Case Study: KTP Tyres

The Use of Deseasonalization Techniques in Demand Forecasting

Mike Simpson, Andrea Genovese

• Éditeur: Kogan Page
• Année: 2016
• ISBN:
  9780749477820
• Édition: 1
• Sujet: Business
• Sous-sujet: Operations

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.

CASE STUDY

SUPPLY CHAIN MANAGEMENT

KTP tyres

The use of deseasonalization techniques in demand forecasting

Andrea Genovese and Mike Simpson

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AUTHOR BIOGRAPHIES

dr andrea genovese and dr mike simpson

andrea genovese is a Lecturer in Logistics and Supply Chain Management at The University of Sheffield Management School.

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Introduction

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. For this reason, demand forecasting is a highly customer-focused activity that can act as a trigger for production-planning processes in make-to-stock environments. Within the wide range of available forecasting techniques, the one based on time series (or historical series) are particularly relevant. A time series or historical series {Yi} is a sequence of values Y1,..,Yi,..,Yn (representing, for instance, demand for a given product) sampled at regular intervals T1,..,Ti,..,Tn for a given time period. Several components can be identified in time series.

The trend component describes the tendency of the demand in the considered time interval. As an example, Figure 1 shows a time series with a strong and eas...