scholarly journals Predictive Sales and Operations Planning Based on a Statistical Treatment of Demand to Increase Efficiency: A Supply Chain Simulation Case Study

2020 ◽  
Vol 11 (1) ◽  
pp. 233
Author(s):  
Sergio Gallego-García ◽  
Manuel García-García
Keyword(s):  
Supply Chain ◽  
Demand Forecasting ◽  
Statistical Treatment ◽  
Random Number Generation ◽  
Service Level ◽  
Good Prediction ◽  
Operations Planning ◽  
Corrective Measures ◽  
Predictive Approach ◽  
Supply Chain Simulation

Forecasting is the basis for planning. Good planning is based on a good prediction of what is going to happen to prepare a company, a department, and their environments for certain future developments and their intermediate states. In this context, resources are allocated to these future states in the most efficient way, given a certain set of resource conditions. Although market volatility demands the high adaptability of companies’ operations, dynamic planning is still not widespread. As a result, the alignment of planning processes with potential scenarios is not given, leading to a lack of solution preparation in the long term, suboptimal decision-making in the medium term, and corrective measures in the short term, with higher costs and a lower service level. Therefore, the aim of this research is to propose a predictive approach that will help managers develop sales and operations planning (S&OP) with higher accuracy and stability. For this purpose, a methodology combining demand scenarios, statistical analysis of the demand, forecasting techniques, random number generation, and system dynamics was developed. The goal of this predictive S&OP is to predict the supply chain system’s behavior to generate plans that prevent potential inefficiencies, thereby avoiding corrective measures. In addition, to assess the methodology, the model is applied in the software Vensim, for an automotive producer´s supply chain, to compare the predictive S&OP model with a classical approach. The results show that the proposed predictive approach can increase a manufacturer’s efficiency by increasing its adaptability through the identification of potential inefficiencies and can also be used to prepare solutions.

scholarly journals CPN Based Modeling of Tourism Demand Forecasting

2016 ◽  
Vol 12 (1) ◽  
pp. 28
Author(s):  
Hua Bai ◽  
Haoyuan Zhang
Keyword(s):  
Supply Chain ◽  
Good Practice ◽  
Demand Forecasting ◽  
Bullwhip Effect ◽  
Service Level ◽  
Supply Chain Collaboration ◽  
Tourism Demand ◽  
High Volatility ◽  
Low Efficiency ◽  
Tourism Supply Chain

The tourism demand has become more and more diversified and sensitive to traveling environment, resulting in the high volatility of tourism market. Travel agencies, scenic spots, hotels and other tourism businesses in the tourism supply chain (TSC) need a tight collaboration in order to minimize cost and improve responsiveness and service level. The existence of the bullwhip effect will cause the waste of resources and low efficiency, thus collaborative demand forecasting becomes a good practice to enhance sharing of information and resources, and as a result improving the efficiency and effectiveness of tourism demand forecasting. This paper proposes a collaborative tourism demand forecasting framework based on Colored Petri Net (CPN), which can simulate and examine the effectiveness of tourism supply chain collaboration.

scholarly journals THE IMPORTANCE OF THE S & OP PROCESS IN THE PRODUCTION AND ECONOMIC ACTIVITIES OF THE ENTERPRISE

2020 ◽  
Author(s):  
Г.С. Укубасова ◽  
Н.В. Ибрагимова ◽  
G. Ukubassova ◽  
N. Ibragimova
Keyword(s):  
Supply Chain ◽  
Economic Activity ◽  
Demand Forecasting ◽  
High Accuracy ◽  
Economic Activities ◽  
System Planning ◽  
Operations Planning ◽  
Production Plans ◽  
New View

В статье раскрываются вопросы, касающиеся sales and operations planning, как процесса системного планирования объемов производства, закупок, хранения, перемещений и поставок потребителям продукции, который позволяет оптимизировать расходы указанных процессов, а также процессов логистики, касающихся этапов производственно-хозяйственной деятельности предприятия. Sales and operations planning это своего рода новый взгляд и подход к осуществлению процесса планирования производственной деятельности предприятия, а так же к его логистической деятельности, дающий возможность адаптироваться к современным тенденциям развития экономики как на микро, так и на макроуровне. Обнаружены проблемы в планировании и организации процессов производства и сбыта продукции на предприятиях, которые приводят к множественным частным корректировкам различного вида производственных планов и тем самым тормозят процессы их деятельности. Предложено внедрять предприятиям на широкой основе систему S&OP, поскольку она способна обеспечить высокую точность прогноза спроса и является залогом отсутствия потерь во всей цепочке поставок, а также способствует оптимизации работы компании в целом. Объектом исследования в статье является процесс планирования продаж и операций (Sales and Operations Planning, S&OP) на предприятиях. The article covers issues related to sales and operations planning, as a process of system planning of production volumes, purchases, storage, movement and delivery of products to consumers, which allows you to optimize the costs of these processes, as well as logistics processes related to the stages of production and economic activity of the enterprise. Sales and operations planning is a kind of new view and approach to the implementation of the process of planning the production activities of the enterprise, as well as to its logistics activities, which makes it possible to adapt to modern trends in the development of the economy both at the micro and macro levels. There are problems in planning and organizing the processes of production and marketing of products to enterprises, which lead to multiple individual adjustments of various types of production plans and thereby slow down the processes of its activities. It is proposed to introduce the S&OP system to enterprises on a broad basis, since it is able to provide high accuracy of demand forecasting and is a guarantee of no losses in the entire supply chain, as well as helps to optimize the company's work as a whole. The object of research in the article is the process of planning sales and operations (Sales and Operations Planning, S&OP) at enterprises.

scholarly journals A Multi-Echelon Network Design in a Dual-Channel Reverse Supply Chain Considering Consumer Preference

2021 ◽  
Vol 18 (9) ◽  
pp. 4760
Author(s):  
Peng Li ◽  
Di Wu
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Environmental Sustainability ◽  
Rapid Development ◽  
Consumer Preference ◽  
Service Level ◽  
Mixed Integer ◽  
Reverse Supply Chain ◽  
Related Factors ◽  
Dual Channel

The rapid development of e-commerce technologies has encouraged collection centers to adopt online recycling channels in addition to their existing traditional (offline) recycling channels, such the idea of coexisting traditional and online recycling channels evolved a new concept of a dual-channel reverse supply chain (DRSC). The adoption of DRSC will make the system lose stability and fall into the trap of complexity. Further the consumer-related factors, such as consumer preference, service level, have also severely affected the system efficiency of DRSC. Therefore, it is necessary to help DRSCs to design their networks for maintaining competitiveness and profitability. This paper focuses on the issues of quantitative modelling for the network design of a general multi-echelon, dual-objective DRSC system. By incorporating consumer preference for the online recycling channel into the system, we investigate a mixed integer linear programming (MILP) model to design the DRSC network with uncertainty and the model is solved using the ε-constraint method to derive optimal Pareto solutions. Numerical results show that there exist positive correlations between consumer preference and total collective quantity, online recycling price and the system profits. The proposed model and solution method could assist recyclers in pricing and service decisions to achieve a balance solution for economic and environmental sustainability.

SISCO: An object-oriented supply chain simulation system

2006 ◽  
Vol 42 (1) ◽  
pp. 422-434 ◽  
Author(s):  
Dean C. Chatfield ◽  
Terry P. Harrison ◽  
Jack C. Hayya
Keyword(s):  
Supply Chain ◽  
Object Oriented ◽  
Simulation System ◽  
Supply Chain Simulation

scholarly journals A literature review on multi-echelon inventory management: the case of pharmaceutical supply chain

2018 ◽  
Vol 200 ◽  
pp. 00013 ◽  
Author(s):  
Nouçaiba Sbai ◽  
Abdelaziz Berrado
Keyword(s):  
Supply Chain ◽  
Customer Service ◽  
Inventory Management ◽  
Raw Materials ◽  
Integrated Approach ◽  
Service Level ◽  
Pharmaceutical Products ◽  
Management Problem ◽  
Pharmaceutical Supply Chain ◽  
Customer Service Level

Inventory management remains a key challenge in supply chain management. Many companies recognize the benefits of a good inventory management system. An effective inventory management helps reaching a high customer service level while dealing with demand variability. In a complex supply chain network where inventories are found across the entire system as raw materials or finished products, the need for an integrated approach for managing inventory had become crucial. Modelling the system as a multi-echelon inventory system allows to consider all the factors related to inventory optimization. On the other hand, the high criticality of the pharmaceutical products makes the need for a sophisticated supply chain inventory management essential. The implementation of the multi-echelon inventory management in such supply chains helps keeping the stock of pharmaceutical products available at the different installations. This paper provides an insight into the multi-echelon inventory management problem, especially in the pharmaceutical supply chain. A classification of several multi-echelon inventory systems according to a set of criteria is provided. A synthesis of multiple multi-echelon pharmaceutical supply chain problems is elaborated.

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