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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM44886
Volume:
9 |
4 |
Apr 2025
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This study investigates the demand forecasting techniques used by Arunnachala Impex Private Limited, Chennai, and evaluates their effectiveness in improving inventory management, production planning, and supply chain efficiency. Demand forecasting plays a vital role in predicting future demand based on historical data, market trends, and external factors, enabling better resource allocation and timely product availability. The research uses both primary data—collected through structured questionnaires and employee interactions—and secondary data from company records and industry literature. A sample of 120 respondents from departments such as supply chain, inventory, and operations was chosen through convenience sampling. Percentage analysis and chi-square tests were used for data analysis. The study finds that forecasting helps reduce inventory costs and improves efficiency, but is challenged by issues like inaccurate data and market fluctuations. The research recommends integrating AI-driven predictive models and real-time data systems to enhance forecasting accuracy and support strategic decision-making.
KEYWORDS
Publication Date
4/17/2025
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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