Look at an application of deseasonalisation techniques and an interpretation of the results they provide.
In a manufacturing context, demand forecasting can be seen as a proactive process of determining production needs. In other words, forecasting methodologies allow estimating what products are needed and in what quantities.
This case study shows how demand forecasting is a highly customer-focused activity that can act as a trigger for production planning processes in make-to-stock environments. This study looks at the example of KTP, a company operating in the tyres industry. The company mainly manufactures tyres for agricultural machines (such as tractors and other types of equipment), with a special focus on tyres for vineyard tractors. The company is not expecting major changes in the business climate and in industry operations in the short term.
Aimed at students on operations management courses, the case demonstrates how in the presence of random, cyclical and seasonal components, the trend element in this forecasting may become less apparent. It looks at the necessity to remove components whose origin may be traced back to a known and predictable pattern (such as seasonal or cyclical). The case presents the use of deseasonalisation techniques - it looks in depth at an application of these techniques and an interpretation of the results they provide.
Mike Simpson and Andrea Genovese show readers how a company can determine a reliable forecast for its overall demand for the next year given the impact of seasonal phenomena on its sales.
Mike Simpson is a Senior Lecturer in Operations Management on the MBA programme and Operations Management and Supply Chain Management on the MSc programmes at The University of Sheffield Management School.
Dr Andrea Genovese is a Lecturer in Logistics and Supply Chain Management at the Management School of the University of Sheffield. He is also a member of the Logistics and Supply Chain Management (LSCM) Research Centre and Centre for Environment Energy and Sustainability (CEES).