Modeling & Decision Tools
Analysis Group has undertaken highly technical and data-intensive cases that require extensive theoretical modeling and statistical analyses. We draw on academic rigor and practical experience in statistics and econometrics to build business models and decision tools for use in industries including pharmaceuticals, biotechnology, automotive manufacturing, and entertainment and sports.
We have developed and implemented models to prioritize development opportunities, inform marketing and pricing strategies, understand cohort behavior under various scenarios, and assess causal relationships and “what if” scenarios. We have also developed models to estimate financial exposure under varying assumptions about resolution of business and legal issues. We are expert in applying sophisticated financial tools to value assets and financial instruments.
We customize models to address client-specific issues. Our work includes:
- Employing statistical modeling to simulate potential business impact in the context of potential policy changes
- Developing a probabilistic model to project the likelihood of a particular outcome related to the production and assembly process of a manufacturing facility
- Assisting the US Department of Justice in various investigations in developing analytical models that include statistical sampling and benchmarking techniques of health care claims
- Implementing Monte Carlo simulation to help an energy provider in financial-forecast planning of its operations over a 15-year period
- Developing decision support tools to display the complex outcomes from analytic models to managers and product planners
- Featured Expert Jun S. Liu Professor of Statistics, Harvard University and Harvard School of Public Health; Guest Professor of Mathematics, Tsinghua University; Guest Professor of Statistics, Peking University
- Health Care Bulletin Global Consequences of Local Pricing Decisions
Modeling the Economics of Growth Opportunities
Managing Risk under New Climate Legislation
Developing a Comprehensive Product Strategy
Expanding an R&D Portfolio