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Paul Jan
Supply chain planning is an important activity in any supply chain. This is where organizations get an idea of the upcoming demand, realize if they have the capacity to meet the demand, and determine how to realize these demands. In this course, we will explore how to use data science to conduct demand and supply planning, how to constrain the forecast, and how to measure the results. As we walk through this process, we will also explore how to use Excel to quantify each step.
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What's inside
Syllabus
Demand Planning
Welcome to Module 1, Demand Planning. In this module, we will explore demand planning, how to identify influencing factors, how to differentiate between the three simple statistical forecast types, and how to compute a few forecast values.
Read more
Syllabus
Demand Planning
Welcome to Module 1, Demand Planning. In this module, we will explore demand planning, how to identify influencing factors, how to differentiate between the three simple statistical forecast types, and how to compute a few forecast values.
Read more
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops fluency in supply chain, demand planning, supply planning, constrained forecast, and measuring results, which are essential skills for supply chain managers
Explores real-life use cases in Excel, which is standard in supply chain planning
Introduces constrained forecasts and consensus meetings, which are common practices in the industry
Teaches how to measure results to improve supply chain planning
Requires students to have basic knowledge of supply chain management and Excel
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Reviews summary
Practical supply chain planning with excel focus
According to students, this course offers a strong foundation in supply chain planning, highly valued for its practical application, particularly through Excel examples. Learners consistently praise the clear explanations and knowledgeable instructor, finding the content directly applicable to their professional roles. While some reviews express a desire for more advanced data science techniques beyond basic statistical methods, the course is generally considered an excellent starting point for those new to the field or seeking to solidify their understanding. Observations from recent reviews suggest potential ongoing course improvements, as concerns about outdated content, highlighted in older feedback, are less prevalent now.
Recent reviews suggest the course has been updated and improved over time.
"I found the course content to be quite up-to-date, despite some older reviews mentioning outdated material."
"The material felt current and relevant; any past issues with outdated content seem to have been addressed."
"While some older reviews mentioned outdated methods, the current course material feels very current and well-structured."
Content is directly applicable to professional roles in supply chain planning.
"Highly recommend for professionals. I found the module on Constrained Forecast especially relevant for my job."
"The content is directly applicable to my work, helping me improve planning processes immediately."
"I learned how to use practical tools and strategies that I could apply immediately to my work."
The instructor provides clear explanations and is highly knowledgeable.
"The instructor explained complex topics clearly and was very engaging."
"I found the instructor to be knowledgeable and effective in delivering the material."
"The pacing was good and the instructor made the topics easy to follow and understand."
Hands-on Excel examples make concepts applicable to real-world scenarios.
"The Excel examples in particular were extremely helpful for applying concepts to real-world scenarios."
"I appreciated the practical Excel usage; it really helps to solidify the theoretical concepts."
"The clear explanations of demand and supply planning, coupled with concrete Excel applications, made this course stand out."
Provides a solid foundation but may not delve into advanced data science techniques.
"Some parts felt a bit rushed, and I wish there was more on advanced data science techniques beyond basic statistical forecasting."
"I felt it was too basic for my needs, hoping for more Python/R integration for data science."
"This is a solid introduction to the subject, but don't expect deep dives into complex algorithms."
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Supply Chain Planning with these
activities:
Review Data Analysis and Modeling Basics
Show steps
Refreshing your data analysis and modeling skills will provide a strong foundation for the quantitative aspects of supply chain planning.
Browse courses on
Data Analysis
Show steps
-
Review statistical principles and regression analysis
-
Practice using data analysis software or tools
Review 'Supply Chain Management: A Logistics Approach'
Show steps
Reviewing this leading textbook can enhance your understanding of key concepts and provide a strong foundation for the course.
View
Supply Chain Logistics Management
on Amazon
Show steps
-
Read Chapter 1: Introduction to Supply Chain Management
-
Summarize key points of Chapter 2: The Scope of Supply Chain Management
-
Complete end-of-chapter questions for Chapters 1 and 2
Follow Tutorials on Supply Chain Capacity Planning
Show steps
Guided tutorials will provide additional support and insights into how to effectively plan supply chain capacity.
Browse courses on
Production Planning
Show steps
-
Identify online tutorials on supply chain capacity planning
-
Watch and take notes from the tutorials
-
Apply the concepts learned in the tutorials to practical scenarios
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice Demand Forecasting with Time Series Analysis
Show steps
Repetitive practice with time series analysis will strengthen your ability to forecast demand accurately.
Browse courses on
Demand Forecasting
Show steps
-
Solve practice problems on moving averages and exponential smoothing
-
Apply time series models to real-world demand data
Create a Supply Chain Demand Planning Model
Show steps
By creating your own model, you will apply the principles learned in Module 1 and develop practical skills in demand forecasting.
Browse courses on
Demand Forecasting
Show steps
-
Identify data sources for historical demand and related variables
-
Select and apply statistical forecasting methods
-
Evaluate and compare forecast accuracy
-
Prepare a report summarizing the model and its findings
Participate in a Study Group for Supply Chain Planning
Show steps
Engaging in peer discussions will foster a deeper understanding of course concepts and enhance your critical thinking skills.
Browse courses on
Supply Chain Planning
Show steps
-
Join or create a study group with classmates
-
Review course materials and prepare discussion topics
-
Actively participate in discussions and share insights
Review Data Analysis and Modeling Basics
Show steps
Refreshing your data analysis and modeling skills will provide a strong foundation for the quantitative aspects of supply chain planning.
Browse courses on
Data Analysis
Show steps
Show steps
Show steps
- Review statistical principles and regression analysis
- Practice using data analysis software or tools
Review 'Supply Chain Management: A Logistics Approach'
Show steps
Reviewing this leading textbook can enhance your understanding of key concepts and provide a strong foundation for the course.
View
Supply Chain Logistics Management
on Amazon
Show steps
Show steps
Show steps
- Read Chapter 1: Introduction to Supply Chain Management
- Summarize key points of Chapter 2: The Scope of Supply Chain Management
- Complete end-of-chapter questions for Chapters 1 and 2
Follow Tutorials on Supply Chain Capacity Planning
Show steps
Guided tutorials will provide additional support and insights into how to effectively plan supply chain capacity.
Browse courses on
Production Planning
Show steps
Show steps
Show steps
- Identify online tutorials on supply chain capacity planning
- Watch and take notes from the tutorials
- Apply the concepts learned in the tutorials to practical scenarios
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice Demand Forecasting with Time Series Analysis
Show steps
Repetitive practice with time series analysis will strengthen your ability to forecast demand accurately.
Browse courses on
Demand Forecasting
Show steps
Show steps
Show steps
- Solve practice problems on moving averages and exponential smoothing
- Apply time series models to real-world demand data
Create a Supply Chain Demand Planning Model
Show steps
By creating your own model, you will apply the principles learned in Module 1 and develop practical skills in demand forecasting.
Browse courses on
Demand Forecasting
Show steps
Show steps
Show steps
- Identify data sources for historical demand and related variables
- Select and apply statistical forecasting methods
- Evaluate and compare forecast accuracy
- Prepare a report summarizing the model and its findings
Participate in a Study Group for Supply Chain Planning
Show steps
Engaging in peer discussions will foster a deeper understanding of course concepts and enhance your critical thinking skills.
Browse courses on
Supply Chain Planning
Show steps
Show steps
Show steps
- Join or create a study group with classmates
- Review course materials and prepare discussion topics
- Actively participate in discussions and share insights
Career center
Learners who complete Supply Chain Planning will develop knowledge and skills
that may be useful to these careers:
Demand Planning Analyst
Demand Planning Analyst
A Demand Planning Analyst uses data science to forecast demand for products and services. They use this information to help businesses make decisions about production, inventory, and pricing. This course provides a strong foundation in the data science techniques used by Demand Planning Analysts, making it a valuable resource for anyone who wants to enter this field.
Supply Chain Analyst
Supply Chain Analyst
A Supply Chain Analyst uses data science to improve the efficiency and effectiveness of supply chains. They use this information to help businesses reduce costs, improve customer service, and mitigate risks. This course provides a strong foundation in the data science techniques used by Supply Chain Analysts, making it a valuable resource for anyone who wants to enter this field.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses data science to solve complex problems in a variety of industries. They use this information to help businesses make better decisions about how to allocate resources, schedule production, and manage inventory. This course provides a strong foundation in the data science techniques used by Operations Research Analysts, making it a valuable resource for anyone who wants to enter this field.
Business Analyst
Business Analyst
A Business Analyst uses data science to help businesses understand their customers, markets, and operations. They use this information to help businesses make better decisions about how to grow their business. This course provides a strong foundation in the data science techniques used by Business Analysts, making it a valuable resource for anyone who wants to enter this field.
Data Scientist
Data Scientist
A Data Scientist uses data science to solve complex problems in a variety of industries. They use this information to help businesses make better decisions about how to allocate resources, schedule production, and manage inventory. This course provides a strong foundation in the data science techniques used by Data Scientists, making it a valuable resource for anyone who wants to enter this field.
Financial Analyst
Financial Analyst
A Financial Analyst uses data science to analyze financial data and make recommendations about investments. They use this information to help businesses make better decisions about how to allocate their resources. This course provides a strong foundation in the data science techniques used by Financial Analysts, making it a valuable resource for anyone who wants to enter this field.
Marketing Analyst
Marketing Analyst
A Marketing Analyst uses data science to analyze marketing data and make recommendations about marketing campaigns. They use this information to help businesses make better decisions about how to reach their target audience. This course provides a strong foundation in the data science techniques used by Marketing Analysts, making it a valuable resource for anyone who wants to enter this field.
Product Manager
Product Manager
A Product Manager uses data science to analyze product data and make recommendations about product development. They use this information to help businesses make better decisions about how to develop and market their products. This course provides a strong foundation in the data science techniques used by Product Managers, making it a valuable resource for anyone who wants to enter this field.
Project Manager
Project Manager
A Project Manager uses data science to analyze project data and make recommendations about project management. They use this information to help businesses make better decisions about how to manage their projects. This course provides a strong foundation in the data science techniques used by Project Managers, making it a valuable resource for anyone who wants to enter this field.
Risk Analyst
Risk Analyst
A Risk Analyst uses data science to analyze risk data and make recommendations about risk management. They use this information to help businesses make better decisions about how to manage their risks. This course provides a strong foundation in the data science techniques used by Risk Analysts, making it a valuable resource for anyone who wants to enter this field.
Sales Analyst
Sales Analyst
A Sales Analyst uses data science to analyze sales data and make recommendations about sales strategies. They use this information to help businesses make better decisions about how to sell their products and services. This course provides a strong foundation in the data science techniques used by Sales Analysts, making it a valuable resource for anyone who wants to enter this field.
Statistician
Statistician
A Statistician uses data science to analyze data and make recommendations about statistical models. They use this information to help businesses make better decisions about how to use their data. This course provides a strong foundation in the data science techniques used by Statisticians, making it a valuable resource for anyone who wants to enter this field.
Teacher
Teacher
A Teacher uses data science to analyze data and make recommendations about teaching methods. They use this information to help students learn more effectively. This course provides a strong foundation in the data science techniques used by Teachers, making it a valuable resource for anyone who wants to enter this field.
Writer
Writer
A Writer uses data science to analyze data and make recommendations about writing style. They use this information to help businesses write more effective marketing materials, blog posts, and other written content. This course provides a strong foundation in the data science techniques used by Writers, making it a valuable resource for anyone who wants to enter this field.
Consultant
Consultant
A Consultant uses data science to analyze data and make recommendations about business strategies. They use this information to help businesses make better decisions about how to grow their business. This course provides a strong foundation in the data science techniques used by Consultants, making it a valuable resource for anyone who wants to enter this field.
For more career information including salaries, visit:
OpenCourser.com/course/g8i09m/supply
Reading list
We've selected seven books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Supply Chain Planning.
This comprehensive textbook provides a solid foundation in supply chain planning and inventory management. It covers topics such as demand forecasting, inventory optimization, and transportation planning, complementing the course's focus on data science applications.
Provides a comprehensive overview of supply chain management, covering topics such as demand forecasting, inventory management, transportation, and logistics. It valuable resource for anyone who wants to learn more about the field of supply chain management.
Provides a comprehensive overview of data mining techniques, which are increasingly used in supply chain planning for demand forecasting, customer segmentation, and other tasks. It offers a deeper understanding of data science applications in the field.
Provides valuable insights into demand-driven material requirements planning (DDMRP), a modern approach to supply chain planning. It can serve as a helpful reference for understanding the concepts covered in the course.
Save
This classic work provides a fictionalized account of a manufacturing plant's journey to improve its operations. It introduces the Theory of Constraints, a problem-solving approach that can be applied to supply chain planning.
This textbook offers a comprehensive overview of operations and supply chain management, providing a foundational understanding of the broader context within which supply chain planning operates.
While not directly related to supply chain planning, this book provides a good introduction to Microsoft Excel, the tool used in the course for quantifying each step of the planning process.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/g8i09m/supply
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Effort
4 weeks of study, 2-3 hours/week
Level
Intermediate
Via
Coursera
Institution
University of California, Irvine
Instructor
Paul Jan
Language
English
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