Abstract for: Optimizing Customer Orders with a Dynamic Balanced Scorecard Model

In today’s competitive business environment, achieving excellence in managing customer orders is essential for organizational success. This necessitates creating value through optimal investments, which enhances the ability to attract and retain customers. The purpose of this study is to leverage the System Dynamics (SD) methodology to explore the influence of organizational capacity on customer orders, considering feedback loops, time delays, and nonlinear relationships. It seeks to optimize customer orders within the Balanced Scorecard (BSC) framework by analyzing the interconnected impacts of organizational capacity, internal processes, customer satisfaction, and financial performance. The study begins by formulating dynamic hypotheses to identify the key factors influencing customer orders. A simulation model is subsequently developed and validated. Finally, a set of policies is identified and evaluated for their impact on the model. The results reveal the optimal investment values for customer orders. The BSC framework offers a standardized framework for aligning goals and initiatives across organizational perspectives. However, optimizing customer orders presents complex challenges, requiring organizations to determine effective investment strategies and implement policies that deliver superior outcomes. This paper presents a case study from a profit-driven business and industry organization in Iran, using SD modeling and simulation to achieve order optimization.