Business

This course provides students with an understanding of the primary financial statements used for internal and external business decision-making in start-up firms and large corporations. It emphasizes underlying accounting concepts captured in financial statements, while highlighting the interdependence among these statements. The course will cover analytical techniques, such as ratio analyses and sensitivity analyses to assess the impact of changes in strategy and outcomes on efficiency and effectiveness measures. It also describes the various users of internal and external financial statements, and the potential conflicts between these various stakeholders.

This course is intended to familiarize the student with the wide variety of ways in which accounting data are used by management as a tool for the attainment of predetermined organizational objectives. The emphasis of the course is on the application of accounting data, rather than on its preparation, and particular attention is given to the use of financial data both in controlling day-to-day activities and planning future operations. Principal topics include: master budgets, cost analysis and classification systems, cost-volume-profit analysis, standard cost accounting and an introduction to capital budgeting. This course will be offered in 2021-22, and in alternating years thereafter.

The global nature of business is indisputable. This course introduces the students to the complexity of the global environment and adopts a multi-dimensional view (cultural, economic, social, legal, political, and technological) of world economy. It promotes understanding the global environment as integrative forces affecting the success or failure of today’s businesses and fosters a global perspective. Topics may include an overview of the world economy, comparative advantage and international trade, cultural distance, FDI/ globalization theory, outsourcing and global supply chain coordination, political and country risk, the global monetary system and currency risk, legal and ethical issues, and risk management.

This course is designed to broaden student perspectives on business through experiential learning in entrepreneurship, finance, strategy and marketing, organizational behavior, and operations. By exposing students to various business disciplines and a wide range of firms and business models, we intend to accelerate student impact through an engaging, immersive experience. During onand off-site situation workshops, students will engage with practitioners to discuss business challenges and decisions in a small-group format. Students will also be matched with alumni to de-brief topics related to cases and prepare a learning portfolio as a culminating assignment. By the end of the course students will have a broader understanding of business domains, increased business fluency, and a better understanding of decision-making within a relevant business context. 

This course addresses the impact of law on business. The course covers fundamental areas of business law, such as torts, contracts, intellectual property, and legal forms of business organizations, and their effects on business decisions. Particular attention is paid to technology-based enterprises where global business issues intersect with law.

This course builds upon students’ understanding of statistics and introduces them to the concepts and methods for analyzing data to support business decision-making. Students will explore data sets using data mining and analytics techniques to create business intelligence, to be used for understanding and improving customers’ experiences, supply chain operations, product management, etc. During the course, students will develop an understanding of the uses of business data analytics and associated models for business decision-making, forecasting, and obtaining and maintaining a competitive advantage. Students will learn a comprehensive set of advanced spreadsheet skills, including how to design, build, test, and use spreadsheets for analyzing business decisions.

This course is designed for the senior student who wishes to acquire or strengthen important skills needed for organizational success. Among the subjects covered is power in organizations, what it is, and how to acquire and appropriately use it. Additionally, this course emphasizes presentation skills, organizational etiquette, cross-cultural communication, and the knowledge of current events. The student will be expected to be familiar with and use all forms of media information for both individual and group projects. The course may be counted as a 4000-level elective for BU, MGE, or MIS, or as a Free Elective for any student at WPI.

This course is designed to provide an introduction to economics, an introduction to entrepreneurship, and an understanding of the linkages between economics and entrepreneurship. Students will apply these concepts to the assessment of opportunities that might arise from participation in WPI projects. Students will engage in exploring how economics and entrepreneurship can inform opportunity assessment within an ambiguous and uncertain context. These decisions are always made with incomplete information and there is typically no single correct answer but rather multiple possible answers — each with pluses and minuses. Students may not earn credits for both ECON 2910/ETR 2910 and ECON 291X/ETR 29IX

In the modern competitive and global world confronting today’s engineers, innovation and entrepreneurship (I&E) are increasingly important perspectives for every engineering career. Individuals proficient in I&E are likely to possess unique competitive advantage over those who do not. This course develops the foundation for developing such proficiency by examining the functional roles of the business/commercial aspects of engineering disciplines as well as establishing a basis for innovative thinking. Specific cases where I&E has led to new products innovation and new enterprise development will supplement course materials.

This course will introduce students to the concept of social entrepreneurship and the ways in which social entrepreneurs are addressing complex social problems with their entrepreneurial ventures. Students will be exposed to the challenges and rewards of running a social enterprise. They will learn valuable business and entrepreneurial tools that can be applied to the design of sustainable social business models. Topics include social opportunity recognition and evaluation, business models in the social sector, social impact assessment, the double-bottom line, scalability of solutions, organizational forms and structures, and social venture financing.
This course will be offered in 2021-22, and in alternating years thereafter.

Selling is a major part of business life, but it is especially important for those who are launching a new venture. They need to sell their business plan to potential investors. Later they need to sell their product or service to a customer. Ultimately they need to create an organization that is focused on meeting customer and other stakeholder needs through effective selling disciplines. This course will examine the elements of the sales cycle in terms of preparation, market research, prospecting, objection handling, closing, techniques for motivating the sales professional and formulation of strategy for the successful selling transaction. As part of the course students will be required to prepare individual sales presentations, one to secure investment for a new venture and one to sell a product or service to a customer. Guest speakers may be used on topics such as sales coaching, inside sales management, and to deliver sales effectiveness training.

This course is designed to foster an understanding of entrepreneurship in the context of innovation and the global economy. It also provides the theoretical and practical knowledge for the preparation of business models. The course includes opportunity identification, team formation, capital and other resource acquisition, exit strategies and other aspects of new venture creation.

One of the most troublesome aspects of entrepreneurship is running the business once it is started. This course focuses on techniques to grow the new venture and how to manage both the growth and operations. Considerable emphasis will be placed on expanding existing markets, finding new markets, anticipating the next generation of products, and managing cash flow.

This course is designed to help the student make well-informed judgments when faced with personal financial decisions. Such decisions are growing in number and complexity, and both individuals and families need a considerable degree of financial expertise in order to utilize optimally their limited incomes. Principal topics include: insurance (medical, life, automobile and disability), consumer credit, estate planning, taxation, personal investments (real estate, securities, etc.), social security legislation and personal financial planning.

This course provides a broad introduction to finance and financial logic, with emphasis on principles, applications and criteria used in decision-making.  Core topics to be covered include interest rates, time value of money, bond valuation, yield curves, stock valuation, and risk and return analysis.  The course is designed to help build students' financial literacy and provide a solid foundation for later courses in financial management, investments, and financial technology.

This course develops expertise in Finance, Technology, Innovation, leadership, and decision-making by focusing on real-world challenges in the field of FinTech. We will be actively discussing and learning how to analyze, identify, and manage/innovate FinTech across many functional disciplines including Financial, Insurance, Banking, Trading, Information Technology, Regulation, and Budgeting. Students are introduced to the Financial industry and the FinTech ecosystem. The course adopts a decision-maker and leadership perspective (business, operational, functional, and technical leadership) by emphasizing the relationships among financial data, their underlying economic events, risk profiles, challenges/opportunities, and the responses by all stakeholders in a business/corporation.

This course introduces students to the financial innovations and digital assets that are significantly transforming the banking and financial services sector. The course exposes students to strategic skills and analytical tools that prepare them to thrive in this digital age. The immersive experience will also include an understanding of the changing dynamics in the global banking and financial services sectors and how leveraging fintech and analytics can drive innovation and digital transformation. The course will also explore how digital currency innovations are increasingly altering basic financial intermediation functions such as payment processing, risk management, information dissemination, price discovery, capital raising, consumer expectations concerning access to funds, and the timing of loan decisions. Students will also spend time exploring the emerging challenges presented by the FinTech revolution, including traditional and emergent competitors as well as demographic, social, ethical, and technological forces facing the industry. Students will have hands-on problem-solving experiences that can be useful in FinTech applications and innovation. Students will demonstrate their knowledge through exercises, exams, and a final project that explores the raising of financing through the decentralized finance ecosystem.

This course provides the foundation for financial data analytics used in business and FinTech applications. The objective of this course is for students to gain experience in analyzing financial data using modern machine learning techniques, statistical methods, and prediction models. Students will develop computational skills to perform data analysis using a modern statistical programming environment and apply these skills to address a range of problems encountered by business firms, including those in the FinTech industry. The topics discussed include an introduction to R language, visualization of financial data, cluster analysis, simple and multiple linear regression, classification models, high dimension data analysis using Lasso, and model assessment and selection using cross validation. Students will have hands-on experience in the development of data analytics applications to analyze real world financial problems.

This course introduces the fundamental concepts and functionality of blockchain technology. It explores how that technology records, organizes, and verifies information and how it implements smart contracts. The various financial and non-financial applications of blockchain technology are reviewed. Students will demonstrate their knowledge through exercises, exams, and a final project that designs and develops a basic blockchain application for a business problem. The course concludes by examining the legal and regulatory framework, along with potential risks and hurdles faced by those implementing and using blockchain technologies for financial and other business contexts.

This course focuses on the ways value can be created and captured through innovation. Focusing on the assessment of customers, organizational capabilities, and competition, students will consider a variety of different types of innovations and their associated ethical and financial value propositions. Students will learn analytic tools to successfully assess and commercialize technology, product, and service innovations in a variety of contexts.

This course introduces students to the theory and practice of database management and the application of database software to implement business information systems that support managerial and operational decision-making. Special topics covered include relational data models, query languages, normalization, locking, concurrency control and recovery. The course covers data administration and the design of data tables for computerized databases. Students will use a commercial database package to design and implement a small business database application.

This course studies the problem of making computers act in ways which we call "intelligent". Topics include major theories, tools and applications of artificial intelligence, aspects of knowledge representation, searching and planning, and natural language understanding. Students will be expected to complete projects which express problems that require search in state spaces, and to propose appropriate methods for solving the problems.

This course offers a business focused data analytics introduction. Using cutting-edge tools and approaches to the analysis of data through supervised machine learning, the course teaches how to utilize “big data” for effective decision-making. The course creates data analytics skills through hands-on exposure to data and analytic techniques embedded in Automated Machine Learning tools. Application areas covered include Marketing (pricing and marketing of luxury shoes), Supply Chain (predicting parts backorders), Finance (predicting safe loans), Talent Management (predicting and explaining attrition), Service Delivery (predicting hospital readmissions), as well as student-centric topics (college grades and starting salaries). This course provides foundations required to successfully apply the machine learning approaches to many of the most common business problems.

This course provides an introduction to the technologies and techniques for organizing, analyzing, visualizing, and presenting data about business operations in a way that creates business value, and prepares students to be knowledgeable producers and consumers of business intelligence. During the course, students will study a variety of business decisions that can be improved by analyzing large volumes of data about customers, sales, operations, and business performance. Students will employ commercially available business intelligence software to organize, summarize, visualize, and analyze data sets and make recommendations to decision makers based on the results. The course explores the technical challenges of conducting analytics on various forms of data including social media data and the managerial challenges of creating value from business intelligence expertise deployed in organizations. The course includes business cases, in-class discussion, hands-on analyses of business data, and methods for presenting results to decision makers. It is designed for any student interested in analyzing data to support business decision-making, including students whose primary focus is Management Information Systems, Marketing, Operations and Industrial Engineering, Business, Management Engineering, Data Science, or Computer Science.

This course integrates students’ background in MIS in a one-term project focusing on development of creative solutions to open-ended business and manufacturing problems. The project will utilize systems analysis and design tools such as systems development life cycle, feasibility study, cost-benefit analysis, structured analysis and design. Students will acquire the skills necessary to analyze, develop, implement, and document real-life information systems. Students must be able to organize themselves and the project to complete their work within a seven week term. It is recommended that MIS majors take this course in preparation for their MQP.

This course focuses on the newest developments in the field of user experience (UX) (e.g., the use of physiological measures such as eye tracking in UX design) and provides an introduction to various methods used in cutting-edge research laboratories to study user experience. Both theoretical concepts and practical skills with appropriate development tools will be addressed within the scope of the class through hands-on projects and assignments. Students will develop a plan to innovate with user experience and will implement a simple prototype of their plan.

This course is based on the hypothesis that high performance firms depend on a sustainable pattern of new and innovative processes and products. Successful companies are examined in regard to their strategies for innovation and technology transfer. Technology alliances among industry, universities, and government are considered in order to increase the leverage of the individual firm. Benchmarking and commercialization from research to actualization is discussed through cases and examples.

Knowing how to manage and interact with customers is a key component for business success. Today, customer needs are continuously evolving as well as how products and services are purchased and consumed. Understanding consumer behavior concepts allows firms to investigate consumption habits and make better informed managerial decisions. The goal of this course is to provide an introduction to various theories and dimensions of consumer behavior, such as the consumer decision-making process, the influence of attitude towards the product, brand, and/or firm, and the impact of culture and subculture. Students will be exposed to how these concepts are linked and applied to marketing, to our roles as consumers, and to everyday decisions.

Every successful business has a strategy for how it provides value and earns profit within its particular industry. Focusing on the contexts of technology, innovation and entrepreneurship, this course develops analytic approaches for assessing the various aspects of strategy such as the competitive environment, the network of stakeholders, ethical implications, investor motivation, operational execution, and financial projections that are necessary to create a complete business plan.

Leadership is a critical role in any global, technological organization. This course explores how the concepts of creativity, entrepreneurial and critical thinking, emotional and self-awareness, passion, diversity, communication, and ethics inform and affect leadership practice. The course considers a variety of contemporary leadership challenges including how leaders work effectively across cultural, technological, and disciplinary boundaries, how leaders foster new ideas and bring them to fruition, how they communicate effectively and persuasively to diverse stakeholders, and how they make decisions that are both ethical and effective. The course is designed to 1) increase students’ awareness of their own leadership styles, 2) examine the responsibilities of leadership, and 3) determine best practices in leadership.

This course focuses on the basic knowledge and processes required of managers to understand behavior in organizations and to apply this knowledge to organizational change. Topics include communication and trust, power and leadership, group and intergroup processes, conflict and conflict management, and work and organizational design. Students apply their knowledge of organizational behavior to the analysis, implementation, and leadership of organizational change. Lectures, video presentations, case studies, group discussions and mini-projects are employed to introduce and illustrate the basic elements of organizational behavior and change.

This upper-level course invites students to consider the importance of ethics, corporate governance, and corporate social responsibility for leading global enterprises effectively. Students will be asked to reflect on their own leadership styles and to engage the complex, ethical dimensions of leadership in modern organizations. The course will engage students using lecture, video presentations, case studies, guest speakers, fieldwork, and mini-projects.

This course provides an introduction to prescriptive analytics, which involves the application of mathematical and computational sciences, such as linear optimization and simulation, to recommend optimal courses of action for decision making. The course will feature decision problems arising from a variety of contexts such as capacity management, finance, healthcare, humanitarian relief, inventory management, production planning, staffing, and supply chain. The emphasis of the course is the application of such techniques to recommend a best strategy or course of action for the particular context.

This course will train students to think critically about the effective and efficient use of computational tools to enhance everyday organizational performance. Students will learn how to create value through productivity tools that will likely include advanced spreadsheet functionality, regular expressions, macros, and scripting. The course will make use of software including Microsoft Excel with Visual Basic for Applications, Python, and advanced text editors, applied to a variety of domains, to improve students’ ability to automate processes and productivity. Students can receive credits for both OIE 2600 and either CS 2119 or CS 2102 or CS 2103. For IE majors, if one of the CS courses previously listed is used as a required programming course, then OIE 2600 can be used as an IE elective. Students cannot receive credit for both OIE 2600 and OIE 3600.

To aid all engineering students in understanding economics and business constraints on engineering decision making. Topics include evaluation of alternative; the six time-value-of-money factors; present worth, annual cash flow and rate-of-return analysis; incremental analysis; depreciation and income taxes; replacement analysis; inflation; handling probabilistic events; public economy; break-even and minimum cost points; and foreign exchange.

Operations are embedded in a constantly changing network of relationships with various stakeholders including customers and suppliers. Within the organization, scarce resources (including financial, human, and technological) need to be allocated and aligned with strategic goals. External to the organization, consideration is given to sustainability and environmentally responsible use of resources. This course focuses on process analysis, engineering design thinking and process implementation within the constraints of stakeholder networks. Professional engineering ethics and the consequences of management decision making are discussed in detail. The course includes a process analysis project and a one-piece-flow hands on laboratory experience. Course assignments follow one-piece-flow principles in education, allowing individual students to complete the course at their own pace.

This course covers the fundamentals of developing efficient layouts for production and service facilities. Methods analysis, work measurement, material handling and material flow analysis are also covered. Mathematical models and computer tools are used to assist decision-making.

This course in an introduction to the planning and controlling the material flow into, through, and out of an organization. It explains fundamental relationships among the activities that occur in the supply chain from suppliers to customers. In particular, the course addresses types of manufacturing systems, demand management and forecasting, master production scheduling, materials requirements planning, capacity management, inventory management, distribution resource planning, JIT and lean principles, and other current topics that are pertinent to managing the material flow of supply chains.

This course provides students with the analytical and management tools necessary to solve manufacturing and service quality problems. Topics include customer needs and quality, quality and cost relationships, process capability analysis, statistical process control, control charts for variables and attributes, design of experiments, and other Six Sigma problem solving methods. Health and safety outcomes and the ethical responsibility that quality assurance leadership owes to the organization’s stakeholders is discussed in detail. Textbook problems and business school case studies form the foundation of the course as well as a hands-on project experience.

This course covers the application of simulation to a variety of managerial problems with examples from operations management, industrial engineering and manufacturing engineering. It introduces the student to the concepts of computer simulation, with an emphasis on the design of a simulation experiment and statistical interpretation of its results. It will discuss simulation of queueing models, inventory and industrial dynamics, and gaming situations. The role and use of computers for the execution of simulations will also be highlighted. A commercial simulation language such as Arena will be used to solve problems from the manufacturing and service industries.

This is an introductory course in probabilistic models and decision-making under risk, with applications to engineering and management decision making. The course first covers quantitative methods for assessing and evaluating risks and how they are used in decision making. Decision making under risk is examined across a wide set of management and engineering problems. The course then introduces a set of probabilistic models commonly used in decision making and operations improvement; specifically, emphasis is placed on Markov chains, Poisson processes, and queuing theory, and their applications in manufacturing and service systems are illustrated.

A number of in-depth case studies in operations and industrial engineering are analyzed. The cases will cover both manufacturing and service systems ranging from production system design to operations planning and control.

This course provides an in-depth focus on prescriptive analytics, which involves the use of data, assumptions, and mathematical modeling of real-world decision problems to ascertain and recommend optimal courses of action. Starting from conceptualization of the problem, to using theory for translational modeling and techniques, to computational solving, and finally interpretation – likely in an iterative manner – students will gain knowledge of tools and practical skills in transforming real-world decision problems into actionable insights. Advanced topics in the prescriptive analytics domain will be covered, such as the use of integer variables to represent important logical constructs, using nonlinear functions to represent real-world decision aspects, the incorporation of stochasticity and uncertainty, and corresponding solution methods. Real-world problems will be selected from a variety of contexts that may include capacity management, data science, finance, healthcare, humanitarian operations, inventory management, production planning, routing, staffing, and supply chain.
  Note: Students cannot take both OIE 4420 and OIE 4430 for credit.

This case-based course will examine methods and strategies for managing and controlling material movement, with particular emphasis on international operations, from the purchase of production materials to the control of work in process to the distribution of the finished product. Strategies that will be discussed include the design of international distribution networks, the use of third-party logistics providers, and the creation of links between logistic systems and marketing to create competitive advantage. The course will also explore tactical issues that must be managed to pursue a logistics strategy successfully, including choices regarding means of transportation, packaging, and inventory policies. Underlying themes of the course will be the use of information technologies (such as electronic data interchange and bar coding) and mathematical models to support logistics decision-making.