat cannot be priced. 88  Management Science /Vol. 47, No. 1, January 2001
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