Optimizing the new product development process in building materials industry

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Vicwest would like to develop a sustainable process model for new product introduction that is based on data and will support the company's business plan with minimum risk. The current models in the literature do not address the complexities that are specific to the building materials industry such as the dynamics of competition and markets, and lack of aggregate industry data. To design such a process, there are several challenges that are inherent to the specific nature of the building materials industry, as opposed to the widely studied retail merchandising sector. In this project, we focus on four challenges: 1) developing reliable forecasts for demand of new products in this sector; 2) determining the optimal launch in regards to current company offerings as well as competing products; 3) understanding the customer adoption patterns of the new products; and 4) integrating the new product demand forecasting with the production planning and inventory management. We will use the company data to design specialized diffusion models to forecast the new product demand. Moreover, we will use the demand forecasts as inputs to a multi-stage stochastic programming model for production planning and inventory control. We will also explore the solution strategies for this multi-stage stochastic programming model. Finally, we will develop the prototypes of the proposed methods. This research project will make contributions to the academia, industry and HQP training. In academia, we will quantify and analyze the different diffusion models with real-size industry data; we will also develop multi-stage stochastic programming models and corresponding solution methodologies for new product production planning and inventory control. In industry, we will help Vicwest develop prototypes of the decision support tools of simulation and optimization. In HQP training, we will provide valuable opportunities in applying the business analytics expertise to a real industry application.