Augmenting Capabilities of Advanced Planning and Scheduling Systems With Curated IIoT Data

Abstract

Supply continuity is being challenged at every stage of the supply chain, with changing workforce dynamics, natural events, and consumer buying patterns. These changes in the operating environment are continuously introducing inefficiencies into the supply chains, and are putting pressure on costs to serve. Even during the pre-pandemic era, execution adherence to plans generated by advanced planning and scheduling systems (APS) was not more than 50%. Rapid evolution of emerging technologies accelerates digitization of supply chains and provides opportunities to enable paradigm shifts in supply chain planning. Integration of planning software with industrial internet of things (IIoT) platforms, which collect real-time data across the value chain, can drive the next level of supply chain optimization. In this chapter, the authors provide specific recommendations, to extracting maximum value from APS systems by addressing some limitations, for example, out-of-sync master data and lack of real-time transactional data, by using curated data feeds from the IIoT platforms to augments APS capabilities.