Executive Development Programme in Forecasting and Demand Sensing Techniques

This course is designed for senior executives and managers responsible for supply chain operations, marketing, and sales. It equips participants with advanced forecasting and demand sensing techniques to optimize inventory management, enhance customer satisfaction, and drive business growth.

Attendees will gain practical skills in applying cutting-edge analytics tools and methodologies to forecast demand accurately and respond to market changes swiftly. The curriculum covers statistical forecasting, machine learning models, and real-time data analysis to make informed business decisions.

1. 1. Forecasting Fundamentals: Learners will study basic statistical forecasting techniques and their application in business contexts. They will gain practical skills in interpreting time series data and selecting appropriate forecasting models.
2. 2. Demand Sensing Techniques: This module covers advanced methods for monitoring and predicting demand fluctuations. Learners will learn to implement real-time demand sensing systems and understand how to integrate these systems with existing supply chain processes.
3. 3. Time Series Analysis: Focusing on advanced time series analysis techniques, learners will explore seasonal adjustments, trend analysis, and forecasting accuracy improvements. Practical skills include using statistical software to analyze complex time series data.
4. 4. Machine Learning for Demand Forecasting: This module introduces machine learning algorithms for forecasting and their application in demand sensing. Learners will gain hands-on experience with implementing and evaluating predictive models using Python or R.
5. 5. Sales and Operations Planning (SOP): Learners will study the integration of forecasting and demand sensing into the sales and operations planning process. They will learn how to optimize inventory levels and production plans based on accurate demand forecasts.
6. 6. Advanced Forecasting Models: This module covers specialized forecasting models such as neural networks and Bayesian approaches. Learners will develop skills in building and validating advanced forecasting models to address complex business challenges.
7. 7. Demand Sensing in Retail: Focused on retail applications, learners will study how to apply demand sensing techniques to manage inventory and improve customer satisfaction. Practical skills include using data visualization tools to present demand insights.
8. 8. Forecasting in Service Industries: This module explores forecasting methods specific to service industries, including call centers and healthcare. Learners will learn how to forecast demand for services and optimize resource allocation.
9. 9. Predictive Analytics for Demand Sensing: Covering predictive analytics in the context of demand sensing, learners will develop skills in using predictive analytics to enhance decision-making processes. Practical exercises include building predictive models for demand patterns.
10. 10. Implementing Demand Sensing Systems: This final module focuses on the practical aspects of deploying demand sensing systems in organizations. Learners will learn how to design, implement, and manage demand sensing systems to support business strategy.