The challenge of accurate software project status reporting: a two stage model incorporating status errors and reporting bias

Software project managers perceive and report about the project's status. Recognizing that their status perceptions might be wrong and that they may not faithfully report what they believe leads to a natural question - how different is the true software project status from the reported status? In this paper, we construct a two-stage model which accounts for project manager errors in perception and bias that might be applied before reporting the project's status to executives. We call the combined effect of errors in perception and bias "project statics distortion". The probabilistic model has its roots in information theory and uses the discrete project status from traffic-light reporting. The true states of projects of varying risk were elicited from a panel of five experts, and these formed the model input. Key findings suggest that executives should be skeptical of favorable status reports, and that, for higher-risk projects, executives should concentrate on reducing bias if they are to improve the accuracy of project reporting.