“Swiftly is a game changer”: Valley Metro improves OTP by 10%
Valley Metro, serving the Phoenix metro area, set out to boost system-wide on-time performance and use accurate historical data to improve its transit schedules. Partnering with Swiftly, a transit data platform, helped the agency make major gains on both fronts.
Valley Metro at a Glance
- Service area: Phoenix Metro Area, AZ
- Fleet size: 933 vehicles across bus and rail
- Ridership: 10 million annual passenger trips
Goal 1: Boost System-Wide On-Time Performance
Valley Metro wanted a clearer, more current picture of what was happening across its network so staff could manage service proactively. Using Swiftly’s Live Operations, On-Time Performance, and Run-Times products, the agency achieved:
- 10% improvement to system-wide on-time performance (OTP)
- 25%+ OTP improvement on one of Valley Metro’s highest-ridership routes
- 6% OTP improvement to all weekday rail service
- OTP data captured for an additional 9% of stops with Swiftly Auto-Assigner
- OTP data corrected for 15% of stops previously mislabeled early or late
- OTP reporting time dropped from 7 days to a few minutes, enabling proactive management
Valley Metro’s Head of Operations shared:
“You have to manage service in the present. Using Swiftly really empowered the staff to get a big picture of what’s happening, live. The level of confidence we gained with Swiftly is a game changer.”
Christopher MacKechnie, Manager of Transit Scheduling, added:
“With Swiftly, we gained instant access to what’s happening right now. We used that data to make meaningful schedule changes across the network, and our OTP jumped to over 85%—a historic gain.”
Goal 2: Improve Transit Schedules Using Accurate Historical Data
The second goal was to use historical performance data to fine-tune schedules across the network. Using Swiftly’s On-Time Performance and Run-Times products, Valley Metro achieved:
- 20% of run-time slack removed from a single route, saving one bus from service with no negative impact on OTP
- Run-times reviewed and recalibrated on 18 routes per service change, across 4 service changes per year
- Early arrivals identified and corrected that were previously hidden between timepoints
- Rail schedules significantly improved by splitting long lines into multiple shorter ones
Christopher MacKechnie shared:
“One of our most extreme changes was cutting a route’s run-time by six minutes in each direction. OTP didn’t suffer at all—and we saved a bus. We’re continuing that process across the network.”
He also noted:
“I love looking at on-time performance by stop, not just by timepoint. What looked like perfect on-time performance in our previous system is actually padded run-time with early departures building up before the next timepoint. Now we can find that and fix it.”
The Takeaway
By combining live operational visibility with granular, stop-level historical data, Valley Metro was able to move the needle on system-wide reliability while also trimming inefficiency out of its schedules—proof that better data can drive gains on both the day-to-day and long-term planning sides of transit operations.
