On prediction of cost and duration for risky software projects based on risk questionnaire

The paper proposes a new approach that can discriminate risky software development projects from smoothly or satisfactorily going projects and give an explanation for the risk. We have already developed a logistic regression model which predicts whether a project becomes risky or not (O. Mizuno et al., 2000). However, the model returned the decision with a calculated probability only. Additionally, a formula was constructed based on the risk questionnaire which includes 23 questions. We therefore try to improve the previous method with respect to accountability and feasibility. In the new approach, we firstly construct a new risk questionnaire including only 9 questions (or risk factors), each of which is concerned with project management. We then apply multiple regression analysis to the actual project data, and clarify a set of factors which contributes essentially to estimate the relative cost error and the relative duration error, respectively. We then apply the constructed formulas to another set of project data. The analysis results show that both the cost and duration of risky projects are estimated fairly well by the formulas. We can thus confirm that our new approach is applicable to software development projects in order to discriminate risky projects from appropriate projects and give reasonable explanations for the risk.