Product Life Cycle Management of Packaged Software

Abstract

As software ages, it is increasingly unable to leverage new technologies and fulfill the evolving user requirements. As a result, firms get an opportunity to introduce and sell upgrades that provide higher utility to consumers compared to an older and out-of-date software product. This is reminiscent of the machine maintenance literature in operations management with the additional complexity that demand-side considerations must also be accounted for. Our research looks at the optimal intervals between upgrades and analyzes how these intervals change over the product’s life cycle. To investigate this issue, we model the costs and revenues associated with a succession of upgrades marketed by a software product monopoly into a homogeneous customer market. We prove that the optimal upgrade intervals are monotonically increasing throughout the product’s life cycle solely because of economic considerations. When the market for the new software product is growing fast, new versions will be introduced quickly. Later, as the market matures, the rate at which new versions are introduced slows down. This finding is in conformity with empirical evidence, thus validating our theoretical model. We then present comparative statics results to analyze the impact of product and market characteristics such as externalities and market growth rates on upgrade introductions. We also examine how the compatibility choice between successive software upgrades affects the upgrade intervals. Finally, we present three separate extensions of our model to incorporate heterogeneous customers, a continuous increase in market size, and more general customer utility and development costs. This subsequent analysis showcases the robustness of our results and adds more insights. Our results can help managers implement upgrade development more effectively. For example, since the cost to create an upgrade is a function of the corresponding upgrade interval, this study can help managers understand how budgeting for upgrades changes over the software life cycle.