Success in implementing statistical process control as a function of contextual variables in 20 manufacturing organizations

Relationships between organizational contextual variables and success in implementation of Statistical Process Control (SPC) were investigated in 20 manufacturing organizations. It was hypothesized that 6 contextual variables would be related to success in implementing SPC: extent of training, quality of training, supportive management, higher management involvement, participation, and planning and evaluation.

In Study 1, 65 participants took part in a pilot study to assess the internal consistency and reliability of the scales used to measure the contextual variables. In Study 2, a separate group of 96 representatives of departments in 20 organizations completed a questionnaire on contextual variables and four indices of success in implementing SPC: fraction of operations monitored, total number of SPC concepts and techniques used, change in machine uptime, change in quality cost.

Data were collected retrospectively through mailout questionnaires. Correlational analyses were performed to assess the relationships between the contextual variables and success in implementing SPC. Length of time involved with SPC and pre-scores on the criteria were statistically controlled in tests of the predicted relationships. Results indicated that supportive management and training quality were related to improved average uptime of machines. Only participation was consistently related to improved quality cost. Participation, extent of training and training quality were related to the total usage of SPC. Finally, the extent of training was related to the fraction of operations monitored. Taken together the six contextual variables were related to improved average uptime of machines and the total usage of SPC, and were not related to improved quality cost and the fraction of operations monitored. The two process criteria, total usage of SPC and fraction of operations monitored, tended to be related to improved average uptime of machines and improved quality cost, although the relation between the fraction of operations monitored and change in average uptime of machines was not as expected. Limitations as well as practical and theoretical implications of the study are discussed.