Introduction to Supply Chain Analytics

Learn functional analytic techniques to evaluate logistics and supply chain performance. Discover critical data interpretation methods and apply the information to improve logistics and supply chain performance. The course will focus on hands-on learning, and excel-based approaches for cleaning and analyzing data.

Program Benefits

Improve your ability to effectively:

• Understand basic principles and techniques related to supply chain analytics
• Identify key areas of logistics and supply chain management for which data collection and analysis may be helpful to the achievement of broader logistics and supply chain objectives
• Determine the types of data and information that may best help you understand and profile activities and processes of interest across the functional areas of customer, product, inventory, transportation and supplier
• Meaningfully evaluate the effectiveness and efficiency of logistics operations through understanding the functional metrics and analyses
• Detect and correct corrupt or inaccurate content in databases of interest
• Recognize contemporary and future advances in supply chain analytics
• Develop plans for improvement of logistics and supply chain activities
• Practice using Excel-based approaches to clean, analyze, and derive value from supply chain databases

This program awards 1.5 CEUs. Penn State Continuing Education Units (CEUs) are available based on a standard of one unit per ten hours of classroom instruction.

Program Content

Faculty leaders will have you take a global view of your organization where you will confront the external factors affecting the business and identify opportunities for innovation.

Fundamentals

• Key principles of data analysis
• Analytics approaches and techniques
• Understanding customer, product, inventory, transportation, and supplier data of relevance to logistics and supply chain management

Tools & Techniques

• Strategies for data collection and aggregation
• Structuring key performance indicators
• Integrating results of functional analyses to better understand logistics and supply chain performance

Future Directions

• Developing improvement strategies based on data analysis
• Introduction to advanced approaches and techniques for supply chain analytics
• Analytics for descriptive, predictive, prescriptive, and cognitive purposes

Group Breakouts

• Detailed, hands-on analysis of supply chain databases
• Normalizing and data cleansing
• Aligning data processes with supply chain and organizational objectives

Value For You and Your Organization

What can big data do to help you make decisions? It can help you address a specific problem, inform of ways corporate initiatives can be impacted by supply chain management, or help you prioritize strategic initiatives based on a cost/benefit determination. Data analysis also lets you answer the question “What did I miss?;” thereby uncovering hidden gems within your systems that reveal competitive advantage or cost savings for your organization.