Evaluating Product Plans Using Real Options

Product planning helps a company to strategically plan its current and future product platforms and offer product variants in the marketplace. Product platforming is widely touted as a successful strategy for mass customization. However, due diligence should be exercised before implementing any product platform strategy. The product planning exercise should account for future uncertainties. Traditional financial tools such as the net present value (NPV) are static since they do not compensate for any exogenous and endogenous uncertainties during the course of the project. The crux of the problem lies in the evaluation model that is used for evaluating the product planning projects. While many view uncertainties in a product planning project as problematic, it can also be viewed as a source of new opportunities. We argue that uncertainties should be an integral part of the evaluation model. If the future possibilities (or strategic options) are not considered in the evaluation model, a corporation may face a “myopic syndrome”.

In this article, we consider two important product planning decisions—platform decisions and product variant decisions. The platform decision involves strategic selection of a concept product platform from various possible alternative concept product platforms. The product variant decision involves deciding how long a company should continue to offer its current product variant in the marketplace and whether the existing product variant should be discontinued, scaled down, or scaled up with additional product features. To address the two aforementioned decisions, we developed a real options–based methodology that considers technical, project implementation, and market-related uncertainties. The proposed methodology uses a binomial and quadranomial lattice approach to build a decision tree. Product planning decisions at various decision tree nodes are evaluated using a risk-neutral option valuation methodology. We demonstrate the working of the proposed methodology using an illustrative example.     

Evaluating growth options as sources of value for pharmaceutical research projects

The financial value of research projects is difficult to assess because they are highly uncertain. Often, the result is either an overly conservative approach to strategic innovation, based on net present value analyses, or an overly aggressive approach based on optimistic qualitative portfolios. R&D project evaluation requires recognizing threats as well as opportunities from uncertain events, and incorporating flexibility in managerial action in response to them. Real options pricing analysis is a widely discussed tool for evaluating such managerial flexibility. The limitation of options pricing lies in its requirement for complete financial markets, in which a replicating asset can be found that reproduces (or, at least, is correlated with) the project’s payoffs in all possible states of the world. However, the major risks of research projects are typically project specific and cannot be replicated in external markets. In this situation, a decision tree is a better tool to represent managerial options during execution of the project, and to evaluate its value. A decision tree is equivalent to options pricing for risks that can be priced in the financial markets (if trading of securities is explicitly included), and moreover, it can incorporate risks and flexibility that are not traded in financial markets. Using decision trees, we demonstrate a quantitative evaluation of compound growth options from research at BestPharma, a large international pharmaceutical company. A growth option is a future opportunity that may arise from a current R&D investment. The growth option may not be related to the primary purpose of the R&D project, or not even be directly foreseeable. Kester (1984) has argued that growth options may account for a large part of project value. BestPharma faced the problem of choosing among several strategic research initiatives. They developed a decision tree representation of the projects, which helped to provide transparency about project value and strategic options. Most importantly, carefully thinking through the tree helped to identify growth options, represented by additional branches in the tree, and to quantify that they represented major sources of value.     

A REAL OPTIONS DESIGN FOR QUALITY CONTROL CHARTS

We develop a financial model for a manufacturing process where quality can be affected by an assignable cause. We value the real options associated with applying a statistical process control chart using the Black-Scholes equation, binomial and pentanomial lattices, and Monte Carlo simulation methods. This valuation gives decision makers a way to choose the appropriate quality control strategy based on an integrated view of the market dynamics with the manufacturing operational aspects. An industry case is used to demonstrate the application of real options to value control chart decisions. Web based programs are given to value the alternatives in the case study, making the valuation task accessible to other users.     

Project valuation in the pharmaceutical industry: a comparison of least‐squares Monte Carlo real option valuation and conventional approaches

Least‐squares Monte Carlo simulation (LSM) is a promising new technique for valuing real options that has received little or no attention in the pharmaceutical industry. This study demonstrates that LSM can handle complex valuation situations with multiple uncertainties and compounded American‐type options. The limited application of real option valuation (ROV) in the pharmaceutical industry is remarkable, given the importance of accurate project valuation in an industry that requires large investments in high‐risk projects with long pay‐back periods, which is furthermore suffering from ever‐increasing development costs and shrinking profit margins. The LSM model developed in this study is constructed as an extension of a discounted cash flow model that should be familiar to economists active in the pharmaceutical industry. A number of pharmaceutical projects have been evaluated using LSM ROV, binominal real option valuation and expected net present value techniques. The different results yielded by these methods are explained in terms of differences in risking assumptions and ability to capture the value of flexibility. The analysis provides a framework to introduce the basic concepts of real option pricing to a non‐specialist audience. The LSM model illustrates the potential for real‐life commercial assessment as the versatility of the technique allows for an easy customisation to specific business problems.     

A REAL OPTIONS DESIGN FOR PRODUCT OUTSOURCING

Product outsourcing is recognized as a way to gain flexibility for competitive advantage. We formulate the outsourcing problem using real options. We develop a financial model to assess the option value of product outsourcing. Specifically, we consider a three state-variable problem and use Monte Carlo simulation to estimate the value of the option. This valuation gives decision makers a way to choose the appropriate outsourcing strategy based on an integrated view of the market dynamics. A case example from the apparel manufacturing industry is used to demonstrate the application of real options to value outsourcing flexibility. We show that the inability of classical net present value methods to address dynamics in the market condition leads to an undervaluing of the outsourcing strategy. Numerical results and sensitivity analysis show how the real options approach can be used to give a better view of the long-term value of outsourcing.     

Dark Fiber Valuation

Valuation of dark fiber has recently generated controversy, sparked particularly by the large sums booked for swaps of dark fiber between companies. One of the issues raised is valuation: i.e., what is the value of an asset that generates no revenue now and may do so at some unknown point in the future but only after investment, in an uncertain business climate, and where prices are dropping? The picture is further complicated because the result of investing to bring the asset to market (i.e. lighting the fiber) changes the supply and demand conditions of the market itself and hence invalidates price predictions. A realistic and consistent valuation methodology is necessary for increasingly cautious companies, auditors, and investors. In this paper we describe such a valuation methodology for dark fibre based on real options. Publicly available bandwidth price services start to make this practical by providing market price information. For dark fibre valuation the real option to be valued are the lighting decisions. We specifically include the effect on the market of adding new capacity by using the price-elasticity of demand within the stochastic price process itself, conditional on lighting decisions. Prices are generally volatile and decreasing with time. The evolution of lighting costs and maintenance are included in the valuation. The real options technique used here is novel in that it combines economic and market factors explicitly with mathematical finance to arrive at a valuation and optimal decisions. We found that the optimal lighting riming and capacity decisions to depend on many of the factors included in the analysis with no simple triggers: the details really matter.     

Expansion planning for transmission network under demand uncertainty: A real options framework

In recent years, there has been much expectation that transmission expansion planning should address ever increasing demands for transmission services under significant and complex economic and regulatory uncertainties. In this article, toward meeting the aforementioned expectation, we develop and analyze a real options framework that provides the valuation of a transmission owner's option to expand in his or her network. What distinguishes our framework from the extant literature is that the evolution of the demand follows a geometric Brownian motion process, it explicitly accounts for the physical flow of the electric power economically manifested as the locational marginal prices, and it shows how the values of the expansion options can be determined in the transmission network. Furthermore, our framework shows how to value an option to expedite or delay can be determined given that a specific expansion is planned. An extensive numerical example is presented to illustrate the key features of our framework.     

Valuation of Learning Options in Software Development Under Private and Market Risk

Commercial software development is an inherently uncertain activity. Private risk is high, schedule and cost overruns are common, and market success is elusive. Such circumstances call for a disciplined project evaluation approach. This paper addresses the use of market and earned value management data in assessing the economic value of commercial software development projects that are simultaneously subject to schedule, development cost, and market risk. The assessment is based on real options analysis, a financial valuation technique that can tackle dynamic investment decisions under uncertainty. The paper demonstrates the application of real options analysis to a development scenario that consists of two consecutive stages: a mandatory prototyping stage and an optional full-development stage. The full-development stage is undertaken only if the prototype is successful and the market outlook is sufficiently positive at the end of the prototyping stage, thus giving the full-development stage the flavor of an option. The project's staged design increases its value. Real options analyses capture the extra value due to optionality.     

Toward a behavioral theory of real options: Noisy signals,bias, and learning

Research Summary: We develop a behavioral theory of real options that relaxes the informational and behavioral assumptions underlying applications of financial options theory to real assets. To do so, we augment real option theory's focus on uncertain future asset values (prospective uncertainty) with feedback learning theory that considers uncertain current asset values (contemporaneous uncertainty). This enables us to incorporate behavioral bias in the feedback learning process underlying the option execution/termination decision. The resulting computational model suggests that firms that inappropriately account for contemporaneous uncertainty and are subject to learning biases may experience substantial downside risk in undertaking real options. Moreover, contrary to the standard option result, greater uncertainty may decrease option value, making commitment to an investment path more effective than remaining flexible. Managerial Summary: Executives recognize the need to make uncertain investments to grow their business while mitigating downside risk. The analogy between financial options and real corporate investments provides an appealing method to consider the practical challenge of such investment decisions. Unfortunately, the “real options” analogy seems to break down in practice. We identify how a second form of uncertainty confounds real options intuition, leading managers to overestimate the value of uncertain investments. We present a behavioral real options model that accounts for both forms of uncertainty and suggest how uncertainty interacts with behavioral bias in the option execution/termination decision. Our model facilitates assessment of the conditions under which investments in uncertain opportunities are usefully considered as real options, and provides a means to evaluate their attractiveness.     

Real options and real value: the role of employee incentives to make specific knowledge investments

Real options reasoning emphasizes the strategic value of making flexible investments in a turbulent environment. Employees' investments in specific human capital are often critical to the success of a real option project, but the very flexibility that allows a firm to change course in response to new information also affects employees' incentives to make such specific human capital investments. We develop a model of real option investment that explicitly incorporates the role of employee incentives. The model suggests that the effect of investing in a real option project on employee incentives may be positive, further increasing the value of the project, or negative, sometimes more than offsetting the benefit of flexibility and resulting in reduced project value. Therefore, firms and managers should take into consideration the role of employee incentives when applying real options logic to investment decision making. Copyright © 2008 John Wiley & Sons, Ltd.     

Valuation of R&D real American sequential exchange options

Valuation of R&D real American sequential exchange options requires specifying the pattern of R&D expenditures and the stochastic process of the eventual R&D project. We model the stages of R&D expense and then the ultimate discovery (and the development cost for the discovery) using real sequential (compound) exchange option models. We study E_Commerce R&D, so the timing is relatively short‐term, with initial R&D, a second phase of R&D, and a final development phase, when the project values are realized. We use proxies from the financial markets for expected project value and cost volatilities (and correlation). Then the real option valuation is based on an approximate American sequential exchange option.     

Optimal exploration investments under price and geological‐technical uncertainty: a real options model

This article develops a real options model for valuing natural resource exploration investments (e.g. oil or copper) when there is joint price and geological‐technical uncertainty. After a successful several‐stage exploration phase, there is a development investment and an extraction phase. All phases are optimized contingent on price and geological‐technical uncertainty.
Several real options are considered. There are flexible investment schedules for all exploration stages and a timing option for the development investment. Once the mine is developed, there are closure, opening and abandonment options for the extraction phase. Our model maintains a relatively simple valuation structure by collapsing price and geological‐technical uncertainty into a one‐factor model.
We apply the model to a copper exploration prospect and find that a significant fraction of total project value is due to the operational, development and exploration options available to project managers.     

R&D as an option on market introduction

Discounted cash flow methods for making R&D investment decisions cannot properly capture the option value in R&D. Since market and technology uncertainties change expectations about the viability of many new products, the value of projects is frequently adjusted during the R&D stages. Capturing the adjustment in expectations has an option value that may significantly differ from the Net Present Value of R&D projects. However, there are no historic time series for estimating the uncertainty of the value of R&D projects. As a result, the standard Black and Scholes model for financial option valuation needs to be adjusted. The aim of this paper is to report the application of a particular option pricing model for setting the budget of R&D projects. The option value of the model captures jumps or business shifts in market or technology conditions. The approach originates from applying current insight into the valuation of R&D projects to the field of multimedia research at Philips Corporate Research. This way, the gap between real option theory and R&D practice is further diminished.     

互补性资产研究综述

本文在归纳不同产业领域中互补性资产的影响和作用基础上,对互补性资产的衡量指标的研究进行了评价分析,认为互补性资产的研究应结合相关领域,研究方法和衡量标准应该符合各产业的实际情况。本文结合建立自主创新型国家、提科研能力的目标,提出从多学科、多角度综合集成的视角探究互补性资产的影响,以及影响的机制和途径。     

Shareholder Value, Real Options, and Innovation in Technology-Intensive Companies

We show how central concepts from technology and innovation management (TIM), sequential models of the New Product Development (NPD) process, and the valuation technique of 'real options' can be linked, to provide a valuation framework that can be used in the value-based management of technology-intensive companies.
We introduce a binomial option tree which incorporates the flexibility and the risks inherent in the NPD process into its evaluation in a theoretically correct way and is at the same time simple and easy to use. In this way, our options-based approach ties the valuation of hitech and life sciences companies closer to the underlying growth opportunities and incorporates much of the 'gut feel' of experienced industry practitioners into the valuation. As a consequence, the approach leads to more defensible valuations and allows powerful insights for the value-based management of technology-intensive companies.
In two numerical examples we demonstrate that the theoretically more sound option tree approach in practice can produce different valuations and lead to different decisions than a simple 'discounted cash flow (DCF) tree' approach and has therefore potential to improve managerial decision making. Finally, we describe a real life situation where our options-based approach was successfully applied in the valuation for the initial public offering of a biotech company.     

Optimised asset replacement strategy in the presence of lead time uncertainty

This paper develops an optimal replacement strategy for capital intensive equipment with long delivery lead time. The strategy is based on an extended version of the real options approach to repeated replacement decisions, in which the goal is to determine the operating cost and delivery lead-time conditions upon which a replacement should be ordered.The real options approach to capital replacement problems is superior to traditional net present value (NPV) approaches, as it values of the option to adapt decisions based on current (rather than predicted) system conditions. However, previous applications of the real options approach to repeated replacement have not considered the impact of long and uncertain lead times, and have therefore focused on when to replace rather than when to order. Delivery lead times are an important consideration in an expanding mining sector in which demand for heavy mobile equipment (HME) exceeds the capacity of suppliers to provide the equipment in a timely manner.The inclusion of a lead time element results in a decision with an “option” period and an “option-less” period. Simulations are used to demonstrate the improved outcome of real options based replacement strategies compared with those derived using a traditional NPV approach, both with and without lead times. Further the performance of the order placement strategy with different boundary conditions, bounded and reflecting, is explored. No appreciable difference in performance of these strategies was identified. The optimal order placement strategy incorporating delivery lead times is displayed on a simple chart which is accessible to fleet management personnel.     

Evaluation of a mining project under the joint effect of commodity price and exchange rate uncertainties using real options valuation

Cash flows generated by mining projects tend to be volatile and are extensively influenced by exogenous variables, notably commodity prices and exchange rates. The traditional discounted cash flow (DCF) method, which is normally used for economic feasibility studies and mining project evaluations, presents inconsistencies because the method fails to adequately address uncertainties and operational flexibilities and often ignores certain specific market conditions. Numerous studies have been carried out for mining project evaluations using the real options valuation (ROV) technique for assessing commodity price uncertainty, but there is no research on the combined effects of price and exchange rate uncertainties. Therefore, in order to assess the economic viability of a mining project more accurately, the commodity price and its inherent volatility, the exchange rate and its inherent volatility, and the correlation parameters between them have been incorporated into the model and used in the evaluation process. One of the interesting findings revealed in the study is that project values are overestimated if only commodity price uncertainty is considered in evaluating the project value instead of the joint effect of commodity price and exchange rate uncertainties. This new ROV technique will explore the opportunity to utilize an alternative methodology for approximating project values and to identify valuation opportunities to enhance economic gains or to mitigate economic losses, where the DCF valuation method does not.     

Integrating Real Options with Managerial Cash Flow Estimates

This article presents a real options model that fits managerial cash flow estimates (optimistic, likely, and pessimistic projections) to a continuous geometric Brownian motion (GBM) cash flow process with changing growth and volatility parameters. The cash flows and the value of a project are correlated to a traded asset, so the real option is priced under the risk-neutral measure with a closed-form solution. The analysis is extended to a sequential compound call option for investments over multiple periods. If the project is correlated to the market, then some of the risk may be mitigated by a delta-hedging strategy. A numerical example shows that the effect of the correlated asset on the real option value is significant, and the relationship between the volatility of the project and the real option value is not analogous to the typical relationship found in financial option pricing. Integrating the expertise and industry knowledge of management, this approach makes possible a more rigorous estimation of model inputs for real option pricing.     

Irreversibility, sunk costs and investment under incomplete information

Despite its importance to economic growth, the investment behavior of firms remains poorly understood. Existing models ignore irreversibility and the opportunity to wait for new information. Even if some recent literature accounts for these two characteristics, these models ignore information costs. This paper presents a framework for the valuation of investment opportunities accounting for information costs regarding the project cash‐flows.
We develop some basic models of irreversible investment to illustrate the option‐like characteristics of investment opportunities under incomplete information. We show how optimal investment rules can be obtained using option pricing theory under incomplete information. It is possible to value real options and investment decisions using our approach in a context of incomplete information. Simulations are provided to illustrate our main results.     

Flexibility planning for managing R&D projects under risk

Incorporating managerial flexibility in an innovative R&D project is important, because managers face greater uncertainty in today's competitive and dynamic changing environment. It is essential to bring managerial flexibility into R&D project planning to decrease technical and market risks, while increasing potential market value. The objective of this paper is to develop a flexibility planning methodology based on real option analysis to improve managerial flexibility for R&D projects. The proposed methodology identifies potential risks that may occur during every R&D stage. It also recognizes a cascading option structure to resolve the identified risks, and evaluates and selects adequate options that maximize the potential value of the project. Instead of using a traditional option pricing method, a dynamic programming model that considers multidimensional product performance and market payoff is used to evaluate the R&D project value. Using the proposed methodology, managers can identify future scenarios as a function of their management actions. The proposed flexibility planning methodology can help managers improve managerial flexibility of R&D project and increase the success rate of product launch. A drug development project is used to illustrate the proposed methodology.