Evaluation of Strategic IT Platform Investments

Abstract

Quantitative evaluation of strategic IT investments remains a challenging task in most organisations today. An important element of the problem is that though some investments appear to have little direct benefits, they may still be profitable when they serve as important investment platforms. These IT platforms provide value in terms of enabling options on future potentially profitable contingent investments in applications, delivering new or enhanced business capabilities. The benefits, as well as the costs associated with, for example, investments in an Enterprise Resource Planning (ERP) system are uncertain and difficult to measure. Not only is the value contingent on the performance of the initial platform investment, but ERP systems also provide the opportunity to add future applications that may, or may not, be known at the time of the initial investment. The complexity involved with evaluating the IT platform and its embedded options is hence subject to a number of different types of risk depending on the type of platform, the organisation involved and the industry environment.

This paper presents a conceptual framework for classifying different types of risks associated with major IT platform Investments in the AEC (Architecture, Engineering and Construction) environment. It then discusses how a real option methodology can be used to extend the classical Discounted Cash Flow (DCF) approach to evaluate and manage the investment by modelling these risks and the associated strategic flexibility. A simple but powerful binomial lattice model is developed and the methodology illustrated in an example where a general contractor has to choose between three alternative investment strategies. Management is faced with the decision whether to upgrade the companies existing management support system or choosing between two different ERP systems. A concluding discussion covers potential implications of using this dynamic evaluation methodology along with opportunities for future research.