Economic analysis of R&D projects: An options approach

Economic analysis of R&D projects: An options approach

Herath, Hemantha S B


An emerging trend in research and development (R&D) project valuation is the use of options approach, which permits a more flexible assessment of the future growth opportunities in the entire process. The traditional DCF method when naively applied fails to capture all the future opportunities that create value, thereby resulting in an under investment in R&D. The options approach is more appropriate in a world of uncertainty because it views an R&D project as an initial investment that creates future follow-on commercial opportunities that are undertaken only if the initial R&D project is successful. Valuation of R&D projects is usually complex due to substantial uncertainties at different project phases, including the R&D phase and commercialization phases.

Several recent papers on real options indicate that valuations of R&D projects based upon an options approach have been neglected by the finance community. To help correct this deficiency, we develop a valuation model that incorporates the risk-free arbitrage features of the binomial option pricing model into a decision tree framework. We apply the model to Gillette’s new MACH3 project to illustrate how one can use the options approach rather than the conventional DCF method to value an R&D investment involving the introduction of a new product. In addition, we demonstrate how valuation can be linked to a company’s stock price to make more-meaningful economic decisions in the real world. Our approach enhances traditional economic analysis methods and thinking by linking capital budgeting decisions and stock prices within an options framework. The purpose is to demonstrate value of future opportunities for companies that strive to maintain stock price growth. In doing so, we challenge the typical engineering economic analysis that views engineering projects in isolation, thereby creating a big gap between theory and practice.


All major corporations annually allocate substantial funds for research and development (R&D). These R&D projects typically have high associated uncertainties with no immediate payoffs, which makes it difficult to economically justify such investments. Usually, R&D investments are not made on the expectation of immediate payoffs but rather on the expectations of creating future investment opportunities that will be profitable. One therefore should view R&D projects as a series of sequential decisions involving an R&D phase and a commercialization phase with different risks and uncertainties [14]. Commercialization will be undertaken only if the R&D phase is successful. R&D projects thus create opportunities to undertake commercialization, conditional on the success of R&D. The sequential nature of these investments provide decisionmakers with the choice of whether and when to undertake investment opportunities. As a result, R&D projects should be valued taking these factors into account.

Myers [16] was the first to emphasize that traditional discounted cash-flow (DCF) methods are not suited to value R&D projects because the total economic value of such investments includes an option value associated with future opportunities to commercialize or to alter course. Kester [ 10] also compares R&D projects with options that enable one to undertake new investment opportunities that create value. Morris, Teisberg and Kolbe [14] analyze a special class of R&D projects in which the expected net present value (NPV) is the same for all the projects but there are different levels of uncertainty and risk. They show that based on an options approach and with capital rationing, undertaking a riskier project is preferable. The reason is that the larger follow-on investment is undertaken only conditional on the success of R&D so any loss would be limited to the sunken investment cost if the R&D fails. Morris, Teisberg and Kolbe use simple examples and apply a decision-tree type analysis to illustrate support of their views. Luehrman [11] argues that when one decides on the amount to spend on R&D or the kind of R&D to pursue, one is really valuing opportunities. He explains that opportunities are different from assets-in-place because a decision-maker acts after resolving uncertainty rather than after making a decision and then finding out what happens. He concludes that the options approach rather than traditional DCF methods is better suited to value opportunities. Faulkner [7] provides an excellent survey of recent research on the options approach to valuing R&D investments. Using an example based on a decision-tree type analysis, he illustrates why the option framework rather than the DCF technique is better suited for valuation. He calls it the options thinking valuation. He distinguishes between a DCF mind-set and an options mind-set, emphasizing that if Western companies desire to emulate Japanese successes they should break away from the traditional DCF approach and instead adopt the options approach. In fact, Eastman Kodak is currently using an options-based approach to value R&D investments. In any event, his paper focuses more on an options approach and strategy rather than on valuation. Nichols [18] discusses using option pricing theory to evaluate R&D strategies at Merck pharmaceutical. Dixit and Pindyck [5,6] point out that R&D investments should be viewed as opportunities and recommend using an options approach to value them. Others who recommend using the options approach to value R&D include Mitchelle and Hamilton [13] and Sharp [20]. Though many of these authors have discussed or mentioned the importance of uncertainty resolution through learning and adaptation in the suggested options approach, this particular aspect has rarely been incorporated into real option valuations. Indeed, Myers [15] highlights the fact that the finance community has neglected valuation of R&D investments as options.

In this paper, we develop a valuation model based on the binomial model for pricing options on common stock for R&D projects. Our objective is to demonstrate that an option-based valuation approach is not only useful but also better than the traditional DCF method. We also demonstrate that the valuation of investment opportunities can be linked to a company’s stock price to make meaningful economic interpretations that are applicable in the real world. Our approach thus enhances traditional economic analysis. Luehrman [11] states that for companies opportunities are frequently the most valuable assets they own. For example, Microsoft’s market capitalization is more than 100 times its book value. Our objective is to highlight the value of future opportunities for companies that strive to maintain stock price growth. We show in particular that sequential exercising of real options can create stockholder value and that the time at which the real options are exercised is important. In this way, we challenge the conventional view that considers engineering projects in isolation. We further illustrate that one can make a stronger case for defending project proposals. We apply our model to Gillette’s new MACH3 project to demonstrate that one could obtain more meaningful economic interpretations by using the options approach rather than the traditional DCF method to value R&D projects. The MACH3 project is presently in the marketing phase. The reasons, however, for using this real-life example are to illustrate how Gillette in 1987 could have applied the options approach to evaluate the R&D investment and why research-based companies like Gillette should adopt the options approach for future R&D projects. The paper is organized as follows. First, we present the valuation model that combines risk-free arbitrage in option pricing and the decision-tree framework. Then we apply the model to a real-world situation by using Gillette’s R&D project to develop a new shaving system (MACH3) as an example. We also discuss how the value of an investment opportunity can be linked to a company’s stock price to provide meaningful economic interpretations. Finally, we discuss the sensitivity of the results on real option values and Gillette’s stock prices.


An R&D project to develop a new product has a sequence of distinct phases. These consist of an initial stage involving the decision to invest in research, a development phase involving prototype development and testing, and a commercialization phase involving construction of manufacturing plants, processes and product launch through advertising and marketing. For evaluating R&D projects, we will identify two distinct phases, an R&D phase and a commercialization phase. This approach is consistent with the one Morris et al. [14] and Faulkner [7] adopted.

As discussed earlier, the sequential nature of R&D investments gives rise to characteristics that are displayed by options. For example, such investments are not usually undertaken for immediate returns, but instead on the expectation that longer-term growth opportunities exist. These future investment opportunities entail growth options that add value when exercised optimally, thereby enabling companies to maintain continuous stock price growth. Examples of a single project’s effect on share prices are common in the pharmaceutical industry. One such example is the much publicized drug Viagra of Pfizer.

R&D projects typically have greater degrees of associated uncertainty arising from specific risk related to both R&D outcomes and to commercialization outcomes. The commercialization decision is undertaken only after resolving uncertainty in the R&D stage. We may, therefore, view R&D investments from an options perspective in which the commercialization venture is considered as an opportunity to invest. An R&D investment can be compared to a call option involving a future commercialization decision to exercise the option to invest only when the R&D outcome is successful. Otherwise, the company need not commit to the full investment [14]. Based upon this analogy, an R&D investment can be viewed as cost (lO) of a real option in which the commercial project proceeds only if the R&D succeeds. More specifically, the investment cost to commercialize the new project can be viewed as the exercise price (I,), and the present value of the future cash flows (V) from commercialization can be viewed as the asset value. The date the new product is introduced into the market can be viewed as the exercise date. While we have assumed that a commercialization decision is likely to be made at time T” a decision-maker could also consider the option to delay the commercialization decision. The option to wait in such instance has value as long as the commercialization option is not exercised. To capture the sequential nature of an R&D investment and the resulting commercialization opportunities we can use a decision-tree framework. FIGURE 1 is a schematic depiction of all the relevant decisions and uncertain outcomes for a typical R&D project to develop a new commercial product.

To describe the uncertainty associated with an R&D outcome, we assign the following probabilities. A successful R&D outcome has probability (P (S) = w), whereas an unsuccessful R&D outcome has probability (P(F) = 1 – w). Notice, however, that in general we can analyze the decision tree for any distribution of R&D outcomes and any number of R&D stages. Here, we consider a single R&D stage only for simplicity. To describe the uncertainty of the commercial venture, we assume that the gross project value (V) takes one of two values.’ A gross project value of (V +) with probability (q) if the market for the new product is favorable, and a value (V -) with probability (1 – q), if the market for the new product is unfavorable. This approach is consistent with the standard binomial stock option pricing model. To price the R&D option to undertake the commercial project if the R&D outcome is successful, we apply the one-period binomial model for valuing real options that is based on the risk-free arbitrage pricing principle. Trigeorgis and Mason [21] and Trigeorgis [22] provide excellent illustrations for applying the binomial model for valuing real options, such as the option to defer, option to expand, and option to contract. In the next section, we summarize a binomial model for valuing real options due to Trigeorgis and Mason [21].


The binomial model for pricing options on common stock is a discrete-time model and uses a tree representation to depict the movement of the stock price over time. It is based on the assumption that there are market opportunities to create the desired payoff patterns for options using traded securities.2 In extending the binomial model to value real options one assumes that both the gross value of a fully constructed plant and the corresponding stock price follow a random walk.3

Suppose the paths of the gross value of a fully constructed plant V and the price of the plant’s twin security S are as follows.4 The gross value V and the stock price (S) at the end of period one are assumed to take one of two values: V + (or uV), S + (or uS) with probability q or V – (or dV), S – (or dS) with probability 1 -q. The gross project value, however, is not the value of the future investment opportunity with respect to starting construction of a new plant. Instead, the value to equity holders of starting construction of a new plant (E) will follow a path that is perfectly correlated to the paths of V and S.5 Therefore, the value of an investment opportunity one period forward is either (E +) with probability q and (E -) with probability 1 -q, as FIGURE 2 shows.

We can now use the standard hedging idea in pricing options on common stocks. Assume that an investor can construct a hedge portfolio of (n) shares of the twin security S financed by ($B) in risk-free bonds to replicate exactly the opportunity to build in the future a new plant independent of whether the project would do well S + or poorly S -. In this market equilibrium approach, which has no risk-free arbitrage opportunities, the investment opportunity E should have the same value as the equivalent portfolio. See Trigeorgis, [21, 22].

The cost of constructing the hedge at the current time is nS – B. The value of this portfolio at the end of one period would be either nS +- Br with probability q, or nS – – Br with probability 1-q. Because the hedge is chosen to exactly replicate the call value at the end of one period, E + = nS + – Br and E -= nS – – Br, where (r) is one plus the risk-free rate. These two equations yield the following expressions for the values of n and B:

No arbitrage opportunity implies that the current value of investment opportunity E can be neither less than the portfolio nor greater than the portfolio. In equilibrium, therefore, the current value of the investment opportunity should be equal to the portfolio (i.e., E = nS – B). Substituting the values for (n) and (B) in these equations yields the following exact formula for the value of the investment opportunity:

where p is the risk-neutral probability as defined in [3].

Notice that the formula is independent of the probability q. Although it was assumed that a stock’s price would take one of two values S + and S -, with probabilities q and 1 -q, respectively, this was never used in the risk-free arbitrage pricing method to value the call. In other words, the risk preferences of investors do not matter since in the binomial approach one can always construct a hedge portfolio and use it with the replication argument to price an investment opportunity under equilibrium conditions [3].


To apply the binomial model, first we need to develop the binomial lattice when the values of S and V in future periods are unknown. In our example, the required binomial lattice is for only one period, although the approach can be easily extended for multiple periods. To develop the lattice, we need to compute the values for (u), (cd) and (p), which can be done easily with the well-known formulas [3] for pricing stock options when using the binomial model. The following formulas are based on a discrete approximation to the Black and Scholes [1] continuous-time model, which is reasonable when (Delta)T is small and especially suitable for pricing options on common stock. More specifically,

where S is the stock price in the initial period (when the commercialization decision is made), (r) is the one plus risk-free rate and (o) is stock-price volatility or the standard deviation of proportional change in stock price that can easily be obtained from historic stock price data.


To value the R&D option associated with a commercialization decision, we can combine the one-period binomial model and the decision-tree framework by making the following assumptions as outlined in [21]:

The commercialization project will be 100% equity financed;

Gross project value (i.e., the present value of future cash flows V of a similar project currently in operation) follows a multiplicative binomial process and is perfectly correlated to the stock price S;

The opportunity to commercialize the new product E is perfectly correlated to both V and S; and

The volatility of the stock is assumed to remain constant over time.

The R&D investment, I^sub o^, is treated as the cost of a real option to commercialize the new product if the R&D is successful. If the R&D is unsuccessful, then one would not undertake the investment to commercialize and the resulting loss is limited to the initial R&D costs or Io. The gross value V is the base level of operation of a similar project at the time of the commercialization decision. The initial R&D investment provides a company an option to invest l^sub c^ to receive an (x%) increase over the base level of operation V. Therefore, the value of an opportunity to introduce a new product to equity holders is equal to E = max[xVI, 0]. If the market for the new product is favorable after one year, then the value of the investment opportunity to equity holders would be E + = max[xV + – I, OJ. Similarly, if the market for the new product is unfavorable, then the value of the investment opportunity to the equity holders would be E – = max[xV – – I, 0]. The R&D investment opportunity including a real option to commercialize the new project, when R&D is successful, is known as the strategic NPV (SNPV). This is given by the following formula:


With the traditional DCF approach, we may value the R&D investment using the expected value criterion, which is different from the options approach, because the asymmetry in payoffs is not taken into consideration. The R&D project would not be viewed as an initial investment that would create future opportunities to undertake commercialization conditional on success at the R&D phase. Instead, the R&D investment would be valued on an expected-value basis, thereby not considering the asymmetry of the payoffs that result from opportunities one could undertake after resolving uncertainty. The value of the R&D project based on the traditional DCF method is computed as follows:

where k = (1 + r’), and r’, the discount rate based on the financial tradition, is usually estimated by determining the project’s beta coefficient and applying the CAPM. In engineering economic analysis, however, the risk-free rate is used as the minimum attractive rate of return (MARR) because the cash flows are discounted only for the time value of money. A cash-flow distribution is developed for each year that is assumed to capture all the associated risks. Uncertainty is treated differently from risk in this approach. The value of the R&D option to undertake commercialization is the real option premium (ROP), which is the difference between the strategic NPV and the conventional NPV. The ROP can be obtained using the following formula [22]:


In this section, we will demonstrate how Gillette in 1987 could have used an option-based approach instead of the traditional DCF approach to evaluate the R&D investment to develop MACH3. The MACH3 project as of mid-July 1998 is in the marketing stage. The product was launched in North America on July 1, 1998. The background information presented below summarizes some events that occurred from the initial R&D investment decision in 1987 to the MACH3 launch in July 1998.


On April 14, 1998, Gillette announced the launch of its new shaving system called the MACH3, backed by a $300 million advertising and marketing campaign, the largest in the company’s history to create a brand name to meet the top-gun image of a sleek, high-performance and aerodynamic shave. From September 1997 to April 1998, Gillette’s stock had increased 50% in anticipation of the much-awaited new shaving system.

Gillette’s CEO, Alfred Zeien, refers to the MACH3 project as the greatest R&D effort in its history. In total expenditures, it surpasses the launch of Gillette’s Sensor family of shaving systems: the Sensor in 1990, Sensor for women in 1992, current top-of-the-line SensorExcel in 1993 and SensorExcel for Women introduced in 1996. The Sensor family itself is a remarkable success story, having surpassed the Atra and Trac II, which were the major brands for more than 20 years. Since its launch in 1990, total worldwide sales of Sensor products have surpassed the $6 billion mark, with 400 million razors and 8 billion blades sold. The Sensor family’s extraordinary success has sent Gillette’s stock price rising from $15.625 in 1990 to $77 in 1996, thereby increasing the company’s market value from $3 billion to a staggering $46 billion over the same period. Gillette’s management believes that the launching of MACH3 on July 1, 1998, will further increase Gillette’s stock price into the next millennium.

The MACH3 project is the biggest project the company has undertaken in its history. It involves a decade of work and $750 million in research, development and tooling costs plus another proposed $300 million for worldwide advertising and marketing. The product is due to arrive in stores in North America and Israel by July 1, 1998, in Europe sometime in September 1998, and then worldwide by 1999. The $300 million in advertising and marketing costs is to be spent in the next 15 months, with a preliminary advertizing campaign in North America, that includes television, radio, print, outdoor and the Internet. MACH3 is a product of remarkable technology and engineering design with six new innovations, including a triple blade (which is the world’s first), single-point cartridge docking, diamond-like carbon-coated DLC blade edge (which is three times stronger than stainless steel and made with chip-making technology), indicator lubricating strip to signal when to replace cartridge, and forward pivot design so that the blades are always in an optimal shaving position. According to Gillette, it is the first and only shaving system with progressively aligned blades that extend gradually to give a perfect shave with a single stroke.

The new shaving system, however, does come with a premium price-in fact, the largest price hike for a cartridge in the history of the blade and razor market. Indeed, the MACH3 is priced to sell at 35% above the retail price of SensorExcel, which amounts to an additional $1.50 per cartridge. It is also the most aggressive price hike Gillette has ever attempted for a new razor. Yet, the new blade technology may create problems for Gillette because the blades will last longer resulting in fewer refills. To overcome the problem that the blades may be used for too long, Gillette’s design engineers introduced an indicator strip that visually signals when to replace the cartridge to get an optimal shave. Nonetheless, Gillette’s management expects a 10% drop in blade consumption due to the new cartridge’s longer life.

TABLE 1 has a product development summary for MACH3. In a prelaunch market test, 49% of recipients polled said they would definitely purchase MACH3 at its current price. Interestingly, this is twice the approval rate for Sensor during its prelaunch consumer test. Will consumers pay $1.50 extra for a shave with greater smoothness and less irritation? What happens if blade consumption drops more than 10%? These are some of the uncertainties that are typical in the commercialization phase of an R&D project; they will be resolved only with time as new information becomes available.

Consider for a moment how Gillette’s MACH3 project team was able to convince management to undertake R&D in 1987. At that time, most of the information Gillette now has of the market for refillable razors and blades would not have been available. Over time, however, Gillette would have obtained vital information on research successes, development possibilities and, most importantly, the blade and razor market for refillable razors. It is highly likely that Gillette learned much about the potential of the MACH3 project through research, prototype development and successive Sensor family product launches, which probably explains the reason Gillette management is counting on MACH3. Still remaining to overcome are undoubtedly production hurdles, pricing issues and market uncertainties.

Gillette’s successive launch of Sensor products since the first launch of Sensor in 1990 has significantly contributed to the explosive growth in cash flows and hence the market value of the company. In many respects, we may compare these successive product launches to Gillette’s management exercising real options after resolving uncertainty and then making sequential decisions. The growth options were available to Gillette because of its investments in Sensor product R&D in Careful analysis of Sensor family product launches indicates that Gillette’s management has successfully timed the exercise of its real options to maintain continuous stock price growth. As a result, Gillette’s stock price has grown at an annual compound rate of 33% from 1987 to 1997, which exceeds the Standard & Poor’s 500 (S&P 500) and the Dow Jones Industrial Average (DJIA). Convincing senior management to approve R&D budgets for projects of such magnitude as the MACH3 are not easy because Gillette’s Sensor was not even launched. Conventional DCF methods often discourage such R&D projects because there is no immediate payoff and research results could often could go either wayproceed or terminate. As already discussed, the options approach is better suited to analyze R&D projects because it considers future opportunities in the valuation process at the time of the initial R&D decision, whether or not these opportunities would be undertaken in the future. In the next section, we demonstrate how we can use the options approach to value an R&D project.


In this section, using Gillette’s MACH3 project as an example, we will illustrate how we could use the options approach to evaluate R&D projects. We assume that the data for 1998 were estimated in 1987, although we used actual data in our analysis. In the binomial approach to value a real option, one would use the gross value of a similar operation to value an investment opportunity. Because Gillette’s gross project values from its existing blade and razor operations come mainly from revenues attributable to the Sensor family of products, we may assume the blade and razor operations have comparable risk characteristics to those of MACH3. We can then use the gross project values from blade and razor operations to value the opportunity to commercialize MACH3 that will be used to evaluate the R&D investment.

In 1987, Gillette was considering whether to undertake a $200 million R&D investment to develop a new shaving system (MACH3) that would revolutionize shaving and substitute for its Sensor operations after product maturity. The R&D outcome was assumed to be known within two to three years after the initial R&D investment decision. If the R&D were successful, Gillette could introduce MACH3 in the market in 1998 on Sensor products reaching maturity.

Based upon experience, the company estimated a 70% chance of the R&D outcome being successful. If the R&D were successful, Gillette could invest an additional $850 million that would include $200 million for advertising, and building a manufacturing plant in 1998. The market for MACH3 was uncertain, with a 40% chance of acceptability being favorable. The company estimated that MACH3 would generate incremental cash flows of x% over the projected baselevel cash flows from blade and razor operations amounting to Vat that time. If the market acceptability for MACH3 were successful, Gillette expected x% over V + the projected gross project values from blade and razor operations in 1999; and x% of V – if market acceptability were unsuccessful. In retrospect, should Gillette have undertaken the R&D investment in MACH3, assuming a risk-free rate of 8%? FIGURE 3 shows the decision tree that evolves for the MACH3 R&D project.


The R&D investment for MACH3 can be viewed from an options approach with the initial investment of I^sub o^ = $200 million as the cost of an option to commercialize MACH3 in 1998 if R&D is successful. Notice that Gillette management anticipates revenue growth from blade and razor operations to slow by 1998. One can therefore view the commercialization project as an option with an exercise price of I, = $850 million producing an x% increase over the base level of blade and razor operations V in 1998. If the R&D is unsuccessful, Gillette’s management will not make the commercialization decision and the resulting loss is limited to the sunk cost of $200 million. The following assumptions are made with respect to the MACH3 R&D project.

Gillette’s stock price volatility sigma is estimated to be 28% and is assumed to remain constant. FIGURE 4 presents the binomial tree for Gillette’s stock with a stock volatility of 28% along with the actual stock prices (high).

Stock price S and the gross project value from blade and razor operations V at the time of the commercialization decision can be estimated. Both S and V follow a multiplicative binomial process consistent with the standard binomial random walk assumption for pricing options on common stocks. The gross project value of blade and razor (Sensor) operations and the stock price are perfectly correlated.

The equity claim E for the opportunity to commercialize the MACH3 project in 1998 is perfectly correlated to S and V. This assumption is required for risk-free arbitrage pricing of real options [21,22].

An economic life of 8 years is assumed for the blade and razor operations as well as all other operations. Gillette’s 1998 annual operating levels are assumed to continue throughout the project’s economic life.

A discount rate, r’= 14%, and a constant risk-free rate, rf = 8%, are assumed. Thus k = 1+ 0.14 and r = 1+ 0.08.

A constant ratio (M) of project payoff (gross or annualized) V to stock value S is assumed over time.

All gross project values are expressed in present value terms except those for 1999.


To apply the binomial model to value an R&D option for commercializing MACH3, we need to determine the stock price S and the gross project value V for 1998. FIGURE 5 presents the one-period binomial lattice for Gillette’s stock price, gross project value and equity claim. The gross annual cash flows from Gillette’s blade and razor operations during 1997 are assumed to be the annualized gross values from an identical project for evaluating MACH3. Gillette’s 1997 year-end stock price is assumed to be the beginning stock price S for 1998. The historical stock price data and the annualized gross values for 1997 are from Gillette’s 1997 Annual Report (see data in TABLE 2). Gillette annually earns revenues from several operations, which include blade and razor, toiletries and cosmetics, stationary products, Braun products, Oral B products and Duracell batteries. To evaluate the R&D option using the binomial model, we separate Gillette’s total operations into blade and razor operations denoted by (B) and all others operations (O) (which consists of toiletries and cosmetics, stationery products, Braun products, Oral B products and Duracell batteries). Gillette’s total operations (7) are the sum of these two operations.:

The data for evaluating the R&D project are:

Stock price at the beginning of 1998, S = $100

Annualized gross project value from blade and razor operations V^sub AB^ = $875 million

Annualized gross project value from other operations V^sub AO^ = $804 million

Annualized gross project value from Gillette’s total operations V^sub AT^= $1,679 million

Gillette’s annual stock price volatility sigma= 28%

r = 1.08

k =1.14



Substituting these values in EQUATIONS (5-7), we obtain the following values for u, d and the risk-neutral probability p. One can then use these values to develop the one-period binomial lattice for Gillette’s stock price and annualized gross project values. FIGURE 6 presents the annualized gross project values pertaining to each of Gillette’s operations for 1999. For example, if the market outcome is favorable, the projected stock price in 1999 is S + = uS = ($100)(1.33) = $133, and the projected annualized gross value for blade and razor operations is V^sub AB^ = $(875)(1.33) = $1,164.

To evaluate the R&D option, we need the gross values from Gillette’s overall operations rather than simply the annualized value. In doing so, we assume that Gillette’s operations continue at the current levels over an economic life of 8 years. We can then obtain the required gross values using the present value formula of an equal payment series. For example, the projected gross value from blade and razor operations when market acceptability is favorable is GV^sub B^ = V^sub AB^(P/A, 8%, 8) = 875(P/A, 8%, 8) = $5,028. Using these values, one can compute the constant ratio M of project payoff Vto stock value S for blade and razor operation, all other operations and combined operations. TABLE 3 contains the constant payoff to stock price ratios along with the projected annualized and total gross values. FIGURE 7 shows the binomial lattice for the stock price and gross project values.

Notice that the projected stock prices and both projected annualized and gross project values are perfectly correlated. These values have been obtained assuming a constant volatility for Gillette’s stock prices. To price the real option, one needs to determine the value to equity holders of the opportunity to commercialize MACH3. Based on the model, the value of the investment opportunity to equity holders is given by E = max[xV^sub B^ – I^sub c^, 0], where xV^sub B^ is the incremental gross value resulting from introducing the new shaving system. If market acceptability a year later for MACH3 is favorable after introducing the product, the value of the investment opportunity to equity holders is given by E + = max[xV +^sub R^ – I^sub c^., 0]. Similarly, if market acceptability for MACH3 in 1999 is unfavorable, the value of the investment opportunity to the equity holders is equal to E – = max[xV^sub B^ – I^sub c^ 0]. Under the standard risk-free arbitrage pricing method, the value of the opportunity to commercialize MACH3 is implicitly assumed to move in a manner that is perfectly correlated to both Gillette’s stock price and the gross values from blade and razor operations. Substituting the value for x, V^sub B^ and l^sub c^, one obtains the following values for E + and E -:

In summary, if one uses the traditional DCF approach, as the NPV of the R&D investment is -$55 million, the decision is not to undertake the R&D investment to develop the MACH3 shaving system. This analysis therefore demonstrates that the conventional NPV rule fails to consider the strategic nature of R&D projects. The options approach considers the initial R&D investment as a growth option that creates an opportunity to undertake commercialization if and only if R&D is successful. When the R&D fails, commercialization is not undertaken and the resulting loss is limited to the initial cost of the R&D investment or $200 million, which is relatively small compared to the investment cost and payoff associated with the commercialization. The value of the real option associated with the R&D investment is ROP = SNPV – NPV = 30 – (- 55) = $85 million. However, the ROP needed to undertake the commercialization decision is $85 million, and the decision is made to undertake the R&D investment to introduce MACH3.


In this section, we analyze the ways in which undertaking commercialization of MACH3 in 1998 could affect the price of Gillette’s stock. Financial and operating information pertaining to the blade and razor operations from 1996 to 1997 indicate that revenues have grown at a slower pace than in past years. The net increase in cash flows attributable to the blade and razor operations during this period is only $33 million. Gillette’s management may anticipate that its Sensor product family is reaching product maturity. The moderate growth in blade and razor operations could have influenced Gillette’s management to exercise the option to introduce MACH3 this year. Gillette has continuously maintained an annual growth rate of 33% in its stock price over the past 10 years, and the launch of MACH3 would appear to be required to maintain this continual stock price growth.


Suppose Gillette’s management decides to exercise the real option to commercialize MACH3 in 1998. It then could earn an annualized incremental cash flow of (Delta)AB = E(A/P, 8%, 8) or $108 million if the market acceptability for MACH3 is favorable, and zero if the market acceptability for MACH3 is unfavorable. When the market acceptability for MACH3 is unfavorable, the incremental gross value from commercializing MACH3 is zero because Gillette would not exercise an out-of-the-money option. The annualized incremental cash flows from blade and razor operations as a result of introducing MACH3 are computed as follows:

Using these values, we may compute the annualized gross values from blade and razor operations with the launch of MACH3. The annualized gross values from other operations are assumed to increase at the projected rate. TABLE 4 presents all these values.

SCENARIO B: GILLETTE’S MANAGEMENT DOES NOT EXERCISE THE REAL OPTION We next analyze what happens to its stock if Gillette’s management does not exercise the real option to launch MACH3 in 1998. A likely scenario is that the blade and razor operations will grow only moderately. We, therefore, assume that the annualized incremental gross value from blade and razor operations continues to grow at the 1996/1997 pace, which amounts to $33 million in the best case. For the worst case, we assume that blade and razor operations fall as under the projected scenario. TABLE 5 contains the annualized gross values and resulting stock prices.


In TABLE 6, we summarize the projected gross project values and the resulting stock prices. Notice that these are the target values Gillette needs to achieve to continuously maintain a 33% stock price growth rate each year.

FIGURE 8 presents Gillette’s high and low stock prices under each scenario. Our analysis indicates that a projected 33% annualized growth rate in Gillette’s stock price yields a high of $133 at the beginning of 1999. Achieving such a target is difficult unless Gillette earns $520 million from other operations to offset the slow growth in the blade and razor operations if management does not launch MACH3. If we assume that the razor and blade operations continue to grow at the 1996/1997 pace, the high stock price is $117.75. However, by launching MACH3, management could anticipate a stock price of at least $122.25 if market acceptability of MACH3 is favorable. In this situation, the target stock price would satisfy shareholder interest and maintain investor confidence.


A sensitivity analysis of the real option values and the resulting high and low stock prices assuming Gillette launches MACH3 in 1998 was done by varying (x), the percentage increase in the gross values resulting from the new product launch.


When x varies from 10% to 50%, the high value for Gillette’s stock price in 1999 increases from $115.78 to $141.6, while the low value increases from $75 to $84.90. If Gillette’s MACH3 launch generates more than $295 million in cash flows during 1998 from blade and razor operations (a 38% increase in cash flows from base-level operations), the high value for its stock price is likely to exceed the 1998 year-end target of $133. The corresponding low value for the stock price is $81. FIGURE 9 shows the high and low values for Gillette’s 1998 year-end stock price with the MACH3 launch for different levels of x. In our example, we have considered only the effect of a commercialization decision on stock price. However, factors such as changes in investor beliefs, due to delay or abandoning of a good project, or a failure of a single project may affect the stock price. Considering all these factors could complicate valuation models and strategic plans.


In FIGURE 10, we show how the ROP, SNPV, and NPV vary with the percentage increase in gross values from the base level that results from launching MACH3. Notice that the strategic NPV is negative when x is less than 20.8%, indicating that the R&D investment would be rejected based on the options approach using the SNPV criterion that includes an opportunity to commercialize. However, even when the SNPV is negative, there is an associated positive option premium, indicating that a rejection decision is inappropriate because the worst outcome is still preferable to the one based on the NPV criterion. When a conventional analysis is based on an expected value criterion, the value of x that yields a positive NPV is greater than 23.8%. For instance, when x is less than 20.8%, both the options approach and the conventional approach recommend not undertaking the R&D investment. On the other hand, when 20.8%

Therefore, the range of values for x critical to an accept/reject R&D decision that differs when the NPV criterion is used lies between 20.8% and 23.8%. The incremental gross value from blade and razor operations pertaining to this critical region amounts to $109 million, and the corresponding ROPs amount to $85.5 million and $75.2 million, respectively. Our analysis indicates that when x is varied, the ROP decreases rapidly, bottoms out, and then increases slowly when both the NPV criterion and the options approach produce the same decision. The corresponding values for the high stock price in the critical region range from $121 to $123.5, respectively, and the corresponding low stock prices remain unchanged at $75.


In previous sections, we assumed that the uncertainty related to market acceptance for MACH3 in the commercialization phase could be estimated accurately and would remain constant. For example, the probability associated with market acceptance being favorable was estimated to be (q = 0.4). In reality, however, market uncertainty could differ from the estimates and hence it is important to investigate how such changes would affect the SNPV, NPV and the ROP. To analyze how option values change with different levels of uncertainty in the commercialization phase, three different values for the probability of a favorable market acceptance are considered: (q = 0.3) and (q = 0.4), to describe high market uncertainty, and (q = 0.5) for medium market uncertainty. FIGURE 11 shows the results for ROP, SNPV and NPV under these three market uncertainty outcomes when x is varied from 10% to 50%. Our analysis indicates that the SNPV remains unchanged for different levels of market uncertainty because risk-neutral probabilities are used instead of the actual probabilities. This is consistent with the risk-free arbitrage condition for pricing options when using the binomial model.

In contrast, the NPV criterion, which is based on expected values, varies with different levels of market uncertainty. When market uncertainties are high (q = 0.3 or q = 0.4), the NPV curves remain farther to the left of the SNPV curve, indicating that the critical region for x increases as the chance of making an incorrect decision increases, particularly when the conventional NPV criterion is used in making investment decisions under conditions of uncertainty. When market uncertainties tend to be lower, such as a medium level of market uncertainty, the ROPs tend to be smaller and the critical range for x, narrower, where the two valuation approaches recommend opposite actions. When there is no uncertainty, SNPV and NPV coincide and the ROP is zero, indicating that the NPV criterion can be used. TABLE 7 presents the range of values pertaining to the critical region for x with different levels of market uncertainty along with the ROPs when x = 20.8% (SNPV = 0) and x = 22%. Notice that the high and low stock prices do not vary with different levels of uncertainty because they are computed based on the risk-free arbitrage pricing approach in which actual probabilities are not used. Furthermore, the high and low values for Gillette’s stock price are dependent only on the actual cash-flow realizations rather than on the option values.


We have demonstrated how one can evaluate R&D projects using the options approach instead of traditional DCF techniques. We illustrated the importance of this point by using a valuation model that incorporates the risk-free arbitrage pricing conditions in option pricing within a decision-tree framework. We also discussed the weaknesses of the conventional NPV criterion in evaluating R&D projects under conditions of uncertainty. In particular, we showed why the options approach is better suited to value R&D investments. It is generally difficult to justify R&D projects by simply using traditional methods; consequently, companies tend to under invest in R&D. The options approach remedies the shortcomings of the NPV criterion when applied to projects that have high degrees of uncertainty. In addition, we demonstrated how valuations could be linked to a company’s stock price. Our approach enhances traditional economic analysis by enabling moremeaningful economic interpretations that view engineering projects from an integrated perspective within the overall corporate strategy rather than in isolation.

We have specifically attempted to illustrate the options approach and how one could incorporate the risk-free arbitrage condition to price real options in R&D ventures. However, as a potential area of additional research, we suggest how one may incorporate Bayesian methods within an options framework to value R&D projects. We also suggest developing valuation models that allow one to use a more general and realistic set of assumptions than those required for risk-free arbitrage pricing in valuing R&D projects. Finally, future research should also be directed at applying the options approach ideas to value real-world engineering-type R&D projects so as to help bridge the gap between theory and practice.

1The gross project value would also depend on the available capacity of the plant.

2This is the standard assumption for risk-free arbitrage pricing models.

3This section is based on Trigeorgis and Mason [21] and Trigeorgis [22].

4In traditional capital budgeting taught in finance courses, the plant’s expected cash flows would be discounted using the rate of return on the plant’s twin security (i.e., comparable company’s stock). The discount rate is estimated by selecting a suitable project beta and applying the capital asset pricing model (CAPM) [21].

5The limitation of this assumption is that the volatility of an individual project could be much higher than a firm’s volatility. This simplifying assumption, however, is important as it allows combining project valuation with corporate strategy through real option pricing technology.

6Sensor was launched in 1990 after 13 years R&D.


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DR. HEMANTHA S. B. HERATH worked as a consultant in the Oil and Gas Division of the World Bank in 1997 and during the summer of 1995 and 1996. He is currently a consultant with Robert Half International, Toronto. He is a graduate of the University of Kelaniya (B.Sc.), the University of Sri Jayawardenapura (M.B.A.), and Auburn University (M.S.I.E., Ph.D. Industrial Engineering). He is a Junior Fulbright Scholar and has been an Associate Member of the Chartered Institute of Management Accountants (U.K.) since 1992. His research interests are in real options, economic decision analysis and project finance in the energy industry.

DR. CHAN S. PARK is a Professor of Industrial and Systems Engineering at Auburn University. He received his B.S. from Hanyang University, his M.S.I.E. from Purdue University, and his Ph.D. in Industrial Engineering from the Georgia Institute of Technology. His main research interests include engineering/manufacturing economics, decision analysis, and real option analysis. Dr. Park has published numerous articles on these topics and has received several research awards for his publications from the Society of Manufacturing Engineers, the American Society of Engineering Education, the Institute of Industrial Engineers, and Sigma Xi. Dr. Park has also authored several texts, including Advanced Engineering Economics (John Wiley) and Contemporary Engineering Economics (Addison Wesley Longman). Since 1997, he has been serving as Editor of THE ENGINEERING ECONOMIST.

Copyright Institute of Industrial Engineers 1999

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