This article aims at analyzing the impact of implementing a product configuration system (PCS) on the increased accuracy of the cost calculations and the increased profitability of the products. Companies that have implemented PCSs have achieved substantial benefits in terms of being more in control of their product assortment, making the right decisions in the sales phase and increasing sales of optimal products. These benefits should have an impact on the company's ability to make more accurate cost estimations in the sales phase, which can positively affect the products' profitability. However, previous studies have not addressed this relationship to a great extent. For that reason, a configure-to-order (CTO) manufacturing company was analyzed. A longitudinal field study was performed in which the accuracy of the cost calculations and the products' profitability were analyzed before and after a PCS was implemented. The comparison in the case study revealed that increased accuracy of the cost calculations in the sales phase and consequently increased profitability can be achieved by implementing a PCS.
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In recent years, there has been an increasing demand for customized products. Product configuration systems (PCS) are introduced as one of the most successful systems of artificial intelligent for providing customized products. One of the main challenges in PCSs projects are described in relation with knowledge representations and communications with domain experts. The results presented in the paper are therefore aimed to provide insight into the impact from using visual knowledge representations techniques in PCSs projects. The findings indicate that use of visual knowledge representations techniques in PCSs projects will result in improved quality of maintenance and development support for the knowledge base and improved quality of the communication with domain experts.
This article investigates the cost implications of using a not sufficiently maintained product configuration system (PCS). A case study is conducted to investigate the financial loss due to poor data quality in products sold through a not-maintained PCS. We calculated the financial loss by comparing the quotations generated by the not-maintained PCS and the quotations for the same product when the PCS was updated. The results indicate that the company has been selling the products with a miscalculated 20% lower cost than the actual one. Comparing this financial loss to the cost required to keep the PCS up-to-date, we show that the former is significantly higher than the latter. The research concludes that the realized success and benefits of utilizing a PCS are related to its maintenance and data quality.206 Rasmussen et al. IJIEM section 3 presents the research method and introduces the case company. Section 4 presents the results and answers the research questions. Section 5 discusses the results and concludes.
Configuration lifecycle management (CLM) encompasses all configuration models across a product's life cycle. CLM covers manufacturers' needs for complex configurable products, which tend to require more seamless integration of all their business units and external stakeholders in terms of process continuity and data exchange. CLM differs from existing life cycle management tools because it focuses on sharing the configuration knowledge and data of a configurable product throughout its entire life cycle across all the involved business units of an organization. Therefore, assessing the maturity level of the organization is important for more effective and efficient implementation of CLM. Based on this, the contribution of this research is the development of a CLM maturity model that serves as a guide for the transition to complete horizontal and vertical integration of CLM knowledge and tools across and beyond an organization. The proposed maturity model is validated against the literature and existing maturity models, in addition to being examined through a workshop with industry representatives and empirical cases.
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