Brett Saraniti
Brett Saraniti

Visiting Professor of Managerial Economics & Decision Sciences

Print Overview

Brett Saraniti received his PhD in Managerial Economics and Decision Sciences from the Kellogg School of Management at Northwestern University in 1997.  His dissertation chair was Roger Myerson, Nobel Laureate 2007.  He is currently a Professor of Economics and Quantitative Methods at Hawaii Pacific University where he has taught full time since 1997.

In addition to teaching at HPU, Brett has taught MBA and executive courses at Kellogg every summer since 1995 where he has been honored with two teaching awards.  He has also taught in the Kellogg-Recanati program in Tel Aviv and the Kellogg-HKUDST program in Hong Kong.  Brett has been a visiting professor at INSEAD every year since 2008 winning the Best Teacher Award for the Core Classes in September 2008.  He has been a frequent visitor at the Sasin Graduate Institute in Bangkok, Thailand; IESE in Barcelona; the Brisbane Graduate School of Business in Queensland, Australia; the Thunderbird School of Global Management; and the Helsinki School of Economics and Business Administration in Finland.  He has also delivered executive management seminars through the Haas School of Business at Seminarium International in both Chile & Costa Rica.

Professor Saraniti is the author of two textbooks: Managerial Statistics: A Case Based Approach, with Peter Klibanoff, Boaz Moselle, and Alvaro Sandroni, and (forthcoming) Vital Statistics: Statistics for Business and Economics with William Sandholm.

He has also worked, taught, and/or consulted for McKinsey & Company, Xerox Corporation, Hiscox Insurance, Chevron Oil Field Research, LG Electronics, Cantor Fitzgerald/Hollywood Stock Exchange, Alstom,, Love & Kirschenbaum LLC (expert witness), MRJ Technologies,,, Lee Ceramics, and Surflight Hawaii.

Brett spends most of his time at his beach house in Waialua with his wife Samantha and their three children Francesca, Carlo & Enzo who enjoy beating him at Monopoly and beating on him with Jedi Light Sabers.

Print Vita
Grants and Awards
Chairs’ Core Course Teaching Award, Kellogg School of Management, 2000-2001

Print Research
Klibanoff, Peter, Boaz Moselle, Brett Saraniti and Alvaro Sandroni. 2006. Managerial Statistics: A Case-Based Approach. Mason, OH: Cengage Learning (formerly Thomson South-Western).
Saraniti, Brett. 2008. The Hawaiian Airline Industry, 2001–2008. Case 5-108-005 (KEL351).

Print Teaching
Full-Time / Part-Time MBA
Business Analytics I (DECS-430-A)
Analytics is the discovery and communication of meaningful patterns in data. This course will provide students with an analytics toolkit, reinforcing basic probability and statistics while throughout emphasizing the value and pitfalls of reasoning with data. Applications will focus on connections among analytical tools, data, and business decision-making

Business Analytics II (DECS-431-0)
This sequel to DECS-430 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables, primarily through multivariate regression. In addition to learning basic regression skills, including modeling and estimation, students will deepen their understanding of hypothesis testing and how to make inferences and predictions from data. Students will also learn new principles such as identification and robustness. The course has an intense focus on managerially relevant applications, cases and interpretations.

Decision Making Under Uncertainty (DECS-433-0)

This course counts toward the following majors: Decision Sciences.

Provides frameworks for reasoning about decisions in uncertain environments. Case studies and experiments are used to motivate the importance of probabilistic reasoning to avoid the systematic biases that cloud managers' decision making. Formal probabilistic tools are introduced and their relevance to modern business issues is conveyed via cases, exercises, and class experiments. Some of the applications include: inventory management with uncertain demand, principal-agent models, herd behavior, selection bias, rare events, real options and risk. The course is self-contained, and should be of value to all students, including those with prior exposure to formal probability models.

Statistical Methods For Management Decisions (DECS-434-0)

This course counts toward the following majors: Decision Sciences.

This sequel to DECS-433 extends the statistical techniques learned in that course to allow for the exploration of relationships between variables. Topics include one- and two-population hypothesis testing, correlation, simple and multiple regression analysis, and qualitative variables. The course also covers applications of the material and a number of case studies. Extensive use of spreadsheet statistical analysis software is required.

Managerial Decision Analysis (DECS-438-A)
This course presents the standard approach taken in all Kellogg courses in dealing with risk and uncertainty. The principal focus is on the language of probability, random variables, decision trees and commonly encountered probability distributions. A number of applications are explored, with most analysis performed using spreadsheets.

Statistical Decision Analysis (DECS-439-B)
The study of statistics at Kellogg has two complementary goals: The first is to master the two languages of statistics: How to measure how much an estimate can be trusted and how to measure the weight of evidence with respect to a claim that has been made. The objective is to become knowledgeable consumers of statistical reports, effective managers of those doing the statistical "dirty work" and confident critics of statistics done badly. The other goal is to become facile at performing regression analysis, a tool for understanding the types of relationships all managers must deal with. A spreadsheet-based statistical analysis package is provided to all students.

Turbo Decision Making and Statistics (DECS-445-0)
coming soon

Competitive Strategy and Industrial Structure (MECN-441-0)

This course counts toward the following majors: Management & Strategy, Managerial Analytics, Managerial Economics.

The course studies the determinants nature of competitive strategy in a variety of industry structures. The course considers how the structure of a firm's industry affects its strategic choices and performance. Topics include the dynamic aspects of pricing, entry and predation in concentrated industries, and product differentiation, product proliferation and innovation as competitive strategies.