Every morning, someone in your operation sits down and figures out who is going where. Maybe it is you. Maybe it is a dispatcher. Maybe it is the drivers themselves, dividing up a stack of work orders over coffee. However it happens, the process looks roughly the same: pull out the list of stops, group them by area as best you can, hand them off, and hope nobody drives past the same intersection three times before lunch.
This is the way portable sanitation routing has worked for decades. And for a 2-3 truck operation, it is survivable. But the moment you start scaling — adding a fourth route, picking up new construction contracts, handling event work on top of regular service — the cracks become expensive.
The Real Cost of Manual Route Planning
Let us put numbers on it. A typical portable sanitation route covers 15-25 service stops per day, spread across a metro area. When a human plans that route, they are doing something that feels intuitive — clustering stops by neighborhood, working north to south, minimizing obvious backtracking. The problem is that human intuition cannot process every variable simultaneously.
Consider a route with 20 stops. There are over 2.4 quintillion possible orderings of those 20 stops. That is 2,432,902,008,176,640,000 permutations. Even if you narrow it down to a few "obviously good" orderings, you are still making choices based on gut feel rather than math. And gut feel has measurable costs:
- 15-30% more miles driven per route compared to an optimized sequence
- 45-90 minutes of extra windshield time per driver per day
- 2-4 fewer stops per route due to wasted driving time
- Higher fuel costs — at current diesel prices, the extra mileage adds up fast
For a 5-truck operation running five days a week, those 45-90 minutes per driver per day translate to roughly 19-38 hours of wasted driving time every single week. That is nearly a full-time employee's worth of labor, evaporating into unproductive windshield time.
How Route Optimization Algorithms Actually Work
Route optimization is not just "sort the stops on a map." Modern optimization engines solve what mathematicians call the Traveling Salesman Problem — finding the shortest possible route that visits every stop exactly once and returns to the starting point.
Here is what the algorithm actually considers that a human cannot easily process all at once:
- Drive time, not just distance. A stop that is 5 miles away on surface streets might take longer to reach than one that is 10 miles away on the highway. The algorithm uses real road network data, not straight-line distance.
- Turn penalties. Left turns across traffic slow your drivers down. Good optimization minimizes difficult turns and favors right-turn-heavy routing where possible.
- Time windows. Some sites have access restrictions — construction gates that open at 7 AM, event venues that need service before 6 AM setup. The optimizer sequences stops to hit time-sensitive locations first.
- Start and end points. Your trucks start at the yard each morning and need to return there. The algorithm plans roundtrip routes, not one-way paths.
The result is a route that a human would never come up with on their own — not because the human is bad at their job, but because the math is genuinely beyond what any person can do mentally with 20+ variables and real-world road constraints.
The Impact on Your Bottom Line
Let us walk through a concrete scenario. Say you run 5 trucks, each doing 20 stops per day, five days a week. Before optimization:
- Average route: 95 miles, 8.5 hours including service time
- Weekly fuel cost (all trucks): ~$1,200 at $4.50/gallon with trucks getting 8 mpg
- Stops completed per day: 100 across the fleet
After optimization, the numbers shift meaningfully:
- Average route: 72 miles, 7 hours including service time
- Weekly fuel cost: ~$910 — a savings of roughly $290 per week
- Stops completed per day: 110-115 across the fleet (the saved driving time becomes service time)
That fuel savings alone adds up to over $15,000 per year. But the real win is the extra stops. If each additional stop generates $75 in revenue, those 10-15 extra daily stops represent $3,750-$5,625 in additional weekly revenue. Over a year, that is $195,000-$292,000 in new revenue capacity you were leaving on the table — not because you didn't have the trucks or the drivers, but because inefficient routing was eating their available hours.
Beyond the Numbers: Driver Satisfaction
There is another benefit that does not show up directly on a P&L statement but matters enormously: driver retention. Ask any experienced portable sanitation operator what their biggest headache is, and driver turnover will be near the top of the list.
Drivers who spend their day stuck in traffic, backtracking across town, and feeling like their route was thrown together on a napkin — those drivers burn out. They come back to the yard frustrated. They start looking for other work. And replacing a trained driver costs you $3,000-$5,000 in recruiting, onboarding, and the productivity gap while the new hire gets up to speed.
Optimized routes are tighter, more logical, and less stressful. Drivers finish earlier or fit in more stops without feeling run ragged. They can see that the route makes sense. It is a small thing that adds up to meaningful quality-of-life improvement for the people doing the hardest work in your operation.
How DropHaul Handles Route Optimization
DropHaul's route optimization is built directly into the dispatch workflow. Here is how it works in practice:
- Build your route. Add jobs from your queue to a driver's route for the day. Drag and drop, select from the map, or let the system auto-assign based on proximity.
- Hit "Optimize." One tap sends all the stops through our Mapbox-powered optimization engine. It returns the fastest possible sequence, accounting for real road conditions and your start/end location.
- Review and dispatch. See the optimized route on the map with estimated drive times. Make manual adjustments if needed — maybe you know a road is closed or a customer prefers an early morning service. Then push it to your driver's phone.
- Real-time updates. If a stop gets added or cancelled mid-day, re-optimize on the fly. The driver sees the updated route instantly.
The entire process takes less than a minute per route. Compare that to the 15-30 minutes of manual planning, mental math, and map-checking that the old process requires — and multiply by the number of routes you dispatch every day.
Getting Started
If you are running routes manually today, switching to optimized routing is the single highest-ROI change you can make to your operation. The math is simple: less fuel, more stops, happier drivers, lower turnover. Every day you wait is another day of wasted miles and missed revenue.
DropHaul offers a free trial with full route optimization included. Build your first optimized route in under five minutes and see the difference for yourself. No credit card required, no long-term commitment — just better routes, starting today.