Natalia Santamaría teaches classes in project management and operations management for non-business graduate students. Her research, which focuses on competitive bidding and decision making under competition and uncertainty, has been published in Management Science, Manufacturing & Service Operations Management, and Production and Operations Management. Prior to joining Johnson in 2014, she was an assistant professor in the industrial engineering school at Universidad de Los Andes in Colombia. She earned a BS and an MSc in industrial engineering from Universidad de Los Andes, an MSc in operations research from Rutgers University, and a Ph.D. in supply chain management and operations research from the Pennsylvania State University.
Course Overview
An organization's service operations encompass all of the processes and systems through which the organization provides care and service to its customers, whether it's human contact, automated systems, or virtually. Ensuring that service operations are optimized for effectiveness and efficiency as well as positive customer experiences is the goal of service operations management. Since the level of demand in these systems is often variable, analysis and improvement can be challenging.
In this course, you will review the probability and statistics concepts necessary to analyze a service process where the level of demand is variable and explore how that variability affects the efficiency of systems. You will practice using tools of queue analysis, including the Lq approximation and Little's Law, to analyze service operations, and you will investigate ways to reduce variability in service processes. Finally, you will analyze a specific service process and recommend improvements to reduce processing and wait times.
This course requires the use of Microsoft Excel (desktop or online). While advanced skills aren't necessary, students should be familiar with formatting cells, using simple functions and formulas, and creating basic charts.
The following course is required to be completed before taking this course:
- Process Analysis in Operations
Key Course Takeaways
- Determine the steady state for a service process or system
- Use queueing theory to analyze a service process whose levels of demand are variable
- Recommend strategies to improve a service process
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Course Length
2 weeks
Effort
5 to 7 hours of study per week
Format
100% online, instructor-led
Course Author
Natalia Santamaría
Visiting Senior Lecturer
Cornell SC Johnson College of Business
Visiting Senior Lecturer of Operations Management
Who Should Enroll
- Managers and executives
- Manufacturers
- Business analysts
- MBA students
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