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1 - 10 of 14 results for: OIT ; Currently searching winter courses. You can expand your search to include all quarters

OIT 269: MSx: Operations and Strategies

Operations refer to the processes through which businesses produce and deliver products or services. Managing operations well is necessary in order for these processes to be completed in a timely manner, consume minimal resources and costs, and achieve their goal effectively. This course focuses on managerial issues arising in the operations of manufacturing and service industries. The objectives of the course are to introduce operational problems and challenges faced by managers, as well as language, conceptual models, analytical techniques and strategies that are broadly applicable in confronting such problems.
Units: 3 | Grading: GSB Letter Graded

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 276: Data and Decisions - Accelerated (Flipped Classroom)

Accelerated 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 more 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 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. The accelerated course is designed for students with strong quantitative backgrounds. Students taking this course need to be comfortable with mathematical notation, algebra, and basic probability. Students without quantitative backgrounds should consider enrolling in the base version of the course.
Units: 4 | Grading: GSB Letter Graded

OIT 333: 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 356: Electronic Business

The course focuses on the analysis and design of business models that are enabled by Information Technology (IT). It considers the impact of IT on multiple industries and ways to take advantage of new opportunities that are enabled by new technologies. Preparation includes case studies involving both qualitative and quantitative analyses; homework assignments involving quantitative and some qualitative analyses; pre-class online quizzes and a group project involving the design of a new business model that takes advantage of modern IT. A typical class will cover an aspect of a business model which is enabled by IT in an industry which is transformed by technology. Sample topics include the transformation of retail, media, electronic commerce logistics, transportation and healthcare. Some classes will focus on the interaction of strategy and IT, building on what you learned earlier in the program. Students opting to go into technology would probably benefit the most from the course, but this will require a significant time commitment. For students rooted in technology, some of the classes will reinforce and structure things they have experienced already, and others would introduce them to new applications. MSx students are invited to petition to take the course.
Units: 3 | Grading: GSB Letter Graded

OIT 367: Business Intelligence from Big Data

The objective of this course is to analyze real-world situations where significant competitive advantage can be obtained through large-scale data analysis, with special attention to what can be done with the data and where the potential pitfalls lie. Students will be challenged to develop business-relevant questions and then solve for them by manipulating large data sets. Problems from advertising, eCommerce, finance, healthcare, marketing, and revenue management are presented. Students learn to apply software (such as R and SQL) to data sets to create knowledge that will inform decisions. The course covers fundamentals of statistical modeling, machine learning, and data-driven decision making. Students are expected to layer these topics over an existing facility with mathematical notation, algebra, calculus, probability, and basic statistics.
Units: 3 | Grading: GSB Letter Graded
Instructors: Bayati, M. (PI)

OIT 368: Innovation Strategy and Operations

In this course, we will take an operations view of innovation. The course relies on three principles, 1) innovation requires strong processes that can both guide the development and execution of a firm's innovation strategy; 2) strong processes can guide innovation through the evolutionary stages of a company: growth, scale, change, and stable; and 3) strong processes are ambidextrous - they can generate both incremental and disruptive innovations, and the talented operations leader can guide the processes by adapting their area of focus. The perspective in the course will be that of a very senior Operations Manager such as the Chief Operations Officer and students will be expected to develop and test innovation strategies using a combination of qualitative and quantitative approaches. Specific Topics: Lean mindset as a framework for innovation process, Lean processes, Design thinking and Lean startups. Formulating an innovation strategy with an eye towards execution and implementation more »
In this course, we will take an operations view of innovation. The course relies on three principles, 1) innovation requires strong processes that can both guide the development and execution of a firm's innovation strategy; 2) strong processes can guide innovation through the evolutionary stages of a company: growth, scale, change, and stable; and 3) strong processes are ambidextrous - they can generate both incremental and disruptive innovations, and the talented operations leader can guide the processes by adapting their area of focus. The perspective in the course will be that of a very senior Operations Manager such as the Chief Operations Officer and students will be expected to develop and test innovation strategies using a combination of qualitative and quantitative approaches. Specific Topics: Lean mindset as a framework for innovation process, Lean processes, Design thinking and Lean startups. Formulating an innovation strategy with an eye towards execution and implementation, Leveraging the value chain eco-system to accelerate and support innovations, Developing operation processes for scaling innovations, and Design of business model to create values from innovations. The course will utilize a series of workshops on lean and design thinking to learn the underlying innovation processes, and case studies and projects to apply the concepts. Case studies will involve a multi session deep dive into specific industries and issues in a variety of industries and sectors. For example we will explore Boeing's innovation strategy and processes through the development and launch of the Boeing 787, design sprints to test different value chain innovations for the production and assembly of the 787, how the potential development of battery powered airplanes may disrupt Boeing's business model, take a deep dive into 3d printing and investigate how this technology can disrupt different industry verticals, and we will consider Crocs on how they adapt their value chain processes to support the growth of their initial innovation, as well as how that can then be leveraged for further innovations. A project leveraging design thinking and lean startup will focus on developing a specific disruption hypothesis for an established organization.
Units: 3 | Grading: GSB Student Option LTR/PF

OIT 384: Biodesign Innovation: Needs Finding and Concept Creation

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, coa more »
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 652: OIT Modeling

This course is designed for OIT students of all cohorts. It will focus on alternative approaches to modeling the types of problems that arise in OIT research, based on the analysis of papers in the area.
Units: 3 | Grading: GSB Letter Graded

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
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