Performance Metrics & Data Analytics

Services Provided: Big Data Analytics, COVID Impacts on Travel Demand, Travel Market Analysis, GTFS Feed Summarization, Visualization

Insight, as part of a consultant team, provided data analytics for Metra’s Route Restoration Study. Metra is the commuter rail system in the Chicago metropolitan area serving the city of Chicago and its surrounding suburbs via the Union Pacific Railroad, BNSF Railway, and other railroads. The system operates 242 stations on 11 rail lines. As ridership slowly rebounded post COVID, Metra added back service in different capacities per line, but still overall provided less service than the pre-COVID levels. The primary task of the project was to analyze regional trip origin-destination data sets and use the findings to make recommendations to Metra’s schedules to better serve various ridership markets, such as core market to CBD, as well as weekend and off-peak markets.  

For internal use and public distribution, the consultant team developed 153 zone-specific four-page spreads, each containing a series of maps, tables and graphs. Insight led the data processing and summarizing part of the study.  Insight analyzed Replica data to create zone-specific choropleth maps of trips flows. Insight also provided data on trips at a block group specific level, to help identify where within each zone trips began and ended. Insight also developed data to present time of day histograms of trip flows by hour in 2019 and 2022, enabling pre-and-post pandemic comparisons, and showing shifts in the timing of traveling. In each analysis, Insight filtered out ‘internal’ trips to the zone that could not effectively be served by Metra service.   

Conductor train counts and data from the Ventra ticketing app were also analyzed to show shifts in travel behavior. Comparison between Ventra data and Replica data made it possible for Metra to estimate its market share’ of total Replica trips that were currently being served by Metra service. Insight summarized GTFS feeds of operating schedules for Fall 2019 and Fall 2022 by daytime (weekday & Saturday) by line, by time period and station, which was used to produce histograms of average trains per hour for zonal travel-sheds for five time periods. 

The combination of analysis on market share, GTFS-based service provision, trip distribution with each zone, and trips by time of day permitted Metra to identify day, time period and location combinations that would benefit the most from restored or enhanced service.

Services Provided: Socioeconomic Analysis, Title VI Evaluation, Transit Planning 

Insight provided socioeconomic analysis, Title VI evaluation, and transit planning support for TriMet’s Title VI Analysis for Security & Access Control Enhancements Study. The study aimed to assess which neighborhoods and populations around transit stations might face disproportionate impacts from proposed security measures intended to harden facilities, including elevators, grade-separated stations, and park-and-ride locations. The focus was particularly on disadvantaged groups, such as minority and low-income populations, who have historically been more vulnerable to the negative effects of such policy decisions. 

To evaluate potential impacts, Insight analyzed American Community Survey (2019–2023 five-year estimates) data at the Census Block Group level. The analysis covered five geographic areas: a half-mile and one-mile radius around 10 selected stations, a half-mile and one-mile radius around MAX lines (excluding WES and Streetcar), and the overall TriMet service area. Insight developed area weights to refine the assessment, ensuring only the portions of Block Groups within the defined study areas were included, which improved the analysis’ accuracy in measuring potential impacts on nearby populations.

Services Provided: Scenario Planning, Big Data Analytics, COVID Impacts on Travel Demand, Travel Market Analysis and Forecasting 

Insight provided data analytics support for Metra’s Systemwide Network Planning Study. Metra is the commuter rail system in the Chicago metropolitan area serving the city of Chicago and its surrounding suburbs via the Union Pacific Railroad, BNSF Railway, and other railroads. The system operates 242 stations on 11 rail lines. The primary task of this project was to analyze regional trip origin-destination data sets and use the findings to make recommendations to Metra’s schedules to better serve various ridership markets, such as core market to CBD as well as weekend and off-peak markets. For this project, Insight helped develop scenarios of future travel markets in the Chicago region for the year 2050 based on previous work, regional projections, and trend analysis. 

Insight’s previous work on Metra’s Route Restoration Study (RRS) identified current travel markets based on analysis of Replica data. For this study, Insight revisited trip flows that the RRS identified as market opportunities but could not be served without additional capital investments. Insight also reviewed recent regional efforts to forecast future travel market changes including CMAP’s Mobility Recovery Efforts and RTA’s Strategic Plan. Insight helped develop a market assessment summary of findings leading to the identification of an initial list of up to eight future travel demand scenarios, based on: 

• Commute times deviate from traditional peak periods. 
• Employment decentralized away from Chicago’s Downtown with no new infill development. 
• Employment clustered around existing centers and all new developments were infilled. 
• Work-from-home rates varied from pre-pandemic to mid-pandemic norms.  

Building on work from the RRS and leveraging relevant CMAP, RTA, and other regional efforts along with additional LBS data, Insight led the development of custom spreadsheet-based travel forecast scenario models to test potential service proposals in subsequent tasks. Insight worked closely with Metra staff to review the initial future travel demand scenarios and target up to four scenarios to be carried forward and integrated into custom spreadsheet-based models for each scenario. The scenario models were utilized as “what if” analysis tool that support planning-level assessments of future demand and their concomitant impacts to operational needs and requirements. Insight also supported the project team in preparing a travel market scenario development technical memorandum detailing the methodology, inputs, findings, and recommendations of this task. 

Finally, Insight also prepared zone-to-zone travel times, transfers required, and service headways using Metra’s GTFS schedules. These inputs fed directly into the ridership forecasting model used for the study. 

Services Provided: Existing Conditions Analysis, On-board Survey, Demand Estimation, Transit Planning 

Insight was part of a consultant team that provided transit planning support to Broward County Transit (BCT) for its 2023 Transit Development Plan (TDP) Major Update. The TDP provides BCT with a 10-year road map for the development of transit services and capital improvements in light of penny tax initiatives and BCT’s premium transit vision plan, named PREMO. The TDP serves as a planning, development, and operational guidance document, based on a ten-year planning horizon and covers the year for which funding is sought and the nine subsequent years.

Insight developed the baseline conditions report, which consisted of compiling, analyzing, visualizing and mapping relevant socio-demographic, transportation, land use, and special generators. In addition, travel demand model data and Replica data were analyzed. Insight staff also assisted in developing the sampling plan, questionnaire design, and administering the Transit On-Board Survey. Insight also developed the mandatory farebox recovery report, analyzing pandemic-induced changes.

Based on future funding projections provided by BCT staff, Insight staff estimated revenue service hours available for a 10- and 30-year plan. Insight staff then developed GTFS files for new services, and edited GTFS files for existing services to develop future year vision GTFS networks. Insight then calibrated a Federal Transit Administration (FTA) Simplified Trips on Project (STOPS) model, and used the calibrated model to forecast 5-, 10-, and 30-year ridership by route. 

Insight’s efforts helped with the successful completion of the TDP within a demanding schedule. 

Services Provided: Traffic Forecast Data Analysis, Statistical Analysis

Insight is leading an effort for the Metropolitan Council to evaluate the accuracy and robustness of long-range traffic forecasts. This project builds on decades of traffic forecasting research and marks the third regional forecast accuracy assessment conducted in the Twin Cities, and the first to incorporate the methodological advancements from the National Cooperative Highway Research Program (NCHRP) Report 934.

The objective of this work is to assess the reliability of past traffic forecasts, improve modeling procedures, and develop tools to better communicate forecast uncertainty to planners and decision-makers. The analysis will enhance both the Met Council’s and Minnesota Department of Transportation’s (MnDOT) understanding of how forecasted and actual traffic volumes have aligned over time, providing a critical foundation for future infrastructure planning. The key activities are described below: 

• Compiling a robust database of past traffic forecasts, traffic counts, and project metadata. Insight created an innovative ChatGPT- and Python-powered tool to extract key forecast data from over 450 MnDOT traffic reports—many of them lengthy and scanned—into a structured, tabular format.  
• Applying multiple statistical techniques—such as percent difference from forecast (PDFF), quantile regression, and longitudinal comparisons—to quantify forecast accuracy. This analysis will be compared against prior regional assessments to measure improvement over time. 
• Providing recommendations to improve both forecasting procedures and how forecast uncertainty is communicated. Insight will leverage quantile regression and user-focused visualization methods to support decisions under uncertainty and will suggest refinements to the Met Council’s travel demand model based on systematic errors identified in the forecast database.

This study provides the Met Council with a highly defensible and transparent record of forecast accuracy, strengthens the credibility of travel demand models in future decision-making, and equips planners with tools to explain and manage forecast uncertainty in public and interagency settings. Insight’s leadership in this project showcases its unmatched expertise in travel demand model evaluation and its ability to merge technical rigor with actionable, policy-relevant recommendations. The methodologies and tools developed will be scalable for use by MPOs and DOTs nationwide.