A Aidoo-anderson
Demand Forecasting In Manufacturing Pharmaceutical Small and Medium Enterprise’s (SME’s) In Ghana
Aidoo-anderson, A
Abstract
Forecasting is a ubiquitous, multi-discipline area which has received much attention from practitioners and researchers for many several years. It permeates every facet of an organisation’s life as the bedrock of planning and decision making. An organisation’s ability to accurately predict future demand affect cost, supply chain and customer service generating significant gains for an organization. Organisations need to forecast to meet the increasing expectations of customers, shorten lead times and for production and procurement decisions. A plethora of studies have established the damaging impact of poor forecast, from excessive inventory to reduced customer service. A poor choice of forecast method and neglect of high forecast errors is a common cause of organisation’s problems and supply chain disruptions.
This thesis focuses on demand forecasting in Manufacturing Pharmaceutical (Mpharma) SMEs in Ghana to address the gap of insufficient research within the context and the calls for empirical studies on forecasting in emerging economies. The pharmaceutical industry is constantly forecasting to tackle current unfulfilled needs and for drug innovation; from manufacturing of drugs till the time it reaches the customer. Forecasting’s role in the pharmaceutical sector is to inform both clinical and non-clinical decisions and determine how a drug will perform commercially. This study investigate how Mpharma SMEs in Ghana forecast demand, the methods used in forecasting, the importance of accurately forecasting demand as well as the barriers they encounter and how they mitigate these challenges. The investigation was exploratory, framed on phenomenological philosophy and inductive approach. face-to-face semi-structured interviews which involved 14 pharmaceutical manufacturing SMEs were conducted and the qualitative data collected thematically analysed.
The findings confirmed that MPharma SMEs in Ghana forecast demand and encounter divers’ challenges though the forecasting practices differ to an extent among the participating SMEs. It confirmed the lack of formal organisation structures and dedicated /expert forecasters for SMEs, and this is due to their size, limited financial and manufacturing resources. The activity is generally performed by the marketing, sales or purchasing managers or owner CEO’S. Judgement approach was the preferred forecasting approach and technology adoption significantly low. All the SMEs are challenged due to lack of data, lack of training and introduction of new legislations to mention a few. A significant finding of this study is the non-existence of intermittent/ irregular demand forecasting among all the participating SME’s echoing the forecasting gap in the industry.
Though typically the forecasting process of pharmaceuticals is long and winding, the case is different for generic drug manufacturers. Most MPharma in Ghana produce generic drugs explaining the flexibility but lack of structure of their forecasting processes. The thesis concludes and makes recommendations and suggestions for further research highlighting limitation to the study.
Thesis Type | Thesis |
---|---|
Deposit Date | Apr 12, 2022 |
Publicly Available Date | Mar 13, 2024 |
Award Date | Nov 12, 2021 |
Files
Albert Aidoo-Anderson's Thesis.pdf
(3.2 Mb)
PDF
You might also like
Identifying challenges in implementing digital transformation in UK higher education
(2024)
Journal Article
The role of artificial intelligence in project management: a supply chain perspective
(2024)
Journal Article
Knowledge sharing in circular procurement management: a case study from the construction industry
(2024)
Presentation / Conference Contribution
Downloadable Citations
About USIR
Administrator e-mail: library-research@salford.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2025
Advanced Search