Operations and Decision Technologies
Overview
The Operations & Decision Technologies program is designed to provide students with the foundations of management science and operations management. Examples of the disciplines studied include supply chain management, mathematical programming, decision analysis, network design and analysis, stochastic processes, queuing systems, inventory control systems, automated manufacturing systems, design and control of production systems, and quality management.
Course Descriptions
MBA Core Classes
Statistics for Management
Management Science
Operations Management
MBA Electives
Forecasting
Decision Analysis [ITM Course]
Supply Chain Management
Service Operations [ITM Course]
Project Management [ITM Course]
Advanced Topics in Operations Management
Field Studies in Operations Management
Advanced Operations Management
Process Management and Modeling
Misc. ODT
Analytical Decisionmaking Models for Management
Quality Management
Operations Lab
Faculty
Visiting & Affiliated Faculty and Researchers
- John Chen
- Tathagata Dasgupta
- Zvi Drezner
- Thomas Eppel
- Howard Frantz
- Jeff Guyse
- Soheila Jorjani
- Hamid Pourmohammadi
201A Statistics for Management
Methods of statistical inference emphasizing applications to administrative and management decision problems. Topics include classical estimation and hypotheses testing, regression, correlation, analysis of variance, nonparametric methods and statistical probability.
201B Management Science
An introduction to computer-based models for decision-making. Topics include optimization (linear programming, integer programming, network flow models) and computer simulation. The course uses spreadsheets extensively, including Excel built-in and add-in packages. Prerequisite: Basic course in calculus and algebra recommended; 201A recommended.
208 Operations Management
Introduction to strategic and tactical issues in production and operations management. A blend of quantitative and qualitative considerations. Topics: product planning, process design, capacity management, production planning, inventory control, distribution management, just-in-time manufacturing, quality management.
280 Forecasting
Forecasting is in the main process of organizing information about a phenomenon’s past in order to predict a future. As such, forecasts are critical inputs into the wide range of business decision making. Users include accountants, financial experts, human resource managers, production managers, and marketing people. Forecasting is a blend of science and art. In this course, we focus on the science associated with forecasting by studying various methodologies that are increasingly being used to support business decision making. In order to facilitate the use of these methodologies that often require very extensive computation, a computer oriented approach will be followed.
work of decision analysis is very general, you can use it for both professional and personal decision situations.
285 Supply Chain Management
Matching supply with demand is a primary challenge for a firm: excess supply is too costly, inadequate supply irritates customers. Matching supply to demand is easiest when a firm has a flexible supply process, but flexibility is generally expensive. In this course, we will discuss how to assess the appropriate level of supply flexibility for a Global organization and explore strategies for economically increasing a company’s supply flexibility based on worldwide supply strategy, including outsourced manufacturing, supplies, resources, and the vast mesh of complex distribution network that all of the above are spread around. We will study coordination and incentives across multiple groups or players in a supply chain. While tactical models and decisions are part of this course, the emphasis is on the qualitative insights needed by general managers or management consultants. We will demonstrate that companies can use (and have used) the principles from this course to significantly enhance their competitiveness. The course applies best industry practices as well as academic research on Global Supply Chains to current industry problems, and allows students to test their learning through some simulation exercises where all the management techniques, tools, methodologies, and core insights are applied.
287 Project Management [ITM Course]
This course will cover both the qualitative and quantitative aspects of project management. Topics include how to evaluate and select projects, how to staff project organizations, planning, budgeting, scheduling, and resource allocations, and how to terminate and evaluate projects. The course will use a PC-based project manager for reporting and will emphasize management applications.
288 Advanced Topics in Operations Management
Delves more deeply into topics that are currently influencing advances in practice of operations management in both manufacturing and services industries. Topics include modeling and analysis of manufacturing systems, yield management, and workforce scheduling. Appropriate applications in Southern California included. Prerequisite: consent of instructor.
289 Field Studies in Operations Management
Participation in a small group project sponsored by local companies in Southern California. Involves the applications of various concepts taught in operations management and related areas to address real issues faced by the sponsoring companies. NOTE: Enrollment must be approved by instructor (resumes/projects will be matched).
290 Advanced Operations Management
This course builds on an introductory course in Operations Research/Operations Management by delving more deeply into issues of major current interest. The emphasis will be on contemporary practice in manufacturing and service industry and the new approaches that are revolutionizing the management of operations.
290 Process Management and Modeling
This course emphasizes the importance of effective operational planning in business process management. The course also covers the methods by which firms can improve their operational performance through effective business processes design. Students will use process management software to model business processes to understand the effect of various process designs.
290 Analytical Decisionmaking Models for Management
This course introduces a number of quantitative models that are commonly used in decision support systems for managerial decision making. The emphasis of this course is on the applications of these quantitative models to business problems arising in diverse industries and functional areas including operations, finance, and marketing. The course is designed to develop your skills in formulating complex business problems as quantitative decision models and solving these models using Excel spreadsheets. Solutions to these decision models would provide useful managerial insights for the underlying business problems. Topics in this course include linear programming, integer programming, and computer simulation. Linear and integer programming models are widely used to analyze various business problems including product line planning, distribution networks, staff scheduling, and financial portfolios. Simulation models are commonly used to mimic the behavior of a system with uncertainty, and students will learn to build simulation models using the Excel add-in tool, Crystal Ball.
290 Quality Management
Successful quality management touches every aspect of the corporation from the mission statement to each employee. The course begins with an introduction to quality as it pertains to the corporation and the approach of modern quality management to its implementation in the corporation. Student project teams study quality as it is implemented in different parts of the organization. The Six Sigma approach to achieving quality in the design, management and control of the production/service processes is studied. Readings, cases and lectures are used.
295D Operations Lab
This course is designed to complement the concepts covered in the core Operations Management class on process modeling and analysis. Students in this lab will learn the basic skills of modeling and analyzing business processes using a commercial process modeling software. Through the applications of business cases and term project, the students will gain hands-on experience in building computer simulation models for decision making and improving the performance of the underlying business processes.
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