Surge pricing parking on its way for parking at Cubs’ games

Maybe Cubs fans are so busy still celebrating the World Series Championship that they won’t notice parking around Wrigley Field is about to double on game days.  The city is instituting a surge pricing parking strategy to discourage fans from driving to the games.  Parkers will pay $4 per hour, up from the $2 per hour previously charged.  Wrigley Field already has a reputation as an expensive place to watch professional baseball.  During the World Series last year residents around the stadium were charging as much as $100 for fans to park in their garages.

Chicago uses pay boxes around the stadium for parking, and they will be programmed to start the $4 per hour rate two hours prior to the start of a game and can extend beyond the usual 10 pm end to paid parking.  You can read more about the changes and the community reaction in the Chicago Sun-Times and the Chicago Tribune.

The move to digitally capture parking data can be an important tool to evaluate your parking operations and find ways to make improvements that help generate revenue and improve the driver experience. While not everyone looks to parking as a revenue source, they should be evaluating their data to see if they are reaching their goals and maximizing their parking real estate.

In this case, Wrigley Field has adjusted parking rates based on demand or surge pricing parking for peak times and key locations; customizing time limits for individual times, days, or locations; direct traffic to available locations; and identify ways to bring traffic to underutilized spaces.  We cover more about variable rate or demand pricing for parking with examples from other cities in our blog Using Parking Data to Generate Revenue and Improve Driver Experience.   As an example, the City of Edmonton’s EPark system collects occupancy data and lets the City analyze how drivers are using parking in different areas.  They launched their EPark system in 2015 knowing that the data they collected could help them consider a predictive parking model with variable rates based on peak hours and congestion.