Develop advanced forecasting and data analysis skills with Microsoft Excel Advanced Forecasting Method Training, a practical program designed for data analysts, business analysts, finance professionals, managers, planners, researchers, and Excel users who want to turn historical data into meaningful forecasts and support more informed business decisions.
Duration 2 days – 14 hrs
Overview
The Microsoft Excel Advanced Forecasting Method Training is an intensive, hands-on program designed to develop advanced skills in forecasting, predictive analysis, data modeling, and data-driven decision-making using Microsoft Excel. The course is ideal for professionals who need to analyze historical data, identify trends and patterns, develop forecasting models, and use Excel to support accurate business and operational planning.
Participants will explore Excel’s advanced forecasting capabilities and learn how to transform historical datasets into meaningful projections. Through practical exercises, real-world examples, and case studies, learners will gain experience applying forecast functions, trendlines, What-If Analysis, Scenarios, Solver, and Data Tables to evaluate different business situations and potential outcomes.
The training also focuses on building and interpreting advanced Excel forecasting models. Participants will learn how to structure data, analyze trends, evaluate assumptions, and create flexible models that can be adjusted to reflect changing business conditions. These techniques can be applied to areas such as sales forecasting, financial planning, budgeting, demand planning, resource allocation, and business performance analysis.
A key component of the course is understanding how Excel can handle and analyze larger and more complex datasets. Participants will be introduced to the Excel Data Model, which provides powerful capabilities for connecting, organizing, and analyzing data from multiple sources. This enables learners to work more effectively with large datasets and develop more comprehensive analytical models.
By the end of the Microsoft Excel Advanced Forecasting Method Training, participants will be able to build advanced forecasting models, perform What-If Analysis, analyze trends, generate projections, work with large datasets, and interpret forecasting results to support more informed and data-driven decisions.
Learning Objectives
- Master advanced forecasting techniques in Microsoft Excel.
- Learn to analyze historical data trends and patterns.
- Understand and apply time series analysis methods.
- Implement moving averages and exponential smoothing for forecasting.
- Perform regression analysis to identify relationships between variables.
- Gain proficiency in ARIMA modeling for time series forecasting.
- Evaluate forecast accuracy using appropriate metrics.
- Utilize scenario and what-if analysis for decision-making.
Audience
The Microsoft Excel Advanced Forecasting Method Training is designed for professionals who use Excel to analyze data, develop projections, evaluate business scenarios, and support strategic or operational decision-making. It is particularly suitable for:
- Business Analysts – professionals who analyze business trends, performance data, and forecasts to support planning and decision-making.
- Financial Analysts and Finance Professionals – individuals involved in budgeting, financial modeling, revenue projections, and financial planning.
- Data Analysts – professionals who work with historical datasets and need advanced Excel techniques for trend analysis, forecasting, and predictive insights.
- Sales and Marketing Professionals – teams that need to forecast sales, customer demand, campaign performance, and market trends.
- Supply Chain and Demand Planning Professionals – individuals responsible for demand forecasting, inventory planning, procurement, and resource requirements.
- Operations Managers – professionals who use forecasts to support capacity planning, workforce requirements, operational efficiency, and business planning.
- Business Planning and Strategy Professionals – individuals who evaluate future scenarios and use data to support strategic decisions.
- Project Managers – professionals who need forecasting techniques for budgets, resources, timelines, and project planning.
- Researchers and Reporting Professionals – individuals who analyze historical information and create projections or data-driven reports.
- Advanced Excel Users – professionals who already work confidently with Excel and want to develop more advanced forecasting, What-If Analysis, data modeling, and predictive analysis skills.
- Anyone involved in Excel-based data analysis and decision-making who wants to strengthen their ability to create forecasts and use historical data to support future planning.
Recommended Audience: This course is best suited for intermediate to advanced Excel users who are familiar with basic formulas, functions, tables, and data analysis and want to progress into advanced forecasting and predictive modeling techniques.
Pre- requisites
- Introduction to Excel class or equivalent skills and a general understanding of the issues related to forecasting and what-if analysis.
- Intermediate to advanced proficiency in Microsoft Excel, including knowledge of basic functions, formulas, and data manipulation techniques.
- Familiarity with basic statistical concepts such as mean, median, and standard deviation.
Course Content
Forecasting
- Using the Forecast Sheet
- Modifying Options
- Using Forecast Functions
Using the Quick Analysis Tool
- Formatting Options
- Creating Charts
- Applying Totals
- Creating Tables
- Adding Sparklines
Using What-If Analysis
- Working with Scenarios
- Creating Data Tables
- Using Goal Seek
Using Solver
- Adding the Solver Add-in
- Define a Problem Using Solver
- Solving a Problem
- Solver for Capital Budgeting
- Solver for Financial Planning
- Solver to determine Optimal Product Mix
- Perform What-If Analysis with the Solver Tool
Gathering Data
- Using the Power Query Editor
- Appending Data
- Merging Data
- Transforming Data
Using the Excel Data Model
- Viewing a Data Model
- Getting Data
- Linking Tables
- Using the Model
- Creating Calculated Columns
