Transportation in the New Millennium
The cost-benefits of transportation data have not been established. Officials who invest in a data collection program are probably investing in something from which they will derive no benefit. They are generating a bequest to their successors.
Large-scale statistical programs take lots of time and money. Most programs or agencies don't have the money to sustain the needed data programs. Most programs do a bad job of justifying the need for data expenditures.
But being “irrelevant” is a delicate concern. Gauging relevance is like sitting around the campfire: too far from the policy “flame” brings the risk of irrelevance and being frozen out; too close carries the risk of being singed.
The key to solving this dilemma is the anticipation of data needs. Transportation statistics programs, like most other statistics programs, are approximately five percent statistics and ninety-five percent logistics. These programs are complicated exercises in organization and planning. But the most central professional aspect to these efforts is not the statistical skills involved nor the logistical capabilities, but the ability to anticipate the policy and planning data needs of the future: What policies will be significant? What planning horizons matter in the future?
When policy issues arise for the U.S. Department of Transportation (DOT), metropolitan planning organizations (MPOs), state DOTs, or the private sector, it usually is already too late to begin data collection. They cannot respond, “Hold on for a year or so, we’ll be right back!” When a policy question arises, data professionals usually can answer in
Three minutes, if it’s on the shelf;
Three hours, if a little searching is required;
Three days, if some manipulation is required;
Three weeks, if a computer program is involved;
Three months, if major data processing is required; or
Three years, if new data collection is required.
In other words, transportation professionals are forced to work with what they have in the data “cupboard” when a policy issue arises. Therefore, all policy will be made with the extant statistical data set. That must be the goal of all design.
Following are the experiences and discoveries of two states, Kentucky and California, that took a comprehensive look at the need for transportation data.
KENTUCKY’S DATA COLLECTION ENHANCEMENT EFFORT Kentucky transportation professionals are assessing their state’s needs, issues, policies, and gaps with regard to data. They are aggressively pursuing video logging and other technology-oriented, data-enhanced collection efforts.
Accurate and complete information is essential for today’s fast-paced decision-making processes. Technology has responded to the increased demand for information by providing sophisticated database management that includes visual and spatial analysis tools. These computerized tools demand better data content and accuracy. Just as the highway infrastructure is necessary to meet the demands of transporting people, goods, and services, a data infrastructure is required to support transportation planning. If data is treated like an asset, the rewards will follow in such areas as productivity and accountability.