The application of option pricing models to evaluate projects has been reported by researchers and practitioners. Baldwin and Clark (1994) examined how the design of software creates options for rapid deployment of future software products development when software is reused. Kogut and Kulatilaka (1994) used OPMs to gauge the value of production flexibility in worldwide manufacturing operations affected by foreign exchange rate movements. And, Nichols (1994), in an interview with Judy Lewent, then chief financial officer of Merck & Co., the pharmaceutical manufacturer, discusses how OPMs are used to evaluate corporate acquisitions that promote pharmaceutical R&D.
Recent research in the Information Systems (IS) literature (e.g., Clemons, 1991; Dos Santos, 1991; Kambil et al., 1993; Kumar, 1996; Chalasani, Jha and Sullivan, 1997) has recognized the importance of utilizing the theory of irreversible investment under uncertainty (Dixit and Pindyck, 1994) to emphasize the option-like characteristics of information technology (IT) project investments. A project embeds a real option (e.g., Sick, 1990; Nichols, 1994; Trigeorgis, 1995 and 1996) when it offers management the opportunity to take some future action (such as abandoning, deferring, or scaling up the project) in response to events occurring within the firm and its business environment.
Value of IT Projects:
The IS literature argues that a large portion of the value of IT projects comes from the potential value of future projects that are enabled by them. That is, IT projects enable follow-on projects that would be impossible or much more expensive were the current project not completed. Thus, investment in an IT project is analogous to buying an option on those follow-on projects. The Computer Science literature similarly views software development methods such as prototyping, implementing pilot projects, designing to emphasize software reuse, and exploiting the object-oriented (OO) paradigm as incorporating real options.
There are many situations involving IT projects for which the application of option pricing models (OPMs) is appropriate. They include IT infrastructure projects, as well as software application prototypes, decision support systems, data warehouses and data mining, and investments in systems that involve bets on future technology standards and investments in new technologies associated with e-commerce.
As more information becomes available and some of the uncertainties are resolved, management can change a future project -- from any of its details (e.g., timing, vendors, build rate, rollout, etc.) to its overall strategic purpose in the business. Future projects can be deferred, abandoned, expanded, contracted, or otherwise modified, to meet management's requirements. IT investment often creates the opportunity for future growth: the initial stages of a project make follow-on stages possible. Without loss of generality, we can conceptualize the stages of a project as a sequence of related projects.
Any given IT project may act as a link in a series of projects such that the earlier projects provide the necessary conditions or capabilities to carry out follow-on projects. Consider, for example, what happens when a firm upgrades a specific IS application to be in synch with a new generation of technology. The directly measurable cash flows of such a project are difficult to calculate accurately and often fail to cover the requisite large expenditures. However, this type of project may leverage organizational capabilities, such as flexibility and responsiveness to customer needs, and demand shifts in the marketplace, that emphasize competitive adaptability and the firm's absorption of technological innovation and change through possible future projects. Thus, the potential value of follow-on projects or the capabilities that the organization builds in the initial project should be considered when the initial investment is assessed.
Strategic IT investments are highly risky to make, but can offer huge rewards to a firm. The major difficulty occurs in evaluating these investments and justifying them using current IS executive skills and approaches. Typically, organizations fall into two traps: the trap of negative net present value or the trap of vanishing status quo (Clemons, 1991). The first trap occurs due to the difficulty in identifying future benefits and in accurately estimating them in terms of cash flows. This results in conservative estimates of the benefit stream, which coupled with large investment costs, results in negative NPVs. The second mistake that firms make is in assuming a static market and not making any investments. This could result in loss of market share and other bad outcomes due to competitor actions.
The forces that drive the differences in the probabilities of pursuance and expected time of adoption of an innovation by a firm are dependent on the market (industry) as well as firm specific factors e.g. its policies, history of adoption of innovations etc. Important characteristics of real-world technology markets e.g. consideration of ability to respond to future innovations while confronting adoption of a current innovation, uncertainty in the timing and significance of future innovations, realistic cost-concerns etc. were incorporated. It is evident from a survey of prior relevant work that since the nature of technology risk management problems in IT projects is very similar to those involving flexible capital investment and project management decisions, real options methodologies can be used. Mitchell and Hamilton first applied options techniques for strategic positioning in R&D project management.
In the context of IT investment, irreversibility merely implies that the investment costs that bring about an innovation are at least partially sunk and cannot be recovered if the output proves to be undesirable over time.
