A System Dynamics Model for Analyzing Customer Satisfaction Drivers in a Manufacturing Context

Customer satisfaction offers economic benefits and competitive advantage to manufacturing enterprises. However, a gap exists in understanding how to achieve customer satisfaction due to the complexities involved in coordinating various subsystems of an enterprise in an efficient manner. In this paper, we identified four internal and external-to-the-firm customer satisfaction drivers which include: government policies, supply chain reliability, knowledge management, and manufacturing performance criteria such as on-time delivery, quality and cost. We then developed a conceptual framework to define the non-linear mathematical relationships between drivers using system dynamics modeling. We conducted “what-if “scenario analyses for a base case, optimistic case and pessimistic case using three intervention policies: “investing resources in knowledge management”, “inclusion of a safety stock”, and “decreasing cost of inventory” to study the impact of these policies on customer satisfaction. This work contributes to customer satisfaction research by presenting a decision-support tool that will enable the leadership of manufacturing enterprises to create a simplistic mental model of the complex interactions of an enterprise using easy-to-use mathematical relationships to capture system dynamics over time.