Complexity as contingency in sales and operations planning
Abstract
Purpose
The purpose of this paper is to test whether complexity interacts with Sales and Operations Planning (S&OP) practices by positively moderating the impact of S&OP practices on manufacturing operational performance dimensions of quality, flexibility and delivery.
Design/methodology/approach
Three hypotheses are developed on the relationships between S&OP practices, task complexity and process complexity and manufacturing operational performance. Scales are validated with structural equation modelling. The hypotheses are tested through a hierarchical regression analysis using data from a sample of 725 manufacturing plants from 21 countries.
Findings
S&OP practices of organizational management, technological integration, measurement systems and integration of plans impact positively on manufacturing operational dimensions of quality, delivery and flexibility. Process complexity moderates the effect of S&OP practices, amplifying its impact upon all three performance dimensions. Product complexity moderates the effect on quality, but not on delivery and flexibility.
Practical implications
S&OP practices of organizational and technological coordination of manufacturing and new product design; information technology to measure information sharing and planning; dedicated information systems do impact upon manufacturing operational performance. Results are amplified by process complexity. The more complex are the manufacturing processes the larger the gains of S&OP.
Originality/value
This research applies contingency theory to S&OP and empirically demonstrates its impact on manufacturing operational performance and the moderator role of complexity.
Keywords
Acknowledgements
The authors gratefully acknowledge MCT/CNPq (research project: 307996/2011-5), CAPES/DFG (BRAGECRIM research project: 010/09) and CAPES/DAAD (PROBAL).
Citation
M.T. Thomé, A., Soucasaux Sousa, R. and F.R.R.S. do Carmo, L. (2014), "Complexity as contingency in sales and operations planning", Industrial Management & Data Systems, Vol. 114 No. 5, pp. 678-695. https://doi.org/10.1108/IMDS-10-2013-0448
Publisher
:Emerald Group Publishing Limited
Copyright © 2014, Emerald Group Publishing Limited