Supply Chain Agility in FMCG: How Predictive Analytics Shapes Distribution and Production Operations

The fast-moving consumer goods (FMCG) industry operates in a dynamic environment where rapid response to market demands and consumer preferences is essential. This study explores how predictive analytics enhances supply chain agility by optimizing demand forecasting, inventory management, and distribution operations. Using a mixed-methods approach, the research analyzes data from industry case studies and statistical models, highlighting the impact of machine learning algorithms and simulation techniques on improving forecast accuracy, reducing lead times, and cutting distribution costs. The results show that predictive analytics not only enhances operational efficiency but also supports resilience and risk management during demand fluctuations. By leveraging advanced data-driven strategies, FMCG companies can achieve a more responsive, customer-focused, and cost-effective supply chain, positioning themselves competitively in a volatile market.

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Publication Details

Journal
Nanotechnology Perceptions
Published
2024-12-12
DOI
https://doi.org/10.62441/nano-ntp.v20i7.3791
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
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Supply Chain Agility in FMCG: How Predictive Analytics Shapes Distribution and Production Operations

Arun Nanda, Ashish Dhongde
1 citations
Nanotechnology Perceptions
Big Data and Business Intelligence
0.53
article

Supply Chain Agility in FMCG: How Predictive Analytics Shapes Distribution and Production Operations

Arun Nanda, Ashish Dhongde
article en
1 citations

Abstract

The fast-moving consumer goods (FMCG) industry operates in a dynamic environment where rapid response to market demands and consumer preferences is essential. This study explores how predictive analytics enhances supply chain agility by optimizing demand forecasting, inventory management, and distribution operations. Using a mixed-methods approach, the research analyzes data from industry case studies and statistical models, highlighting the impact of machine learning algorithms and simulation techniques on improving forecast accuracy, reducing lead times, and cutting distribution costs. The results show that predictive analytics not only enhances operational efficiency but also supports resilience and risk management during demand fluctuations. By leveraging advanced data-driven strategies, FMCG companies can achieve a more responsive, customer-focused, and cost-effective supply chain, positioning themselves competitively in a volatile market.

Nanotechnology PerceptionsVol. 20(7)
Openalex Percentile: Top 21%
Big Data and Business Intelligence
0.53
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