Predicting future customer requirements for product planning

Abstract

Product planning is an essential phase in the product development cycle. To ensure the success of a product, companies must understand what types of customer requirements need to be presented in the product. Traditionally, the analysis of customer requirement importance rating is done using the Quality Function Deployment (QFD) approach. However it is soon realized that such analysis are only static while the importance of each product attribute veritably varies with time. Thus, forecasting of customer requirements provide a potential solution for companies which want to be ahead of time.

These companies generally come from technology- and design- intensive industries such as electronics and transport. They compete in fast moving markets and hence invest hugely in product development to devise proactive strategies for probing and influencing the future. For this reason, the study aims to derive a suitable solution which emphasizes on effective and efficient short-term forecasting.

This study begins by presenting different methods of forecasting - both qualitative and quantitative. The pros and cons of each method are discussed to understand their effectiveness in customer requirements forecasting. Consequently, a framework for the forecasting process is proposed with particular focus on the quantitative analysis. The selected forecasting method is utilized to forecast a given set of time series data and then compared to various existing methods. In the results and discussion section, the applicability of the proposed method is justified.