BUSINESS ANALYTICS FOR SUPPLY CHAIN: A DYNAMIC-CAPABILITIES FRAMEWORK

TLDR

Supply chain management has gained academic prominence due to globalization and the massive data generated worldwide, necessitating new tools for data management and performance monitoring. The paper proposes an IT‑enabled dynamic‑capabilities framework for supply chain analytics (SCA) comprising data management, analytical supply‑chain process, and performance‑management capabilities. The framework is illustrated through the SCM best practice of sales & operations planning (S&OP), showing how the three capabilities can be integrated to enhance supply‑chain performance. The authors argue that adopting SCA and its individual capabilities positively impacts supply‑chain management performance.

Abstract

Supply chain management has become more important as an academic topic due to trends in globalization leading to massive reallocation of production related advantages. Because of the massive amount of data that is generated in the global economy, new tools need to be developed in order to manage and analyze the data, as well as to monitor organizational performance worldwide. This paper proposes a framework of business analytics for supply chain analytics (SCA) as IT-enabled, analytical dynamic capabilities composed of data management capability, analytical supply chain process capability, and supply chain performance management capability. This paper also presents a dynamic-capabilities view of SCA and extensively describes a set of its three capabilities: data management capability, analytical supply chain process capability, and supply chain performance management capability. Next, using the SCM best practice, sales & operations planning (S&OP), the paper demonstrates opportunities to apply SCA in an integrated way. In discussing the implications of the proposed framework, finally, the paper examines several propositions predicting the positive impact of SCA and its individual capability on SCM performance.