By Dan Mathers:
Quality parking data has become essential for improving driver experience, enabling wayfinding, informing policy, and ensuring efficient operations. Even helping drivers find available parking requires reliable, real-time data. As cities and parking operators face growing pressure to manage curb space, optimize revenue, and support broader mobility goals, the focus has shifted from whether to use data to what type of data is needed.
Not all parking data delivers the same value. Its usefulness depends on three key dimensions: granularity, cadence, and accuracy. Granularity refers to how detailed the data is, from facility-wide summaries to individual stall activity. Cadence reflects how frequently data is updated, determining how actionable it is in day-to-day operations. Accuracy measures how reliable the data is, shaping how confidently organizations can act on the insights it provides.
Parking data generally falls into three categories. Basic data, often derived from payment systems or manual monitoring, provides a high-level overview of usage and revenue. Moderate-level data, gathered through tools such as license plate recognition or zone-based counting, offers deeper operational insight and supports more proactive management. High-level data, often called true occupancy, is captured at the individual stall level and delivers continuous, highly accurate visibility into parking availability.
With high-level data, organizations can power real-time guidance, implement demand-based pricing, improve enforcement, and plan infrastructure more effectively. By replacing assumptions with reliable insights, parking leaders can improve driver experience, reduce congestion, and create policies grounded in real-world conditions, transforming parking into a strategic asset for modern, data-driven communities.
Read the full article in Parking & Mobility magazine.
Dan Mathers is the Chief Executive Officer and President of eleven-x. He can be reached at dan.mathers@eleven-x.com.
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