Dr. Li Chen is a Professor of Operations, Technology and Information Management and Breazzano Family Term Professor of Management at Samuel Curtis Johnson Graduate School of Management at Cornell University. Dr. Chen’s research interests concern supply chain management, operations strategy, and Bayesian methods for predictive and prescriptive analytics. He has published research works in top journals in the operations management field, such as Management Science, Operations Research, and Manufacturing, Service and Operations Management. Prior to joining Johnson School, Dr. Chen was an Associate Professor of Business Administration at The Fuqua School of Business at Duke University. Before his Duke appointment, Dr. Chen spent four years at TrueDemand Software, a supply chain software company in Silicon Valley, where he was the cofounder and lead scientist of the company. Dr. Chen obtained his PhD in Management Science and Engineering from Stanford University in 2005.
Course Overview
Supply chain analytics are everywhere. Consider the similarities between a grocery list and a demand forecast: Before going to the store, you note which groceries you already have in your home. Next, you think about how much of each item you used in the past. Based on this information, you can predict how much of each item you need to purchase. In this micro example, you are acting as a supply chain analyst.
As you look at the implications of a larger-scale supply chain analysis, you'll grasp the complexity that organizations face in making accurate demand forecasts. When grocery shopping, if you make mistakes, you can just go on another trip and correct the purchase. In business situations, however, a mistake could mean a significant loss. In this case, you want to make decisions in a scientific and proven way.
In this course, you will measure performance based on an existing dataset. You will then determine the best forecasting method based on the given data. Finally, you will expand the application of this data by calculating a forecast for future demand and considering holistic approaches for mitigating risk, applying practical skills to incorporate into your future work with supply chain analytics.
Key Course Takeaways
- Measure demand forecast
- Generate demand forecast with and without seasonality
- Assess supply chain variability
How It Works
Course Author
Who Should Enroll
- Individuals seeking to increase skills in supply chain strategy
- Operations analysts
- Market analysts for consumer and industrial products
- Consultants seeking supply chain knowledge
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