Decision Support with Spreadsheets --- Spreadsheets have advanced to the point of providing powerful, general-purpose functionality and are among the most widely used decision-support tools in business today. This course deals with decision support using spreadsheets, including: what if analysis; financial, statistical and time/date functions; graphical presentation of data; organizing, sorting, querying and extracting information from spreadsheet and external databases and the World Wide Web; cross-tabulation of data; data tables; creation and management of scenarios; use of a solver to find optimal solutions to problems; the design to macros to support spreadsheet applications; and data maps. An expert level of spreadsheet use is achieved. Lecture-demonstrations illustrate relevant features of spreadsheet software. Students do assigned cases on a computer to reinforce and extend conceptual and operational aspects of the material. Windows-based spreadsheet software (such as Excel) is used.

Spreadsheet Modeling and Applications --- This course, a continuation of TO 512, emphasizes problem solving using spreadsheet software. Extensive use is made of a spreadsheet solver (such as Solver in Excel) to formulate and solve practical optimization problems from such mathematical programming areas as linear, integer, and nonlinear programming, and multiple-objective decision making. Probabilistic modeling to support risk analysis in the context of spreadsheets is also studied, using native spreadsheet capabilities alone and then supplementing these capabilities with spreadsheet problem analysis, model formulation, implementation, execution and interpretation. Students are assigned computer work to reinforce and extend conceptual and operational aspects of the material.

Business Application Development with Visual Basic for Excel --- This course demonstrates how to use VBA in Excel to automate repetitive and time consuming tasks, generate interactive reports, manipulate charts, filter databases, and run solver. Examples of specific decision support applications, such as product mix and portfolio optimization are presented. Students will develop advanced technical skills with Visual Basic for Excel, and learn how to utilize VBA to create efficient and user friendly business applications. Specifically, students will learn how to enhance applications created in Excel with customized dialog boxes, user defined functions, event-handling procedures, customized toolbars, and more. The course also introduces general programming concepts such as the use of Variables, If statements, Loops, and assignment statements.

Integrated Product Development --- This is a Tauber Institute sponsored elective open to all graduate students. The course is structured so that students form into teams of four, each with mixed disciplinary backgrounds spanning business, engineering and art/architecture. A product category is announced, and each team acts as an independent firm competing in that product market. This is, each team must independently work through an integrated exercise of market research, product design, product development and manufacture, pricing, forecasting, inventory policy and competition with their product against other firms in both a web-based competition and a physical trade show.

Sustainable Operations and Supply Chain Management ---Firms today face increasing pressure from activists, investors, and customers, to reduce the environmental impacts of their operations and supply chains as well as uphold basic human rights and labor standards for the people who produce the materials / components / products. At the same time, using a sustainability lens to look at its operations and supply chain, a firm can identify new opportunities for improving efficiency and innovations. Further sustainability (environmental / social) as an artifact has to be combined with a discussion of responsibility. That is, how is responsibility (for ensuring sustainability) apportioned across the extended value chain that includes the end consumers? This course examines how to design and manage environmentally and socially responsible operations and supply chains.

Innovation in Global Health Delivery: Strategies for Enhancing Growth and Improving Access in Emerging Markets --- New business models built around operational efficiency offer tremendous potential to improve people's health worldwide. This course will examine how innovations in business models, operations, financing and supply chains are allowing far more people to access better quality healthcare. The course draws extensively on real-world case studies and latest research in this field. Class sessions will feature thought leaders from the field of global health delivery and involve lively debates on important topics. Concepts and approaches from strategy, operations, finance, and supply chain management will be used to understand what determines success and failure of businesses that seek to provide healthcare to low income populations. While there will be a strong emphasis on global health, some of the concepts will be applicable more generally to product and service delivery in emerging markets. This course is divided into two modules: The first part of the course will focus on design of systems that ensure access to medicines, vaccines and other health technologies. The second part of the course will focus on design of systems for health service delivery. Specific learning objectives for this course are: - Develop an in-depth understanding of the key issues in designing and managing healthcare delivery (products and services) in emerging markets. - Understand the important role of operations and supply chain management in improving effectiveness and efficiency of healthcare delivery in emerging markets. - Ability to formulate strategies for market entry in the healthcare/life sciences sector in emerging markets. - Understand the role of product and process innovation in global health delivery (through practical examples and cases). - Understand factors that influence the adoption of new health technologies in emerging markets and operational strategies to speed up adoption. - Understand the roles played by different agencies in the provision of healthcare in emerging markets and understand the critical value of inter-agency coordination in this context. - Discover and understand high impact opportunities for social entrepreneurship and operational innovation to improve global health delivery.

Data Mining using Regression Analysis --- The course considers procedures for data collection, effective analysis, and interpretation for management control, planning, and forecasting. The course stresses the capabilities and limitation of statistical methods together with the considerations necessary for their effective application and correct interpretation. The course focuses primarily on multiple regression models, which includes weighted least squares, analysis of variance, and analysis of covariance. Readings, cases, examples and exercises are drawn from diverse areas of business, including finance, marketing research, accounting, economics and general management.

Data Mining and Applied Multivariate Analysis --- Innovations in information technology has resulted in data intensive, managerial environments. A virtual flood of information flows through systems, such as enterprise resource planning and the Internet. What to do with all this data? How can it be transformed into actionable information? The objective of this course is to introduce business leaders to powerful methods for understanding and obtaining managerial insights from multivariate data. The course is designed for both managers who have direct responsibility for producing analyses and for managers who have to interact with area experts who produce the analyses. The methods include data reduction techniques - principle component analysis, factor analysis, and multidimensional scaling; classification methods - discriminate analysis and cluster analysis; and relational methods - multivariate regression, logistic regression, and neural networks. Emphasis is placed on the application of the method, the type of data that it uses, the assumptions behind it, and interpreting the output. User friendly and powerful statistical software will be used.

Applied Business Forecasting I --- Students acquire hands-on experience with building and applying forecasting models to actual data on sales, inventories, income, earnings per share, and other variables widely encountered in business. Understanding practical issues of data acquisition, data analysis, and presentation to management in both oral and written form are emphasized. Problems of trend and seasonal forecasting in marketing, production and finance (other fields are considered, as is short-term forecasting with exponential smoothing.) The course features problem sets, cases, and a capstone case at the end of the term, done by teams.

Action Learning Projects in Operations, Procurement, and Supply Chain Management --- This course provides an opportunity for students to deepen their knowledge in operations, procurement and supply chain management through action learning projects. Students will address a major operations or supply chain problem in a company through a 14-week action learning project. The course is taught in cooperation with AT Kearney, and students will also be provided guest lectures (by AT Kearney and Fortune 500 company executives) on how to approach consulting in operations and supply chain and on recent developments in these areas from different industries.

Project Management --- This course focuses on strategies and tools useful in management of non-repetitive business activities. Examples of such activities include construction, new product development and market introduction, consulting engagements, and organization restructurings. Tools to be introduced include work breakdown structure, network representation, PERT/CPM models and analysis, Gantt charts, time and cost models, PM software, and probabilistic analysis. Strategy considerations covered will include dealing with uncertainty, resource constraints, dealing with shared and requested vs. dedicated and commanded resources, and milestone management.

Applied Business Analytics and Decisions --- Objective: Strategic and tactical decisions problems that firms face became too complex to solve by naive intuition and heuristics. Increasingly, making business decisions requires "intelligent" and "data oriented" decisions, aided by decision support tools and analytics. The ability to make such decisions and use available tools is critical for both managers and firms. In recent years, the toolbox of business analytics has grown. These tools provide the ability to make decisions supported by data and models. This course prepares students to model and manage business decisions with data analytics and decision models. Specifically, the course aims to achieve the following goals: A. To develop the ability to identify key drivers in business decisions and develop analytical models for prediction and prescription. B. To learn a variety of tools and techniques for a range of tactical, operational, and strategic business decision problems that apply in a broad range of problems. C. To develop the ability to communicate the results and findings of analytical solutions to different. Specifically, the course will cover descriptive analytics (e.g., data visualization, query, data slicing), predictive analytics (e.g., forecasting, classification, simulation), and prescriptive analytics (e.g., optimization). Examples include decision problems in supply chain and logistics, retail revenue management, finance, and risk management.

Global Supply Chain Management --- Supply chain is the central nervous system of the global economy. Supply chain consists of all activities involved in fulfilling a customer request. Effective management of supply chain entails management of material, information and financial flows. Supply chain is perhaps the only discipline and business function in an organization that cuts across functional boundaries. Globalization of economy has heightened the strategic importance and of supply chain management and created new opportunities for using supply chain strategy and planning as a competitive tool. Inter- and intra-firm coordination issues are becoming critical for effective management of the supply chain. Depending on the industry sector, supply chain related costs account for 20-25% of a typical firm's total cost. On the revenue side, the supply chain decisions have a direct impact on the market penetration and customer service. Specific learning goals for this course are: -- Develop a general managers perspective on key issues in designing and managing end-to-end global supply chains. -- Know that effective management of end-to-end supply chain entails management of material, information and financial flows. -- Develop an understanding of key drivers of supply chain performance and their inter-relationships with business strategy and other functions within the company such as marketing, manufacturing, accounting, and finance. -- Develop the ability to design and formulate integrated supply chain strategy, so that all components are not only internally synchronized but also tuned to fit corporate strategy, competitive realities and market needs. -- Develop an in depth understanding of elements of supply chain designs for efficiency, responsiveness, and variety. -- Understand the importance of intra-firm coordination strategies and the knowledge of how to execute on such strategies. -- Understand dynamics of flows across firm boundaries, reasons for lack of synchronization, and managerial actions to improve overall supply chain performance. -- Understand the importance risk management in the extended global supply chain; learn the key elements of a robust risk management system and develop execution plans.

Information Technology Strategy in Supply Chain and Logistics --- Digital technologies have permeated every aspect of modern business. The capacity to execute any business model rests heavily on the approach taken by firms in organizing their information architecture. This course will explore the role of information architecture on Supply Chain and Logistics functions. We will discuss the dominant technologies traditionally used in planning, forecasting, scheduling and managing supply chains. We will then explore the emerging new technologies such as SOA ( Service Oriented Architecture) that enable firms to innovate in their business models through dynamic engagement with their supply partners in evolving global supply networks. Class discussions and case studies will include technology and business process choices in new product development, design, MRP, ERP, distribution and logistics.

Strategic Sourcing --- Strategic sourcing is the cross-functional process of critically analyzing how the organization can most effectively secure outside goods and services. This process is rooted in gaining a deep understanding of the overall value chain for the good of service of interest, and the business case behind a mutually beneficial and sustainable relationship between the buyer and supplier(s). This course teaches: analytical tools such as spend analyses (what is bought where?) and cost modeling (what drives cost?) to inform business case development: how to negotiate with suppliers using market-based (competitive bid) or multi-party (negotiation) mechanisms; and ways of structuring relationships and contracts to track results, drive sustainable performance, and mitigate risk.

Mobile Innovation Development --- Mobile platforms have emerged as the preferred vehicle for delivering business innovation to consumers. MBA students, specifically those with interests in entrepreneurship, need to understand the unique requirements of mobile business to successfully design, develop, deploy and manage business innovations. This course is designed to help students conceptualizing, designing, developing, delivering and managing technology solutions by taking them through the application (app) development process covering the full spectrum from identifying customer needs to prototyping/simulating a mobile innovation solution. Students will learn business issues related to mobile businesses including business and revenue models, customer engagement through gamification and personalization, security and privacy challenges, role of big data and mobile analytics, and integration of emerging technology directions such as wearables, smart devices loT, location based features and Social Media Integration. The course will seek to organize students in project groups with a combination of business, design and technology expertise. Project groups will then conceptualize, design and prototype/simulate a mobile business innovation throughout the course. Prior computer programming experience (including MS-Excel VBA programming) is preferred but not required.

Advanced Big Data Analytics --- With the ongoing explosion in availability of large and complex business datasets ("Big Data"), Machine Learning ("ML") algorithms are increasingly being used to automate the analytics process and better manage the volume, velocity and variety of Big Data. This course teaches how to apply the growing body of ML algorithms to various Big Data sources in a business context. By the end of this course students will have a better understanding of processes, methodologies and tools used to transform the large amount of business data available into useful information and support business decision making by applying ML algorithms. The focus of the course is less on the technical aspects of ML algorithms and more on the application of ML algorithms to Big Data available in different domain. The course will use R as the primary data analysis platform and Microsoft Azure as cloud platform for execution and deployment of ML projects. Prior experience with R or Microsoft Azure is not required. Students are assumed to be familiar with basic statistics.

New Age of Innovation --- This course introduces students to the emerging nature of competition and the critical capabilities that firms need to build to thrive in this environment. Based on the contents in a book co-authored by professors C.K. Prahalad and M.S. Krishnan, the course presents a different perspective on business innovation focusing on co-creating customer experience and global resource leverage with the social and technical architecture in the firm as the two key enablers. The specific implications for various business functions in this new approach to compete will be discussed. Students interested in functional roles or consulting will find this course useful.

Artificial Intelligence for Business --- We are living in a fast changing world. The amount of information we generate, receive and process is increasing at an exponential rate. This information explosion is empowering a wave of smart, automated functionalities broadly called Artificial Intelligence ("AI"). AI allows computers and machines to automate the business logic - to work and react like humans. AI comes with a great promise for individuals, organizations and societies but at the same time there are considerable risks, significant societal implications and ethical dilemmas. This course aims to provide students with a conceptual introduction of AI, a broad understanding of AI's basic techniques, how AI is applied to problems, future applications, of AI, and an awareness of the challenges, risks and ethical considerations of use of AI in business. The course does not require a technical background. Students will be able to connect the conceptual nature of this course with the more technical coverage of AI related material in other TO courses - but they are not expected to be familiar with the technical details of AI as pre-requisites.

Behavioral Economics and Behavioral Operations Management --- In recent years, there has been practical and theoretical interests in behavioral study. Behavioral economics combines lessons from psychology and economics to study how people process information and make decisions as employees, managers and consumers. Behavioral operations management applies those insights to managing business operations. The course will provide an understanding of how people's decisions deviate from "optimal" (rational and selfish) choices, as well as the consequences of such deviations in management and the marketplace. This course is devoted to understanding the nature, causes and implication of these limitations. We will then consider how (a) managers and policy makers can intervene to improve decision making and outcomes and (b) how markets are organized around exploiting of remedying deviations from rational decision making. At the end of the course, students should understand the decision making process more thoroughly and be in a position to become a better manager.

FinTech: Blockchain, Cryptocurrencies, and Other Technology Innovations In and Out of Finance --- New technological innovations are poised to fundamentally transform the financial industry in the coming decades, resulting in abundant career opportunities for FinTech professionals who are well-versed in the dual languages of tech and finance. This course introduces students to the most cutting edge topics including blockchain, cryptofinance and smart contracts, mobile payments, P2P lending, and robo-advising. Topics on big data and technology commercialization will be interwoven throughout the course. Students will (1) obtain in-depth technical knowledge of core Fin Tech concepts, (2) connect this technical know-how to current financial theories and market practices, and (3) decipher concepts beyond just the buzz words to provide critical judgments on new Fin Tech ventures. This knowledge will enable students to be the go-to FinTech expert in a wide variety of industries, and give them an important advantage in career advancement over peers who might just know the "buzz words".

Revenue Management---Revenue Management has, in the few decades, become a very important analytical tool for companies to optimize the revenues they can obtain for services or goods under capacity constraints. Revenue Management strongly complements the pricing decisions of firms by developing tools to help companies implement strategies using business analytics. Systems for revenue optimization, also called yield management or revenue management, combine the use of information technology, statistical forecasting, and mathematical optimization to make tactical decisions to maximize revenues.

The airline industry is the poster child for the success of revenue management, but the principles behind revenue management are being applied successfully in other industries as well. Accordingly, the case studies will feature a broad range of existing and potential applications, including: ad words in search engines; ticket revenue management in entertainment; software versioning; markdown optimization; customized pricing in B2B; and revenue management applications in the financial sector. Simulation‐ based instructional games will be used to showcase revenue management applications.

The high‐level course objective is to convey to future business leaders innovative ways to boost the bottom‐line. The course will explore how firms can improve the operational management of the demand for their products (goods or services) to more effectively align it with their supply through business analytics lenses. The course will introduce quantitative methods to improve decision‐making, with special emphasis on spreadsheet modeling and analysis.