Achieving High Individual Service-Levels without Safety Stock? Optimal Rationing Policy of Pooled Resources

2019 ◽  
Author(s):  
Jiashuo Jiang ◽  
Shixin Wang ◽  
Jiawei Zhang
Keyword(s):  
Safety Stock ◽  
Service Levels ◽  
Rationing Policy ◽  
Individual Service

A Machine Learning-Based System for Predicting Service-Level Failures in Supply Chains

2021 ◽  
Author(s):  
Gabrielle Gauthier Melançon ◽  
Philippe Grangier ◽  
Eric Prescott-Gagnon ◽  
Emmanuel Sabourin ◽  
Louis-Martin Rousseau
Keyword(s):  
Machine Learning ◽  
Supply Chain ◽  
Service Level ◽  
Learning System ◽  
Safety Stock ◽  
Service Levels ◽  
Sources Of Uncertainty ◽  
Supply Chain Efficiency ◽  
Percentage Points ◽  
Different Sources

Despite advanced supply chain planning and execution systems, manufacturers and distributors tend to observe service levels below their targets, owing to different sources of uncertainty and risks. These risks, such as drastic changes in demand, machine failures, or systems not properly configured, can lead to planning or execution issues in the supply chain. It is too expensive to have planners continually track all situations at a granular level to ensure that no deviations or configuration problems occur. We present a machine learning system that predicts service-level failures a few weeks in advance and alerts the planners. The system includes a user interface that explains the alerts and helps to identify failure fixes. We conducted this research in cooperation with Michelin. Through experiments carried out over the course of four phases, we confirmed that machine learning can help predict service-level failures. In our last experiment, planners were able to use these predictions to make adjustments on tires for which failures were predicted, resulting in an improvement in the service level of 10 percentage points. Additionally, the system enabled planners to identify recurrent issues in their supply chain, such as safety-stock computation problems, impacting the overall supply chain efficiency. The proposed system showcases the importance of reducing the silos in supply chain management.

scholarly journals Dynamic Customer Service Levels: Evolving Safety Stock Requirements for Changing Business Needs

2020 ◽  
pp. 27-66
Author(s):  
Daniel Patrick Covert ◽  
Joaquin Alberto Ortiz Millan ◽  
Tugba Efendigil
Keyword(s):  
Customer Service ◽  
Safety Stock ◽  
Service Levels ◽  
Business Needs

scholarly journals Alternative methods for calculating optimal safety stock levels

2017 ◽  
Author(s):  
◽  
Ashkan Mirzaee
Keyword(s):  
Large Scale ◽  
Hybrid Approach ◽  
Solution Procedure ◽  
Alternative Methods ◽  
Random Demand ◽  
Safety Stock ◽  
Service Levels ◽  
Gamma Distributions ◽  
Proposed Model

This work considers the problem of safety stock levels for the production of multiple items, each with random demand, across multiple facilities. The traditional methodology for calculating safety stock is discussed and an alternative method for improving service levels is offered. Normal and Gamma distributions are considered to estimate safety stock levels, and the performance of both models, along with a hybrid approach, are tested on a large-scale case study example. The results of this case study indicate that a better inventory policy with less underage and overage cost can be achieved by using the proposed model and solution procedure.

Trimming Safety Stock

2016 ◽  
pp. 250-268
Author(s):  
Tanuj Sood
Keyword(s):  
Customer Service ◽  
Daily Basis ◽  
Statistical Techniques ◽  
Critical Area ◽  
Demand And Supply ◽  
Safety Stock ◽  
Service Levels ◽  
Supply Chain Networks ◽  
Natural Tendency ◽  
The Right

Today's retail environment has become extremely competitive with retailers offering low prices almost on daily basis through various promotional techniques. Majority of their products placed on their shelves are promoted to boost sales, compete efficiently and gain market share. Retailers have a natural tendency to keep a very close watch on various costs in whichever way they can be curtailed or controlled. Costs like Labor, Transportation, Vendor Deals and Inventory reduction are some of the key areas that are tracked and renegotiated very frequently by retailers worldwide. Safety Stock holding is one critical area where a lot of work can be done “empirically” by retailers and distributors to create stock efficiencies across their established supply chain networks. Application of appropriate statistical techniques on the right set of products can help us getting a trimmed down safety stock numbers which are still capable in addressing the demand and supply variability while holding much lesser stock and still achieve greater customer service levels.

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