Demand Forecasting

🔑 Key Pointers:

• Types of Forecasting:

  • Qualitative (expert opinion, market research)

  • Quantitative (time series, causal models)

• Common Methods:

  • Moving Average

  • Exponential Smoothing

  • ARIMA

  • Machine Learning models (e.g., Random Forest, XGBoost)

• Benefits:

  • Optimizes inventory and supply chain

  • Reduces costs due to overstocking or stockouts

  • Enhances customer satisfaction

  • Informs business strategy and planning

• Challenges:

  • Data quality issues

  • Demand volatility and seasonality

  • External factors (economy, competition, etc.)

• Use Cases:

  • Retail and eCommerce

  • Manufacturing

  • Logistics

  • Food and Beverage Industry

Return and Refund policy. If your requirement is not satisfied. 100% refund. TC applicable