Numeritics has been a key partner in an intelligent transportation, smart parking application that provides real-time and predictive information on the availability of garage parking spots within Pittsburgh’s Cultural District. The core of the application is a systems development and integration module that collects real-time parking information from the garages by tapping into their gate counts. This is complemented by a module that uses historical data and an events calendar to make predictions about parking availability. The application includes a robust evaluation component, and is one piece of a broader transportation ecosystem within the Greater Pittsburgh region.

Numeritics is involved in a special study and analysis for a federal agency to conduct fair lending analysis, which will focus on assessing potential disparities across protected classes, in underwriting and pricing outcomes and the analysis of potential redlining, reverse redlining and product steering. The study will analyze relevant data using regression and other statistical and non-statistical techniques. The study also includes the review of policies and procedures used by mortgage lenders to underwrite and price loans.

A manufacturing entity facing uncertain demand for its products requested Numeritics’ help in fashioning the firm’s long term strategy. The strategy addressed the uncertainties created by the varying cost of key inputs and market demand. In addition, it also communicated the process down to the level of business units and employees. These objectives were achieved by implementing a planning model that runs simulation exercises to tackle the uncertainties in the strategic planning process and that focuses on the firm's operational activities in a manner that drives the firm's strategic objectives.

An example of a consulting engagement that centers on the analysis of large dataset is a health insurance coverage analysis project that utilizes data obtained from the U.S. Census Public Use Micro-data Series (PUMS) and provides decision-makers key information on health insurance coverage at the region, state, county or sub-county levels. Information obtained from the analysis allows decision-makers to identify pockets of the population where the uninsured are concentrated, flag individuals that may be at the highest risk of not having health insurance, identify patterns that could be localized to particular population cohorts and use these findings to design targeted policy responses, products and services that better address each sub-group of interest.

A Fortune 500 company retained Numeritics to create a workforce projection model to estimate the composition of its workforce, given historical recruitment and turnover patterns, and to help determine whether the company is on track to achieve desired workforce targets in the next 5 years. We generated forecasts for each subgroup of workers the firm is interested in using distribution functions obtained from the firm’s historical workforce data. We subsequently used these forecasts to conduct a gap analysis by comparing actual targets with projected estimates.

A finance company wishes to determine how it can minimize exposure to different forms of risk while maintaining the appropriate combination of assets and liabilities in order to maximize shareholders’ wealth. Numeritics developed a model that generated risk-return combinations that maximize profits and ensured the long term sustainability of the financial company.