Supply Chain Management and Knowledge Management

At a recent gathering of 30 top executives from non-competing customerfacing firms at an innovation summit, discussions centred on how to innovative more effectively (Petrick 2007a). These companies are struggling with how to identify the best talent, how to fund and manage the innovation process, and how to measure its effectiveness. Without exception, these executives believe that leveraging their company’s supply chain and the talent and technologies located within it are a key to success. A major barrier to this, however, was captured by one executive’s comment, ‘Within our company, and even outside of it, information gets shared. Insight doesn’t.’ This chapter focuses on the theoretical understanding and practical realities of networked innovation. We specifically explore the challenges of creating and sharing insights in supply chain networks.

To improve their performance and respond to market pressures such as international competitiveness, outsourcing and harder to please customers, manufacturing firms are now being forced to develop closer relationships with their suppliers and customers (Corbett, Blackburn and Van Wassenhove 1999, Kotabe, Martin and Domoto 2003). These new inter-organizational structures have resulted in the emergence of tightly coupled networks, also called supply chains, within many sectors (Andersen and Christensen, 2005).

The development of the field of supply chain management (SCM) has led to the realization of significant, firm-level and industry-wide financial efficiencies, as inventory levels are managed through the application of a variety of knowledge management techniques to logistics management. Independently, the field of strategic technology planning (STP) has grown, addressing the longer-term needs of firms as they develop options for current investment and potential future return.

Networked organization structures have become common practice for cornpanies to strengthen their competitive position. Examples of such networks include temporary project-based cooperations (e.g. in product design or system development projects), marketing organizations and industrial clusters sharing expensive resources. Such networks can take form of supply chains (SC) integrating enterprises based on their contribution to the value chain. SC are typically governed by common economical and value-creation objectives and proactively form cooperations for a given demand. These cooperations are geographically distributed, respond quickly and are flexible to market demands. The life cycle of SC, including a description of needs and services of the cycle phases, is presented in Figure 4.1 and Table 4.1.

It is well established that supply chains can be multitiered dynamic systems where each tier may have multiple entities (such as suppliers or manufacturers) and the linear flow of goods is uncommon (Riddalls, Bennett and Tipi 2000). This complexity is exacerbated when entities in the supply chain may be involved in a multitude of other supply chains, each with differing requirements or objectives (Sahin and Robinson 2002). In a supply chain system, there are forward flows of materials as product is moved from the supply base, to the manufacturers and eventually to the end customer. These material flows are triggered by information flows, which move in the reverse direction through the supply chain as shown in Figure 6.1.

In order to improve upon competitive capabilities, firms need to understand how manufacturing and supply chain operations should be designed to better support market requirements. The interrelationships between product characteristics, supply chain design, process choice and the design of manufacturing planning and control principles is a complex problem generating increasing interest in industry and academia. How these decisions should be coordinated is an important issue for operational and supply chain performance. How product characteristics affect one or the other has previously been discussed in the literature. Three fundamental theoretical models are the product-supply chain model by Fisher (1997), the product-process matrix by Hayes and Wheelwright (1979a) and the systems-strategy model for linking manufacturing planning and control (MPC) system choices to product characteristics by Berry and Hill (1992). Other models have been proposed for linking product characteristics to supply chain design, process choice and MPC approaches, but all relate strongly to these three models. Thus, these three models can be considered as baseline reference models. They have been tested before, but only one at the time. Here, we provide a comprehensive analysis of all four factors.

The chapter will start with a description of the background to the problem and related literature. The next section will provide a general outline of the proposed new methodology, which makes use of phase plane analysis to detect patterns and profiles associated with decision frontiers. The third section describes some of the theory underlying the new approach, as well as the applications where it can be used. The final section ends with a conclusion and indications of further research.

A supply chain consists of a network of business units that procure raw materials, transform them into final products and distribute them to customers through a distribution system. The aim of supply chain management (SCM) is to manage these activities so that products go through the network in the shortest time and at the lowest costs (Lee and Billington 1995). For many companies the supply chain is the most crucial element in their entire value proposition to customers. A great deal of current commercial effort is being devoted to technology to support and manage supply chains.

For the past few years, many companies have investigated potential of radio frequency identification (RFID) technologies by conducting pilot project. Whereas successful cases were reported for supply chains, companies experienced under-achievement of their target on return on investment (ROI) due to various reasons. First of all, RFID hardware itself would be limited in satisfying functionality and performance of user requirements. The RFID hardware has been mature because RFID vendors have made a lot of effort to develop more robust RFID tags and readers. Except for harsh manufacturing environment, RFID hardware can be satisfactorily implemented right through RF design and calibration. Second, RFID would have been applied to inappropriate applications. In order to take a competitive advantage, some companies rushed to implement the RFID by selecting improper applications. The RFID is effective in an environment where materials, work-in-process and finished products are moving dynamically. Third, no sufficient planning and analysis would have been conducted as to the use of RFID data, the impact of RFID on other business processes and the connectivity to related information systems. This can lessen business benefits of the RFID capability.

An order coordination policy based on the order-up-to (OUT) policy that minimizes the total inventory costs for a three-level supply chain will be examined. For a single level of a supply chain, Vassian (1955) introduced an ordering policy with a work in progress (WIP) feedback loop and showed that this ordering policy minimizes the variance of the end of period net stock levels. In addition, Vassian showed that the minimized variance of the end-period net inventory level is identical to the variance of the error in the forecast of demand over the lead time plus review period. In this research, Vassian’s ordering policy is called as the traditional OUT policy.¹ From Vassian’s seminal contribution, it is obvious that in a single-level supply chain case, the traditional OUT policy is an optimal policy for minimizing the variance of the end of period net stock levels over time. In a multi-level supply chain scenario, however, it might be reasonable to assume that a sequence of traditional OUT policies may not be optimal any more as there is no guarantee that a succession of local minimizations will result in a global optimum, as shown in Hosoda and Disney (2006a). Since the traditional OUT policy does not provide much freedom to manipulate the dynamics of the ordering process, Hosoda and Disney (2006a) have investigated a two-level supply chain using the traditional OUT policy modified to include a proportional controller.

Successful companies seem to be, nowadays, those that have carefully linked their internal processes to external suppliers and customers in unique supply chains (Frohlich and Westbrook 2001, Boyer, Frohlich and Hult 2004). In this effort towards linking internal processes to external suppliers and customers, the sharing of information among enterprises is absolutely critical. Electronic data interchange (EDI) in the past and the internet in the last decade have enabled supply chain partners to act upon the same data (Christopher 2005). This reality explains much of companies’ initial enthusiasm regarding the introduction of the internet and internet-based application in the early 1990s. Companies’ ultimate goal of process integration across the entire supply chain was now much more feasible than ever before.

In the present environment of rapid change, organizations collaborate in order to rapidly deploy resources, and the extant literature acknowledges that increased inter-organizational learning is a beneficial consequence of such collaboration (Chen, Paulraj and Lado 2004, Simchi-Levi, Kaminsky and Simchi-Levi 2003). Such collaborative learning strengthens the development of joint capabilities (Lane and Lubatkin 1998, Lui and Ngo 2005, Selnes and Sallis 2003), provides a constant stream of innovation (Hall and Adriani 1998) and ensures a greater balance of bargaining power (Hall and Adriani 1998).

In the 21st century, logistics has emerged as a leading and complex field. Logistics deals with everything involving planning, organizing and managing activities that provides goods or services (Logistics World 1997). Main factors that have contributed to the emergence and complexity of logistics include: globalization, outsourcing, contract manufacturing, shortened product life cycles, pressure to reduce carbon-emissions, multichannel distribution and the need for adequate return channels.

The growth in e-business over recent years, driven by developments in information and communication technology, has resulted in the increased use of electronic marketplaces (EMs) for business-to-business transactions. Potentially, EMs can have a significant influence over the way that transactions are carried out, relationships are formed, supply chains are structured and profit flows are operated (Kaplan and Sawhney 2000). While many aspects of supply chain management have been considered, there are only a few studies that investigate the development of these EMs in logistics (Grieger 2003). In this chapter, we focus upon these electronic logistics marketplaces (ELMs), which are electronic hubs that use web-based systems to link shippers and carriers together for the purpose of collaboration or trading. At a basic level, an ELM involves three main parties — the shipper of goods, the carrier and a technology provider. While any of these parties can lead the ELM development, it is usual for the leader to be the shipper.

The product chain — the chain of interacting suppliers and customers, which together make up the activities from raw material extraction to handling of waste connected to a product — plays an important role in the shaping and management of environmental aspects connected to the production and consumption of a product, for example, a piece of clothing. To illustrate, with lack of environmental focus, a retail chain may only be willing to pay a certain price for the product because their business strategy focuses on price competition with the other retailers. Therefore the retail chain does not care about the environmental protection measures taken by their suppliers and the retail chain procurement persons do not control the environmental aspects of the manufacturing at the suppliers’ facilities. In contrast, as an example of proactive environmental management, a manufacturing company may initiate direct supply of organic cotton from a number of small farmers in order to be able to protect their own workers during the manufacturing of T-shirts from the cotton.