image
The Ultimate Drawing Course Beginner to Advanced...
$179
$79
image
User Experience Design Essentials - Adobe XD UI UX...
$179
$79
Total:
$659

Description

Many industry analyst predict that both supply chain management and analytics 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.
You will also receive a downloadable
Glossary of Terminology
early in the course that you can use to study offline. The 110+ terms were carefully chosen to not only cover the key ides in this course, but also to give you starting points into more in-depth or adjacent topics.
Here's what Udemy students are saying
about "Introduction to Supply Chain Analytics using Microsoft Excel":
"Very great course if you are starting out in the Supply Chain field. Found it very informative and engaging."
- Isabel B.
"The course was outstanding, I've learnt things about inventory that I never heard of before."
- Jerry O.
"A well-designed course... Very helpful to start learning Supply Chain diagnostics. Thank you, Ray!"
- Nakul T.
"It's my first course about supply chain analytics and I love it! Easy to understand, recommended for beginners."
- Haidar A.
"One of the best courses I have taken on Udemy."
- Laxman S.
"Great tools for the Supply Chain professional! Engaging and very knowledgeable of the overall subject."
 - Stephanie M.
"I love how topics are being explained in a very easy to understand manner. Attended a few Udemy courses and this is one of the better ones. Kudos."
- Clifford C.
Plus Over 900 5-star Reviews!!
"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 powerful 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
Buyers
Purchasing managers
Industrial engineers
Quality engineers and managers
Operations managers

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

Requirements

  • You will need a copy of Adobe XD 2019 or above. A free trial can be downloaded from Adobe.
  • No previous design experience is needed.
  • No previous Adobe XD skills are needed.

Course Content

27 sections • 95 lectures
Expand All Sections
1-Introduction to Supply Chain Analytics
5
1.1-Introduction
1.2-What is a Supply Chain?
1.3-What is Supply Chain Management?
1.4-What is Analytics?
1.5-Glossary of Terminology
2-Descriptive Analytics
17
2.1-Case Study #1, Descriptive Analytics
2.2-Descriptive Analytics in Excel, Pt 1
2.3-Quartiles
2.4-Quartiles in Excel
2.5-Histograms in Excel
2.6-From Data to Distributions
2.7-Comments on Distributions
2.8-Data Models
2.9-The Normal Distribution
2.10-Descriptive Analytics in Excel, Pt 2
2.11-The Norminv Function
2.12-Summing Normal Distributions
2.13-Summing Normal Distributions in Excel
2.14-Calculating Process Yield
2.15-Descriptive Analytics Quiz
2.16-Wrap Up and Launch Points from Descriptive Analytics
2.17-Descriptive Analytics Practice Exercises
3-Predictive Analytics
16
3.1-Case Study #2, Predictive Analytics
3.2-Approaches to Demand Forecasting
3.3-Introduction to Time Series Analysis
3.4-Excel Add-ins
3.5-Baseline Analysis in Excel, Pt 1
3.6-Baseline Analysis in Excel, Pt 2
3.7-Analyzing Seasonality
3.8-Upper and Lower Forecast Estimates
3.9-Algebraic Properties of a Line
3.10-Linear Trend Analysis
3.11-Excel's Regression Analysis Tool
3.12-Analyzing Seasonality and Growth Combined
3.13-Review of Analysis Methods
3.14-Predictive Analytics Quiz
3.15-Wrap Up and Launch Points from Predictive Analytics
3.16-Predictive Analytics Practice Exercises
4-Prescriptive Analytics
18
4.1-Introduction to Prescriptive Analytics
4.2-Case Study #3, Prescriptive Analytics
4.3-EOQ, Pt 1
4.4-EOQ, Pt 2
4.5-EOQ in Excel
4.6-Building an EOQ Data Model
4.7-Mathematical Programming, Pt 1
4.8-Mathematical Programming, Pt 2
4.9-Adding Constraints
4.10-Case Study #4, The Product Mix Problem
4.11-Solving the Product Mix Problem, Pt 1
4.12-Solving the Product Mix Problem, Pt 2
4.13-Solving the Product Mix Problem, Pt 3
4.14-Prescriptive Analytics Quiz
4.15-Wrap Up and Launch Points from Prescriptive Analytics
4.16-Prescriptive Analytics Practice Problems
4.17-Conclusion
4.18-Bonus Lecture