Introduction to Supply Chain Analytics using Microsoft Excel
Introduction to Supply Chain Analytics using Microsoft Excel, available at $94.99, has an average rating of 4.59, with 52 lectures, 3 quizzes, based on 1374 reviews, and has 5801 subscribers.
You will learn about 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 This course is ideal for individuals who are Supply chain managers or Manufacturing professionals or Inventory analysts or Logistics professionals or Production planners or Buyers or Purchasing managers or Industrial engineers or Quality engineers and managers or Operations managers It is particularly useful for Supply chain managers or Manufacturing professionals or Inventory analysts or Logistics professionals or Production planners or Buyers or Purchasing managers or Industrial engineers or Quality engineers and managers or Operations managers.
Enroll now: Introduction to Supply Chain Analytics using Microsoft Excel
Summary
Title: Introduction to Supply Chain Analytics using Microsoft Excel
Price: $94.99
Average Rating: 4.59
Number of Lectures: 52
Number of Quizzes: 3
Number of Published Lectures: 52
Number of Published Quizzes: 3
Number of Curriculum Items: 55
Number of Published Curriculum Objects: 55
Original Price: $39.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- Supply chain managers
- Manufacturing professionals
- Inventory analysts
- Logistics professionals
- Production planners
- Buyers
- Purchasing managers
- Industrial engineers
- Quality engineers and managers
- Operations managers
Target Audiences
- Supply chain managers
- Manufacturing professionals
- Inventory analysts
- Logistics professionals
- Production planners
- Buyers
- Purchasing managers
- Industrial engineers
- Quality engineers and managers
- Operations managers
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:
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Example of parametric and nonparametric statistics
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Measures of central tendency and dispersion
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How to use the normal distribution to describe processes
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How to combine the normal random variables
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How to calculate process yield
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Lots of practical applications for descriptive analytics
In the predictive analytics section you will learn:
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The basics of time series analysis
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How to build a linear regression model in Excel
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How to calculate seasonality
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How to combine baseline, trend and seasonality to build forecasts
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How to use Excel Data Analysis Add-in
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Real life applications of time series forecasting
In the prescriptive analytics section you will learn:
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The basics of mathematical programming
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How to use Excel’s Solver Add-in
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How to build data models using objective functions and constraints
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The Economic Order Quantity and how to use it to cut your Total Inventory Costs
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How to integrate management policies into your linear programs
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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”:
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“Very great course if you are starting out in the Supply Chain field. Found it very informative and engaging.” – Isabel B.
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“The course was outstanding, I’ve learnt things about inventory that I never heard of before.” – Jerry O.
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“A well-designed course… Very helpful to start learning Supply Chain diagnostics. Thank you, Ray!” – Nakul T.
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“It’s my first course about supply chain analytics and I love it! Easy to understand, recommended for beginners.” – Haidar A.
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“One of the best courses I have taken on Udemy.” – Laxman S.
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“Great tools for the Supply Chain professional! Engaging and very knowledgeable of the overall subject.” – Stephanie M.
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“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.
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Plus Over 700 5-star Reviews!!
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Course Curriculum
Chapter 1: Introduction to Supply Chain Analytics
Lecture 1: Introduction
Lecture 2: What is a Supply Chain?
Lecture 3: What is Supply Chain Management?
Lecture 4: What is Analytics?
Chapter 2: Descriptive Analytics
Lecture 1: Case Study #1, Descriptive Analytics
Lecture 2: Descriptive Analytics in Excel, Pt 1
Lecture 3: Quartiles
Lecture 4: Quartiles in Excel
Lecture 5: Histograms in Excel
Lecture 6: From Data to Distributions
Lecture 7: Comments on Distributions
Lecture 8: Data Models
Lecture 9: The Normal Distribution
Lecture 10: Descriptive Analytics in Excel, Pt 2
Lecture 11: The Norminv Function
Lecture 12: Summing Normal Distributions
Lecture 13: Summing Normal Distributions in Excel
Lecture 14: Calculating Process Yield
Lecture 15: Wrap Up and Launch Points from Descriptive Analytics
Lecture 16: Descriptive Analytics Practice Exercises
Chapter 3: Predictive Analytics
Lecture 1: Case Study #2, Predictive Analytics
Lecture 2: Approaches to Demand Forecasting
Lecture 3: Introduction to Time Series Analysis
Lecture 4: Excel Add-ins
Lecture 5: Baseline Analysis in Excel, Pt 1
Lecture 6: Baseline Analysis in Excel, Pt 2
Lecture 7: Analyzing Seasonality
Lecture 8: Upper and Lower Forecast Estimates
Lecture 9: Algebraic Properties of a Line
Lecture 10: Linear Trend Analysis
Lecture 11: Excel's Regression Analysis Tool
Lecture 12: Analyzing Seasonality and Growth Combined
Lecture 13: Review of Analysis Methods
Lecture 14: Wrap Up and Launch Points from Predictive Analytics
Lecture 15: Predictive Analytics Practice Exercises
Chapter 4: Prescriptive Analytics
Lecture 1: Introduction to Prescriptive Analytics
Lecture 2: Case Study #3, Prescriptive Analytics
Lecture 3: EOQ, Pt 1
Lecture 4: EOQ, Pt 2
Lecture 5: EOQ in Excel
Lecture 6: Building an EOQ Data Model
Lecture 7: Mathematical Programming, Pt 1
Lecture 8: Mathematical Programming, Pt 2
Lecture 9: Adding Constraints
Lecture 10: Case Study #4, The Product Mix Problem
Lecture 11: Solving the Product Mix Problem, Pt 1
Lecture 12: Solving the Product Mix Problem, Pt 2
Lecture 13: Solving the Product Mix Problem, Pt 3
Lecture 14: Wrap Up and Launch Points from Prescriptive Analytics
Lecture 15: Prescriptive Analytics Practice Problems
Lecture 16: Conclusion
Lecture 17: Bonus Lecture
Instructors
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Ray Harkins, The Manufacturing Academy
Senior Manufacturing Professional, Online Educator
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 10 votes
- 3 stars: 103 votes
- 4 stars: 485 votes
- 5 stars: 773 votes
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