For public school districts across the U.S., transportation budgets have become a source of chronic financial strain. Despite careful planning, a persistent gap between projected and actual spending diverts millions from educational priorities to cover operational overruns. This is a systemic, widespread issue, with annual spending exceeding $28 billion and per-student costs rising significantly.1 The solution lies not in incremental adjustments but in a fundamental shift to a data-driven management model that transforms transportation from a reactive cost center into a predictable, strategic asset.
The Anatomy of a Budget Overrun
The gap between budgeted and actual spending is caused by a cascade of interconnected pressures that traditional, static planning cannot manage. In addition to fuel price volatility, the most significant factors include:
- Driver Shortage and Overtime: Affecting more than 90% of districts,2 driver shortages force costly measures like route consolidation (which increases mileage and overtime), the use of non-transportation staff as drivers (creating productivity losses elsewhere), and higher wages to attract limited talent. In addition, driver shortages make managing overtime even more critical, as optimal hour distribution has a larger financial impact.
- Driver Idle Time: Unproductive time, including waiting time, can account for a substantial portion of the drivers’ cost portion of the overall budget.
- Growing Complexity: The rise of school choice and mandated transportation for students with special needs also impacts standard, geographically clustered routing. Routes are now longer, more intricate, and inherently less cost-effective and efficient to operate.
Among these variables, driver overtime stands out as one of the most unpredictable and financially damaging line items. It is a direct consequence of operational inefficiency—every route delay, vehicle breakdown, or driver absence can trigger premium pay. Controlling overtime is not about limiting hours but about fixing the systemic failures that cause those hours to accrue.
The Solution: From Raw Data to Financial Control
The key to mastering these costs is already within reach. Most districts have invested in fleet management platforms, e.g., Tyler Technologies, Samsara, or Synovia, that generate a constant stream of data from on-board GPS and telematics. The challenge is leveraging this data for deep operational analysis.
By conducting an in-depth “time and motion” study of the fleet and drivers, managers can move from guesswork to an evidence-based diagnosis of inefficiency. This involves:
- Planned vs. Actual Analysis: Overlaying GPS data onto planned routes to identify deviations that add time and mileage.
- Schedule Adherence Monitoring: Tracking arrival and departure times for every stop to pinpoint specific circumstances that consistently trigger overtime.
- Engine Idle Time Analysis: Quantifying extra paid time (and fuel cost) from buses left idle unnecessarily.
This granular analysis reveals the true root cause of overruns, allowing for targeted solutions. A problem initially blamed on a driver might be revealed as a broader issue with school schedules, sub-optimal routing software, or a vehicle in need of preventive maintenance.
The Modern Toolkit & the AI Frontier
Effectively using this data requires an integrated technology ecosystem where routing software, telematics, driver tablets, student ridership systems, and parent communication apps work in concert. This creates a closed-loop system for planning, execution, monitoring, and analysis.
The next frontier is leveraging artificial intelligence (AI) and machine learning (ML) to move from reactive analysis to proactive control. AI-powered dynamic routing can analyze real-time traffic, weather, and road closures to adjust routes on the fly, helping prevent delays before they happen. This capability directly mitigates the primary drivers of budget overruns—overtime and excess fuel consumption—and helps build a new level of financial resilience into the system.
A Road Map for Successful Implementation
Adopting this model is a change management project that rests on three pillars:
- People: Gaining buy-in from drivers by promoting adherence to policies.
- Process: Redesigning workflows to leverage real-time data and establishing data-driven key performance indicators (KPIs).
- Technology: Framing technology as a tool for enhanced operational (and financial) performance, as well as safety.
By embracing this data-driven framework, financial leaders can transform school transportation. They can close the gap between projected and actual expenses; help enhance budget predictability; and, most importantly, protect funding for what matters most: the students in the classroom.
Appendix: Case Study in Data-Driven Transformation
Our client is a major public school district in the U.S. with more than 30,000 students and a ballooning transportation budget. Despite initiatives to increase the number of drivers and improve routes and the bus system, a substantial gap between projected and actual expenses continued to weigh on financials, presumably due to driver inefficiencies.
Context
Forvis Mazars was engaged to identify the underlying causes of the budget overruns and suggest effective remediation. Deliverables included:
- Extensive data analysis spanning two years of time, motion, and labor data, including hours logged by drivers and wages paid.
- An in-depth report detailing the primary factors contributing to inflated costs, quantifying the impact of overtime and idle time inefficiencies, and describing recommended corrective actions across people and processes.
- Newly built automated dashboards fed daily from available transportation data, providing a fresh way for stakeholders to track (almost in real time) KPIs, cost drivers, and progress toward set targets.
Approach & Results
Forvis Mazars analyzed more than two years’ worth of data extracted from the driver system API. We then turned this analysis into powerful, intuitive dashboards and a detailed report with our findings and recommendations.
Our dashboards and reporting highlighted and quantified potential savings opportunities for our client—including approximately 50,000 hours identified as either partially or fully recoverable—through scheduling process improvements and real-time labor tracking.
Moreover, these dashboards enable our client’s finance and transportation departments to:
- Track key indicators such as idle time, overtime, and non-compliant shift selections.
- Monitor and measure progress relative to non-compliant hour logs on a continuous, daily basis.
- Reduce time-to-decision by providing daily insights into critical metrics and issues, leading to better informed and more proactive actions.
- Democratize access to data for all relevant end-users, fostering a collaborative environment, enhancing transparency, and encouraging accountability.
- Improve financial performance with a clear way to uncover and address inefficiencies, helping provide a path to significant cost savings and better financial management.
Click here to open image in a new tab
This example dashbord is for illustrative purposes only.
At Forvis Mazars, our Analytics team uses data mining skills and knowledge with leading vehicle tracking and driver behavior monitoring software to help deliver actionable insights, enable a collaborative and transparent environment, and help reduce costs. Don’t wait to potentially save on avoidable costs and reach out to one of our professionals to learn more.