Title
Big data fueled process management of supply risks: Sensing, prediction, evaluation and mitigation
Abstract
Supplier risks jeopardize on-time or complete delivery of supply in a supply chain. Traditionally, a company can merely do an ex-post evaluation of a supplier's performance, and handles emergencies in a reactive rather than a proactive way. We propose an agile process management framework to monitor and manage supply risks. The innovation is two fold - Firstly, a business process is established to make sure that the right data, the right insights, and the right decision-makers are in place at the right time. Secondly, we install a big data analytics component, a simulation component and an optimization component into the business process. The big data analytics component senses and predicts supply disruptions with internally (operational) and external (environmental) data. The simulation component supports risk evaluation to convert predicted risk severity to key performance indices (KPIs) such as cost and stockout percentage. The optimization component assists the risk-hedging decision-making.
Year
DOI
Venue
2014
10.1109/WSC.2014.7019960
Winter Simulation Conference
Keywords
Field
DocType
key performance indices,optimisation,decision making,risk evaluation,supply chain management,supply chains,business process,data analysis,simulation component,big data analytics component,operational data,risk management,risk-hedging decision-making,environmental data,digital simulation,big data fueled process management,kpis,big data,supply risk management,business data processing,supply chain,agile process management framework,optimization component,supply disruption prediction
Performance indicator,Service management,Business process,Systems engineering,Computer science,Supply chain risk management,Supply chain management,Supply chain,Big data,Stockout,Process management
Conference
ISSN
ISBN
Citations 
0891-7736
978-1-4673-9741-4
0
PageRank 
References 
Authors
0.34
4
5
Name
Order
Citations
PageRank
Miao He184.89
Hao Ji200.68
Qinhua Wang3166.45
Changrui Ren48214.85
Robin Lougee500.34