Solutions

What Ordova changes for each team.

Ordova gives every role in a transport operation the same operational truth, and the specific view they need to act on it.

For executives

Reliability, cost and visibility.

CEO · COO · CIO · CTO · transit and authority executives

What you care about

  • Reliability and service quality
  • Fleet utilization and cost
  • Operational visibility
  • ROI, risk and compliance

How Ordova helps

  • Real-time dashboards replace end-of-day reports
  • KPI framework with formulas, targets and owners
  • Depot benchmarking to find the gap to best
  • A conservative, phased business case, not Year-1 hype
See the KPI framework
Ordova depot peer comparison matrix comparing fleet availability, on-time dispatch, cancellation rate, PM compliance, MTBF, MTTR and fuel efficiency across depots.
Depot peer benchmarking Real Ordova screen · demo data

For operations teams

Fewer calls, faster fixes.

Operations, dispatch, depot, fleet and scheduling managers

What you care about

  • Live operations and exceptions
  • Vehicle and driver availability
  • Schedule adherence
  • Incidents and recovery

How Ordova helps

  • Ranked exception queue with one decision card
  • Best-fit reserve vehicle and driver recommendations
  • HOS countdowns and qualification checks
  • Pull-out readiness and depot sequencing
See how operations run
Ordova Depot Management overview with vehicles available, under maintenance, drivers available, parking and maintenance bay utilization, and Maximo facility alerts.
Depot Management Real Ordova screen · demo data

For IT & architecture

Clear integration and a full audit trail.

Enterprise and integration architects · IT directors · data and AI teams

What you care about

  • APIs and integration
  • Security and access control
  • Data ownership and system of record
  • Reliability under feed failure

How Ordova helps

  • Ordova owns operational decisions; your maintenance, ticketing, ERP and HR systems keep their records
  • Stale-data flags and blocked auto-execution on stale feeds
  • Idempotent messaging, retry with backoff, reconciliation queues
  • Role-based access scoped by action and depot
See the integration architecture
Ordova Role Management editor showing permissions grouped by module for the Depot Manager role.
Role Management Real Ordova screen · demo data

For government & authorities

Audit trails and reporting.

Transport authority leadership, regulators and compliance officers

What you care about

  • Compliance and audit trails
  • Transparency and public accountability
  • Service levels and passenger experience
  • Operational resilience

How Ordova helps

  • Audit-trail logging on every action and AI decision
  • Authority-level sign-off for full service suspensions
  • Automated regulatory compilation with human review
  • Priority-route protection using ridership and social-equity criteria
See security & governance
Ordova Role Management editor showing permissions grouped by module for the Depot Manager role.
Role Management Real Ordova screen · demo data

Real-world scenarios

25 real situations and how Ordova handles them.

Pick a scenario to see how Ordova detects it, what data it uses, what it recommends, where a person approves, what happens next, and which KPIs move.

Scenario 1 Vehicle Critical severity

Bus breakdown during peak hours

  1. Detection

    Driver panic-button or radio call, GPS shows the vehicle stationary off-schedule, engine telemetry fault code (if IoT-equipped).

  2. Data

    Nearest reserve vehicle location, driver availability, passengers onboard, route geometry.

  3. Recommendation

    Dispatch the nearest reserve vehicle; if none is within an acceptable ETA, short-turn the following bus to absorb passengers.

    Alternatives: Mutual-aid vehicle from an adjacent depot; bridging via a different route.

  4. Approval

    Yes: dispatcher confirms the replacement dispatch.

    Automation: Auto-detection and auto-recommendation yes; auto-dispatch no (safety/liability).

  5. Action

    Dispatch order to driver app; PIS passenger notification auto-published; trip status updated.

  6. Outcome

    Service restored; incident ticket auto-populated with the full timeline. Closure needs dispatcher sign-off + maintenance root-cause code.

KPIs affected
OTPBreakdown rateMean-time-to-recovery
Full dispatch workflow (12 steps)
  1. Detection
  2. Impact analysis
  3. Identify replacement vehicle
  4. Identify driver
  5. Check route/depot compatibility
  6. Passenger impact calc
  7. Recommend
  8. Approve
  9. Dispatch
  10. Notify driver/passengers
  11. Update trip/KPI
  12. Close

Severity shown is indicative.

Before vs. with Ordova

Before and after Ordova.

Before Ordova

Reactive coordination

  • Disconnected systems
  • Manual coordination
  • Radio/phone-based dispatch
  • Delayed information
  • Reactive decisions
  • 5–7 screens per incident
  • End-of-day reporting

8–12 min to reassign a vehicle manually

With Ordova

Exception-driven decisions

  • Unified operational view
  • Exception-first workflow
  • AI recommendations
  • Real-time visibility
  • Human-in-the-loop decisions
  • Integrated systems
  • Predictive insights
  • Continuous operational intelligence

2–3 min system-assisted reassignment

Illustrative Reassignment times are typical 12-month targets, not customer results.

Business value

An example business case.

Illustrative assumptions, not customer actuals

All figures come from our conservative planning model for a reference fleet. They are not drawn from any authority’s actuals and are not guaranteed savings; replace them with your own baseline before any funding submission.

Reference fleet

  • 5,000 buses
  • 10,000 drivers
  • 300 routes
  • 20 depots
  • 1M passenger journeys / day

Estimated annual benefit by area ($M / year, low–high)

Total ≈ $29M–$46M / year at steady state

  • Fuel / energy reduction $5.6–8.4M
  • Reduced overtime $5.4–7.2M
  • Reduced maintenance cost $4.5–7.2M
  • Improved driver / vehicle utilization $3–6M
  • Reduced vehicle downtime $3–5M
  • Reduced trip cancellations / SLA penalties $2.4–3.2M
  • Reduced revenue leakage $1.8–3.6M
  • Reduced manual admin work $2–3M
  • Reduced breakdowns $1.5–2.5M
View assumptions as a table
Benefit areaCurrent state (assumed)Realistic improvementAnnual benefit
Fuel / energy reduction$140M/yr total fuel spend4–6% (less deadhead, idling; anomaly catch)$5.6M–$8.4M
Reduced overtime~8% of $450M driver payroll = $36M OT15–20% reduction of OT$5.4M–$7.2M
Reduced maintenance cost$90M/yr maintenance5–8% (predictive vs. reactive)$4.5M–$7.2M
Reduced vehicle downtimeNot quantified2–3 pts higher fleet availability$3M–$5M (fewer standby vehicles needed)
Reduced breakdownsNot quantified10–15% fewer breakdown events$1.5M–$2.5M (towing, penalty, replacement cost)
Reduced trip cancellations / SLA penaltiesAssume $8M/yr penalty exposure30–40% reduction$2.4M–$3.2M
Reduced revenue leakage2–3% of $360M revenue at riskRecover 0.5–1 pt$1.8M–$3.6M
Reduced manual admin workNot quantified40–60 FTE-hours / depot / week saved$2M–$3M
Improved driver / vehicle utilizationNot quantified2–4% better utilization$3M–$6M (deferred fleet expansion)
Implementation cost
$42M
one-time (midpoint)
Annual operating cost
$7.5M
post go-live
Annual gross benefit
$37.5M
steady-state midpoint
Net annual benefit
~$30M
Year 2 onward
Payback
16–20 mo
after go-live
3-year ROI
~114%
5-year ~250%

Ramp-up matters. Benefits ramp over 18–24 months as adoption matures; Year 1 typically realises only 30–40% of steady-state benefit. Presenting Year-1 numbers as run-rate is the most common credibility mistake in transit technology business cases.

Labelled assumptions

  • AAverage annual fuel/energy cost per bus: $28,000
  • BAverage annual maintenance cost per bus: $18,000
  • CAverage fully-loaded driver cost: $45,000/yr, of which ~8% is overtime today
  • DAverage revenue: $1.20 per journey × 1M journeys/day × 300 days = $360M/yr
  • EImplementation (software, integration, telemetry rollout, change management): $35–50M one-time
  • FAnnual operating/support cost after go-live: $6–9M/yr

Top ROI drivers

  1. Overtime reduction
  2. Fuel / deadhead reduction
  3. Maintenance cost reduction
  4. Reduced SLA penalties
  5. Reduced standby fleet needs
  6. Revenue leakage recovery
  7. Admin labour savings
  8. Reduced breakdown / towing cost
  9. Better utilization deferring fleet expansion
  10. Ridership retention from reliability

Implementation risks to plan for

  • Data quality from legacy AVL/telemetry
  • Driver and dispatcher adoption resistance
  • Maintenance-system integration complexity and data-ownership disputes
  • Over-automating safety-adjacent decisions too early
  • Underestimating change management across many depots
  • Union negotiation on any automation touching labour scheduling
  • Unrealistic Year-1 ROI expectations with finance and political stakeholders

12-month transformation

Typical results after the first year.

Typical targets for a large operator across reliability, availability, cost, maintenance, passengers and reporting effort.

Where operations could be after 12 months

Illustrative 12-month targets: on-time performance from 78% to 88–90%; fleet availability from 85% to 92% or more; preventive maintenance compliance from about 75% to 95%. 70% 75% 80% 85% 90% 95% 100% On-time performance 78% 88–90% Fleet availability 85% 92%+ Preventive maintenance compliance ~75% 95%

Dispatcher reassignment time

8–12 min manual
2–3 min system-assisted
View all 10 dimensions as a table
DimensionBeforeAfter 12 months (realistic)
On-time performance78%88–90%
Fleet availability85%92%+
Preventive maintenance compliance~75%95%
Dispatcher reassignment time8–12 min manual2–3 min system-assisted
Overtime costBaseline−15–20%
Breakdown rateBaseline−10–15%
Trip cancellationsBaseline−30%
Passenger complaints (reliability)Baseline−20–25%
Management visibilityEnd-of-day reportsReal-time dashboards
Regulatory reporting effortManual compilation, daysAutomated, hours
  • Overtime cost−15–20%
  • Breakdown rate−10–15%
  • Trip cancellations−30%
  • Passenger complaints (reliability)−20–25%
  • Management visibilityReal-time dashboards
  • Regulatory reporting effortAutomated, hours

Illustrative planning targets Not customer results; actual outcomes depend on baseline, data quality and adoption.

Next step

Get a business case with your own numbers.

We’ll replace the example assumptions with your fleet, routes and baseline KPIs.