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21 - 30 of 40 results for: OIT

OIT 256: Electronic Business (Accelerated)

This course focuses on the intersection of strategy and information technology. It considers how you can take advantage of new technology opportunities and how they change the structure of firms, industries and value chains, with an emphasis on business issues. Classes combine lecture and case study discussions and the workload is above the GSB average.

OIT 258: Incentive Mechanisms for Societal Networks

In many of the challenges faced by the modern world, from overcrowded road networks to overstretched healthcare systems, large benefits for society come about from small changes by very many individuals. This course survey the problems and the cost they impose on society. It describes a series of pilot projects which aim to develop principles for inducing small changes in behavior in Societal Networks--transportation networks, wellness programs, recycling systems and, if time permits, energy grids. Students will learn how low-cost sensing and networking technology can be used for sensing individual behavior, and how incentives and social norming can be used to influence the behavior. The effectiveness of this approach in pilots conducted in Bangalore (commuting), Singapore (public transit system), Stanford (congestion and parking), and a wellness program at Accenture-USA will be discussed. Students may experience the incentive platform as participants.

OIT 267: Data and Decisions - Accelerated

Data and Decisions - Accelerated is a first-year MBA course in probability, statistics, multiple regression analysis, and decision trees for students with strong quantitative backgrounds. Probability provides the foundation for modeling uncertainties. Statistics provides techniques for interpreting data, permitting managers to use small amounts of information to answer larger questions. Regression analysis provides a method for determining the relationship between a dependent variable and predictor variables. Decision tree analysis consists of quantitative approaches to decision making under uncertainty. Students taking this course need to be comfortable with mathematical notation, algebra, and some calculus. If you are not confident with your quantitative abilities, then you should enroll in OIT 265. Accelerated D&D will cover material covered in OIT 265 faster and in more depth. One main difference is that Accelerated D&D will cover the additional topics of advanced multiple regression analysis (e.g., correction for autocorrelation), discrete dependent variable models, and panel data. A multiple regression group project is required.

OIT 268: Making Data Relevant

Data is everywhere. Firms collect it. Data on customers' preferences are collected through websites or loyalty programs or cash registers. Data on employees' traits are collected through in-house databanks or social networking sites. All of us are used to thinking about data. How can you make data relevant to doing your job? How can data analysis serve to increase your competitive advantage over that of others? This class goes beyond graphing data in bar charts or time trends. It makes you think about causal relationships. The examples we use are primarily taken from talent management, because it's easy to think about our own careers or those of our employees. But the tools covered extend to all contexts, and your project is on an idea of your choosing. The class focuses on the use of regressions to think experimentally. To take the class, you should have covered regression analysis in a former class (such as an econometrics course for economics majors) or be comfortable with learning basic math concepts quickly. You also should understand distributions of data (such as the Bell curve, or normal distribution), but this topic is not covered. There are no required proofs or derivations; you've done that as undergraduates. This is about using data: we use cases, examples, Notes written for the class, and a quiz, final exam, and several assignments in which you play with data sets to answer questions. Note that this 4-unit course, if successfully completed, counts for the Data Analysis foundations requirement.
Instructors: Shaw, K. (PI)

OIT 269: Sloan: 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.

OIT 343: D-Lab: Design for Service Innovation

Students in multidisciplinary teams work with a partner organization to design new services that address the needs of an underserved population of users. Teams identify an unmet customer needs, develop and prototype new service designs (e.g. web services, services with a product component, educational campaigns), test these services with real customers and develop an implementation plan. Fundraising strategies are also explored and tested. We will offer two sections: financial services (MW: 1:15 pm - 3:00 pm); health services (MW: 4:15 pm - 6:00 pm). The specific domains for the two sections will be announced in the fall based on the needs of partner organizations. Possible domains for financial services: financial literacy for young adults, planning for major expenses at retirement, financial services for the underserved. For health services: transition to adulthood of pediatric patients with chronic conditions, transitions to nursing care for elderly patients. See http://designforservice.stanford.edu/.

OIT 356: Electronic Business

This course focuses on the intersection of strategy and information technology. It considers how you can take advantage of new technology opportunities and how they change the structure of firms, industries and value chains, with an emphasis on business issues. Case studies include Salesforce.com, Apple, Google, Netflix, Linden Lab (Second Life), Amazon (The Kindle), Zappos and PayPal. Classes combine lecture and case study discussions and the workload is above the GSB average.

OIT 542: Price and Revenue Optimization

This is the Advanced Application option in the menu of courses that satisfy the Management Foundations requirement in Optimization and Simulation Modeling(OSM). Three core modeling topics are covered in rapid-review fashion - model representation in a spreadsheet environment, optimization theory, and stochastic models - but primary emphasis is on the application domain described immediately below. OIT 542 is a two-unit course, with nine class sessions plus a final exam. nnnSystems for price and revenue optimization - also called yield management, dynamic pricing, or revenue management - combine the use of information technology, statistical forecasting, and mathematical optimization to make tactical decisions about pricing and product availability. A familiar example is the passenger airline industry, where a carrier may sell seats on the same flight at many different fares, with fare availability changing as time advances and uncommitted capacity declines. Over the last 30-35 years, revenue optimization practices have transformed the transportation and hospitality industries, where fixed capacity and advance reservations by customers are important structural factors. But model-based, data-driven pricing systems are increasingly common in other industries that have different structures, such as financial services and retail clothing.nnnIn this course students learn about the model structures and modelling techniques that underlie systems for price and revenue optimization. Two topics are given roughly equal emphasis: model-based tactical pricing, including customized pricing and retail markdown management; and classical revenue management, where automated logic is used for booking control (that is, to make yes-or-no decisions in response to booking requests from customers), rather than to set prices explicitly.nnnOIT 542 is tailored to students who already have command of basic modelling techniques and wish to learn about their application in an important business context. To be specific, a prior college course on optimization modelling is assumed as background. (Typically, such courses focus on linear programming, or linear optimization, with secondary coverage of non-linear programming and discrete optimization.) Various aspects of optimization theory will be covered in quick-review format, along with the basics of spreadsheet model representation and stochastic modelling, in order to standardize terminology and establish certain conventions that facilitate grading. In exceptional cases, for students who have strong math background and high mathematical aptitude but no prior coursework on optimization, the background knowledge assumed in OIT 542 may be acquired through self-study; appropriate study materials will be suggested by the instructor upon request. The course is entirely appropriate for second-year MBA students who have completed either base or accelerated MODS in their first year.nnnOIT 542 draws on knowledge acquired and skills developed in two other Management Foundations courses that are taken simultaneously: Data and Decisions ( OIT 265) and Microeconomics ( MGTECON 200 or 203). Students are required to construct and analyze at least one model for every class session.

OIT 562: Supply Chain Management & Technology

Supply chain management (SCM) deals with the management of materials, information and financial flows in a network consisting of suppliers, manufacturers, distributors, retailers and customers. The coordination and integration of these flows within and across companies are critical in effective supply chain management. In this course, we introduce key concepts and new developments in information technologies (IT) for use in SCM. In particular, the advances of information technologies such as enterprise systems, the Internet, collaborative network, operational analytics and wireless technologies have a profound impact on how supply chains are structured and run. You are all challenged to think, discuss, share, and debate on the issues brought up.
Instructors: Whang, S. (PI)

OIT 565: The Role of Information Technology in the New Energy Economy

One of the most interesting and underexplored areas in modern technology is, as Dan Reicher at Stanford has put it, "where energy technology (ET) meets information technology (IT)". The main driver of widespread use of computing in the modern age is the rapid reduction in the cost of computing services caused by Moore's law. At the same time, a substantial increase in the energy efficiency of computing (doubling every year and a half for more than six decades) has led to a proliferation of mobile computers, sensors, and controls, with implications that have only recently begun to be understood.nnnThis class will explore the direct and indirect implications of applying information technology to the production, delivery, and use of energy and associated services. It will first review current knowledge about the direct energy use associated with information technology, including data centers, personal computers, cellular telephones, mobile sensors, and other IT equipment. It will also summarize the state of knowledge about the types, amount, and growth rates of energy services delivered in the US and globally. Finally, it will explore the applications to which information technologies have been put in the energy industry, ranging from the use of visualization and analysis techniques to improve the results of oil and gas exploration, to the computer-aided design of wind turbines and automobiles, to the implications of wireless sensors and controls for the more efficient and effective use of energy. The class will culminate in student projects, typically business plans for new ventures using IT to radically transform how we understand and respond to the world around us.
Instructors: Koomey, J. (PI)
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