This course aims to sharpen students' ability to conduct quantitative analyses of business problems. The primary focus is on problem formulation and analysis -- identifying the key components of a decision problem, structuring it, translating it into a graphical chart, and then building the appropriate mathematical and spreadsheet models. These models are used to generate valuable qualitative and quantitative managerial insights. Students will be introduced to data management and decision tools such as Formula Diagrams, Linear Optimization, and Error Detection methodologies, as well as to Parametric Sensitivity Analyses. While each business problem is distinctive, a disciplined approach to problem solving can be incredibly useful across many career contexts. The concepts and exercises in this course will sharpen the student's professional ability to structure a messy problem and do some disciplined analysis on it. Developing these modeling skills requires the opportunity to brainstorm, reflect, and practice it on a wide variety of problems. Hence, the course includes intensive team-centered workshop sessions where all students get hands-on practice working with a group of peers to frame various problems in appropriate analytical terms, develop a solution approach, and critically reflect on the results. Examples will be drawn from Strategy, Operations, Technology Management, Marketing, and Finance to expose students to the broad applications of the concepts and tools learned in this class. Many of the up- to-the-minute Excel techniques covered in the course are now considered standard in industry, and developing a good understanding of them will deepen the student's ability to identify opportunities in which spreadsheet analytics can be used to improve performance, drive value, and support important decisions. Finally, students will learn the latest technologies for effectively linking spreadsheets to relational databases, and to manage reliably large scale spreadsheet development projects.
[ 3 cr.]