Demand Analytics

Rutgers the State University of New Jersey

Demand Analytics

This course is part of Supply Chain Analytics Specialization

Instructor: Yao Zhao

22,252 already enrolled

Included with Coursera Plus

Learn more

4 modules

Gain insight into a topic and learn the fundamentals.

4.6

(290 reviews)

Beginner level

No prior experience required

14 hours to complete

3 weeks at 4 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

4.6

(290 reviews)

Beginner level

No prior experience required

14 hours to complete

3 weeks at 4 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Use data analytics to predict demand with trend (as in new product introduction), seasonality, price elasticity and other environmental factors.
Identify the key drivers for demand and quantify their impact.
Build, validate and improve forecasting models with both continuous and categorical variables.

Skills you'll gain

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the Supply Chain Analytics Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

There are 4 modules in this course

Welcome to Demand Analytics - one of the most sought-after skills in supply chain management and marketing!

Through the real-life story and data of a leading cookware manufacturer in North America, you will learn the data analytics skills for demand planning and forecasting. Upon the completion of this course, you will be able to 1. Improve the forecasting accuracy by building and validating demand prediction models. 2. Better stimulate and influence demand by identifying the drivers (e.g., time, seasonality, price, and other environmental factors) for demand and quantifying their impact. AK is a leading cookware manufacturer in North America. Its newly launched top-line product was gaining momentum in the marketplace. However, a price adjustment at the peak season stimulated a significant demand surge which took AK completely by surprise and resulted in huge backorders. AK faced the risk of losing the market momentum due to the upset customers and the high cost associated with over-time production and expedited shipping. Accurate demand forecast is essential for increasing revenue and reducing cost. Identifying the drivers for demand and assessing their impact on demand can help companies better influence and stimulate demand. I hope you enjoy the course!

Welcome to the exciting world of Demand Analytics! In Week 1, you will learn the crisis that AK MetalCrafters (a leading cookware manufacturer in North America) faced in launching new products, and how AK successfully resolved the crisis using Demand Analytics. You will also learn the general principles of demand planning and forecasting, and how it fits into a firm's integrated business planning.

What's included

3 videos2 readings1 assignment1 peer review1 discussion prompt

3 videosTotal 15 minutes

The story of AK MetalCrafters3 minutesPreview module
Course overview5 minutes
General principles of demand planning and forecasting5 minutes

2 readingsTotal 60 minutes

Is this course right for me?30 minutes
Four Pillars of Demand Planning Excellence30 minutes

1 assignmentTotal 30 minutes

General principles30 minutes

1 peer reviewTotal 60 minutes

Demand planning and forecasting example(s)60 minutes

1 discussion promptTotal 30 minutes

Introduction30 minutes

Welcome to Week 2 of Demand Analytics! In Week 1, you learned the general principles, now in Week 2, you will put them to action by building and interpreting a linear model for predicting the trend (as in new product introduction). You will also learn data collection, pre-processing and visualization techniques, which are critical to model building.

What's included

5 videos3 readings1 assignment2 peer reviews

5 videosTotal 23 minutes

The basics of statistical forecasting models6 minutesPreview module
Data collection, pre-processing and visualization2 minutes
Data visualization screencast3 minutes
Build and interpret a linear model8 minutes
Build and interpret a linear model screencast2 minutes

3 readingsTotal 90 minutes

Software selection and preparation30 minutes
The visualization example30 minutes
Build and interpret a linear model: example30 minutes

1 assignmentTotal 30 minutes

Predicting trend30 minutes

2 peer reviewsTotal 120 minutes

Data visualization60 minutes
Build a linear model60 minutes

Welcome to Week 3 of Demand Analytics! In Week 2, you built a linear model to predict the trend. In this week, you will validate and improve the model by first analyzing its errors to identify missing variables and then building a multiple regression model to capture not only the trend but also the impact of price and other environmental factors.

What's included

3 videos1 reading2 assignments1 peer review

3 videosTotal 15 minutes

Model validation and improvement5 minutesPreview module
Multiple regression for trend, price and other factors6 minutes
Multiple regression screencast3 minutes

1 readingTotal 30 minutes

Multiple regression example30 minutes

2 assignmentsTotal 80 minutes

Model validation and improvement40 minutes
Multiple regression40 minutes

1 peer reviewTotal 60 minutes

A mini-project - build your multiple regression model without home sales60 minutes

In this last week of Demand Analytics, you will further improve your demand forecasting model built in Week 3 by including seasonality to capture the periodic patterns in the errors; you will learn how to model and format categorical variables, and how to create and test your forecast.

What's included

3 videos2 readings1 assignment1 peer review1 discussion prompt

3 videosTotal 16 minutes

Categorical variable (seasonality) modeling and formatting7 minutesPreview module
Forecasting and testing4 minutes
Forecasting and testing screencast4 minutes

2 readingsTotal 60 minutes

Categorical variables example30 minutes
Forecasting and testing example30 minutes

1 assignmentTotal 30 minutes

Modeling and formatting categorical variables30 minutes

1 peer reviewTotal 90 minutes

A mini-project: Build a new seasonality model on your own90 minutes

1 discussion promptTotal 30 minutes

Recap - back to the future30 minutes

Instructor

Instructor ratings

4.6 (77 ratings)

Yao Zhao

6 Courses96,320 learners

Offered by

Rutgers the State University of New Jersey

Explore more from Business Essentials

LearnQuest
Demand Forecasting Using Time Series
Course
University of Pennsylvania
Customer Analytics
Course
Coursera Project Network
Demand Planning in RStudio: Create Demand Forecast
Course
University of Virginia
Marketing Analytics
Course

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Learner reviews

4.6

290 reviews

5 stars
71.72%
4 stars
19.65%
3 stars
4.13%
2 stars
2.75%
1 star
1.72%

Showing 3 of 290

Reviewed on Jun 16, 2020

Thanks to Coursera and Professor Yao Zhao for providing the simplest and best way to get a hands-on experience of demand analytics

Reviewed on Apr 17, 2020

This course if good for beginners to get understanding of forecasting techniques. Also provides better understanding of Regression analysis and various modelling methods to Supply chain personals,

Reviewed on Oct 10, 2022

Was expecting a bit more advanced techniques for forecasting demand. However, it's a great course for a beginner.

View more reviews

New to Business Essentials? Start here.

Open new doors with Coursera Plus

Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Learn more

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Explore degrees

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Learn more

Frequently asked questions

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.