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O M X72T O M 372T  Topics in Operations Management  3 Hours

3 Lecture Hours  0 Lab Hours  
Three lecture hours a week for one semester.
Pre/Corequisites: Varies with the topic.  
Restrictions: Restricted to students in a business major.  
Grading: Student Option  
Repeatable for credit: May be repeated for credit when the topics vary.  
Academic Level: Upper Division  
Topic 1: Total Quality Management. Operations Management 337 (Topic 1) and 372T (Topic 1) may not both be counted. Additional prerequisite: For business majors, Operations Management 334M, 235, or 235H; for others, admission to an appropriate major sequence in engineering.

Topic 2: Sustainable Operations. Operations Management 337 (Topic: Sustainable Operations) and 372T (Topic 2) may not both be counted.

Topic 5: Project Management. Operations Management 337 (Topic 5) and 372T (Topic 5) may not both be counted. Additional prerequisite: Upper-division standing.

Topic 7: New Product Development. Examine the integration of supply chain management into the product design and development process. Learn skills and knowledge involving product development and incorporating supply chain considerations with an emphasis on designing products that optimize the supply chain while maintaining the products vision from concept to customer. Operations Management 337 (Topic 7) and 372T (Topic 7) may not both be counted. Additional prerequisite: Upper-division standing.

Topic 12: Information Technology for Supply Chains. Learn how information technology is used to coordinate supply chain activities across different industries. Only one of the following may be counted: Management Information Systems 373 (Topic 13), 372T (Topic 12), Operations Management 337 (Topic 4), 372T (Topic 12). Same as: MIS 372T.12 Additional prerequisite: Management Information Systems 301, 301H, or 302F.

Topic 17: Health Care Analytics. Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality. Only one of the following may be counted: Business Analytics 372 (Topic 17), 372T (Topic 17), Management Information Systems 373 (Topic 26), 372T (Topic 17) Operations Management 337 (Topic 8), 372T (Topic 17). Same as: BAX 372T.17, MIS 372T.17

Topic 20: Supply Chain Analytics. Study dynamic demand forecasting models based on both data aggregation as well as hierarchical aggregation of point-of-sale predictive analytics. Explore the use of developed predictive dynamic models for operations planning and operations decision maing. Only one of the following may be counted: Business Analytics 372 (Topic 16), 372T (Topic 20), Operations Management 337 (Topic 6), 372T (Topic 20). Same as: BAX 372T.20 Additional prerequisite: Credit or registration for Operations Management 334M, 235 or 235H.

Topic 21: Time Series Forecasting. Examine statistical forecasting methods used in business. Discuss Box-Jenkins models; exponential smoothing models; ARCH/GARCH models for varying volatility in financial returns; seasonal adjustment of time series; tests for nonstationary of time series; and modeling multiple time series. Only one of the following may be counted: Business Analytics 372 (Topic 21), 372T (Topic 21), Operations Management 372T (Topic: Time Series Forecasting), 372T (Topic 21), Statistics 372 (Topic 9), 372T (Topic 21). Same as: BAX 372T.21, STA 372T.21 Additional prerequisite: Statistics 235, 235H, Statistics and Data Sciences 358, Economics 341K, or other course with basic knowledge about regression.

Topic 24: Data-Driven Revenue Management. Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples. Only one of the following may be counted: Business Analytics 372T (Topic 24), Management Information Systems 372T (Topic 24), Operations Management 372T (Topic 24). Same as: BAX 372T.24, MIS 372T.24
  

O M X72T.1 O M 372T.1  Total Quality Management  3 Hours

3 Lecture Hours  0 Lab Hours  
Operations Management 337 (Topic 1) and 372T (Topic 1) may not both be counted.
Pre/Corequisites: For business majors, Operations Management 334M, 235, or 235H; for others, admission to an appropriate major sequence in engineering.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.2 O M 372T.2  Sustainable Operations  3 Hours

3 Lecture Hours  0 Lab Hours  
Operations Management 337 (Topic: Sustainable Operations) and 372T (Topic 2) may not both be counted.
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.5 O M 372T.5  Project Management  3 Hours

3 Lecture Hours  0 Lab Hours  
Operations Management 337 (Topic 5) and 372T (Topic 5) may not both be counted.
Pre/Corequisites: Upper-division standing.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.7 O M 372T.7  New Product Development  3 Hours

3 Lecture Hours  0 Lab Hours  
Examine the integration of supply chain management into the product design and development process. Learn skills and knowledge involving product development and incorporating supply chain considerations with an emphasis on designing products that optimize the supply chain while maintaining the products vision from concept to customer. Operations Management 337 (Topic 7) and 372T (Topic 7) may not both be counted.
Pre/Corequisites: Upper-division standing.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.12 O M 372T.12  Information Technology for Supply Chains  3 Hours

3 Lecture Hours  0 Lab Hours  
Learn how information technology is used to coordinate supply chain activities across different industries. Only one of the following may be counted: Management Information Systems 373 (Topic 13), 372T (Topic 12), Operations Management 337 (Topic 4), 372T (Topic 12).
Same as: MIS 372T.12  
Pre/Corequisites: Management Information Systems 301, 301H, or 302F.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.17 O M 372T.17  Health Care Analytics  3 Hours

3 Lecture Hours  0 Lab Hours  
Explore key management challenges and how data may be leveraged to guide decisions and improve operations, with the unifying theme of providing health care services in a manner that leads to lower cost and higher quality. Only one of the following may be counted: Business Analytics 372 (Topic 17), 372T (Topic 17), Management Information Systems 373 (Topic 26), 372T (Topic 17) Operations Management 337 (Topic 8), 372T (Topic 17).
Same as: BAX 372T.17, MIS 372T.17  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.20 O M 372T.20  Supply Chain Analytics  3 Hours

3 Lecture Hours  0 Lab Hours  
Study dynamic demand forecasting models based on both data aggregation as well as hierarchical aggregation of point-of-sale predictive analytics. Explore the use of developed predictive dynamic models for operations planning and operations decision maing. Only one of the following may be counted: Business Analytics 372 (Topic 16), 372T (Topic 20), Operations Management 337 (Topic 6), 372T (Topic 20).
Same as: BAX 372T.20  
Pre/Corequisites: Credit or registration for Operations Management 334M, 235 or 235H.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.24 O M 372T.24  Data-Driven Revenue Management  3 Hours

3 Lecture Hours  0 Lab Hours  
Use data-driven tactics and strategies to predict consumer demand and optimize price and capacity/inventory availability to maximize revenue or profit. Explore demand analytics and revenue management techniques, produce rigorous and practical insights, and develop data analysis and optimization skills, based on business cases, datasets, and exercises. Examine diverse contexts and industries, such as conventional retailing, e-commerce, airline/hotel, and contemporary platform and cloud services (e.g., Uber, Dropbox, Netflix, AWS), by utilizing software (Excel, R, or Python) to build models, conduct optimization, and develop insights for a variety of revenue management examples. Only one of the following may be counted: Business Analytics 372T (Topic 24), Management Information Systems 372T (Topic 24), Operations Management 372T (Topic 24).
Same as: BAX 372T.24, MIS 372T.24  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division  

O M X72T.21 O M 372T.21  Time Series Forecasting  3 Hours

3 Lecture Hours  0 Lab Hours  
Examine statistical forecasting methods used in business. Discuss Box-Jenkins models; exponential smoothing models; ARCH/GARCH models for varying volatility in financial returns; seasonal adjustment of time series; tests for nonstationary of time series; and modeling multiple time series. Only one of the following may be counted: Business Analytics 372 (Topic 21), 372T (Topic 21), Operations Management 372T (Topic: Time Series Forecasting), 372T (Topic 21), Statistics 372 (Topic 9), 372T (Topic 21).
Same as: BAX 372T.21, STA 372T.21  
Pre/Corequisites: Statistics 235, 235H, Statistics and Data Sciences 358, Economics 341K, or other course with basic knowledge about regression.  
Grading: Student Option  
Repeatable for credit: No  
Academic Level: Upper Division