scholarly journals SALES FORECAST FOR AGGREGATE PLANNING: CASE STUDY OF AN INDUSTRIAL PRODUCTS COMPANY IN MEXICO

2021 ◽  
Vol 8 (4) ◽  
pp. 381-392
Author(s):  
Ignacio Alvarez Placencia ◽  
Diana Sánchez-Partida ◽  
José-Luis Martínez-Flores ◽  
Patricia Cano-Olivos
Keyword(s):  
Supply Chain ◽  
Forecasting Model ◽  
Aggregate Level ◽  
Industrial Products ◽  
Sales Forecast ◽  
Demand Pattern ◽  
Best Execution ◽  
The Cost ◽  
Significant Effort

This case study presents the analysis through the use of sales estimation tools for planning demand for aggregate level as a finished product in a leading industrial products company in the market in Mexico. First, it aligned the demand plan and the supply plan, recommending the best execution scenario to increase operational efficiency and reduce the cost of operating the supply chain to increase the company's productivity and stay competitive. Then, after analysing the behaviour of the demand for selected products, the authors determined as the main affectation the inadequate precision of the method forecasting and the lack of an aggregate forecasting strategy that allows reducing the variation. Due to this, the most significant effort was concentrated on determining a better-forecasting model and the decision to aggregate the demand based on three relevant criteria: the demand pattern based on the Soft, Intermittent, Erratic or Irregular quadrant, the best method of the forecast for each product and the time in quarters. As a result, a reduction between 20% and 46% in the forecast variation can be obtained from the above.

Data-Driven Inventory Management in the Healthcare Supply Chain

2020 ◽  
pp. 1390-1403
Author(s):  
Shuojiang Xu ◽  
Kim Hua Tan
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Inventory Management ◽  
Data Driven ◽  
Forecasting Model ◽  
Market Demand ◽  
Improved Model ◽  
Future Work ◽  
Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

Costs and benefits of using cross-docking in the retail supply chain

2019 ◽  
Vol 47 (4) ◽  
pp. 412-432 ◽  
Author(s):  
Yassine Benrqya
Keyword(s):  
Supply Chain ◽  
Cost Model ◽  
Costs And Benefits ◽  
Actual Case ◽  
Content Type ◽  
Cross Docking ◽  
The Cross ◽  
The Right ◽  
The Cost

Purpose The purpose of this paper is to investigate the costs/benefits of implementing the cross-docking strategy in a retail supply chain context using a cost model. In particular, the effects of using different typologies of cross-docking compared to traditional warehousing are investigated, taking into consideration an actual case study of a fast-moving consumer goods (FMCG) company and a major French retailer. Design/methodology/approach The research is based on a case study of an FMCG company and a major French retailer. The case study is used to develop a cost model and to identify the main cost parameters impacted by implementing the cross-docking strategy. Based on the cost model, a comparison of the main cost factors characterizing four different configurations is made. The configurations studied are, the traditional warehousing strategy (AS-IS configuration, the reference configuration for comparison), where both retailers and suppliers keep inventory in their warehouses; the cross-docking pick-by-line strategy, where inventory is removed from the retailer warehouse and the allocation and sorting are performed at the retailer distribution centre (DC) level (TO-BE1 configuration); the cross-docking pick-by-store strategy, where the allocation and sorting are done at the supplier DC level (TO-BE2 configuration); and finally a combination of cross-docking pick-by-line strategy and traditional warehousing strategy (TO-BE3 configuration). Findings The case study provides three main observations. First, compared to traditional warehousing, cross-docking with sorting and allocation done at the supplier level increases the entire supply chain cost by 5.3 per cent. Second, cross-docking with allocation and sorting of the products done at the retailer level is more economical than traditional warehousing: a 1 per cent reduction of the cost. Third, combining cross-docking and traditional warehousing reduces the supply chain cost by 6.4 per cent. Research limitations/implications A quantitative case study may not be highly generalisable; however, the findings form a foundation for further understanding of the reconfiguration of a retail supply chain. Originality/value This paper fills a gap by proposing a cost analysis based on a real case study and by investigating the costs and benefits of implementing different configurations in the retail supply chain context. Furthermore, the cost model may be used to help managers choose the right distribution strategy for their supply chain.

scholarly journals Assessing the Impact of Prices Fluctuation on Demand Distortion Within a Multi-echelon Supply Chain

2012 ◽  
Vol 23 (2) ◽  
pp. 131-140 ◽  
Author(s):  
Francisco Campuzano Bolarín ◽  
Antonio Guillamón Frutos ◽  
Andrej Lisec
Keyword(s):  
Supply Chain ◽  
Supply Chain Management ◽  
Bullwhip Effect ◽  
Forecasting Model ◽  
Systems Dynamics ◽  
Price Fluctuation ◽  
Chain Management ◽  
On Demand ◽  
Demand Pattern ◽  
The Impact

Price fluctuation is a practice commonly used by companies to stimulate demand and a main cause of the Bullwhip effect. Assuming a staggered step demand pattern that responds elastically to retailer’s price fluctuation, and by using a supply chain management dynamic model, we will analyse the impact of these fluctuations on the variability of the orders placed along a traditional multilevel supply chain. Subsequently, the results obtained will serve to propose a forecasting model enabling to calculate the potential variability of orders placed by each echelon on the basis of the price pattern used. Finally, under the hypothesis of an environment of collaboration between the different members of the chain, we propose a predictive model that makes it possible to quantify the distortion of the orders generated by each level. KEYWORDS: Bullwhip effect, systems dynamics, price fluctuation, supply chain management

Determination of the Optimal Number of Suppliers Considering the Risk: Emersun Company as a Case Study

2012 ◽  
Vol 433-440 ◽  
pp. 5873-5880 ◽  
Author(s):  
Nasim Mirahmadi ◽  
Esmaeel Saberi ◽  
Ebrahim Teimoury
Keyword(s):  
Supply Chain ◽  
Optimal Number ◽  
Development Cost ◽  
Supply Risk ◽  
Proposed Model ◽  
Management Area ◽  
The Cost ◽  
Tree Approach

Determining the number of suppliers chosen for cooperation in a supply chain is one of the most important problems in the supply chain management area. Regarding the fact that simultaneously decreasing the risk and cost is one of the most important objectives of every organization, besides the cost, the risk has also been introduced in the recent researches, as one of the most important criteria. In this paper, the decision tree approach is used for determining the optimal number of suppliers considering the supply risk and it has been tried to develop an applied method through expanding the cost criteria. The proposed model in this paper, therefore, contains any kind of cost ingredients such as cost of suppliers development, cost of suppliers management, cost of missing discount in volume due to increase in number of suppliers in supply base, and loss cost due to supply postponement from suppliers. This approach is implemented in Emersun Company.

scholarly journals Coordinating Supply Chain Financing for E-commerce Companies Through a Loan Contract

SAGE Open ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 215824402110654
Author(s):  
Jinjin Zhang ◽  
Xin Li ◽  
Yong-Hong Kuo ◽  
Yan Chen
Keyword(s):  
Supply Chain ◽  
Risk Premium ◽  
Wholesale Price ◽  
Fully Integrated ◽  
Finance Company ◽  
Supply Chain Financing ◽  
Financing Problem ◽  
The Cost ◽  
Loan Contract

This paper considers an online retailer and his or her manufacturer, both facing financial constraints and wishing to get loans from their e-commerce platform-backed finance company. Based on shared transaction data and monitored sales accounts, a tripartite loan contract is proposed to coordinate three parties’ actions in this supply chain financing problem. We prove that the proposed loan contract aligns the decentralized decision-makings of each party and duplicates the optimal channel performance under a fully integrated decision-making framework. A case study is then conducted to illustrate the performance of the proposed loan contract. The result shows that the proposed loan contract outperforms wholesale-price contracts, where coordination does not take place, and buyback contracts, where coordination happens between the retailer and the manufacturer only. Furthermore, a sensitivity analysis reveals that profit allocations among the lender, the retailer, and the manufacturer resulted from the proposed loan contract are more balanced when the cost-to-retail ratio or risk premium is high.

Managing Cost of Quality in Supply Chains

2020 ◽  
pp. 231-249
Author(s):  
Ali Ghandour
Keyword(s):  
Supply Chain ◽  
Poor Quality ◽  
Chain Process ◽  
Cost Of Quality ◽  
The Past ◽  
The World ◽  
Key Factor ◽  
Supply Chain Process ◽  
The Cost

The purpose of this case study is to analyze the cost of quality (COQ) in the supply chain process at Arctic North Inc., one of the winter jackets manufacturers in Montreal, Canada. In addition to the case study, some proposed solutions and recommendations will be chosen based on the studied performance of the company. Over the past decades, quality is becoming more and more a key factor in customers' expectations. Organizations and businesses around the world are very interested in applying methodologies and techniques to reach higher quality levels since this will distinguish them from other competitors in the market. Furthermore, measuring the COQ in an organization is very important in order to be able to identify the problem of poor quality, quantify it, and analyze its causes to be able to solve it.

scholarly journals Biofuel from Balanites aegyptiaca: Optimization of the Feedstock Supply Chain

2018 ◽  
Vol 10 (12) ◽  
pp. 4501 ◽  
Author(s):  
Linda Bambara ◽  
Marie Sawadogo ◽  
Daniel Roy ◽  
Didier Anciaux ◽  
Joël Blin ◽  
...  
Keyword(s):  
Supply Chain ◽  
Cost Price ◽  
Transport Costs ◽  
Balanites Aegyptiaca ◽  
Optimal Organization ◽  
Seed Supply ◽  
Efficient Option ◽  
The Cost ◽  
And Storage

In arid and semi-arid climates, Balanites aegyptiaca (B. aegyptiaca) is a potential plant to produce oilseed-based biofuels. In this paper an optimization model for a wild biomass supply chain is presented. The model was developed to identify the optimal organization of the supply network that minimizes the cost of supplying the feedstock. It was applied to a case study on a B. aegyptiaca seed supply chain in Burkina Faso. Considering different means of transport and different pre-processing locations, the results show that in contexts such as Burkina Faso’s, the most efficient option for the supply of B. aegyptiaca seeds is using animal drawn carts to transport the biomass from the harvest sites to the collection points. Feedstock pre-processing should take place before transport and an improvement in pre-processing operations by mechanical de-hulling could help reduce the cost price of the seeds. The results also show that more than 35% of the cost price of B. aegyptiaca seed is accounted for by transport costs. Pre-processing, handling, and storage costs account for about 50% of the cost of the seeds.

Data-Driven Inventory Management in the Healthcare Supply Chain

2017 ◽  
pp. 75-91
Author(s):  
Shuojiang Xu ◽  
Kim Hua Tan
Keyword(s):  
Big Data ◽  
Supply Chain ◽  
Inventory Management ◽  
Data Driven ◽  
Forecasting Model ◽  
Market Demand ◽  
Improved Model ◽  
Future Work ◽  
Statistic Approach

From 21st century, enterprises combine supply chain management with big data to improve their products and services level. In China healthcare industry, supply chain decisions are made based on experience, due to the environment complexities, such as changing policies and license delay. A flexible and dynamic big data driven analysis approach for supply chain decisions is urgently required. This report demonstrates a case study on CRT forecasting model of inventory data to predict the market demand based on pervious transaction data. First a basic statistic approach has been applied to represent the superficial patterns and suggest some decisions. After that a CRT model has been built based on the several independent variables. And there is also a comparison between CRT and CHAID models to choose a better one to further build an improved model. Finally some limitations and future work have been proposed.

Empowering Farmers through Future Price Information: A Case Study of Price Forecasting of Brinjal in Eastern Uttar Pradesh

2020 ◽  
pp. 479-488
Keyword(s):  
Supply Chain ◽  
Economies Of Scale ◽  
Uttar Pradesh ◽  
Future Price ◽  
Forecasting Model ◽  
Price Forecasting ◽  
Price Information ◽  
Marketing Activities ◽  
Eastern Uttar Pradesh

The study developed ARIMA forecasting model for brinjal prices for the markets of Eastern Uttar Pradesh. It was observed that the ARIMA (1,0,1) with non-zero mean was suitable for both Lucknow and Allahabad markets. ARIMA (2,0,0) (0,1,0) (52), ARIMA (1,1,0) (1,1,0) (52), ARIMA (1,1,2), ARIMA (2,0,0) (1,0,0) (52), ARIMA (3,1,1) were suitable for Delhi, Varanasi, Kolkata, Gorakhpur, and Kanpur markets, respectively, based on lowest AIC values. The farmers and other supply chain actors of Eastern Uttar Pradesh could plan their production and marketing activities looking into the price scenario projected for major markets in the study. The highest price of brinjal was likely to prevail in the Kolkata market. To exploit distant markets, the farmers need to organize themselves into groups to exploit economies of scale.

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