The Power of Analytics Applying and Implementing Analytics – How to, When to, and Why May 23, 2016 Session 2 Presented by Dan Morgan, Chief Data Officer, Department of Transportation and Tom Roff, Department of Transportation Analytics Implementation Case #1: Department of Transportation Highway Statistics Production

DOT’s Federal Highway Administration (FHWA) maintains a wealth of information regarding the extent, use, condition, and funding of the highway infrastructure across the United States. This information is stored and managed in legacy systems that impede turning data into information. Specifically, the annual publication of Highway Statistics has been a challenge and a resource drain. Highway Statistics are a series of tables produced from several datasets throughout the FHWA. Many of these are in PDF and downloadable in excel. The tables contain information that ranges from how many miles of roads to how many licensed drivers to how much gasoline revenue was generated to drive on those roads. A specific example is the VM-2 Table or Vehicle-Miles of Travel (see Appendix). This measure represents how many vehicles drive over a defined length of highway multiplied across the nation. The data is cut by State, according to urban area, how the road is classed, etc. Analytics Implementation Case #1: Department of Transportation Highway Statistics Production Case Introduction 2

Analytics Implementation Case #1: Department of Transportation Highway Statistics Production What are our analytics project objectives? The issue for FHWA is that Highway Statistics are static tables and don't provide a good mechanism for analysis. Users that want to delve deeper require them to acquire the data and put it into a local system for analysis. This results in requests for customized queries and data dumps to be delivered by FHWA staff. Specifically, the tables we generate are developed annually – we do not maintain an easy time series to facilitate analysis. The data we make available to the public is roughly the same as the way we keep the data internally. Some insights FHWA hopes to gain: How might we structure a team to experiment with analytics approaches? How might we develop an analytics plan that includes prototypes and proofs of concept to prove out the value? How might we manage costs associated with analytics projects? What tools and libraries exist to help us get started, and what is the learning curve with those tools? How might we present the results of our nascent analytics projects in a way that garners leadership buy-in? 3

Analytics Implementation Case #1: Department of Transportation Highway Statistics Production Current Situation at FHWA FHWA has several homegrown applications to manage data (for the most part in MSSQL Server). Much of this data is accessed internally through custom developed code. FHWA conducts statistical analysis in Microsoft Excel and SAS, and is experimenting with technologies such as R and python to facilitate analytics. FHWA has concentrations of talent with the necessary skills to conduct advanced analytics. There is a small group of advanced GIS analysts sprinkled throughout the Administration. There are interest groups surrounding Data Science tools that is growing. 4

Access to data based on security concerns. Fear that data will be misused. Much of the data is sampled. There is a certain fear that this data will be modeled to create “data” where it does not exist through interpolation methods. Much of this analysis comes back to FHWA for a response. In-House technology support contractors reluctant to utilize COTS solutions. Several Offices regard this effort as beyond the spirit of the legislation – that is, advanced analytics on these data sets is considered to be potentially expensive and time-consuming, distracting from the core mission of developing and publishing the data products. Analytics Implementation Case #1: Department of Transportation Highway Statistics Production Challenges, Risks and Roadblocks at FHWA FHWA has been playing around with some open products like Google Public Data Explorer (see: and Leaflet but these are very unofficial and operate in the IT shadows. Officially, we have created a Data Visualization Center for some of our products but there is no direct access to the data. The Department has developed the DOT Innovation Sandbox as a way to test out new technologies in the cloud, lowering the barriers to prototyping. However, this capability is very new and agencies have not developed ways to scale what is learned from the Innovation Sandbox prototyping process. Mitigation Strategies Already Employed 5

Case Solution - Provide the following: 1.Recommendations: What are the 3-5 priority activities/actions FHWA should undertake to strengthen its analytics capability, from a people, process, and tools perspective? 2.What will these activities cost FHWA (ROM only)? 3.In what sequence or priority should these activities be planned and/or executed? 4.What other key considerations should FHWA take into account? Analytics Implementation Case #1: Department of Transportation Highway Statistics Production 6

Appendix: Sample Highway Statistics Table – Annual Vehicle Miles of Travel, Analytics Implementation Case #1: Department of Transportation Highway Statistics Production 7