Supply chain redesign for lead-time reduction through Kraljic purchasing portfolio and AHP integration

2019 ◽  
Vol 26 (4) ◽  
pp. 1194-1209 ◽  
Author(s):  
Augusto Bianchini ◽  
Andrea Benci ◽  
Marco Pellegrini ◽  
Jessica Rossi
Keyword(s):  
Supply Chain ◽  
Business Strategy ◽  
Lead Time ◽  
Small And Medium Enterprises ◽  
Evaluation Criteria ◽  
Portfolio Analysis ◽  
Lead Times ◽  
Content Type ◽  
Lead Time Reduction ◽  
Time Reduction

Purpose The purpose of this paper is to provide a flexible and extensible model for the classification of suppliers, within the purchasing guidelines and market trends of an Italian small company, leader in the production of street lamps. The model is applied to identify critical supply chains with the final objective of lead-time reduction. Design/methodology/approach The model is obtained by the application of the purchasing portfolio analysis through the construction of Kraljic matrix. Profit impact and supply risk criteria are selected according to the main company requirements, and then prioritized by the analytical hierarchy process (AHP). Finally, supply chain lead-times are analyzed with Gantt diagrams. Findings The application of the model allows the determination of company criticalities in terms of high lead-times and of the involved suppliers. The analysis of critical suppliers positioning in the Kraljic matrix allows the definition of some possible strategies to implement for lead-time reduction. Research limitations/implications Purchasing portfolio analysis and Kraljic matrix are practical instruments to quickly frame company purchasing situation, but their application is not simple due to the numerous and different factors involved, especially in small and medium enterprises (SMEs), where resource are scarce and several constraints limit operations. The objective of the research is the development of a practical tool for strategic purchasing, simple and robust to be implemented in SMEs, with limited resources and access to quantitative supplier data. Originality/value Evaluation criteria definition is one of the most difficult phases, such as their univocal and quantitative comparison. The problem of selecting and prioritizing both quantitative and qualitative criteria for suppliers classification is overcome with the combined application of Kraljic matrix and AHP. The newly integration of the two methodologies allows the realization of a reliable and robust model for suppliers classification, which can be easily adapted to company business strategy changes.

Investigating the value of reducing errors in inventory information from a supply chain perspective

Kybernetes ◽  
2015 ◽  
Vol 44 (2) ◽  
pp. 176-185 ◽  
Author(s):  
Kazim Sari
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Lead Time ◽  
Service Level ◽  
Supply Chain Collaboration ◽  
Content Type ◽  
Useful Knowledge ◽  
Lead Time Reduction ◽  
Customer Service Level ◽  
Time Reduction

Purpose – The purpose of this paper is to investigate the value of reducing errors in inventory information from a supply chain perspective. To this end, the benefits of reducing errors in inventory information are compared with those of lead time reduction and supply chain collaboration. Design/methodology/approach – A simulation model is constructed to perform the analysis. Findings – Results show that lead time reduction is the most important strategy for a supply chain in reducing total supply chain cost. In terms of customer service level, on the other hand, strategy of reducing errors in inventory information is observed as the most considerable strategy. However, the results for supply chain collaboration are somewhat unexpected. Namely, in spite of its popularity, supply chain collaboration provides very limited contribution to the supply chain. Practical implications – This research provides useful knowledge for the managers of a business enterprise in prioritizing various supply chain strategies. Originality/value – In supply chain management literature, greater emphasis is given to lead time reduction and supply chain collaboration than dealing with errors in inventory information. This research makes it clear that errors in inventory information should not be underestimated.

Supply chain lead time reduction in a pharmaceutical production warehouse – a case study

2019 ◽  
Vol 14 (1) ◽  
pp. 61-88 ◽  
Author(s):  
Ahmed Zainul Abideen ◽  
Fazeeda Binti Mohamad
Keyword(s):  
Supply Chain ◽  
Lead Time ◽  
Raw Material ◽  
Value Stream Mapping ◽  
Content Type ◽  
Value Stream ◽  
Lead Time Reduction ◽  
Future State ◽  
Time Reduction ◽  
Pharmaceutical Production

Purpose The purpose of this study is to apply value stream mapping (VSM) in Malaysian pharmaceutical production warehouse. A current and future state value stream map from the raw material receiving end to the production unit was developed to find out waste and unwanted lead time. It was very much essential to cut down the supply chain lead time at the initial phase as the raw material unloading, sorting, temporary storage and dispatch to production were seen contributing to a huge lead time build-up. Design/methodology/approach The study was initiated with the selection of a product family, construction of the current state map, identification of various wastes and the development of future state map. Findings The expected outcomes of the study include the quantification of wastes, improvement in value-added percentage and lead time reduction. Research limitations/implications The study was carried out in a single pharmaceutical company. The results of the study are deployable and can be functional in similar production organizations. Contrary to common VSMs that capture core production processes, this study provides strong insights that shall help design lean supply chains, especially in the pharmaceutical domain. This paper has also addressed the viability of the lean in the pharmaceutical warehouse and the reduction in lead time to improve demand forecasting, marketing and sales. Practical implications The results of this study have indicated that a significant reduction in pharmaceutical warehouse supply chain lead time is possible as a result of the implementation of VSM from the supply chain’s perspective. Social implications The insights from this study help in understanding the pharmaceutical supply chain risks and their outcomes. Originality/value The paper reports a real-time study conducted in a warehouse of a pharmaceutical organization. Hence, the contributions are original.

scholarly journals Shipment sizing for autonomous trucks of road freight

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Chun-Miin (Jimmy) Chen ◽  
Yajun Lu
Keyword(s):  
Lead Time ◽  
Economies Of Scale ◽  
Relevant Information ◽  
Cost Information ◽  
Content Type ◽  
Lead Time Reduction ◽  
Road Freight ◽  
Inventory Centralization ◽  
Time Reduction ◽  
Autonomous Technology

PurposeUnprecedented endeavors have been made to take autonomous trucks to the open road. This study aims to provide relevant information on autonomous truck technology and to help logistics managers gain insight into assessing optimal shipment sizes for autonomous trucks.Design/methodology/approachEmpirical data of estimated autonomous truck costs are collected to help revise classic, conceptual models of assessing optimal shipment sizes. Numerical experiments are conducted to illustrate the optimal shipment size when varying the autonomous truck technology cost and transportation lead time reduction.FindingsAutonomous truck technology can cost as much as 70% of the price of a truck. Logistics managers using classic models that disregard the additional cost could underestimate the optimal shipment size for autonomous trucks. This study also predicts the possibility of inventory centralization in the supply chain network.Research limitations/implicationsThe findings are based on information collected from trade articles and academic journals in the domain of logistics management. Other technical or engineering discussions on autonomous trucks are not included in the literature review.Practical implicationsLogistics managers must consider the latest cost information when deciding on shipment sizes of road freight for autonomous trucks. When the economies of scale in autonomous technology prevail, the classic economic order quantity solution might again suffice as a good approximation for optimal shipment size.Originality/valueThis study shows that some models in the literature might no longer be applicable after the introduction of autonomous trucks. We also develop a new cost expression that is a function of the lead time reduction by adopting autonomous trucks.

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