Stefan Boedeker specializes in the application of economic, statistical, and financial models to areas such as solutions to business issues, economic impact studies, and complex litigation cases.
With over 20 years of experience, Mr. Boedeker has provided economic, financial, and statistical consulting and expert services to clients across a wide range of industries, including healthcare, high technology, entertainment, manufacturing, retail, real estate, insurance, and financial services, and federal, state, and local governments. Mr. Boedeker has issued expert reports and given deposition and trial testimony in state and federal courts.
Mr. Boedeker has extensive experience applying economic and statistical theories to class action-related matters, including class certification issues, liability assessment, and calculation of economic damages.
Mr. Boedeker also has extensive experience applying economic and statistical theories and methodologies to employment-related matters such as discrimination, wrongful termination, and wage and hour cases. His work in such cases to date has included designing and conducting surveys, time and motion studies, and observational studies; statistically analyzing the results of such surveys and studies; applying statistical sampling methodologies to extrapolate results from a subset to a universe of individuals; developing statistical models and tests to answer liability questions; applying economic theory to develop damages scenarios; and analyzing large employment-related databases.
Before joining BRG, Mr. Boedeker worked for both privately held and publicly traded litigation consulting firms, as well as national accounting firms. He started his career as an economic and statistical research assistant for the German government.
University of California, San Diego Ph.D. requirements except dissertation, Economics M.A., Economics
University of Dortmund/Germany M.S., Statistics B.S., Statistics B.A., Business Administration
BRG experts were retained first to do an economic analysis of the competitive landscape and identify key drivers for cost and revenue in a specialized software market. The next step was an econometric numbers-based analysis.
Every business needs to acquire more customers than it loses. While market research can generally sum up reasons for customer (dis)loyalty, careful econometric analysis of data around customer departures and arrivals can help identify what customers really value.
While developing a new business plan, a grocery store chain realized it was not utilizing data gathered from its new loyalty card program and at store terminals. It approached BRG experts to turn raw data into predictive insights to improve the loyalty program.