Balancing uncertainty of context in ERP project estimation: an approach and a case study

The increasing demand for Enterprise Resource Planning (ERP) solutions as well as the high rates of troubled ERP implementations and outright cancellations calls for developing effort estimation practices to systematically deal with uncertainties in ERP projects. This paper describes an approach - and a case study - to balancing uncertainties of context in the very early project stages, when an ERP adopter initiates a request-for-proposal process and when alternative bids are to be compared for the purpose of choosing an implementation partner. The proposed empirical approach leverages the complementary application of three techniques, an algorithmic estimation model, Monte Carlo simulation, and portfolio management. Our case study findings show how the ability of our approach to model uncertainty allows practitioners to address the challenging question of how to adjust project context factors so that chances of project success are increased. We also include a discussion on the implications of our approach for practice as well as on the possible validity threats and what the practitioner could do to counterpart them.