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The Complete Operations Management Course - In Excel

Name: The Complete Operations Management Course - In Excel
Rating: 4.3 (74 reviews)

Fundamental and Intermediate Concepts in Operations Management and Engineering

Created byMichael Parent

Last updated 5/2024

English

English [Auto],

What you'll learn

Learn key terms and concepts in the field of Quality and Operations Management
Build Capacity models for factories and production facilities
Optimize operations through linear optimization procedures
Use statistics to understand and visualize business operations
Conduct Hypothesis testing including ANOVA and Regression Analysis
Create Monte Carlo simulations to forecast and understand complex processes
Develop robust quality control methods such as capability analysis and control charting

Course content

7 sections • 37 lectures • 7h 36m total length

Introduction15:39
Explore how operations model value by transforming inputs into outputs through a process mindset across manufacturing, shipping, health care, call centers, and service.
Basic Production14:58
Time14:26
Cost, Manpower, Productivity15:02
Averages & Standard Deviations13:22
Explore descriptive statistics in Excel, including mean, median, mode, and standard deviation, and learn to compute weighted averages with sumproduct.
Appendix #1.1: Enabling the Data Analysis Tool Pak Add-in2:14

Simple Capacity11:32
The Excel files found in this Lecture video are used throughout the lectures in this Module on Capacity Modelling.
The "Empty" capacity model file allows you to follow allow with the lecture. The other file is the final output after all of the lecture videos.
Each tab in this document covers a different type of capacity model.
Normal Capacity18:45
Textile Capacity11:12
Ramp Up Capacity6:31

Change from Deterministic to Stochastic Models8:01
Statistics & Probability16:13
Explore probability and statistics, from descriptive to inferential, using sampling, margin of error, and tests like linear regression, t-tests, and ANOVA in operations modeling.
The Normal Distribution14:03
Explore the normal distribution and central limit theorem, examining symmetry, bell curve shape, mean, median, and mode equality, and using the data analysis tool pack to analyze skewness.
Other Distributions11:47
Explore the uniform and exponential distributions, highlighting equal probability and short vs long-tailed behavior, and apply them to operations modeling, including wait times, downtime, and simulations.
APPENDIX #4.1: The Statistics Reference Card Resource3:01
Explore a nine-tab statistics reference card that lets you adjust mu and standard deviation and compare distributions such as gamma and exponential.

Process Variation12:42
Process Capability15:08
Performing a Capability Analysis13:07
Process Control Charts13:39
Learn how process control charts relate to capability analyses, using real-time data, upper and lower control limits, and detection of special versus common cause variation to improve quality.
Process Control Charting with Time14:28
Process Control Charting with Quality12:49
Learn to apply process control charting to binary pass/fail data by tracking proportions within subgroups, building p-charts, and adjusting control limits using Poisson-based reasoning.
Process Control Charts without Charts8:56

Simulation Fundamentals14:59
Setting up a Monte Carlo Simulation in Excel15:17
Explore a Monte Carlo simulation in Excel by modeling a manufacturing process with 10,000 trials, using normal and gamma processes, and interpreting results to plan staffing.
Case #7.1: Movie Theater Concessions Simulation16:49
Case #7.2: Call Center Operations Simulation19:56
APPENDIX #7.1: Simulation using Historic Data6:47

Requirements

Basic Math

Description

Do you think you need to learn a new software program to model your business operations through data analysis, optimization, simulations and statistics? You Don't! Everything you need to get started in the world of Operations Modelling is already on your computer in the wonderful application called Excel.

This Course is designed to take students through the fundamentals of operations modelling and management. Starting with foundational topics and vocabulary, we build a robust understanding of what operations are and why they matter to businesses. Then, we focus deeply on several quantitative tools and techniques to help us better understand, manage, forecast and predict how our operations will perform and can be improved.

This course is taught entirely in MS Excel which makes it widely accessible to a number of interested participants without the need to purchase, download, or learn a new program or programming language. In addition to learning key concepts in the world of operations management, quality management, data analysis and operations modelling, you will also increase your proficiency in one of the world's most popular and essential programs in business.

Techniques and tools covered:

Capacity Modelling

Descriptive Statistics

Inferential Statistics

Data Distributions

Regression Analysis

ANOVA

Monte Carlo Simulations

Process Capability

Control Charting

Linear Programming and Optimization

And MUCH MORE!

Please message me if you have any questions!

Who this course is for:

Operations Managers
Engineers
Industrial Engineers
MBAs
Quality Managers
Data Analysts
Data Scientists
Business Analysts

The Complete Operations Management Course - In Excel

What you'll learn

Explore related topics

Course content

Introduction to Operations Modelling6 lectures • 1hr 16min

Capacity Modelling4 lectures • 48min

Linear Optimization6 lectures • 1hr 4min

Statistics, Probability and Data Distributions5 lectures • 53min

Statistics: Hypothesis Testing4 lectures • 51min

Quality Management7 lectures • 1hr 31min

Simulation5 lectures • 1hr 14min

Requirements

Description

Who this course is for: