Supply Chain Analytics
Learn the roles of analytics in supply chain management, different types of analytics (descriptive, predictive, and prescriptive), cleaning and preparing data for analyses, conducting exploratory data analyses, visualizing data and creating dashboard, and story telling with data.
Description
Uncovering insights from data is becoming increasingly important in today’s supply chain management. The Covid-19 pandemic has escalated the need for firms to manage and make sense of data. Supply chain analytics involves the use of data and analyses to gain insights about supply chain operations and make better, fact-based decisions. While the scope of analytics spans descriptive analytics, predictive analytics, and prescriptive analytics, average users primarily deal with descriptive analytics in the day-to-day operations. Reports such as those sales and revenue, work flow, and sales are all examples of descriptive analytics.
In supply chain analytics, you’ll learn the roles of analytics in supply chain management, different types of analytics (descriptive, predictive, and prescriptive), cleaning and preparing data for analyses, conducting exploratory data analyses, visualizing data and creating dashboard, and story telling with data.
Faculty:
David Peng, Ph.D., is professor of supply chain management and holds the Dean’s Chair professorship in the College of Business, Lehigh University. Dr. Peng is also chair of the department of Decision and Technology Analytics. He teaches and conducts research in sourcing strategy, technology management, and eBusiness operations.
Participants in this program will:
- Develop conceptual understanding of the role of analytics in supply chain management
- Understand the differences between the three types of analytics and their use in supply chain management
- Develop working knowledge of data visualization using a visualization software
- Use key performance indicators (KPIs) to identify underperformance in supply chains and explore possible causes