COURSE NUMBER: MBA291D.11

This course is cross-listed with the Evening and Weekend MBA Program

COURSE TITLE: Visual Analysis and Presentation of Quantitative Business Data

UNITS OF CREDIT: 1

INSTRUCTOR: Stephen Few

CLASS WEB PAGE LOCATION: http://bspace.berkeley.edu

MEETING DAYS/TIME: Sundays, February 21 and March 14, from 9:00AM – 5:00PM

PREREQUISITES: This is not a statistics course. No training in statistics or financial analysis is required. This is not a Microsoft Excel course, nor a course in any other particular software product.

CLASS FORMAT: Mixture of lectures and group exercises

REQUIRED READINGS: Two textbooks

BASIS FOR FINAL GRADE: Based on two papers, each worth 50% of the total grade

ABSTRACT OF COURSE'S CONTENT AND OBJECTIVES:
Businesses make huge investments in technology to tame the chaos of corporate information, but these efforts rarely deliver the promised return on investment (ROI). We’ve made significant advances in our ability to collect, cleanse, integrate, warehouse, and access information, but these efforts are wasted if we fail to uncover its meaning and clearly communicate what we find to decision makers.

No knowledge is more critical to success than the numbers that measure business performance, identify opportunities, and forecast the future. These numbers, however, are almost always communicated in the form of tables and graphs that are poorly designed—painfully so, often to the point of misinformation. Poor data presentation is a problem that is insidious because it is largely unrecognized. Businesses pay for this failing over and over in the form of flawed decisions. This course exposes the problems of poor data presentation and introduces the simple design practices necessary to communicate quantitative business information clearly, efficiently, and compellingly.

Most business data analysis can be done with relatively simple graphing techniques, but these techniques are rarely taught. Despite their simplicity, the skills that are needed to recognize meaningful patterns, trends, and exceptions in business data are not intuitive, they must be learned. This course identifies what to look for in the data and presents the types of graphs and visual analysis techniques that are most effective for spotting what’s meaningful and making sense of it.

The first day of this course focuses on table and graph design for communication and the second on data visualization for discovery and analysis.

Day 1 Outline

The current state and challenges of quantitative data presentation
Introduction to table and graph design
Introduction to visual perception
Fundamental table structures
Table formatting
Graph visual encoding methods
Graph formatting
Methods for displaying multiple variables

Day 2 Outline

Introduction to information visualization
Visual characteristics to look for in the data
Quantitative business analysis by type
Tips for valid and revealing quantitative analysis
Analytical navigation
The pitfalls and challenges of popular data analysis software
Critical contributions of the information visualization research community
Analyzing more than three variables concurrently

MODIFICATIONS TO COURSE FROM ITS MOST RECENT OFFERING: None.

BIOGRAPHICAL SKETCH:
Stephen Few has over 25 years of experience as business intelligence innovator, consultant, and educator. Today, as principal of the consultancy Perceptual Edge, he focuses on the use of data visualization for analyzing and presenting quantitative business information. In addition to teaching this course at Haas, Stephen writes the monthly Visual Business Intelligence Newsletter, provides business consulting and training services, and speaks frequently at conferences. He is the author of the three best-selling books in the field of information visualization: Show Me the Numbers: Designing Tables and Graphs to Enlighten (2004), Information Dashboard Design: The Effective Visual Communication of Data (2006), and Now You See It: Simple Visualization Techniques for Quantitative Analysis (2009).