This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE SYSTEMS JOURNAL 1 An Innovative Fuzzy Logic Based Approach for Supply Chain Performance Management Nedaa Agami, Mohamed Saleh, and Mohamed Rasmy Abstract —In the last decade, the topic of supply chain per- formance measurement has attracted the attention of many researchers and practitioners worldwide. A series of significant changes and advancements in the theory and applications has been noticed. Nevertheless, gaps still exist. Current supply chain performance measurement systems still suffer from being too inward looking, ignoring external environmental factors that might affect the overall supply chain performance in the fu- ture when setting new targets. In this paper, we introduce an innovative approach to supply chain performance management. The proposed idea integrates fuzzy logic with trend impact analysis and provides a scenarios-based method that simulates and quantifies the possible effect of external factors on the supply chain performance, and thus enables setting realistic achievable targets. The idea is novel and beyond the state of the art of supply chain performance measurement. Index Terms—Fuzzy logic, performance management, supply chain, trend impact analysis. I. Introduction P ERFORMANCE measurement is a fundamental build- ing block of successful organizations. It constitutes an essential element of effective planning, control, and decision making by providing decision makers and stakeholders with necessary feedback information to identify problems, diagnose them, and hence design improvement strategies accordingly. In the supply chain management context, measurement results reveal the effects of strategies and highlight potential opportu- nities for sustainable improvement. Supply chain performance measurement (SCPM) has attracted much attention from both researchers and practitioners in the last decade. So far, there have been numerous studies, articles, and papers addressing this topic. However, a gap between the developed approaches and practical requirements for implementation still exists [1]. In a recent study, Agami et al. [2] have introduced a hybrid dynamic framework for supply chain performance improvement that addressed most, but not all, of the SCPM challenges highlighted in the literature. The gaps in their approach are the main motivation behind this research. We use their approach as our point of departure. Table I illustrates the Manuscript received June 5, 2012; revised September 5, 2012; accepted September 15, 2012. The authors are with the Department of Operations Research and Decision Support, Faculty of Computers and Information, Cairo University, Giza 12613, Egypt (e-mail: n.agami@fci-cu.edu.eg; m.saleh@fci-cu.edu.eg; m.rasmy@fci-cu.edu.eg). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JSYST.2012.2219913 main advantages and gaps of their approach. In this research, we focus specifically on addressing and tackling the seventh limitation that criticizes the current SCPM approaches for being too inward looking. Research on SCPM can generally be classified into two groups. The first group focuses on models and frameworks discussing what to measure, i.e., key performance indicators (KPIs), whereas the second group focuses on analytical tech- niques and quantification of performance for further improve- ment. The approach proposed in this paper falls under the second group. We propose an innovative fuzzy logic based trend impact analysis approach for supply chain performance management. It enables decision makers to consider external environmental factors that might affect the overall supply chain performance in the future when designing improvement strategies and setting new performance targets and thus make more effective decisions. The remainder of this paper is organized as follows. In Section II, we explain the problem addressed. In Section III, we briefly discuss the fuzzy logic based trend impact analysis approach adopted in this research. Then, in Section IV, we discuss the proposed approach in the SCPM context in detail that is followed by a case study to demonstrate how it works in Section V. In Section VI, we conclude and discuss future work. II. Problem Addressed Performance measurement is an indispensable management tool and the vehicle to achieve supply chain success, as it enables stakeholders to strategically manage and continuously control achieving objectives. Despite being crucial for achiev- ing supply chain success, the contributions of the currently existing SCPM systems are discounted by the existence of several critical flaws, as highlighted in Table I. By realizing these flaws, Agami et al. [2] recently proposed a hybrid dynamic framework for SCPM that tackled most of them. However, the unaddressed limitations still constitute a gap for effective practical implementation of their approach. It is still criticized for being too inward looking because it evaluates the performance of supply chains by taking into consideration only internal operations across the chain while ignoring the effect of possible external environmental incidents that would impact the overall supply chain performance if they were said to occur. In many cases, this leads to setting unrealistic new performance targets. So, the main idea is to base target setting on more realistic forecasted values. This is done by utilizing fuzzy logic based trend impact analysis. 1932-8184/$31.00 c  2012 IEEE