Performance Measurement on Inventory Management and Logistics Through Various Forecasting Techniques

This case study is designed to explore the challenges of forecasting and inventory management in spare parts industry. Most items in this industry have lumpy, intermittent, erratic and slow demand patterns. Traditional forecasting techniques cannot be applied to this group. Also most textbook methods on inventory planning, assumes the demand is normally distributed – which is also not the case in spare parts industry. Strategies can be tested for the demand data provide for about 40 items

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The links between just-in-time practices and alignment of benchmarking performance measures

The TQM Journal ◽

10.1108/tqm-08-2013-0098 ◽

2015 ◽

Vol 27 (1) ◽

pp. 108-121 ◽

Cited By ~ 3

Author(s):

Mohammad Z. Meybodi

Keyword(s):

Performance Measurement ◽

Inventory Management ◽

Performance Measures ◽

Core Competencies ◽

Organizational Strategy ◽

Just In Time ◽

Critical Element ◽

Content Type ◽

Effective Performance ◽

Benchmarking Performance

Purpose – The purpose of this paper is to examine if there are links between just-in-time (JIT) practices and consistency of benchmarking performance measures at various levels of organization. Design/methodology/approach – A set of ten hypotheses were used to examine the differences between traditional and JIT organizations in the effectiveness of benchmarking performance measures. A questionnaire-based survey data were used to test the hypotheses. The target population was manufacturing firms in Midwestern US; the sample covers organizations in a variety of industries. Out of 91 completed surveys received, 84 surveys were usable resulting in a response rate of 17 per cent. Out of 84 usable surveys, 33 organizations were grouped as JIT and 51 as traditional organizations. Findings – JIT organizations are better in recognizing external environmental factors, developing organizational core competencies, building learning organization through knowledge workforce, and using a broad and balanced mix of performance measures that are consistent with organizational strategy. Research limitations/implications – Research is general and not industry specific. Practical implications – Effective performance measurement is a critical element of organizational success. It requires a thorough understanding of organizational strategy and deployment of the strategy into consistent sub-strategies and action plans. Originality/value – The benefits of JIT principles go beyond inventory management. These principles can be applied to other areas such as effective performance measurement.

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Stocks management through application of demand forecast methods: a case study

Independent Journal of Management & Production ◽

10.14807/ijmp.v7i5.458 ◽

2016 ◽

Vol 7 (5) ◽

pp. 699

Author(s):

Lucas Lopes Filholino Rodrigues ◽

Igor Henrique Inácio de Oliveira ◽

Maurílio Fagundes Alexandre ◽

Rodrigo Rodrigues Castorani ◽

Celso Jacubavicius

Keyword(s):

Inventory Management ◽

Moving Average ◽

Demand Forecasting ◽

Metropolitan Region ◽

Demand Forecast ◽

Naive Method ◽

Forecast Models ◽

The One ◽

First Moment ◽

Forecasting Techniques

The present study consists in assessing the feasibility of implementing demand forecasting techniques due to the optimization of inventory management, so that it is objective the reduce storage costs and to have the least amount of stationary material stock in a certain period. Data analysis was for application of techniques based on the real case of a multinational company in the segment of electronic and digital systems in the infrastructure area, which operates in the metropolitan region of São Paulo.The study aims to evaluate the behavior of the studied company demand, in order to demonstrate some forecast models for it and thus being able to identify the most appropriate method to get the highest possible degree of assertiveness. At a first moment, there will be a survey of data concerning the company's historical demand, including the forecast used at the latest period, and then to survey the state of the art discussed topic, in order to clarify the reader, and as a result: the analysis of the collected data and the implementation of demand forecasting techniques presented in bibliographic references.After performing an analysis of the naive method demand forecasting practiced by the company, was carried out the application of different forecasting methods and found out that the method that best suits the given demand was the moving average, which provided the optimization of cost of storage in approximately 63% of the one presented by the naive method and also a gain of approximately R $ 2,000,000.00 during the studied period, thus proving the effectiveness of demand forecasting application for inventory management.

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Forecasting Models of Natural Gas

International Journal of Scientific Research in Science and Technology ◽

10.32628/ijsrst218375 ◽

2021 ◽

pp. 251-258

Author(s):

Dr. Meenakshi Thalor ◽

Ritesh Choudhary ◽

Ajay Jangid ◽

Deep Gandhecha ◽

Rishab Bhat

Keyword(s):

Natural Gas ◽

Inventory Management ◽

Demand Forecasting ◽

Liquefied Petroleum Gas ◽

Survey Paper ◽

Natural Gas Demand ◽

Performance Results ◽

Consumption Demand ◽

Gas Supply ◽

Forecasting Techniques

This work gives away a survey of different published papers related to forecasting techniques in natural gas demand and consumption. Demand forecasting plays an important role in the company's decision making and inventory management process. It is important for local natural gas distributors to accurately predict the natural gas needs of their customers. While classifying the recent natural gas demand forecasting techniques, we have taken into account their methodologies, approach, data size, performance, results and limitations. Aim of this survey paper is to present a classified study of liquefied petroleum gas and natural gas related assets forecasting algorithms. This study provides readers with an understanding of the recent research in the natural gas supply-demand forecasting techniques.

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