OM - Operations Management

A problem-solving course which introduces the student to deterministic and stochastic models which are useful for production planning and operations management in business and government. Note: Students are expected to have basic familiarity with microcomputer applications. Prerequisite: MATH 154 or equivalent and STAT 161 or equivalent. Students may not receive credit for both OM 252 and OM 352.

The course focuses on the strategic role of the supply chain, key drivers of supply chain performance, and analytical methods for supply chain analysis. Possible topics include inventory planning and management, sourcing, transporting, and pricing products, supply chain network design, and coordination and value of information in a supply chain. Prerequisites: MGTSC 312 and OM 352.

Business use processes to produce and deliver goods and services to customers. This course is about the conceptual and quantitative analysis of those business processes. The emphasis is on strategic and tactical decision making about operations so as to create competitive advantage for the organization. Possible topics include process mapping, process flow analysis, inventory, and quality. The topics will be illustrated through discussion and analysis of several case studies. The topics and techniques selected for this course are applicable to a wide variety of industries. Prerequisites: MGTSC 312.

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 352 or OM 352.

Visual displays of quantitative information include charts, tables, maps, dashboards, animations, and more. Such displays can be used to understand, to inform, and to convince. This course will focus on strategies for carefully and clearly communicating analytical findings to the people who need to take action based on them. We will learn to use both basic tools (MS Excel) and advanced tools (Tableau and R) to create visual displays. Evaluation components will include assignments, presentations, and exams (midterm and final exam). Prerequisites: MGTSC 312.

Computer modelling of management systems in such functional areas as accounting, finance, marketing and operations. Basic concepts of deterministic and probabilistic (Monte Carlo) simulation and their applications. Microcomputer implementation of case studies using spreadsheets particularly emphasized. Required term project. Prerequisites: MGTSC 312 (or equivalent STAT course), MGTSC 352 or OM 352; and FIN 301 or ACCTG 311. Not to be taken by students with credit in MGTSC 422.

Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions. Evaluation components will consist of assignments, case studies, group projects, and two midterm exams. Prerequisites: OM 252 or 352

Prescriptive analytics modeling of efficient distribution of goods and services from points of origin to customers. Topics include strategic decisions, such as aggregate distribution plans and warehouse location, as well as operational decisions, such as selection of delivery routes and dispatching. Formulation and solution of models to prescribe optimal decisions using exact and heuristic methods. This course involves extensive computer modeling and heuristic design. Prerequisite: MGTSC 312 and OM 352.

This course applies the techniques developed in MGTSC 312, OM 352, and business analytics courses to a group project. The emphasis in the projects is on quantitative approaches to business problems. Student groups will be assigned to consulting projects from businesses and other organizations. Groups will work on their projects under the supervision of the instructor(s). Prerequisites: MGTSC 312 (or equivalent) and OM 352. Restricted to fourth year students.

The course focuses on the creation of decision support systems using Microsoft Excel-based spreadsheet models and the associated macro programming language, Visual Basic for Applications (VBA). Students will learn how to create Excel-based applications to aid managers in making decisions based on data and analytics. These applications will have graphical user interfaces, appropriate models in the spreadsheet or in the background, and output reports. Fundamentals of VBA, such as the Excel object model, variables, control logic and loops, subroutines and function subroutines, and user forms will be introduced. Prior programming experience is not assumed. Student projects in this implementation-oriented course will come from different areas such as forecasting, regression, supply chain network design, employee scheduling, and portfolio optimization. Prerequisites: MGTSC 312, MGTSC 352 or OM 352.

Preparation of the honors essay required for students in the Operations Management Honors program. Prerequisite: consent of the Department.

Normally restricted to third- and fourth-year Business students. Prerequisites will depend on topic but may include: MGTSC 312, OM 352 or consent of Department. Additional prerequisites may be required.

Special Study for advanced undergraduates. Prerequisites: consent of the Instructor and Associate Dean, Undergraduate Program.

This course focuses on (1) the competitive advantage that a business unit can derive from innovative and efficient production and delivery of its goods and services and on (2) analytical approaches that are useful in understanding and improving an organization's operations. Specific modules include process diagramming and analysis; measuring and managing flow times; inventory control and optimization; supply chain coordination and operations strategy. Cases will be used to illustrate operational efficiency and its significance to the profitability of a firm. Prerequisite: MGTSC 501. Not to be taken by students with credit in MGTSC 502.

This course is a blend of both experiential learning and theory with the objective of making the student more effective in all types of bargaining. A study of positive theories on how to improve negotiation skills will be combined with analytical models of the game theoretic structure of bargaining. Through this mix of theories and several case studies and bargaining exercises, students will see both the opportunities for joint gain (win-win) and the constraints which can lead to inferior outcomes. Sections offered at an increased rate of fee assessment; refer to the Tuition and Fees page in the University Regulations sections of the Calendar. Prerequisites: First year MBA core courses. Not to be taken by students with credit in MGTSC 604.

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 501.

Visual displays of quantitative information include charts, tables, maps, dashboards, animations, and more. Such displays can be used to understand, to inform, and to convince. This course will focus on strategies for carefully and clearly communicating analytical findings to the people who need to take action based on them. We will learn to use both basic tools (such as MS Excel) and advanced tools (such as Tableau and R) to create visual displays. Evaluation components will include assignments, presentations, and exams. Prerequisites: MGTSC 501.

This course will discuss computer modelling of management systems in such functional areas as accounting, finance, marketing, and production. Basic concepts of deterministic and probabilistic (Monte Carlo) simulation and their applications will also be covered. Micro computer implementations of case studies using spreadsheets will be particularly emphasized. A term project will be required. Prerequisite: MGTSC 502 or OM 502. Not to be taken by students with credit in MGTSC 632.

Prescriptive analytics involves the use of data, mathematical models, and algorithms to identify optimal solutions for achieving organizational goals. This process builds on descriptive and predictive analytics, going beyond the interpretation of past events and the forecasting of future scenarios to also provide advice on the most effective actions to meet business objectives. Students acquire the skills to convert complex business problems into mathematical models, and employ Python programming and commercial solvers to derive optimal decisions. Evaluation components will consist of assignments, case studies, group projects, and two midterm exams. Prerequisites: OM 502.

Examines project management including investigation and analysis, scope definition, resource analysis and estimation, timing estimation, cost estimation, scheduling, monitoring, and implementation.

Prescriptive analytics modeling of efficient distribution of goods and services from points of origin to customers. Topics include strategic decisions, such as aggregate distribution plans and warehouse location, as well as operational decisions, such as selection of delivery routes and dispatching. Formulation and solution of models to prescribe optimal decisions using exact and heuristic methods. The course involves extensive computer modeling and heuristic design. Prerequisite: MGTSC 501.

The course focuses on the creation of decision support systems using Microsoft Excel-based spreadsheet models and the associated macro programming language, Visual Basic for Applications (VBA). Students will learn how to create Excel-based applications to aid managers in making decisions based on data and analytics. These applications will have graphical user interfaces, appropriate models in the spreadsheet or in the background, and output reports. Fundamentals of VBA, such as the Excel object model, variables, control logic and loops, subroutines and function subroutines, and user forms will be introduced. Prior programming experience is not assumed. Student projects in this implementation-oriented course will come from different areas such as forecasting, regression, supply chain network design, employee scheduling, and portfolio optimization. Prerequisite: MGTSC 501.

Topics may vary from year to year. Students should check with the MBA Office for pre/corequisites of specific sections.

This course provides a general introduction to the major research fields of operations management (OM). The focus will be on reading and evaluating current papers from prominent OM journals. The theory of science and the review process will be briefly discussed. Students are expected to have as mathematical background the equivalent of an upper-level undergraduate or first-year graduate courses in optimization and probability or stochastic modeling. This course may be appropriate for some graduate students in engineering or computing science. Prerequisite: A graduate or undergraduate course in operations management. Open to all doctoral students or with the written permission of the instructor. Approval of the Business PhD Program Director is also required for non-PhD students.

This course will provide an in-depth introduction to a particular methodology or a particular setting that is relevant to research in operations management. The topic may vary from year to year. Possible topics include optimization modeling and formulation, stochastic modeling and optimization, behavioural research in operations management, and health care operations management. The required background for students will vary depending on the topic. This course may be appropriate for some graduate students in engineering or computing science. Prerequisite: Written permission of the instructor. Approval of the Business PhD Program Director is also required for non-PhD students.

This course is a blend of both experiential learning and theory with the objective of making the student more effective in all types of bargaining. A study of positive theories on how to improve negotiation skills will be combined with analytical models of the game theoretic structure of bargaining. Through this mix of theories and several case studies and bargaining exercises, students will see both the opportunities for joint gain (win-win) and the constraints which can lead to inferior outcomes. Restricted to students registered in the MBA China Program.

This course is a blend of both experiential learning and theory with the objective of making the student more effective in all types of bargaining. A study of positive theories on how to improve negotiation skills will be combined with analytical models of the game theoretic structure of bargaining. Through this mix of theories and several case studies and bargaining exercises, students will see both the opportunities for joint gain (win-win) and the constraints which can lead to inferior outcomes. Restricted to Executive MBA students only.

Understanding the strategic role of operations in an enterprise and the relationship between operations and other business functions; designing, implementing and controlling an effective and efficient operating process. Restricted to Executive MBA students only. Not to be taken by students with credit in MGTSC 830.