The impact of poor data quality on the typical enterprise
Communications of the ACM
Emerging technologies to support supply chain management
Communications of the ACM - Why CS students need math
Manufacturing Planning and Control for Supply Chain Management
Manufacturing Planning and Control for Supply Chain Management
A decision support system for managing inventory at GlaxoSmithKline
Decision Support Systems
Competing on Analytics: The New Science of Winning
Competing on Analytics: The New Science of Winning
The impact of business analytics on supply chain performance
Decision Support Systems
Business Analytics and Competitive Advantage: A Review and a Research Agenda
Proceedings of the 2010 conference on Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade
Organizational impact of system quality, information quality, and service quality
The Journal of Strategic Information Systems
Research Commentary---Seeking the Configurations of Digital Ecodynamics: It Takes Three to Tango
Information Systems Research
An elusive antecedent of superior firm performance: The knowledge management factor
Decision Support Systems
Information technology and organizational capabilities: A longitudinal study of the apparel industry
Decision Support Systems
Data, information and analytics as services
Decision Support Systems
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This study is interested in the impact of two specific business analytic (BA) resources-accurate manufacturing data and advanced analytics-on a firms' operational performance. The use of advanced analytics, such as mathematical optimization techniques, and the importance of manufacturing data accuracy have long been recognized as potential organizational resources or assets for improving the quality of manufacturing planning and control and of a firms' overall operational performance. This research adopted a contingent resource based theory (RBT), suggesting the moderating and mediating role of fact-based SCM initiatives as complementary resources. This research proposition was tested using Global Manufacturing Research Group (GMRG) survey data and was analyzed using partial least squares/structured equation modeling. The research findings shed light on the critical role of fact-based SCM initiatives as complementary resources, which moderate the impact of data accuracy on manufacturing planning quality and mediate the impact of advanced analytics on operational performance. The implication is that the impact of business analytics for manufacturing is contingent on contexts, specifically, the use of fact-based SCM initiatives such as TQM, JIT, and statistical process control. Moreover, in order for manufacturers to take advantage of the use of data and analytics for better operational performance, complementary resources such as fact-based SCM initiatives must be combined with BA initiatives focusing on data quality and advanced analytics.