Customer Delivery Performance Research Articles

EFashion Inc. Warehouse (A)

Design of a warehouse includes estimating the number of storage location, establishing the number of tiers, aisles etc. Optimal warehouse design affects the order pick time and customer delivery performance. The participant will use concepts from inventory management to obtain the number of storage spaces and also learn to partition the warehouse space into a forward and a reserve area. Such partition will allow to minimize the throughput times.

A conceptual model for factors affecting the relationship between supply chain integration and customer delivery performance

Supply chain is a widely used concept around the world. Nowadays, companies need to integrate their production processes, from the raw materials to the end-user. Supply chain management is a phenomenon that achieves this in a way that ensures customers get reliable and fast service and high quality products at the lowest possible cost. There is very limited and sporadic research on supply chain integration and how it affects supply chain performance. Therefore there is no real understanding of the concept of supply chain integration and how it affects supply chain performance nor is there a holistic model. This paper thus aims to present a model that identifies factors affecting the relationship between supply chain integration and customer delivery performance. After analyzing the collected data on supply chain integration and customer delivery performance, the preliminary model was proposed and completed, and using expert opinion in the Imam Khomeini Oil Refinery the final model and for factors affecting the relationship between supply chain integration and customer delivery performance were presented. To determine how these factors interrelate with each other, the DEMATEL method was then used. The statistical population included the staff at Imam Khomeini Oil Refinery in Shazand. The data, collected through the standard DEMATEL questionnaire, were analyzed using the DEMATEL method and a MATLAB program. The DEMATEL results indicate that intra-organizational factors, institutional norms, technological certainties are causal factors which influence other factors that affect the relationship between supply chain integration and customer

A Study of Theory of Constraints Supply Chain Replenishment System

An effective inventory replenishment method implemented in the supply chain is one of the key success factors to achieve low inventory while maintaining high customer delivery performance. The Theory of Constraints (TOC) Supply Chain Replenishment System (TOC-SCRS) is one of the solutions to get this improvement in a multi-echelon supply chain. The TOC-SCRS is a replenishment method of the TOC supply chain solution. The TOC is a global managerial methodology that helps the manager to concentrate on the most critical issues. The TOC-SCRS is based on the following two strategies to decouple the bullwhip effect (or excess inventory in each node) and maintain the inventory availability to consumers (next nodes): (1) each node holds enough stock to cover demand during the time it takes to reliably replenish; (2) each node only needs to replenish what was sold. The TOC- SCRS is now being implemented by a growing number of companies. The performance reported by the implemented companies includes reduction of inventory level, lead-time and transportation costs and increasing forecast accuracy and customer service levels. However, the exploration of TOC-SCRS is lack in the literature. In this study, the concept and method of TOC-SCRS is first reviewed and modeled. A virtual supply chain case is secondly designed to show the behavior of the TOC-SCRS. A three factorial experiment, i.e., fluctuation of demand, time of replenishment and frequency of replenishment, is then presented to explore the feasibility and effectiveness of TOC-SCRS. A simulation model is designed to complete the experiment.

Achieving customer service excellence using Lean Pull Replenishment

PurposeThe purpose of this study is to highlight a key strategic initiative within the former ADC Company (now part of TE Connectivity) called “Lean Pull Replenishment”, designed and implemented to achieve Six Sigma customer service excellence. This case study would also help facilitate problem‐based learning pedagogy.Design/methodology/approachThe study showcases implementation of the Lean Pull Replenishment approach using the define, measure, analyze, improve and control (DMAIC) framework. Key input variables were analyzed that contributed to historically inconsistent and unsatisfactory customer delivery performance. Analysis resulted in improving the allocative efficiency of critical input variables through pilot programs on strategic value streams by deploying dozens of kaizen events, and sustaining the gains through leveraging best practices and effective change management principles.FindingsThe study presents a strong case for the team work and the cultural transformation that occurred during the course of implementing this initiative across ADC supply chain. The paper also summarizes the improvement in customer service metrics and financials of the company.Originality/valueThrough this study, it has been established that with consistency of purpose, using the right tools for solving problems and through teaching Lean principles, remarkable results can be achieved, which can be sustained for the long‐term and become a self‐sustaining business philosophy.

The moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance

PurposeThe purpose of this paper is to test the moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance.Design/methodology/approachBased on a survey questionnaire with 151 participants in the Thai automotive industry supply chain, hierarchical regressions are used to test the moderating effects.FindingsInternal and supplier integration, but not customer integration, were positively associated with customer delivery performance. Technological and demand uncertainties were found to moderate the relationships between internal integration and customer delivery performance, and supplier integration and customer delivery performance.Research limitations/implicationsThe moderating effects of technological and demand uncertainties in the Thai automotive just‐in‐time (JIT) environment are explained. This research contributes to the development of a contingency theory of supply chain integration suggesting that the impacts of supply chain integration on customer delivery performance vary under different levels of technological and demand uncertainties.Practical implicationsManagers recognize the diminishing effects of internal integration and supplier integration under demand uncertainty, and the increasing effect of supplier integration under high technological uncertainty.Originality/valueThis study contributes to the supply chain management literature by clarifying the moderating effects of technological and demand uncertainties on the relationship between supply chain integration and customer delivery performance.

Research on Inventory Control Policies for Nonstationary Demand based on TOC

An effective inventory replenishment method employed in the supply chain is one of the key factors to achieving low inventory while maintaining high customer delivery performance. The state of demand process is often not directly observed by the decision maker. Thus, in many literatures, the inventory control problem is a composite-state, partially observed Markov decision process (POMDP), which is an appropriate model for a number of dynamic demand problems. In practice, managers often use certainty equivalent control (CEC) policies to solve such a problem. However, in reality, Theory of Constraints (TOC) has brought a practical control policy that almost always provides much better solutions for this problem than the CEC policies commonly used in practice. In this paper, we proposed three different inventory control policies based on TOC buffer management framework, and use simulation approach to compare them with traditional adaptive (s,S,T) policy. The computational results indicate how specific probl...

Performance prediction using supply chain uncertainty modelling

This paper presents a new quantitative method and a holistic approach to assess the impact of supply chain uncertainty on customer delivery performance. We adopt system theory, Multi Criterion Decision Making (MCDM) theory – Analytical Hierarchy Process (AHP) and Theory of Constraints (TOC) as the underpinning theoretical frameworks for this new method. Some 72 UK companies have verified this method and we call this – the Supply Chain Uncertainty Impact Assessment (SCUIA) method. Some 66 types of supply chain uncertainty are assessed. This method involves three levels of assessment, namely: (1) relative percentage occurrences of each supply chain uncertainty, (2) relative upstream and downstream impact of each supply chain uncertainty and (3) relative likelihood of each underlying causes of supply chain uncertainty. The findings show that underlying causes of supply chain uncertainty with higher likelihood of occurrences do not necessarily result in greater impact on the downstream delivery performance in the supply chain. It can be concluded that decision makers should not use the likelihood of occurrence or impact criteria in isolation when devising solutions to tackle supply chain uncertainty, but to tackle those underlying causes of supply chain uncertainty that have both greater impact and higher likelihood of occurrence.

Causal modeling alternatives in operations research: Overview and application

This paper uses the relationships between three basic, fundamental and proven concepts in manufacturing (resource commitment to improvement programs, flexibility to changes in operations, and customer delivery performance) as the empirical context for reviewing and comparing two casual modeling approaches (structural equation modeling and Bayesian networks). Specifically, investments in total quality management (TQM), process analysis, and employee participation programs are considered as resource commitments. The paper begins with the central issue of the requirements for a model of associations to be considered causal. This philosophical issue is addressed in reference to probabilistic causation theory. Then, each method is reviewed in the context of a unified causal modeling framework consistent with probabilistic causation theory and applied to a common dataset. The comparisons include concept representation, distribution and functional assumptions, sample size and model complexity considerations, measurement issues, specification search, model adequacy, theory testing and inference capabilities. The paper concludes with a summary of relative advantages and disadvantages of the methods and highlights the findings relevant to the literature on TQM and on-time deliveries.

Work load responsive adjustment of planned lead times

Mechanisms to adjust planned lead times based on current work loads are desirable for time‐phased planning systems. This paper investigates the use of exponentially smoothed order flow time feedback in setting planned lead times dynamically. The system studied is a supply chain with capacity‐constrained processing stations and transit times between stations. Lot sizes are based on the minimization of flow times using queuing approximations. Both seasonal and level demand patterns with uncertainty are considered. Since both dependent and independent demands are assumed at each station, customer delivery performance depends on the distribution of inventory along the supply chain. Results show that dynamic planned lead time setting can be used effectively to control delivery performance along the supply chain. Performance is also influenced significantly by appropriate lot size selection.

Measuring uncertainties in MRP environments

Many uncertainties in Material Requirements Planning (MRP) systems are treated as “controllable” elements, with a variety of buffering, dampening and other approaches being used to cope with them. However, such approaches are often found wanting, forcing enterprises into emergency measures to ensure delivery performance. Based upon the results of a questionnaire survey, this paper analyses the uncertainties in the aggregate, intermediate and operational levels that affect customer delivery performance in MRP environments. These uncertainties have been quantified and the relative importance to performance has been investigated. The results also show the widespread use of buffering, dampening and other approaches to provide a level of delivery reliability. It is contended that by concentrating on minimising the effects of the uncertainties, the underlying causes have not been addressed, resulting in sub‐optimisation of system performance.

Managing Manufacturing Operations in the U.K.

This paper describes some of the major findings relating to the management of manufacturing operations which have emerged from survey work originally carried out in conjunction with the British Institute of Management. More detailed follow-up studies are also outlined relating to delivery performance and a particular industrial sector: capital electronics goods. The paper summarises the main results of the original survey based on replies from manufacturing managers in 186 plants (representing 158 companies), relating to the characteristics of the companies surveyed, the personal and career details of the responding managers, the nature of the manufacturing operations carried out in the 186 plants, particularly with regard to customer delivery performance and manufacturing lead times, use of computers and sophisticated techniques in manufacturing, and the control systems used in the initiation of production orders. Finally, calling on data from later studies, an attempt is made to focus attention on the key issues in manufacturing management as they relate to U.K. industrial performance.