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A 2020 Vision: Changes in the Expectations of Parking Management

Updated: May 12, 2022

During the past decade, the world has been dazzled by autonomous vehicles, bitcoin, and a major comeback of AI. Meanwhile, significant changes were happening quietly and rapidly in parking, a massive $100B+ industry here in the US.

Within the past couple of decades, a tremendous amount of data has become available to parking stakeholders through implementing parking access revenue control systems (PARCS). The majority of paid parking (105MM+ spaces) in the US is now covered by digital devices.

Per our estimate, the volume of parking transaction data generated across the US exceeds the total information volume of the US Congress Library in a week!

But most of it wasn't available until the recently. I remember at my first parking trade show, in 2015, no one I spoke to knew what an “API” was. Today, the requirement of “make my parking data available to me via an API however I want it” is standard in RFP's and contracts.

Some of the most competitive parking payment and access control solution providers are the ones that made their API available to their customers the earliest.

So, what does it mean for me?

For those who own and manage parking assets, here are some of my predictions to validate in the coming days, of the biggest changes underway.

1. Demand-based pricing will dominate the parking world

For decades, the pricing of parking inventory has been largely based on competition (off-street) or convention (on-street). This will change significantly as demand-based pricing is finally available and puts your parking data to work.

Parking exhibits the dynamics of fixed, perishable inventory, and constantly varied demand. Pricing is THE most effective lever to alter business results, such as revenue for privately owned parking lots or convenience for city owned on-street spots.

The lack of access to demand data made it extremely difficult for stakeholders to take a true economics (supply-demand equilibrium) approach. It used to be easier to look at Joe’s garage across the street, go fifty cents below, and call it a day.

Even worse goes with on-street parking. Residents hate paying for parking, and every elected government official hates to piss off residents. Resulting in many cities charging below market value for parking assets (only $0.00-$.25/hour in downtown core), resulting in the demand to exceed the supply, and causing major congestion.

It's no longer an effective approach.

The unique market dynamics per locations make it difficult for stakeholders to understand price elasticity and forecast the impact of future price changes.

Automatic Yield Management allows organizations to accurately price inventory based on the demand of the location and increase the frequency of rate changes (~400+ unique pricing levels, updated multiple times per day). It eliminates the need of manual review and allows teams to spend their time elsewhere.

Leading organizations have enabled yield management, and you don’t want to be left sitting on the bench.

  • Unico Properties, a Seattle based $4.5B commercial real estate company, successfully enabled demand-based pricing for event and monthly parking, and achieved a significant NOI increase.

  • City of Aspen, a well known tourist destination, successfully reduced congestion by 12.5%, while increasing downtown business volume by 20%.

Leaders in the real estate and parking management world are hesitant to publish what their advantages are, in order to keep their competitive edge. But the truth is, most of them adopted data enabled practices years ago. Without disclosing it to the world, they’ve been quietly boosting the NOI of their parking assets.

Some went to the next level, by integrating data with artificial intelligence to optimize dynamic pricing. Such as:

2. Data will drive operational strategy

For too long, parking management has revolved around cash collecting activities and hospitality/customer service. While this is still important, the expectation is increasing for data-backed decisions and operation strategy. Such as:

  • What’s the optimal oversell ratio for my monthly parkers in different tenant groups?

  • How many people should I staff onsite to ensure both the highest consumer satisfaction and the lowest labor cost?

  • How should the on-street parking hour limits get properly determined in different neighborhoods?

  • How much inventory should I reserve for nearby events?

  • When and how should online reservation platforms be leveraged? How much inventory should be allocated and at what price points?

The list goes on.

Asset owners, city council members, and executives in parking management expect the answers to be backed by data, and available in real-time. How come? Because everyone is doing it and it works.

  • Ryan Holgan, VP of Real Estate at JP Morgan, made it very clear in this 2min