Krannert Full-Time MBA | MIS Concentration
The Krannert full time MBA Management Information Systems (MIS) concentration or option area is the use of people, processes and technologies in solving business problems. More specifically, how can we use technologies to help people better manage business processes? Are you interested in leading the business in the use of technology to increase its competitive stance (e.g., by increasing employee productivity, improving team collaboration, enhancing global reach, creating business partnerships and alliances, and facilitating organizational transformation)? Then the MIS concentration or even a few MIS electives might be a good choice for you.
- To improve your information technology knowledge and skill for acquiring, organizing, and communicating information required to solve business problems and become a knowledgeable participant in IT-related decisions and discussions.
- To develop your expertise in identifying ways to use information technology in your area of responsibility by way of understanding alternative IT infrastructures.
- To familiarize you with some classic examples of strategic uses of IT, organizational change through IT, and business transformation using information technology in order to identify future opportunities.
The positions taken by our students range from financial and business analysts to consultants, as well as positions in all functional areas within high-tech firms.
Past major employers include Cummins, Raytheon, IBM, Bank of America, AT Kearney, ABG Consulting, Air Products, Stryker, ITaP (Purdue University), and Sears Holdings.
Students in MIS should possess logical skills and a mind open to new ideas and experiences. No previous technical experience is required.
10 elective credit hours (5 classes) are required beyond the core course.
This course provides the basic concepts and skills needed to analyze and organize business data, as well as to utilize the organized data to answer a variety of business queries. After successful completion of the course, students will be able to appreciate why database management is important, analyze the data requirements of a business scenario and represent these requirements by means of entity-relationship (ER) diagrams, translate an ER diagram into normalized tables for a relational database management system, write simple and relatively complex data retrieval commands in the SQL language for Oracle and Microsoft Access databases, and be familiar with several current topics in the business data management arena. The major ideas and techniques will be reinforced through the work on successive segments of a group project.
Managers across the firm are faced with managing information risk springing from the massive amounts of data generated, collected, processed, and stored by firm activities and processes, including, but not limited to, data analytics, cross-channel marketing, and supply chain optimization. Managers in all areas of the firm must contend with regulatory and compliance issues affecting data such as the Gramm-Leach-Bliley Act, the Health Insurance Portability and Accountability Act (HIPAA), and the Data Protection Directive (Directive 95/46/EC), as well as potential liability and consumer sentiment issues when data is lost, stolen, or otherwise misused. Perhaps most critical is the ability to protect the firm’s intellectual property. This course will present both the real and potential risks as well as frameworks for managing such information risks in a global, digital economy. Guest speakers and a team project will round out the course.
The Internet and other emerging technologies have enabled new ways for companies to organize their businesses. Companies are also increasingly dealing with digital information that is different in many ways from other goods and services. The purpose of this course is to explore how new digital business models and digital information affect company strategy, market structure, and pricing. We will use lectures, cases, class discussions, and team projects to examine a variety of topics including Internet markets, pricing and competition on the Internet, Internet retailing, pricing of information goods, network effects, platform, and a variety of other topics. Fundamental economic principles will be illustrated using business case studies. At times, we will also discuss emerging digital technologies, business models, and industry structures.
Gamification techniques are increasingly becoming popular. The main idea is for firms to use the techniques of game designers to serve objectives as varied as marketing, human resources management, productivity enhancement, training, innovation, and customer engagement. In this course, you will examine the mechanisms of gamification and develop an understanding of their effective use in the modern firm.
As with any other business technique, in order to be effective, Gamification requires clearly defined strategies and well-managed execution. To identify effective strategies, techniques, and metrics for the application of games to business, this course will draw upon interdisciplinary source material as well as real-world case studies. It will also identify a number of significant pitfalls to gamification techniques, as well as notable legal and ethical issues, and the problems with implementing radical change in established firms. As a part of this class, you will be designing, playing, and evaluating various games.
The following courses from Quantitative Methods can also be taken as part of the MIS concentration:
Over the past decade, electronic spreadsheets have become the standard tool that business people use to model and analyze quantitative problems. The latest versions of these spreadsheet packages contain powerful analytical tools that could be possible only with mainframe computers and mathematically trained personnel a decade ago. This course covers up-to-date and practical spreadsheet modeling tools which can be applied to a wide variety of business problems in finance, marketing, and operations. The topical coverage consists of the following three modules (1) simulation modeling techniques to analyze risk and uncertainties in business environment, (2) optimization techniques to determine the best managerial actions under internally- and/or externally-imposed constraints, and (3) real-world examples and cases to demonstrate broad applications of spreadsheet modeling and simulations in manufacturing and service operations, supply chain systems, yield management, asset dynamics, option pricing, etc. This course is case-oriented and provides hands-on experience of computer applications using Microsoft Excel, spreadsheet add-ins @Risk and RiskOptimizer, and SimQuick (process simulation with Excel).
Data mining is the non trivial extraction of implicit, previously unknown, and potentially useful information from data William J. Frawley, Gregory Piatetsky-Shapiro and Christopher J. Matheus. Variety of techniques to identify nuggets of information or decision-making knowledge in bodies of data, and extracting these in such a way that they can be put to use in the area such as decision support, prediction, forecasting and estimation. The data is often voluminous, but as it stands of low value as no direct use can be made of it; it is the hidden information in the data that is useful.