Extraction of Fundamental KPIs in New Product Development Using Bayesian Network Analysis

Abstract

Setting key performance indicators (KPIs) that influence Key Goal Indicators (KGIs) such as sales, sales volume, market share, among others, in a new product development program of an enterprise is extremely in important management matters. Although there are many candidates for KPIs, there have been no studies that have explored the causal relationship between them and KGIs using a mathematical model. In this study, to reduce the complexity of a new product development program and to enable focus on appropriate management, the association between 5 KGIs and 32 KPIs was modeled through Bayesian network analysis based on 250 actual values. The results were further examined from the viewpoint of product development management. Six KPIs that seem to have more possibility to influence KGIs were extracted as “Fundamental KPIs”. From now on, extracting the fundamental KPIs reflecting the actual situation more deeply and exploring the key points for their management is required. This is done by further narrowing down KGIs and KPIs based on the results and increasing the number of actual values.