A knowledge-based supplier intelligence retrieval system for outsource manufacturing

Abstract

Knowledge management is to promote business success through a formal, structured initiative to improve the use of knowledge in an organization, in which an effective organizational memory information system plays an increasingly important role. Unlike the past, the performance of an enterprise now depends much on the performance and relationship of its customer–suppliers in the value chain. Good customer–supplier relationships are important for an organization to respond to dynamic and unpredictable changes. This paper describes a knowledge-based supplier selection and evaluation system, which is a case-based reasoning decision support system for outsourcing operations at Honeywell Consumer Products (Hong Kong) Limited in China. As a result, collaborative suppliers are identified quickly during the new product development process. By using the system, the cumulative performance of suppliers is constantly updated automatically according to past practice. This means that the knowledge of suppliers can be retained, categorized, retrieved and managed effectively.

Introduction

Management of suppliers' competitiveness and alternative suppliers has become a critical activity for manufacturers because many outsourcing activities are knowledge-driven. It is therefore critical for an outsourced type manufacturer to manage this knowledge in a coherent manner. This leads to the management of supplier intelligence (SI), the knowledge of which is important for the daily operations of purchasers. However, for an effective supplier management system to be functional, the types of supplier knowledge (i.e. both quantitative and qualitative) need to be captured, codified, and cataloged.

Over the past two decades, globalizations of economies and advances in IT technology have complicated purchasing decisions. For example, the rapid expansion of information technologies means that manufacturing industries are gradually moving to a borderless business environment. Different factories play different strategic roles to co-operate and form collaborative partners within the value chain in order to increase their competitiveness. In addition, the role of the buyer–seller relationship has evolved from arms-length to collaborative, making purchasing decisions even more complicated. In fact, the quality of buyer–seller relationship becomes more important when the environment is uncertain and dynamic [1]. As for flexible and efficient purchasing decisions, there is a growing trend that companies divide supplier bases into two categories—competitive and collaborative. Hence, a knowledge-based system is therefore in great demand for supplier categorization purpose. Such system is essential for company to acquire, share and retain knowledge [2] of suppliers. However, there is little literature regarding the management of SI such as the integration of supplier categorization, supplier assessment criteria and supplier performance rating system using knowledge-based systems.

When companies outsource a significant part of their business, the process of supplier selection is involved. Consequently, supplier categorization, supplier assessment criteria and supplier performance measurement must be adopted and retrieved when a decision on outsourcing has to be made. Nevertheless, no such system is currently available in the market. In this paper, a case-based supplier selection and evaluation system (CSSES) for the new product development process is presented. At present, research on the use of Artificial Intelligent technology to integrate supplier management activities is limited. The purpose of this paper is to perform supplier selection and categorization system based on suppliers' past practices. A conceptual new approach of allying collaborative suppliers as strategic partners with manufacturers who outsource significantly is explained.

This paper is divided into eight sections. Section 2 introduces SI and its role in supplier management. Section 3 is the introduction of Case-based reasoning (CBR) technique and its application in managing SI. Section 4 describes an integrative model linking three different supplier management activities. The construction of CSSES using a hybrid inductive-nearest neighbor CBR approach is explained in Section 5. Section 6 is about an application case study using CSSES in the purchasing department of Honeywell Consumer Product (Hong Kong) Limited to aid the supplier selection process. While the detail of implementation, result and benefits are addressed in Section 7, a conclusion of the application in general is made in Section 8.