Print Settings
 

OIT 262: Operations

This course focuses on basic managerial issues arising in the operations of both manufacturing and service industries. The objectives of the course are to familiarize students with the problems and issues confronting operations managers and to introduce language, conceptual models, and analytical techniques that are broadly applicable in confronting such problems. The spectrum of different process types used to provide goods and services is developed and then examined through methods of process analysis and design.
Units: 3 | Grading: GSB Letter Graded
Instructors: ; Plambeck, E. (PI)

OIT 271: Operations - Accelerated

This course, which is an accelerated version of OIT 262 (Operations), focuses on basic managerial issues arising in the operations of both manufacturing and service industries, and on strategic issues arising in global supply chains. The objectives of the course are to familiarize students with the problems and issues confronting operations managers and to introduce language, conceptual models, and analytical techniques that are broadly applicable in confronting such problems.
Units: 3 | Grading: GSB Letter Graded
Instructors: ; Wein, L. (PI)

OIT 272: Online Marketplaces

How does Uber match drivers to passengers? How does Airbnb select the set of listings to show to a guest in a search? How does eBay manage trust and reputation between buyers and sellers? How does Google optimize auctions for billions of dollars' worth of online advertising? This course focuses on the basic analytic and data science tools used to address these and other challenges encountered in the most exciting online marketplaces in the world. With hands-on exercises we will open and understand the "black-box" of online marketplaces' operations. We will cover application areas such as transportation, rentals, sharing, e-commerce, labor markets, and advertising, leveraging tools from D&D, OSM, and Micro (all base). In particular, the course will use tools from R covered in D&D. Overall, the course will provide basic business knowledge for future investors, product managers, sales and marketing managers, operation managers, and anyone interested on online marketplaces.
Units: 2 | Grading: GSB Letter Graded
Instructors: ; Weintraub, G. (PI)

OIT 274: Data and Decisions - Base (Flipped Classroom)

Base Data and Decisions is a first-year MBA course in statistics and regression analysis. The course is taught using a flipped classroom model that combines extensive online materials with a lab-based classroom approach. Traditional lecture content will be learned through online videos, simulations, and exercises, while time spent in the classroom will be discussions, problem solving, or computer lab sessions. Content covered includes basic probability, sampling techniques, hypothesis testing, t-tests, linear regression, and prediction models. The group regression project is a key component of the course, and all students will learn the statistical software package R.
Units: 4 | Grading: GSB Letter Graded

OIT 275: Online Marketplaces, Accelerated

How does Uber match drivers to passengers? How does Airbnb select the set of listings to show to a guest in a search? How does eBay manage trust and reputation between buyers and sellers? How does Google optimize auctions for billions of dollars' worth of online advertising? This course focuses on analytics and data science tools used to address these and other challenges encountered in the most exciting online marketplaces in the world. With hands-on exercises we will open and understand the "black-box" of online marketplaces' operations. We will cover application areas such as transportation, rentals, sharing, e-commerce, labor markets, and advertising, leveraging tools from D&D, OSM, and Micro. In particular, the course will use tools from R covered in D&D. Overall, the course will provide business knowledge for future investors, product managers, sales and marketing managers, operation managers, and anyone interested on online marketplaces. [This is the accelerated version of OIT 272 and knowledge from D&D and OSM is expected at the accelerated (or advanced) level.]
Units: 2 | Grading: GSB Letter Graded
Instructors: ; Weintraub, G. (PI)

OIT 334: Design for Extreme Affordability

Design for Extreme Affordability is a two-quarter project-based course hosted by Stanford's d.school and jointly offered by the Graduate School of Business and the School of Mechanical Engineering. We focus on the development of products and services to improve the lives of the world's poorest citizens. This multidisciplinary project-based experience creates an enabling environment in which students learn to design products and services that will change lives. Topics include user empathy, product and service design, rapid prototype engineering and testing, social entrepreneurship, business modeling, ethics, partnerships, team dynamics and project management. Since the course was first offered, we have executed 140 projects with 57 partners in 31 emerging and developing economies around the world. Many of the projects have been implemented and are achieving significant social impact. Students have worked on Agricultural, Medical, Water, Sanitation, Energy, Lighting, Nutrition and Education based projects. For further information go to extreme.stanford.edu
Units: 4 | Grading: GSB Letter Graded

OIT 364: Global Operations

Globalization of businesses has resulted in companies having to manage global networks of suppliers, integrators, contract manufacturers, logistics service providers, distributors, and service support operators in geographically dispersed locations. The customer network is also globally distributed. This course will focus on (1) how global and international companies can overcome the geographical, cultural, and organizational barriers, and leverage the strengths of the network to create values, (2) how these companies should best structure their network, like in-sourcing or outsourcing, and off-shoring or on-shoring, to give the best competitive advantage, and (3) how operations can support the overall business strategies.. The course will be based on cases on innovative strategies and tactics used by global and international companies, including how they can do so in emerging economies.
Units: 3 | Grading: GSB Letter Graded
Instructors: ; Lee, H. (PI)

OIT 385: Biodesign Innovation: Concept Development and Implementation

In this two-quarter course series (OIT 384/5), multidisciplinary student teams from medicine, business, and engineering work together to identify real-world unmet healthcare needs, invent new health technologies to address them, and plan for their development and implementation into patient care. During the first quarter (winter 2019), students select and characterize an important unmet healthcare problem, validate it through primary interviews and secondary research, and then brainstorm and screen initial technology-based solutions. In the second quarter (spring 2019), teams screen their ideas, select a lead solution, and move it toward the market through prototyping, technical re-risking, strategies to address healthcare-specific requirements (regulation, reimbursement), and business planning. Final presentations in winter and spring are made to a panel of prominent health technology industry experts and investors. Class sessions include faculty-led instruction and case studies, coaching sessions by industry specialists, expert guest lecturers, and interactive team meetings. Enrollment is by application only, and students are expected to participate in both quarters of the course. Visit http://biodesign.stanford.edu/programs/stanford-courses/biodesign-innovation.html to access the application, examples of past projects, and student testimonials. More information about Stanford Biodesign, which has led to the creation of more than 40 venture-backed healthcare companies and has helped hundreds of students launch health technology careers, can be found at http://biodesign.stanford.edu/.
Units: 4 | Grading: GSB Student Option LTR/PF

OIT 521: Data Science for Platforms

This is an MBA compressed course that covers analytic and data science tools that are currently being used to operate some of the most exciting online platforms and marketplaces in the world. This course will consist of guest lectures from industry leaders involved in these efforts, emphasizing practical challenges associated with implementing analytics and data science projects. We will cover online platforms and marketplaces in diverse application areas such as transportation, rentals, sharing, e-commerce, labor markets, media, and advertising.
Units: 2 | Grading: GSB Letter Graded

OIT 604: Data, Learning, and Decision-Making

This aim of this course is to cover modern tools for data-driven decision making. Most decision making tasks involve uncertainty that is directly impacted by the amount and complexity of data at hand. Classical decision models rely on strong distributional assumptions about the uncertain events. But in recent years, and due to growing availability of rich data, there has been a rapid adoption of models from machine learning and statistics that provide more accurate and personalized picture of uncertainty which in turn lead to better decisions. The interplay between the multiple objectives of modeling the data, personalization, and decision optimization has created a number mathematical models that the course aims to cover. Examples of topics include graphical models and message-passing algorithms, high-dimensional and tensor models, and multi-armed bandits.
Units: 3 | Grading: GSB Student Option LTR/PF
Instructors: ; Bayati, M. (PI)

OIT 691: PhD Directed Reading (ACCT 691, FINANCE 691, GSBGEN 691, HRMGT 691, MGTECON 691, MKTG 691, OB 691, POLECON 691, STRAMGT 691)

This course is offered for students requiring specialized training in an area not covered by existing courses. To register, a student must obtain permission from the faculty member who is willing to supervise the reading.
Units: 1-15 | Repeatable for credit | Grading: GSB Pass/Fail

OIT 692: PhD Dissertation Research (ACCT 692, FINANCE 692, GSBGEN 692, HRMGT 692, MGTECON 692, MKTG 692, OB 692, POLECON 692, STRAMGT 692)

This course is elected as soon as a student is ready to begin research for the dissertation, usually shortly after admission to candidacy. To register, a student must obtain permission from the faculty member who is willing to supervise the research.
Units: 1-15 | Repeatable for credit | Grading: GSB Pass/Fail

OIT 698: Doctoral Practicum in Teaching

Doctoral Practicum in Teaching
Units: 1 | Repeatable for credit | Grading: GSB Letter Graded

OIT 699: Doctoral Practicum in Research

Doctoral Practicum in Research
Units: 1 | Repeatable for credit | Grading: GSB Letter Graded

OIT 802: TGR Dissertation (ACCT 802, FINANCE 802, GSBGEN 802, HRMGT 802, MGTECON 802, MKTG 802, OB 802, POLECON 802, STRAMGT 802)

Units: 0 | Repeatable for credit | Grading: GSB Pass/Fail
© Stanford University | Terms of Use | Copyright Complaints