SUPPLY CHAIN MANAGEMENT COORDINATION MECHANISMS

Journal of Business Logistics, 2006 by Fugate, Brian, Sahin, Funda, Mentzer, John T

There is growing interest from industry and academic disciplines regarding coordination in supply chains, particularly addressing coordination mechanisms available to eliminate sub-optimization within supply chains. However, there is a disconnect between what is known in academic research about coordination mechanisms and what mechanisms practitioners apply and consider useful. This research fills a gap in the literature by conducting an in-depth qualitative study of supply chain coordination mechanisms, primarily price, non-price, and flow coordination mechanisms. Results suggest that: (1) managers prefer flow coordination mechanisms over price and non-price coordination mechanisms; (2) supply chain orientation and learning orientation are important for the implementation of flow coordination mechanisms; and (3) technology, capital, and volume are not pre-requisites for flow coordination mechanisms.

Key Words: Coordination Mechanisms; Qualitative Research; Supply Chain Management; Supply Chain Orientation

INTRODUCTION

A supply chain is composed of trading partners that are interconnected with financial, information, and product/service flows. Effective management of these flows requires creating synergistic relationships between the supply and distribution partners with the objective of maximizing customer value and providing a profit for each supply chain member. However, often there is not an effective control mechanism to coordinate the actions of the individual supply chain members such that their decisions are aligned with global supply chain objectives. In this case, each supply chain member attempts to optimize a part of the system without giving full consideration to the impact of their myopic decisions on total system performance. This decentralized decision-making process is the traditional mode of operation in today's business environment. Optimizing portions of the system often yields sub-optimal performance, resulting in an inefficient allocation of scarce resources, higher system costs, compromised customer service, and a weakened strategic position.

Pitfalls associated with optimizing the individual system components while neglecting the whole are well documented in the literature. Spengler (1950) provides early documentation with his findings on "double marginalization," where the retailer does not consider the supplier's profit margin when making inventory stocking decisions, and therefore orders too little product for system optimization. Forrester's (1958) seminal study of industrial dynamics in a four channel supply chain illustrates how rational decision-makers acting independently can cause customer demand information to distort and amplify while moving upstream in the supply chain, resulting in inaccurate forecasts, inefficient asset utilization, and poor customer service. In the 1990s, this phenomenon was re-introduced by Lee, Padmanabhan, and Whang (1997), when they coined the term "bullwhip effect" in supply chains to refer to the sub-optimization phenomenon. They suggested information sharing among supply chain members and the re-alignment of decision-maker incentives to accomplish supply chain objectives.

Rapid advances in information technology spurred the interest in industrial dynamics and the bullwhip effect, leading to significant research activity on supply chain management. Sahin and Robinson (2002) surveyed the literature on supply chain integration and proposed information sharing and coordination among supply chain members as the primary drivers of supply chain performance. Their findings indicated that the potential savings associated with enhanced information sharing and decision coordination could reach as high as 35% of total system costs, depending upon the particular operating environment and problem assumptions. A key finding from the study showed that while information sharing was often considered a "silver bullet" for supply chain improvement, even greater benefits in system performance are available through decision-making coordination, which aligns all information and incentives to support global system objectives.

Establishing the organizational relationships among partners to attain system coordination, however, is a challenging task that requires identifying the magnitude of anticipated benefits and devising strategies for sharing the benefits, costs, and requisite investments among supply chain members. This underscores the need for additional research investigating the economics of coordination and its application in order to better understand how to justify and build long-term inter-organizational relationships. Cannon and Perreault (1999) also call for more research on exploring coordination mechanisms.

Coordination is the essence of supply chain management as evidenced by some of the definitions of supply chain management listed in Table 1. Benefits from coordination of supply chain activities are well-documented in the literature (see Table 2 for a brief set of potential benefits). There is a growing body of academic research, in a variety of disciplines, on coordination in supply chains, particularly addressing the potential coordination mechanisms available to eliminate sub-optimization within supply chains. Similarly, there is a growing interest in industry to better understand supply chain coordination and the coordination mechanisms that are available to assist the supply chain manager. Nonetheless, there is a disconnect between what is known in academic research about coordination mechanisms and what mechanisms practitioners apply and consider useful. Most of the academic research on coordination mechanisms presents economic and/or normative models that indicate what should happen when applying particular coordination mechanisms. Unfortunately, how managers apply coordination mechanisms and what actually happens in practice remains unknown. Additionally, the disjointed scattering of research activity in a variety of disciplines makes it more difficult to represent what is currently known and whether the body of knowledge is in sync with what is practiced and perceived in industry as effective.