Towards customization : Evaluation of integrated sales, product, and production configuration

Acknowledgement We are grateful to the anonymous reviewers for their constructive comments, which helped us improve both the quality and presentation of the paper.Peer reviewedPostprin

Optimization Of Strategic Planning Processes For Configurable Products: Considerations For Global Supply, Demand, And Sustainability Issues

The assortment planning problem is to decide on the set of products that a retailer or manufacturer will offer to its customers to maximize profitability. While assortment planning research has been expanding in recent years, the current models are inadequate for the needs of a configurable product manufacturer. In particular, we address assortment planning for an automobile manufacturer. We develop models to integrate assortment planning and supply chain management, designed for use by a large automaker in its strategic planning phase. Our model utilizes a multinomial logit model transformed into a mixed integer linear program through the Charnes-Cooper transformation. It is able to scale to problems that contain thousands of configurations to possibly be offered, a necessity given the number of possible configurations an automaker can build. In addition, most research in assortment planning contains simplified costs associated with product complexity. We model a full supply chain and give a rich treatment of the complexity associated with product complexity. We believe that our model can significantly aid automotive manufacturers to balance their product complexity with supply chain complexity, thus increasing profitability. In addition, we study the effect of packaging on the assortment and supply chain of an automaker. We develop a new model for mathematically expressing the effect that packaging has on the way in which customers choose products. Packaging significantly complicates the search space of the assortment planning problem. We introduce a heuristic method based on our packaging model that speeds up the solve times of the models while finding reasonably good solutions. Finally, we extend our initial model to study the effects of sustainability requirements on an automaker\u27s assortment and supply chain. We introduce constraints on the vehicle program average fuel economy, greenhouse gas emissions in the supply chain, and greenhouse gas emissions in the product use phase. We dive deep into each case to glean insights about how automakers can change their decision-making process to balance making their companies more sustainable with profit maximization. While all the examples discussed are from the automotive industry, the models developed can be adapted to address assortment planning for other types of configurable products (e.g., computers, printers, phones)

Decision Support Models For The External Variety Of Configurable Products

The decision of what configurations of a product to offer is a difficult one for marketing and sales departments. In this study, we developed decision support models that can help decision makers when using operational models to manage external variety of configurable products. Our main objective is to reduce the number of product variants offered in a proper way so that inventory and demand models do not suffer from the curse of dimension. Due to its ability and flexibility, our framework can be employed under various marketing actions. We applied our framework to both qualitative and quantitative data

Planning Product Configurations Based on Sales Data

Abstract—Manufacturing companies are currently focusing on mass customization. Delivering products that meet the requirements of individual customers complicates the production process, and diminishes the benefits of the economy of scale. By exploring commonality among products, this complexity can be significantly reduced. To determine product configurations sought by the customers and to produce them in large quantities, a new approach is proposed. The proposed approach uses a modified k-means clustering algorithm to analyze past sales data for capturing prime product configurations. The most suitable configurations are selected by solving an integer-programming model or using a sorting-based algorithm. The proposed approach was tested with an industrial case study involving sales data of large trucks collected over a period of one year. Index Terms—Clustering, mass customization, product complexity reduction, product configuration management, sales data. I