Highly effective companies in supplier quality surveillance practices: a quantitative analysis

Abstract

Results presented are part of a larger mixed-mode study on supplier quality practices focusing on the cross-analysis of interviews, focus groups, and a questionnaire, which collected actual data about timing, costs, practices, and non-conformances associated with purchase orders (POs) from Engineering Procure and Construct (EPC) projects for four material types considered relevant to projects built by EPC contractors based in the United States. The present discussion specifically focuses on the analysis of the non-parametric dataset obtained from the POs to investigate a subset of companies labelled as highly effective companies (HECs). This contribution is unique as it used a mixed-mode approach to collect data beyond construction sites and investigate the product/supplier side of construction processes to advance knowledge of how materials can be sent to construction project sites free of defects and rework and indicates practices that contribute to this goal. When compared to other companies in the dataset, HECs engage in more hours of observation in suppliers’ facilities, communicate more often with suppliers, put more effort and time in the planning stages of the project, use more practices related to supplier quality surveillance and supplier quality management, and find non-conformances earlier in the project.

Keywords:

• Supplier
• engineering
• survey
• quality management
• early supplier involvement
• nonparametric statistics
• engineering-procure-construct
• United States

Disclosure statement

No potential conflict of interest was reported by the authors.

Data availability

The authors followed the guidelines set by the CII and approved by the Institutional Review Boards (IRBs) at the University of Arkansas and San Diego State University to obtain, store, and analyze the data. Sharing of the raw data with identifiers of those who submitted data is not allowed. However, the Construction Industry Institute can be contacted so that data without identifiers can be obtained. All identifiers were removed before the analysis was conducted and that should not limit the results obtained in any way.

Additional information

Funding

This work was supported by Construction Industry Institute [RT-308].