This paper describes a study that focuses on advanced analytics and accurate manufacturing data as two primary resources for influencing operational performance in a manufacturing context. The study demonstrates that in order for manufacturers to take advantage of manufacturing analytics and associated data, complementary supply chain management resources (such as just in time (JIT), total quality management (TQM), and statistical process control) should be integral components of a firm’s business analytics investment strategy. A key finding of this research is that these supplemental resources will interact with and increase the value of the primary resources.

This study consists of an exploratory research focusing on clarifying the relationships between business analytics-related resources and manufacturing operations performance. It employs data from the Global Manufacturing Research Group’s website (http://gmrg.org). GMRG is a worldwide community of researchers addressing manufacturing supply chain management, and this group has been collecting data across the globe since 1985. This study utilizes data collected in the latest round of this surveying process. Research models and resulting hypotheses were tested using partial least squares (PLS) analysis, and results were deduced as summarized above.

There is growing interest in deploying costly data handling and analytics tools and techniques for business, broadly described as “business analytics.” This research implies a critical role for supply chain initiatives as resources that complement and enhance analytics-related influences on manufacturing performance.