ContextThe agency has a longstanding practice of collecting and using data to report on our results. We have been using some of the data we collect to analyze our performance, especially for pavements and bridges. We need additional data to meet legislative requirements and ensure we are making wise investment decisions. Our current system limitations do not always provide adequate data validity and reliability, which makes it difficult to perform meaningful analysis and reporting. We want to determine what new data sources might be available to meet our needs in a cost-effective and efficient way. We also want to make sure that we minimize risk to the agency of using any external data sources. We want to leverage additional data science techniques enhance our ability to make investment decisions. Our long-term goal is to use leading performance measures and predictive analytics to become more adaptive in our programming and funding strategies to maximize our return on investment. We also want to put data in the hands of our staff, so they can have access across our IT systems to data they need to perform analyses and make operational decisions.
Technology Advancement. Today, our volume of data is much greater than our ability to use it. Our current systems need to be upgraded. Eventually, we want to move beyond having dedicated staff synthesizing data from separate, disconnected systems to creating an agency with integrated data that trained practitioners can use as a single source of truth to perform the analysis they need to do their jobs. In addition, we want to take advantage of machine learning and other technologies that are making it easier to collect data that can be used for predictive decision-making.
Legislation, Regulation, and Funding. Federal transportation performance management, performance-based planning and programming, and other requirements are drivers moving the agency toward linking data to investment decision-making, but our knowledge of how to align them is inadequate, and our current measurement system and local priorities are separate and not connected to the requirements. Legislation also creates opportunities to leverage data and analytics available from third parties and federal partners, especially in areas of national performance measurement.
Workforce Evolution. Advances in systems and reporting platforms should eventually make data more accessible to practitioners than they were in the past, but we still don’t have the specialized analysis and reporting skills we need to use data effectively for decision-making in all performance measurement areas. We want to create a set of standardized data elements that can easily be used across the agency for reporting. We want to train existing staff in data science skills and recruit new staff with business intelligence (BI), business analysis (BA), including forecasting and investment decision-making across performance areas.