A systematic methodology to deal with the dynamics of customer needs in Quality Function Deployment

In the context of a customer-driven product or service design process, a timely update of customer needs information may not only serve as a useful indicator to observe how things change over time, but it also provides the company a better ground to formulate strategies to meet the future needs of its customer. This paper proposes a systematic methodology to deal with customer needs’ dynamics, in terms of their relative weights, in the QFD. Compared to previous research, its contribution is three-fold. First, it proposes the use of a forecasting technique which is effective to model the dynamics of Analytic Hierarchy Process (AHP) based importance rating. This is owing to the fact that the AHP has been applied very extensively in the QFD and there is, unfortunately, almost no tool to model the dynamics. Second, it describes more comprehensively on how future uncertainty in the weights of customer needs may be estimated and transmitted to the design attributes. Third, it proposes the use a quantitative approach that takes into account the decision maker’s attitude towards risk to optimize the QFD decision making analysis. Finally, an example based on a real-world application of QFD is provided to show the practical applicability of the proposed methodology.

Research highlights
► When the cost of not producing a product that the customer wants is tremendously large, it is reasonable to make extra efforts to monitor and follow the customer preference change over time.
► A timely update of customer needs information provides a company a better ground to formulate strategies to meet the future needs of its customer.
► How precisely one can model or learn from the past data may critically determine how precisely one may estimate or understand the future.