DEMAND FORECASTING FOR INVENTORY OPTIMISATION IN AN E-COMMERCE COMPANY

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DEMAND FORECASTING FOR INVENTORY OPTIMISATION IN AN E-COMMERCE COMPANY

Abstract:
Demand forecasting plays a critical role in inventory optimization for e-commerce companies, enabling them to efficiently manage their inventory levels and meet customer demands while minimizing costs. This abstract presents an overview of the process of demand forecasting and its significance in achieving inventory optimization within an e-commerce company.

Effective demand forecasting involves analyzing historical sales data, market trends, customer behavior, and other relevant factors to predict future product demand accurately. By utilizing advanced statistical and machine learning techniques, companies can generate reliable forecasts that serve as a basis for optimizing their inventory management strategies.

Inventory optimization aims to strike a balance between having sufficient stock to meet customer demand and avoiding overstocking that leads to increased holding costs and potential obsolescence. By implementing accurate demand forecasting techniques, e-commerce companies can achieve several key benefits, including improved customer satisfaction, reduced stockouts, minimized inventory carrying costs, and increased operational efficiency.

This abstract explores various demand forecasting methods commonly used in e-commerce, including time series analysis, regression analysis, and machine learning algorithms such as neural networks and random forests. Additionally, it highlights the importance of incorporating external factors like seasonality, promotions, and market dynamics into the forecasting models to enhance accuracy.

Furthermore, the abstract discusses the challenges associated with demand forecasting in an e-commerce context, such as demand volatility, short product life cycles, and the presence of large product catalogues. It emphasises the need for continuous monitoring and updating of forecasting models to adapt to changing market conditions and customer preferences.

In conclusion, demand forecasting is a crucial component of inventory optimisation in e-commerce companies. By leveraging accurate predictions, companies can enhance their supply chain management, reduce costs, and improve customer satisfaction. This abstract provides a comprehensive overview of demand forecasting techniques and highlights their significance in achieving inventory optimization within the dynamic e-commerce landscape.

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