Analysis of time to market complexity: A case study of application of Bayesian networks as a forecasting tool

This study is dedicated to the research of the main critical factors that exist during the product concept phase and the influence of these factors have on defining time to market. The main factors were identified by a survey involving experts from different segments of the industry. The validation of the main factors was done by the simulation applying Bayesian network inside the New Product Development Area (NPD) of the one company leader of market in Brazil. The results show that two common factors contribute heavily to the delay in the launch of new products in this sector. The factors identified include the introduction of non-dominated technologies into new products and the competence of the project leader. The empirical application of artificial intelligence using the Bayesian networks as a statistical tool is analyzed as an alternative to the statistical methods commonly employed for the study of project performance.