Enhancing Supply Chain Efficiency: A Holistic Examination of Hybrid Forecasting Models Employing Mode and PERT Technique as Deterministic Factors

Muhammad Azmat*, Raheel Siddiqui

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Inaccurate forecasts can cause severe financial consequences and disrupt supply chain operations for organisations. This study focuses on the pharmaceutical industry, renowned for its complex supply chain and diverse data attributes. It proposes a novel approach to identify the optimal combination of demand forecasting models that enhance accuracy by leveraging deterministic factors using Mode and PERT. By refining model selection in the pharmaceutical industry, this research aims to improve both forecasting precision and supply chain efficiency. A four-level framework based on deterministic factors is proposed to evaluate the extent of hybrid modelling in demand forecasting, empowering practitioners to make informed decisions even in challenging circumstances. The findings offer decision-makers flexibility in selecting suitable forecasting models and assist in tailoring methods to specific conditions. Furthermore, this research highlights the industry's ability to leverage digital technologies and transform existing forecasting methodologies, ensuring uninterrupted business operations during disruptions such as the COVID-19 pandemic.
Original languageEnglish
JournalInternational Journal of Logistics Research and Applications
Early online date8 Nov 2023
DOIs
Publication statusE-pub ahead of print - 8 Nov 2023

Bibliographical note

© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.

Keywords

  • Advanced forecasting techniques
  • Demand forecasting
  • Forecasting accuracy
  • Hybrid forecasting
  • Inventory optimization
  • Pharmaceutical supply chain

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