General information

Business Analytics and Technologies
Concentration Information

Today’s businesses operate on a glut of data. In the last 15 years, due to modern information technologies – the Internet, ubiquitous networking, digitized data collection technologies, web logs, wireless sensors, miniaturized devices – organizations collect, store and transport massive amounts of data about customers, inventories, business operations, product performance, prices, sales, advertising campaigns, employees, supply chain, and so on. How can organizations create business value from this glut of data? It requires managerial talent that combines business savvy, needed to identify business value opportunities or recognize problems, with a solid understanding of analytical methods needed to link the technical talent and functional managers who can implement business change.

The Business Analytics and Technologies concentration aims to develop this managerial talent through a series of courses that cover methods for critical and analytical thinking, information technologies and tools for implementing these methods, and business applications that heavily employ these methods and technologies. Departing from the old approach of being the “quant skills” component of MBA education, this area is designed around a critical balance between general analytical thinking, technology, and applications. The design of the concentration is guided by a Business Advisory Board, comprising leading industry executives who are substantially invested in business applications of analytical methods and technologies. The Board will also facilitate the educational component (e.g., by providing practical problems for class projects) and knowledge transfer through student internships and career placement.

Possible Career Paths

  • Market or Strategic Research
  • Data Management and Analysis
  • Consulting
  • Knowledge Management

Suggested Courses

Elective

206 Decision Making and Management Science

Considers management science for decision makers. Topics include an introduction to modeling and decision analysis, an introduction to optimization and linear programming, modeling and solving linear programming problems in a spread sheet, sensitivity analysis and the simplex method, networks, integer linear programming, project management and decision analysis.

Elective

203B Forecasting and Managerial Research Methods

Introduces modern and practical statistical methods for managerial decision-making. Topics include regression analysis, time series analysis and forecasting, design and analysis of experiments in managerial research and contingency table analysis. Applications of these methods include marketing, finance, accounting, production, operations, and public policy. Case studies and examples of computer-aided analysis are provided to illustrate various applications.

Elective

285 Time Series Analysis and Forecasting

Helps managers face problems of forecasting the future value of external and internal factors such as product demand, input prices, inventory levels, interest rates, advertising budgets, etc. Covers techniques to aid in this task, including time series analysis, which is the statistical analysis of past data series to produce forecasts for future values of the series. Covers methods such as exponential smoothing, Box-Jenkins modeling, seasonal adjustment, decomposition, curve fitting and multiple regression.

Elective

207 Management Information Systems

Information technologies are pervasive, and transform what they touch. This course covers questions such as: What technologies are critical to operations, marketing, decision making and e-business activities? How has the role of technology changed over time, and what factors govern the choice of IT applications? How does IT influence business strategy, and strategy in other areas such as marketing and operations? What are the key challenges in managing IT resources, and what factors limit business’ ability to exploit the latest information

Elective

269 Business Intelligence Technologies – Data Mining

Data are a key source of intelligence and competitive advantage for business organizations. With the explosion of electronic data available to organizations and demand for better and faster decisions, the role of data-driven intelligence is becoming central.

Elective

234 Pricing

Presents concepts and tools that are useful when making pricing decisions. Topics include cost analysis, demand and the factors that influence it, pricing in competitive environments, product line pricing, bundling, international pricing, quantity dependent pricing, and pricing in the Internet environment.

Elective

243 Customer Relationship Management

Customer Relationship Management (CRM) is a management approach under which marketing activities are organized and measured around customers (rather than around brands.) This approach is appealing because customers, not brands, make buying decisions. Applications of CRM are on the rise because recent advances in information technologies and the Internet allow managers to develop and monitor customer relationships in a simple and efficient way.

Core Course

252 Managing for Operational Excellence

Explores operations in manufacturing and service sectors from both inside and outside a company. Quantitative methods and their organizational implications are also examined.

Elective

282 Supply Chain Management

Matching supply with demand is a primary challenge for a firm: excess supply is too costly, inadequate supply irritates customers. Matching supply to demand is easiest when a firm has a flexible supply process, but flexibility is generally expensive.

Commands

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