UPDATE AND ENHANCE JOBMOD 4.0 TOOL, FEDERAL HIGHWAY ADMINISTRATION (FHWA)

This is a request for information for a Federal Highway Adminstration (FHWA) requirement to "Update and Enhance JOBMOD 4.0 Tool" from Microsoft Excel to a Python-based platform. 

SUBMITTAL INFORMATION

• ISSUE DATE: June 15, 2026
• DUE DATE FOR RESPONSES: July 7th, 2026
• SUBMIT RESPONSES TO: Carolyn.Lethert@dot.gov and Donna.Franzese@dot.gov
• SUBMIT QUESTIONS TO: Carolyn.Lethert@dot.gov and Donna.Franzese@dot.gov

1. INTRODUCTION

Request for Information. This is NOT a solicitation for proposals, proposal abstracts, or quotations. The Federal Highway Administration (FHWA), Office of Transportation Policy Studies (HPL), is conducting a market survey to identify potential sources for an anticipated contract to update and modernize the JOBMOD tool.

2. BACKGROUND

FHWA has a long history of developing methodologies, such as the JOBMOD input-output economic model, to assess the employment impacts of highway construction spending.

• Model Foundation: JOBMOD estimates employment vacancies supported by federal-aid highway construction based on the U.S. Commerce Department’s Benchmark Input-Output Accounts, modified for highway-specific labor and material usage.
• Evolution of JOBMOD:
  • JOBMOD 1 (2003): Introduced three employment components: Direct (on-site construction and materials), Indirect (supplier industries like steel and finance), and Induced (consumer spending by employees).
  • JOBMOD 2 (2005/2007): Refined the methodology using BLS employment cost indices to account for wage inflation and defined a "job" as a Full-Time Equivalent (FTE) of 40 hours per week.
  • JOBMOD (ARRA) (2009): Developed to assess projects under the American Recovery and Reinvestment Act; it remains the most rigorously evaluated model in the series.
  • JOBMOD 3.1 (Current): Integrated "Buy American" import penetration analysis and first-year employment realization estimates.
• Policy Applications: The model is used to estimate highway expenditures as economic stimulus during recessions and to identify potential workforce shortfalls when the economy is near full employment.
• Need for Modernization: While functional, JOBMOD 3.1 is a spreadsheet-based tool with hard-coded data and limited transparency. FHWA aims to move this workflow into a Python environment using Py-Shiny to automate analysis and reduce manual errors.

3. SCOPE

The Contractor shall provide all personnel, equipment, and services necessary to develop JOBMOD 4.0, a transparent tool that utilizes the latest Bureau of Economic Analysis (BEA) I-O tables, BLS National Compensation Survey data, and highway construction cost data. Key objectives and requirements include:

• I-O Account Updates: The Contractor shall update input-output accounts to the latest available version, ensuring seamless integration into JOBMOD.
• Technical Coefficient Refinement: The Contractor shall review and refine technical coefficients for each highway improvement category, incorporating updated cost breakdowns based on BidTabs data and other relevant data sources.
• Framework Implementation: The Contractor shall implement FHWA-approved improvements, ensuring consistency with JOBMOD’s employment estimation framework. Improvement types will be provided by FHWA based on the Financial Management Information System (FMIS).
• Python Development: Develop a transparent, Python-based model with centralized input sheets for easy data updates.
• Dashboard Implementation: Implement a user-friendly Py-Shiny dashboard for data visualization and parameter adjustment.
• Documentation: Deliver comprehensive documentation to ensure FHWA staff can operate and maintain the model independently.
• Performance Details:

• Period of Performance: Twelve (12) months from the date of award.
• Contract Type: Firm-Fixed-Price (FFP).
• Place of Performance: Contractor’s facility.

4. REQUESTED CONTENT OF RESPONSES TO THIS RFI

Interested organizations are invited to submit a Capability Statement (maximum 5 pages excluding resume) identifying the following:

4.1 Corporate Information

• Name, Address, Point of Contact include phone and email, SAM / Unique Entity ID
• Size Standard under NAICS code 541720 - Research and Development in the Social Sciences and Humanities  
• Socio-economic classifications (e.g., Small Business, 8(a), SDVOSB) .
• Applicable governmentwide vehicle name and numbers (e.g., GSA OASIS+) and a clear statement if this work can be performed under the listed vehicle.

4.2 Technical Capabilities and Relevant Experience

Describe technical capabilities to perform the tasks in the draft Performance Work Statement (PWS), specifically:

• Modernization: Designing a Python-based system from the ground up to replace legacy spreadsheets.
• Data Automation: Implementing workflows to automatically gather and verify BEA, BLS, BidTabs data and other relevant software such as RS Means.
• Economic Engineering: Calculating new economic coefficients based on highway improvement categories that are based on Financial Management Information System (FMIS).
• Interface Development: Building interactive web dashboards using Py-Shiny for data visualization.
• Section 508 Compliance: Ensuring all digital products meet accessibility standards.

4.3 Representative Resumes

The Contractor shall ensure that all personnel assigned to this effort possess the professional credentials, technical skills, and experience necessary to fulfill the requirements of the PWS. The project team must have at least one personnel member who has documented experience in economic analysis, specifically regarding the application and execution of Input-Output (I-O) models. Additionally, the team shall include at least a computer programmer/developer with a proven track record of designing, developing, and deploying Python tools and interactive dashboards using the Shiny for Python framework. Provide information/resumes showing the ability to demonstrate compliance with these experience requirements.

4.4 Relevant Similar Projects

Provide information on company past experiences related to economic modeling, Python software development, or transportation-related data analysis. Please note if the listed experiences supported the federal government or another type of entity. Also note the period of performance of any listed experiences.