Fast moving product demand forecasting model with multi linear regression

Farizal, Yusuf Qaradhawi, Caesario Isak Cornelis, Muhammad Dachyar

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accuracy of demand forecasting greatly influences the performance of the supply chain system which ultimately has a direct impact on the business perfomance. Accurate forecasting will be able to utilize company resources efficiently. However, in practice many companies admit that their forecasting process is not going as well as they expected. Most companies only use historical data to forecast future demand. Whereas past demand data is not enough to be used as the basis for future forecasts. Therefore it is necessary to build a model that is able to accommodate this phenomenon. This study proposed a multiple linear regression forecasting model for fast moving product. The independent variables used are climate, promotion, cannibalization, holidays, product prices, number of stores, population and income that always change over time. The results show that the proposed multiple linear forecasting model is more than three time more accurate than company forecast.

Original languageEnglish
Title of host publicationRecent Progress on
Subtitle of host publicationMechanical, Infrastructure and Industrial Engineering - Proceedings of the International Symposium on Advances in Mechanical Engineering, ISAME 2019: Quality in Research 2019
Editors Nahry, Dwinanti Rika Marthanty
PublisherAmerican Institute of Physics Inc.
ISBN (Electronic)9780735419865
DOIs
Publication statusPublished - 6 May 2020
Event16th International Conference on Quality in Research, QiR 2019 - 2019 International Symposium on Advances in Mechanical Engineering, ISAME 2019 - Padang, Indonesia
Duration: 22 Jul 201924 Jul 2019

Publication series

NameAIP Conference Proceedings
Volume2227
ISSN (Print)0094-243X
ISSN (Electronic)1551-7616

Conference

Conference16th International Conference on Quality in Research, QiR 2019 - 2019 International Symposium on Advances in Mechanical Engineering, ISAME 2019
CountryIndonesia
CityPadang
Period22/07/1924/07/19

Keywords

  • Fast moving good
  • Forecasting
  • Multi linear regression model

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