Information systems project prioritization using data envelopment analysis

Large organizations continually struggle with problems related to allocating their development dollars to various competing projects. Project prioritization is at the heart of these issues because there are always more demand than money available, so choosing the right projects is important. This situation is further aggravated by the omni-present political environment where some managers get their projects done because they have the political power to get them on the agenda. This paper presents a new model within the data envelopment analysis framework for prioritizing information system (IS) projects. The criteria used to judge the importance of projects are the inputs and outputs of the model. A set of sample/artificial projects is created for which the criteria and priority score are defined by decision makers. Each real project is compared to the set of defined projects and receives a score. The new model is tested on a real case of prioritizing IS projects at a large financial institution. The proposed model provides fair and equitable ranking, it is complex enough to model the problem reasonably and accurately and yet simple enough to be understood by the user community. More importantly, a new project can be prioritized at any time without affecting the priority of already assessed projects.