Introduction to Supply Chain Analytics using Microsoft Excel
What you'll learn
- Fundamental tools of descriptive, predictive and descriptive analytics
- How to answer the questions, "What happened?", "What will happen?", and "What should we do?"
- Analytical tools for assessing demand forecasts, production outputs and product mix strategies
- Introductory time series analysis tools
- Baseline, Trend, Seasonality and Error
- Linear programming using Excel Solver
- Statistical tools in Excel like quartiles, the data analysis tool kit, Norminv, linear regression, mathematical programming, and more!
- How to use the Economic Order Quantity (EOQ)
- "Launch points" for further study in analytics
- Basic Microsoft Excel skills
- Basic understanding of manufacturing or logistics
- Basic business acumen
- Some supply chain or operations experience would be helpful.
Many industry analyst predict that both supply chain management and analytic will be among the most in-demand workplace skills the coming years. This class, "Introduction to Supply Chain Analytics using Microsoft Excel" will teach you many of the fundamental tools of descriptive (What happened?), predictive (What will happen?), and prescriptive (What should we do?) analytics, all within the familiar context of Excel.
In the descriptive analytics section you will learn:
Example of parametric and nonparametric statistics
Measures of central tendency and dispersion
How to use the normal distribution to describe processes
How to combine the normal random variables
How to calculate process yield
Lots of practical applications for descriptive analytics
In the predictive analytics section you will learn:
The basics of time series analysis
How to build a linear regression model in Excel
How to calculate seasonality
How to combine baseline, trend and seasonality to build forecasts
How to use Excel Data Analysis Add-in
Real life applications of time series forecasting
In the prescriptive analytics section you will learn:
The basics of mathematical programming
How to use Excel's Solver Add-in
How to build data models using objective functions and constraints
The Economic Order Quantity and how to use it to cut your Total Inventory Costs
How to integrate management policies into your linear programs
How to apply linear programming in a "classic" product mix problem
Plus for each section -- descriptive, predictive, and prescriptive -- you will have a chance to practice your newly learned skills with Excel-based, downloadable practice exercises covering all the major tools within each section.
The class "Introduction to Supply Chain Analytics using Microsoft Excel" will serve as the starting point to advance your analytical problem solving skills. No need to feel intimidated by statistics or heavy-duty math ... this class will step you through a power selection of analytical tools at a pace and level that any professional can handle. Sign up today!!
Who this course is for:
- Supply chain managers
- Manufacturing professionals
- Inventory analysts
- Logistics professionals
- Production planners
- Purchasing managers
- Industrial engineers
- Quality engineers and managers
- Operations managers
Ray Harkins is a senior manufacturing professional with 30 years experience in manufacturing engineering, quality management, and business analysis. During his career, he has toured hundreds of manufacturing facilities and worked with leading industry professionals throughout North America and Japan.
He earned his Bachelor of Science from the University of Akron where he majored in Engineering Technology, his Master of Science from Rochester Institute of Technology where he majored in Manufacturing Leadership and Project Management, and is about to complete his Master of Business Administration from Youngstown State University.
He is a senior member of the American Society of Quality, and holds their Quality Engineering (CQE), Quality Technician (CQT), Quality Auditing (CQA) and Calibration Technician (CCT) certifications.
Ray has written extensively for national trade publications on the topics of quality engineering and career management, and has taught nearly 30,000 students through the Udemy platform on a range of manufacturing-related topics.