Strategies to Strengthen Data-Driven Decision Making

State DOTs are seeking to derive more decisions from data, improve real time performance management, and integrate advancements in data science. While data analytics, automation and machine learning are increasing, current data architectures are fragmented and costly, adding complexity and delay for information system development and management. This makes it difficult to maintain alignment with business needs. Business and enterprise architectures are used by some state departments of transportation as well as many other public and private organizations. Examples of these architectures include the Zachman Framework for Enterprise Architectures, The Open Group Architecture Framework (TOGAF), and the Federal Enterprise Architecture (FEA). The goal of this project is to identify business architectures that support and optimize faster decisions, data relevance and usability across the organization, and current business needs and responsive to evolving needs. The objective of this project is to explore business and enterprise architectures for their potential to improve the alignment of data with business needs and provide timely support for changes in business strategies.

• Record URL:
  http://apps.trb.org/cmsfeed/TRBNetProjectDisplay.asp?ProjectID=5215

Language

• English

Project

• Status: Proposed
• Funding: $300000
• Contract Numbers:

  Project 23-27

• Sponsor Organizations:

  National Cooperative Highway Research Program

  Transportation Research Board
  500 Fifth Street, NW
  Washington, DC  United States  20001

  American Association of State Highway and Transportation Officials (AASHTO)

  444 North Capitol Street, NW
  Washington, DC  United States  20001

  Federal Highway Administration

  1200 New Jersey Avenue, SE
  Washington, DC  United States  20590
• Project Managers:

  Hartell, Ann

• Start Date: 20220217
• Expected Completion Date: 0
• Actual Completion Date: 0

Subject/Index Terms

• TRT Terms: Data analysis; Decision making; State departments of transportation; System architecture
• Subject Areas: Data and Information Technology; Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01836062
• Record Type: Research project
• Source Agency: Transportation Research Board
• Contract Numbers: Project 23-27
• Files: TRB, RIP
• Created Date: Feb 17 2022 11:09AM