Supply Chain Analytics - Demand Forecasting
A Comprehensive Guide to Time Series and Causal Modeling in Excel
What you will learn
Harnessing the Power of Time: A Comprehensive Guide to Time Series and Causal Modeling in Excel
From Data to Insights: A Step-by-Step Guide to Time Series and Causal Modeling in Excel
Moving Average & Weighted Moving Average Model
Learn to Calculate Forecasting KPIs - MAD , MAPE & RMSE
AR Model
ARIMA Model
Causal Model
Linear & Multiple Regression Analysis
Making Sense of Data
Forecasting and Predictive Analytics
Causal Inference and Counterfactual Analysis
Understand the assumptions and limitations of different time series forecasting models
Why take this course?
“There are two kinds of forecasters: those who don't know, and those who don't know they don't know.”
Wouldn’t it be nice to see into the future of your business?
With business forecasting, this is a reality; by using current and historical data you are able to have accurate predictions for future trends and forecasts. With this increased visibility you can analyze your business as a whole with the utmost confidence in the data.
The course will start with the basic principles of forecasting and take you to advance industry practices.
You will learn to build the following Time Series & Causal models.
1. Naive Forecasting
2. Moving Average
3. Weighted Average
4. Exponential Smoothing ( Single, Double & Triple )
5. AR ( Auto Regressive ) Model
6 . ARIMA (Auto Regressive Integrated Moving Average ) Model
7. Linear & Multiple Regression Analysis
8. Causal Models
Not everyone is an expert in programming languages so Excel can be a good alternative or good start to build models.
Learning forecasting in Excel is the foundation of learning forecasting in programming languages like Python and R.
Practice assignments for all the models forecasting and KPI calculation is part of the course. Get ready to make your hands dirty.
Forecasting is an essential business process that helps organizations plan and prepare for the future by predicting consumer demand for products and services. Excel is a powerful tool that can be used to create accurate demand forecasts and assist in decision-making processes. Here are some reasons why you should learn demand forecasting with Excel:
Widely Used: Excel is a widely used spreadsheet program and is readily available in most organizations. Learning demand forecasting with Excel can help you use a tool that is accessible to you and your colleagues.
Easy to Learn: Excel is relatively easy to learn, and many online resources provide tutorials and courses to learn the basics of using Excel for demand forecasting.
Cost-Effective: Excel is a cost-effective solution for demand forecasting compared to other more expensive software tools.
Versatile: Excel is a versatile tool that can handle large data sets and can be used to create a wide range of models and visualizations.
Integrates with other tools: Excel can be used in conjunction with other business tools such as ERP systems, CRM systems, and BI software.
By learning demand forecasting with Excel, you can improve your forecasting accuracy, save time, and make more informed business decisions.
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