COURSE NUMBER: MBA 240.1
This course is dual-listed with the Evening-Weekend MBA program.

COURSE TITLE: Decision Models

UNITS OF CREDIT: 2 units

INSTRUCTOR: Yiangos Papanastasiou

E-MAIL ADDRESS: yiangos@haas.berkeley.edu

PREREQUISITE(S): Core curriculum

CLASS FORMAT: The course consists of lectures, small breakout exercises and computer workshops in which you will be given the opportunity to put into action the theoretical models introduced in the class in a supervised learning environment. Throughout the course we will make an extensive use of Microsoft Excel and Analytic Solver Platform.

REQUIRED READINGS: Throughout the course the instructor will provide recommendations for further readings from the following textbook:
Spreadsheet Modeling and Decision Analysis (8th Edition), by Cliff T. Ragsdale

BASIS FOR FINAL GRADE: Students will be assessed on the three following components:

1. Class participation (max 10 points)
2. Workshop reports (max 20 points)
3. Final Exam (max 70 points)

To pass this course, students are required to achieve a minimum of 60 (out of 100) total points.

CAREER FIELD: This course is useful for students interested in learning how to develop, adjust, and interpret quantitative spreadsheet-based models that support complex decision making.

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES: In today's rapidly-changing business environment, decisions are typically taken under considerable uncertainty and time pressure. The ability to analyse complex trade-offs efficiently and to appreciate the risks associated with each decision can therefore be a major competitive advantage. This course aims to enhance your ability to understand and structure complicated decision problems, and to equip you with state-of-the-art decision support tools that allow you to evaluate different courses of action. By the end of this elective, you should be in a position to develop analytical models that inform a broad array of decisions in areas including revenue management, project evaluation, financial planning, and resource allocation. You should also be able to recognize when and where business analysis can add the most value within an organization, what kind of data may be necessary to collect, and what type and level of analysis can be conducted in a quick-turnaround, high-impact fashion. The course is multi-disciplinary in nature and, through the choice of business problems, links to a number of other areas including Accounting, Finance, Marketing and Operations Management, thus adding to the analytic dimension of these areas.

BIOGRAPHICAL SKETCH: Yiangos Papanastasiou is an Assistant Professor in the Operations and Information Technology Management group at the Haas School of Business. Yiangos holds a PhD in Management Science and Operations from the London Business School, a MEng in Information and Computer Engineering from the University of Cambridge, and a BA in Engineering for the Life Sciences also from the University of Cambridge. In his research, Yiangos develops and analyses quantitative models that address business problems on the intersection of information economics and operations management.