A dynamic performance measurement system for supply chain management

Purpose: This paper aims to propose a dynamic model for measurement supply chain performance (SCP) based on a dynamic balanced scorecard (DBSC). Balanced scorecard (BSC) can be defined as a popular performance measurement method that can translate the strategy into a set of performance indicators and manage the status of implementing the various strategies. However, BSC is unable to simulate the complicated environment and the dynamic behavior of performance metrics. Therefore, the author combines BSC with system dynamics (SD) to explore a more efficient tool for measurement SCP. Design/methodology/approach: A dynamic causal model is proposed based on the causal hypotheses. The developed DBSC enables managers to evaluate and measure the SCP in a much-balanced way. Using DBSC makes it possible that different SCP metrics to be reviewed and distributed into the four above-mentioned perspectives. It also enables supply chain (SC) managers to evaluate different strategies to improve SCP. Findings: investigates two strategies to improve SCP as follows: (1) competitive strategy and (2) harvesting big data and using data mining techniques to determine the customer's expectations and then compares the results of these two strategies based on the four perspectives of DBSC and introduce the best strategy. Finally, harvesting big data and data mining is selected as the best strategy. Originality/value: This study proposes a novel strategic management tool for measurement SCP and simulation of the complicated environment and the dynamic behavior of performance metrics. The proposed DBSC model enables managers to compare different strategies and select the best strategy.