Master Forecasting Demand:From Basics To Advanced Techniques
Published 7/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.38 GB | Duration: 2h 24m
Published 7/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.38 GB | Duration: 2h 24m
Learn key methods like Moving Averages, Exponential Smoothing, Last Value, Trend, Seasonality and many more
What you'll learn
Understand and apply key demand forecasting methods, including moving average, exponential smoothing, Holt, and Winters techniques.
Perform demand forecasting using Excel step-by-step, with real-world data and examples.
Identify when to use different forecasting methods based on business scenarios like trends, seasonality, or no data.
Forecast demand for new products or markets using expert opinion, market research, and analogous product techniques.
Requirements
No prior forecasting or supply chain knowledge needed.
A willingness to learn with real-world examples and hands-on practice.
Basic Excel familiarity (entering formulas, using AVERAGE function) is helpful but not required.
Description
Are you ready to master demand forecasting for business, supply chain, and operations? This course takes you from beginner to advanced techniques, helping you forecast demand confidently using Mathematical Models, Excel and real-world examples.In this course, you will:1. Understand the entire supply chain flow - from forecasting to last-mile delivery.2. Learn key forecasting methods like Last Value, Simple Average, Moving Average, Weighted Moving Average, Exponential Smoothing, Holt’s Trend Method, and Winters Method (Holt-Winters).3. Forecast demand when historical data is missing using expert opinion, analogous products, market research, and judgmental forecasting.4. Solve practical problems with easy-to-copy Excel data and step-by-step instructions.5. Discover how to choose the right forecasting method depending on the business situation.Who is this course for?This course is designed for supply chain professionals, business managers, MBA students, entrepreneurs, and data enthusiasts who want to apply forecasting methods to real business problems.No prior experience with forecasting is needed. Basic Excel skills (or willingness to learn) are sufficient - everything else is taught step-by-step.By the end of this course, you will be able to create reliable forecasts using Excel and apply these skills to real projects in supply chain, inventory, production, and business planning.
Overview
Section 1: Sample Lecture
Lecture 1 Excel Implentation of Trend Forecasting Method
Section 2: Supply Chain Flow
Lecture 2 Supply Chain Flow
Section 3: Forecasting Demand Basics
Lecture 3 Forecasting Demand Basics
Section 4: Forecasting Demand Method 1
Lecture 4 Forecasting Demand Method 1
Lecture 5 Excel Implementation
Section 5: Forecasting Demand Method 2
Lecture 6 Forecasting Demand Method 2
Lecture 7 Excel Implementation
Section 6: Forecasting Demand Method 3
Lecture 8 Forecasting Demand Method 3
Lecture 9 Excel Implementation
Section 7: Forecasting Demand Method 4
Lecture 10 Forecasting Demand Method 4
Lecture 11 Excel Implementation
Section 8: Forecasting Demand Method 5
Lecture 12 Forecasting Demand Method 5
Lecture 13 Excel Implementation
Section 9: Forecasting Demand Method 6
Lecture 14 Forecasting Demand Method 6
Lecture 15 Excel Implementation
Section 10: Forecasting Demand Method 7
Lecture 16 Forecasting Demand Method 7
Lecture 17 Excel Implementation
Section 11: Forecasting Demand Method 8
Lecture 18 Forecasting Demand Method 8
Section 12: Forecasting Demand Method 9
Lecture 19 Forecasting Demand Method 9
Section 13: Forecasting Demand Method 10
Lecture 20 Forecasting Demand Method 10
Supply chain and operations beginners looking to understand forecasting methods.,MBA students, business analysts, or entrepreneurs wanting to forecast demand effectively.,Data enthusiasts or Excel users interested in applying forecasting techniques to real data.,Professionals entering supply chain, inventory, or production planning roles.