Planning for franchising? Start with your performance data

Franchising offers transport authorities more control over service quality. But that control is only meaningful if decisions are grounded in data. Long before a single contract is awarded, authorities need a clear picture of how their existing network is performing. This is where the planning stage becomes critical. It’s the foundation for everything that follows.

Setting your franchised network performance up for in-life success

At the planning stage, data helps authorities get a clear picture of what’s working, what’s not, and what needs to change. It should be used to set realistic performance targets, identify infrastructure gaps, and make evidence-based decisions about the future network.

Taking a data-led approach ensures decisions aren’t based on assumptions, historical habits, or political pressure—but on evidence. 

When planning the new franchised network, performance data from the existing network should be used to:

• Understand the baseline performance of the existing network to set realistic KPIs: Establishing the current level of performance ensures KPIs are grounded in operational reality rather than assumptions, and avoids setting targets that are either unachievable or too stringent.
  
  • Data and insights needed:
    
    • Punctuality by route, stop, and time period
    • Schedule adherence and on-time departure/arrival rates
    • Trip completion rates (missed or cancelled trips)
    • Run time variability across the day/week
    • Excess Wait Time (EWT) on high-frequency routes
    • Passenger delay minutes to quantify impact

• Use performance insights to inform targets and identify infrastructure needs: By tying performance issues to their root causes, such as persistent congestion or long boarding delays, authorities can set smarter, context-sensitive targets and flag where infrastructure investment, like bus priority or stop upgrades, could be most impactful.
  
  • Data and insights needed:
    
    • Congestion hotspots and slow-speed zones
    • Stops with high dwell times
    • Average boarding/alighting time per stop or stop group
    • Variability in run times across peak/off-peak periods
    • Passenger load profiles to assess stop-level demand

• Simulate the cost of a network that meets performance targets: Simulating performance improvements, like better punctuality or reduced crowding, allows authorities to plan for different scenarios and estimate the cost and resource implications of achieving those goals, balancing ambition with affordability.
  
  • Data and insights needed:
    
    • Scheduled vs actual vehicle hours
    • Layover and turnaround times
    • Dead running mileage
    • Passenger per vehicle hour / per trip ratios
    • Peak Vehicle Requirement (PVR) and resource modelling

• Identify infrastructure improvement opportunities: Targeted infrastructure interventions, like signal priority, stop redesign, or bus lanes, are most effective when driven by data to ensure they enhance the passenger experience and reduce operational disruption.
  
  • Data and insights needed:
    
    • Stops or corridors with consistent delays or late departures
    • Passenger-weighted punctuality issues (for example, stops where delays affect the most people)
    • High-boarding/alighting stops with limited space or poor design
    • Dwell time outliers and variability

• Understand passenger origin–destination (OD) flows to inform network design: A data-informed view of how people move across the network helps authorities design a franchised network that aligns with passengers needs.
  
  • Data and insights needed:
    
    • OD showing boarding and alighting locations
    • Passenger journey patterns by time of day and day of week
    • Trip chaining and multi-leg journeys
    • Demand hotspots and under-served areas
    • Travel corridors with consistently high or low occupancy

What happens if you don’t use performance data when planning for franchising?

If performance data isn’t used at this stage, authorities may find themselves franchising a flawed version of their existing network. Common risks include:

• Untested or unsupported performance measures: Performance expectations that can’t be reliably measured lead to confusion, poor contract compliance, and difficulty holding operators accountable or rewarding success.
• Inaccurate or overlooked network costing: Misaligned cost estimates, due to missing or misused data, can result in underbudgeted contracts, unexpected funding gaps, and delayed implementation.
• Route performance not considered in costing: Ignoring individual route complexity means bids may not reflect true operating conditions, increasing the risk of underperformance and inefficient resource allocation.
• Failure to design a realistic and high-performing network: Without performance data, network plans may look viable on paper but break down in practice, leading to reliability issues, unhappy passengers, and reputational damage.

Start planning early to deliver a better network

The earlier you begin planning, the more prepared you’ll be to build a franchised network that truly delivers — reliably, efficiently, and in line with what passengers actually need. By embedding performance data early in the process, you’ll avoid carrying over legacy issues, set achievable KPIs, and lay the groundwork for a network that’s built to perform from day one.

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