Use of analytics and information technology in sales and operations planning

Objectives of the Study Sales and operations planning (S&OP) is management process aiming to balance supply and demand. It functions as a link between strategic planning and operational planning. This thesis objective was to investigate the use of analytics and information technology (IT) within S&OP. The objective was further divided into three research questions: (1) How can analytics and information technology support S&OP process? (2) What tools are used within case companies and how well they support their S&OP process? (3) How use of analytics and IT is linked to S&OP maturity? These questions are answered by literature review and empirical case study. Academic background and methodology In the first part of the literature review, sales and operations planning process is presented together with potential benefits, success factors and implementation challenges. It also covers three S&OP maturity models presented in academic and professional research material. The second part of literature review focuses on analytics and information technology within S&OP. A technological framework is presented, which was later used in the empirical study. The empirical part of the study is based on case studies conducted in three Finnish companies. This study is qualitative research and the selected data collection method in the case studies was interviews. Findings and conclusions Three case companies were analyzed by describing their business environment (markets, products, production processes), S&OP process, and analytics and information technology used for running S&OP. Each company's level of S&OP maturity was assessed by using three maturity models presented in literature review. The main finding of the study is that mature S&OP process cannot be run without supporting information technology. Additionally, following findings were lifted from the literature and case studies as key findings: (1) mature S&OP process requires sufficient maturity from existing IT architecture; (2) profit optimization requires advanced capabilities from S&OP tools; (3) firm's business environment can affect remarkably to S&OP tool selection. In all, the study was able to answer the presented research questions, but limitation to three case studies makes generalizations to theory difficult