- by Jamescon, Editor
- 7/14/2014 8:24:03 AM
@SethBreelove. Right, metro areas need to promote options to the single-person auto, and analytics can play a huge role in making public transit both effective and efficient. One of the problems with current transit strategies is that they really tend to be inflexible, in part because where they rely on tracks there it isn't like you can easily move the tracks, and in part because of politics. Something as simple as reducing bus service on one route even slightly (cancelling two or three trips a day) will have entire neighborhoods talking revolution.
Where analytics come into play (beyond things like maintenance and staffing) is in identifying where the jobs are and where the people (who fill those jobs) live. For example, many transit systems are based on a spoke and wheel layout where people on the outer portion of the wheel (outlying neighborhoods) ride the spokes to or from downtown. But what do you do in situations when jobs or populations shift and the commuter flow has to be across spokes (from one neighborhood to another)? That's the type of trend that analytics can identify, allowing the transit system to add/subtract service as needed over the course of years.
- by rbaz, Data Doctor
- 7/13/2014 7:36:46 PM
The efforts to maximize efficiency as far as offering relevant and dependable service can only be achieved by understanding ever changing needs. Data collection is the all important first step and does create a tall challenge in making full and effective use with all the varied sources. The progress made so far is encouraging and will result in cost efficiency by service augmentation.
- by SethBreedlove, Data Doctor
- 7/11/2014 6:56:32 PM
Public transit needs all the help it can get. With local governments trying to encourage people to use public transporation, rather than driving their cars, to reduce pollution and traffic, it's vital that these systems run efficiently and have some level of comfort.
- by Jamescon, Editor
- 7/11/2014 3:03:41 PM
@Doug. Great point about the disparate data sources that any transit system (or other transportation system) faces. While it can be obvious that a transit system will have separate systems for things like fare collection and accounting, scheduling, and inventory management within their own organizations, they also are reliant on data sitting on the systems of other parties. They have to consider data sources such as commuter traffic reports, police updates, even the projected time for a ballgame to wrap up at Petco. It sounds like San Diego transit and its peers around the world have to make the extra effort to be good data partners with any number of agencies and other organizations.