By Katherine Beaty

I was sitting in a conference breakout session on data strategy when it hit me: Most parking operators aren’t struggling because they lack data. They’re stuck because they don’t know where to begin.

Looking around the room, I saw a mix of confused expressions and frantically scribbled notes. Everyone’s being told to build a high-performance data machine, but no one handed out the manual, or even explained where the wheels go.

That’s when I thought about my childhood Matchbox car collection.

The box under your desk: the data you already have

When I was a kid, I had a beat-up cardboard box filled with Matchbox cars. Some were shiny and pristine, others missing wheels or covered in scratches. But they were all part of my collection. And that’s exactly how most parking operators feel about their data: It’s everywhere, it’s inconsistent, and they’re unsure what to do with it.

Here’s the truth — you already have data. It’s hiding in plain sight:

• Parking access and revenue control system (PARCS) equipment logs

• Valet tracking systems

• License plate recognition (LPR) captures

• Enforcement system records

• Customer service tickets

• Rate sheets

• Occupancy counts

• Payment system records

• Mobile app interactions

• Surveys

Let me share a quick story. I worked with a parking management team that thought they needed to invest thousands in new data collection systems. But after just two hours of digging through existing systems, we discovered a treasure trove of untapped information. They already had everything they needed. They just hadn’t looked closely enough.

You don’t need to start from scratch. You just need to look under the desk and start sorting.

Putting cars on the track: structuring your data

I remember the day I decided to build a proper track for my Matchbox cars. I quickly realized that if the pieces didn’t line up or were bent out of shape, nothing worked. The cars would fly off the edge, jam up, or stop completely.

Data works exactly the same way. If you’re not structuring it, if your timestamps don’t match formats, or your location names are spelled five different ways, you’re not going to get a smooth ride. Structure isn’t sexy, but it’s the difference between a data crash and a data cruise.

Pro tip: Create a data dictionary. It sounds fancier than it really is — it’s essentially a roadmap for your data. Define how each piece of information should be recorded, what it means, and how it connects to other data points. This simple step can save you hundreds of hours of headaches down the line.

Some cars go together, some don’t: relationships between data points

Not every Matchbox car fits every track. Some are too big. Some are too lightweight. But when you find a good match, you get real speed.

Data relationships are just like that. Don’t try to force connections that don’t make sense. But when you do link the right data points, such as comparing revenue by shift to staffing levels or connecting event schedules with peak occupancy, you unlock insights that can transform how you operate.

I once worked with a parking garage that discovered a fascinating correlation. By analyzing their data, they found that during major downtown events, their hourly rates were actually deterring customers. By creating a dynamic pricing model that adjusted rates in real-time, they increased revenue by 22% and improved customer satisfaction.

Don’t just collect, race: using data for action

Collecting Matchbox cars is fun. Racing them is better. The same goes for data. Stop hoarding reports that nobody reads. Pick a metric and race it. Change a rate. Track a trend. Watch the result.

I’ve seen it happen: Maybe your off-peak rates are actually driving longer stays. Perhaps a location is hitting high occupancy but low revenue. Or your customers might be circling the lot and leaving in frustration. Or citation appeals are high due to bad signage or a bad enforcement officer. Data doesn’t just tell you what happened: It shows you where to go next.

Think of data like a GPS for your business. It’s not just about knowing where you are. It’s about finding the best route forward and sometimes it lets you know of traffic delays and speed traps and can help you reroute your course.

Final lap: get on the track and get that checkered flag

You don’t need a Ph.D. in data science or a million-dollar business intelligence tool to get started. You need a clear view of the data you already have, the willingness to connect the dots, and the courage to act on what you learn.

So, open the box. Dust off the cars. Build a simple track. And let your data take the wheel.

The most powerful insights often come from the most unexpected places — just like that beat-up Matchbox car that suddenly wins the race.

KATHERINE BEATY is executive vice president of customer experience for TEZ Technology. She can be reached at [email protected].