# Dispatch Routing Logic

*/Opportunities/Dispatch_Routing_Logic*

## Opportunity Overview

**Wedge**: Target residential HVAC fleets during peak summer cooling seasons where emergency call volumes overwhelm human dispatchers. Win this niche by integrating into existing field service management systems to automate only the emergency exception-routing, proving immediate reduction in response times. Expand by taking over the full daily scheduling board, and then move laterally into commercial plumbing and electrical fleets.
**Timing**: Large language models process unstructured text from incoming emergency tickets to extract skill requirements and urgency, while highly available geospatial APIs handle real-time traffic and distance matrices in milliseconds. This combination allows an agentic system to evaluate thousands of route permutations instantly without human data entry.
**Why This I C P**: Mid-market HVAC and plumbing businesses operate 20 to 50 trucks and face daily emergency calls that disrupt pre-planned routes. They feel acute pain from misrouted technicians but possess enough volume to justify an automated dispatch logic layer, unlike single-truck operators.
**Size Of Prize**: 150,000 mid-market field service fleets in the US and Europe x $12,000 annual spend on dispatch inefficiency and routing software = $1.8B addressable market.
**Gap Narrative**: Field service dispatchers manually match technicians to jobs using geographic zones and simple availability. They lack a routing engine that dynamically recalculates technician skill, vehicle inventory, real-time traffic, and shift constraints to optimize the board as emergencies arise. Current tools only provide static routing, leaving dispatchers to handle exceptions via phone calls and whiteboards.
**Defensibility**: Defensibility stems from deep workflow lock-in and proprietary routing data. As the system learns specific technician speeds, typical job duration by zip code, and local traffic nuances, its routing suggestions become mathematically superior to off-the-shelf geospatial tools. Ripping it out requires the dispatch team to revert to manual exception handling, creating high switching costs.
**Why This Thesis**: An autonomous routing agent directly executes the dispatcher exception-handling workflow by reading the ticket, checking truck inventory, and rearranging the calendar. This fits because dispatching is highly rules-based but mathematically complex, making it an ideal target for a persistent background agent rather than passive software.

## Opportunity Linked Thesis

**Thesis**: [Software](/Theses/Software)

## Opportunity Linked I C P

**Icp**: [Field Service Provider](/CompanyTypes/Field_Service_Provider)

## Opportunity Market Sizing

_Illustrative — target and order-of-magnitude estimate figures, not an achieved track record (this Thing is concept-stage)._

**S A M**: ~$800M-1.2B (US and Canada mid-market providers with 20+ field technicians)
**S O M**: ~$15M-40M
**T A M**: ~400k global field service businesses × ~$8k/yr optimization software spend ≈ ~$3.2B
**Growth Rate**: ~12-16%/yr, driven by rising fleet fuel costs and competitive pressure for narrower service arrival windows
**Paid Comparable Spend**: ~$45k-65k/yr per manual dispatcher FTE, plus ~$400/yr per truck on basic GPS telematics subscriptions

## Opportunity Incumbents

- [Onfleet Routing](/Products/Onfleet_Routing) — Tool
- [Routific Route Planner](/Products/Routific_Route_Planner) — Tool
- [Descartes RoutePlanner](/Products/Descartes_RoutePlanner) — Tool
- [Samsara Dispatch](/Products/Samsara_Dispatch) — Tool
- [Microsoft Excel](/Products/Microsoft_Excel) — Spreadsheet
- [Google Maps Manual](/Products/Google_Maps_Manual) — DIY

## Opportunity Win Conditions

**Kill Thresholds**:
- Fewer than 50% of generated routes executed without manual overrides after day 14
- Average daily dispatcher route planning time decreases by less than 25%
- Day 30 active usage drops below 40% of onboarded dispatchers
- Sales cycle exceeds 45 days for an $8,000 ACV contract
- Cost to acquire a customer exceeds $4,000 at the 90-day mark
**Leading Metrics**:
- Percentage of system-generated routes accepted without manual edits
- Minutes spent per dispatcher finalizing the daily schedule
- Percentage of fleet vehicles connected to the routing engine via telematics API
- Variance between estimated system travel time and actual logged travel time
- On-time arrival rate for technicians using system routes
**What Proves Right**: Dispatchers connect their telematics and work order sources within 48 hours and shift at least 60% of daily route planning to the automated engine. Mid-market field service businesses pay $8,000 annually because the logic demonstrably reduces daily fleet mileage by 12% and eliminates two hours of manual dispatching per day. Cohorts retain at over 90% past the three-month mark as realized fuel savings exceed the monthly subscription cost.
**What Proves Wrong**: Dispatchers abandon the tool within two weeks because the routing logic generates impossible travel times or ignores local commercial vehicle restrictions, forcing them back to manual Excel planning. Technicians miss tight service arrival windows, prompting operations managers to revoke the system routing authority. Conversion to paid stalls at zero because buyers view the output as indistinguishable from free Google Maps routing.

## Opportunity Build Profile

**Hardest Part**: Resolving conflicting constraints in real-time without causing cascading delays across the daily schedule. Achieving a system state where emergency inserts do not completely invalidate the remaining dispatch plan requires complex heuristic optimization.
**Min Viable Scope**: Focus exclusively on single-day residential repair jobs in a defined urban market, optimizing solely for technician skill and drive time. Deliberately exclude multi-day job scheduling, parts inventory constraints, and third-party contractor dispatch.
**Cold Start Problem**: Without historical job duration and localized transit data, initial routing schedules generate missed appointments or excessive idle time. Break this by ingesting 12 months of a regional fleet's past dispatch logs to baseline duration estimates before turning on live routing.
**Time To First Value**: 1-2 weeks of onboarding to integrate with the existing ticketing system and baseline historical transit models.
**Data Moat Available**: true
**Technical Difficulty**: High

## Neighborhood

### Where the gap lives

- [Installation](/Skills/Installation) — latent gap · Skills

### Incumbent in

- [Microsoft Excel](/Software/Microsoft_Excel) — incumbent in · Software
- [Routific Route Planner](/Products/Routific_Route_Planner) — incumbent in · Products
- [Samsara Dispatch](/Products/Samsara_Dispatch) — incumbent in · Products
- [Descartes RoutePlanner](/Products/Descartes_RoutePlanner) — incumbent in · Products
- [Google Maps Manual](/Products/Google_Maps_Manual) — incumbent in · Products
- [Onfleet Routing](/Products/Onfleet_Routing) — incumbent in · Products

### Applies thesis

- [Field Service Provider](/CompanyTypes/Field_Service_Provider) — applies thesis · CompanyTypes

### Embodies

- [Software](/Theses/Software) — embodies · Theses

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