Introduction to Supply Chain Analytics using Microsoft Excel | Udemy

Introduction to Supply Chain Analytics using Microsoft Excel | Udemy [Update 10/2022]
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Genre: eLearning

Your first steps in descriptive, predictive and prescriptive analytics to solve your toughest supply chain problems

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

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.

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 120 5-star Reviews!!

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


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