Travel & Margin Analysis

Quantify excess travel cost and identify optimization opportunities across your field service operation

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WOs Analyzed

182

Total Travel Cost

$19,695

29,395 miles

Avoidable Cost

$18,496

27,606 excess miles

Optimal Cost

$1,199

If closest tech always used

Avg Excess / WO

151.7 mi

$101.63 per WO

Median Excess

32.5 mi

Outlier Rate (>50mi)

38.5%

70 WOs

Actual Travel Expenses

From 77 WOs with expense data

Total Expenses

$17,286

Labor - Travel

$15,716

Mileage

Lodging

$537

Airfare

Car Rental

Per Diem

$275

Meals

Other

$758

Cost Overview Actual Expenses Cost Breakdowns Coordinator Analysis Tech Utilization Quick Wins Coverage Gaps Low Hanging Fruit

🎯 Low Hanging Fruit — Biggest Drivers of Excess Travel Cost

Ranked by total avoidable cost across five dimensions. Focus on the top items in each category for the highest ROI improvements.

By Vertical

Which service verticals generate the most excess travel? Clinical Education stands out with very high per-WO excess.

#	Vertical	WOs	Avoidable Cost	Impact	Avg Excess	Outliers	Flew	Actual Expense	Techs
1	Project	71	$14,455	78.2%	303.9 mi	40	—	$415	7
2	FCO	111	$4,041	21.8%	54.3 mi	30	—	$16,871	18

By State

States with the highest total avoidable travel cost.

#	State	WOs	Avoidable Cost	Avg Excess	Flew
1	FL	73	$15,216	311.1 mi	—
2	NJ	36	$1,628	67.5 mi	—
3	NY	55	$842	22.9 mi	—
4	PA	11	$568	77.1 mi	—

By City

Top cities by total avoidable cost. These are your biggest geographic hotspots.

#	City	State	WOs	Avoidable Cost	Avg Excess	Flew
1	Orlando	FL	39	$9,778	374.2 mi	—
2	Altamonte Springs	FL	23	$2,099	136.2 mi	—
3	Kissimmee	FL	6	$2,003	498.4 mi	—
4	Apopka	FL	4	$1,223	456.2 mi	—
5	Camden	NJ	6	$1,047	260.4 mi	—
6	Exton	PA	8	$413	77.0 mi	—
7	Pennsauken	NJ	7	$306	65.2 mi	—
8	Allendale	NJ	14	$164	17.5 mi	—
9	New York	NY	13	$151	17.3 mi	—
10	Brooklyn	NY	9	$125	20.7 mi	—
11	NEW YORK	NY	6	$86	21.3 mi	—
12	Mineola	NY	3	$78	39.1 mi	—
13	Bronx	NY	3	$57	28.4 mi	—
14	BRONX	NY	8	$17	3.2 mi	—

By Coordinator

Coordinators whose dispatching decisions result in the most excess travel. High avg excess suggests systematic over-dispatching; high WO count with moderate excess suggests volume-driven impact.

#	Coordinator	WOs	Avoidable Cost	Impact	Avg Excess	Outliers	Flew	Actual Expense	Techs Used
1	Rebecca Arnold	182	$18,496		151.7 mi	70	—	$17,286	23

By Technician — Repeat Offenders

Techs who consistently travel far beyond the closest available option. High states-served count may indicate a roaming/national tech; high avg excess with few states suggests a misplaced home base.

#	Technician	WOs	Avoidable Cost	Avg Actual Dist	Avg Excess	Outliers	Flew	States	Actual Expense
1	Konstantin Barskiy	31	$12,967	636 mi	624.3 mi	30	—	3	$3,787
2	Luis Iser	10	$1,476	227 mi	220.3 mi	10	—	1	$155
3	Raymond Ebanks	8	$872	170 mi	162.7 mi	8	—	1	$203
4	Fady Messak	21	$543	52 mi	38.6 mi	0	—	3	—
5	Fady Khouzam	16	$517	57 mi	48.3 mi	11	—	2	$2,322
6	Alberto Galan	19	$278	31 mi	21.8 mi	2	—	2	$4,023
7	Israel Martell	17	$88	16 mi	7.8 mi	0	—	2	$4,012
8	Philmon Mehari	5	$60	29 mi	17.7 mi	0	—	2	$1,482
9	Robert Lewis	11	$22	11 mi	3.0 mi	0	—	1	$7
10	Derick Velazquez	19	$0	6 mi	0.0 mi	0	—	1	—