Foster Rosenblatt

Advanced Modeling

Practice Leader

Ricardo Uribe, MBA
ruribe@fosterrosenblatt.com  |  +1 866 940 0648

Practice Overview

This practice provides advanced model shells that support a variety of marketing needs for both our clients and our internal consulting groups.

Value Proposition

  1. Design and building of functionally advanced predictive and/or analytical model shells
  2. Design and building of market simulator shells with advanced “what-if” capabilities
  3. Providing modeling “software as a service” that is maintained by Foster|Rosenblatt

Use Cases

Capacity Enhancement

    Providing additional capacity during times of high workload

Expertise Acquisition

    Providing technical expertise in new therapy areas or geographies
    Delivering advanced platforms for forecasting, scenario planning, pricing/market access, promotional response, war gaming and valuation
    Delivering Monte Carlo and risk analysis platforms for modeling uncertainty

Enterprise Solutions

    Modeling software available across the enterprise
    Common “best practice” platform for all forecasters that may be updated as new versions are available

Approaches

Model Platform – Models are built in EXCEL with (or without) VBA code according to the client’s technical and process requirements, and most model elements may be edited by clients
Modular Construction – Models are designed to be modular and elements can be “mixed and matched” to provide off-the-shelf or custom functionality
Data Sources – Models are compatible with all external and internal data sources, and dynamic data updates can be programmed for models that feed dashboards or other analytical tools

Development Methods & Quality Assurance

Our approach to building models and software utilizes a proprietary Rapid Application Development method focusing on high quality and fast turnaround times. The key emphasis is on matrix team collaboration and the development of business rules based on user needs. Embedded in all our work are logic checks known as User Failsafe Protocols to protect the integrity of models from inputs or data flows that would break acceptable business rules.