Optimize Field Service Routes

Goal

Reduce drive time + fuel costs + windshield time by routing technicians efficiently. The average residential service tech wastes 60-90 minutes per day on inefficient routing - that's 5-7 hours per week × 50 weeks = 250-350 hours per tech per year. For a 5-tech shop, that's 1,200-1,750 hours of unbilled drive time annually. Smart routing recovers most of it.

Prerequisites

• Geocoded customer addresses in CRM (lat/lng OR full address)
• Tech home/start locations
• Job duration estimates (per service type)
• Tech availability + skills mapped to job types
• Service area boundaries defined
• For non-residential: depot or warehouse location

Steps

Step 1: Audit your current routing (1-2 hours)

For 1 week, track each tech's:

• Total driving minutes per day
• Total job minutes per day
• Drive ratio = driving ÷ (driving + job time)

Healthy ratios:

• Residential service (varied locations): 25-35% drive time is normal
• Residential service (geographically clustered): 15-25% drive time achievable
• Commercial service (concentrated routes): 10-20% drive time

If you're above 40% drive time, you have a big optimization opportunity.

Step 2: Cluster geographically (1 hour)

Most field-service inefficiency comes from "ping-pong" routing - tech zigzags between distant jobs. Fix by clustering:

• Divide service area into zones (4-10 zones depending on size)
• Tag every customer with their zone
• Assign techs to zones (1 tech per zone, OR 2 techs sharing a zone for redundancy)
• Schedule each tech's day within their zone where possible

This single change typically reduces drive time by 25-40%.

Step 3: Front-load efficient days (30 min)

Best practices:

• Monday + Tuesday: tighter schedules (techs are fresh, want full days)
• Wednesday + Thursday: standard schedules with flex for emergency calls
• Friday: lighter schedules + maintenance jobs (allow for catch-up + emergencies)

Schedule the most "stop-density" days early; leave Fridays + Saturdays for the spread-out calls.

Step 4: Use TSP routing tools (1 hour)

Traveling Salesman Problem (TSP) is computer-solvable for typical residential routes (5-15 stops). Free + low-cost tools:

• Google Maps: enter all addresses, get optimized order (free, up to 10 stops)
• OptimoRoute:/month, handles complex constraints
• Route4Me: similar tier, slightly different feature set
• Built-in Manuall Routes: see Routes module in app

Inputs the tool needs:

• All stops (addresses)
• Tech start location (home / depot)
• Tech end location (home / depot)
• Time windows for each stop (if customer-specified)
• Job duration estimates

Output: optimized order + estimated drive time savings (typically 15-30%).

Step 5: Build in slack (15 min per day)

Don't pack 100% of tech's day. Real-world friction:

• Traffic surprises
• Customer running late
• Job taking longer than expected
• Unexpected emergency call
• Bathroom + meal breaks

Schedule 80-85% capacity. Reserve 15-20% as "slack." Empty slack = tech gets to leave early (paid time bank) or take a call.

Step 6: Handle exceptions intelligently (ongoing)

Emergency calls disrupt routes. Decision framework:

• High value + emergency: yes, redirect tech if cost is reasonable
• Low value + emergency: schedule for next day if customer can wait
• Medium value + emergency: dispatch decides based on tech's current workload

Document the policy. Don't let every customer perceive every call as "emergency."

Step 7: Track + iterate (monthly)

Weekly KPIs:

• Avg drive time per tech per day
• Drive ratio (drive minutes ÷ total work minutes)
• Jobs per tech per day
• Late arrivals (window misses)
• Customer complaints about timing

Monthly review:

• Which techs / zones are improving?
• Where's friction? (specific neighborhoods, customers, times)
• What's the cost savings vs prior month?

Common mistakes

• Optimizing for "feels right": human intuition is bad at routing math
• Hard-pinning techs to specific customers: prevents zone optimization
• Ignoring time-of-day traffic: school traffic, rush hour matter
• Over-promising windows: 8-12 AM window too tight when other calls intervene
• No tracking: can't improve what isn't measured
• Optimizing only routes, not schedule: smart routing on a bad schedule still wastes time
• Tech preferences: if a tech only wants east-side jobs, that's a different problem

Routing for different business models

Residential repair (high volume, varied jobs):

• Cluster aggressively
• Plan day before, but adjust 1 hour ahead
• 6-10 jobs per tech per day typical

Residential maintenance (recurring contracts):

• Pre-build the entire month at once
• Same tech on same customer (relationship + efficiency)
• 8-12 jobs per tech per day typical

Commercial (fewer, larger jobs):

• Routes shorter, simpler
• 3-5 jobs per tech per day typical
• Optimize for predictability + customer relationship

On-call / emergency (single tech response):

• Routing matters less; response time matters
• Track average response time
• Position techs strategically across service area

When traffic patterns matter

Heavy traffic adds 30-60% to drive time. Route accordingly:

• Early morning (6-8 AM): light traffic, push jobs in this window
• Late morning (10 AM-2 PM): mid traffic, balanced day
• Afternoon rush (4-6 PM): heavy; avoid major arterials
• Evening (after 6 PM): light again, good for premium emergency calls

Real-time traffic from Google Maps / Waze should factor into dispatch decisions for time-sensitive jobs.

Service-area math

Defining service area is a routing decision:

• Tight area (5-mile radius): low drive time, fewer customers
• Medium area (10-15 mile radius): balanced
• Wide area (25+ mile radius): more customers, higher drive cost

Calculate breakeven: at fully-loaded cost (fuel + maintenance + wear), can a 25-mile drive earn enough net revenue to be worth it? Often no.

Service-area boundaries should be reviewed quarterly. Tight areas can grow with capacity; wide areas can be cut with no customer loss if you're not currently serving them well.

Fuel cost as a forcing function

A fuel bill that keeps climbing faster than job count says "we have a routing problem." Strategies:

• Reduce drive time: see above
• Vehicle efficiency: maintain at proper PSI, regular service, fuel-efficient models
• Hybrid / EV fleet: ~30-50% fuel savings, often offset by higher upfront cost
• Driver behavior: aggressive driving costs 15-25% more fuel; coaching helps

References

• Operations Research literature on TSP
• Service Roundtable routing benchmarks
• Manuall internal: Daily Vehicle Pre-Trip Inspection, Financial KPIs for a Service Business