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Systems dynamics model for the expanded S&OP process

Abstract

Despite the S&OP (Sales and Operations Planning) process not being a new procedure in enterprises, especially the large size, it is still a research subject for their practices and computational tools support. Computational models and tools focused to aid the S&OP process are used and can contribute to improve the quality of its implementation and results. The most common tools are those based on spreadsheets; and the most sophisticated ones are based on operational research techniques inserted in Advanced Planning Systems (APS). The literature review on theory and computational techniques used to aid the S&OP process identified a lack of studies related to the use of System Dynamics. Additionally, the review indicates the need for economic and financial analysis integration studies during the preparation of aggregates plans and the use of probabilistic variables in the process enabling the statistical analysis in order to provide more reliable plans. Another relevant issue observed is that managers involved in the S&OP process do not always have a global vision of all variables and constraints involved in the process, therefore, the techniques and tools used to implement the S&OP process do not provide a holistic view of the activities and variables involved. Hence, this paper proposes a System Dynamics Model simulation that provides a holistic vision for the S&OP process, allowing the integration of finance processes and the use of probabilistic variables. The evaluation of the simulations results performed with the model, supported by a design of experiments (DoE), shows that the generated plans are compatible if compared to business procedure, with the advantage of dealing simultaneously with economic and financial analysis and still allows the generation of numerous scenarios of S&OP plans.

Keywords:
Sales and operations planning; Simulation; System dynamics; Holistic vision; Finance integration

Universidade Federal de São Carlos Departamento de Engenharia de Produção , Caixa Postal 676 , 13.565-905 São Carlos SP Brazil, Tel.: +55 16 3351 8471 - São Carlos - SP - Brazil
E-mail: gp@dep.ufscar.br