Programme Content
Delivered through a mix of lectures, case studies, and analytical tools
1.
What are Sales Forecasting and Demand Planning?
Demand Planning process
Demand Forecasting Unit (DFU)
Introducing the process of demand planning in industries
2.
Forecasting Accuracy Metrics and Tracking Signal
Bias
MSE, MAD, MAPE, MASE, SMAPE, WMAPE
Tracking Signal
Familiarizing with different accuracy metrics used in the industry
3.
Introduction to Time Series Analysis
Basic Time series-based algorithms like naïve, seasonal naïve, moving average, weighted moving average, etc.
Decomposition of basic time series
Familiarizing with the basics of Time Series
4.
Smoothing-Based Forecasting Techniques
Exponential Smoothing
Holts Method
Holt-Winters Method
Familiarizing with the basics of Smoothing-based methods
5.
Advanced
Time Series Techniques
Stationarity of Time Series
White Noise, Random Walk, AR Process, MA Process, ARMA Process, ARIMA Process
Regression-based methods in forecasting, ARIMAX Process
Familiarizing with Time Series Analysis
6.
Forecasting for New Products
GompertzModel
Logistic Model
Bass Model
Modified Bass Model
Familiarizing with long-term forecasting models
