You upgraded your route optimization software three months ago. Your dispatcher says it’s going well. Your drivers say the routes are better. But you don’t actually know if delivery efficiency improved — because you don’t have a metric that tells you.
Stops per hour is that metric. It’s the single number that captures whether your route planner is producing routes that drivers can execute productively — and whether your operation is improving over time.
What Stops Per Hour Actually Measures?
Stops per hour is simple to calculate: total stops completed divided by total driver hours worked. A driver who completes 24 stops in an 8-hour shift has a stops-per-hour rate of 3.0.
What this number captures is the combined output of routing efficiency, stop execution speed, and driver time management. A low stops-per-hour rate could mean routes are poorly sequenced (too much drive time between stops), drivers are slow at each stop (POD steps taking too long), or drivers are taking unplanned breaks. Good routing software improves the first cause. The metric reveals whether it’s actually doing that.
The power of stops per hour is that it converts vague impressions — “the routes seem better” — into a specific, trackable number that reveals improvement or stagnation.
“The routes are better” is not a KPI. Stops per hour is. If your route optimization improved, the number moves. If it doesn’t move, something isn’t working.
What Good Looks Like (and Why Context Matters)?
Stops per hour benchmarks vary significantly by delivery type. Use these as reference ranges, not universal targets:
Urban food delivery (restaurant, grocery, meal prep)
Dense stop clustering, short inter-stop distances, high stop frequency. Expect 4 to 6 stops per hour for well-optimized routes. Urban drivers spending more than 8 minutes per stop on average are likely experiencing process inefficiencies, not routing problems.
Suburban multi-stop delivery (retail, e-commerce, B2B)
Moderate inter-stop distances, mixed residential and commercial stops. Expect 2.5 to 4 stops per hour. More variation here because suburban stop types vary widely.
Rural delivery
Long inter-stop distances dominate the math. Expect 1 to 2.5 stops per hour. In rural markets, stops per hour is less useful than miles per stop as the primary efficiency metric — inter-stop distance is the variable that route optimization most directly affects.
How to Use Stops Per Hour to Measure Route Planning Improvement?
Route planning software generates the route. Your delivery analytics tells you whether the route produced results. Here’s how to connect them.
Establish a baseline before changing your routing
Before switching to a new route planner — or adding new optimization features — record your stops-per-hour rate for the prior 30 days, broken out by driver and route type. This is your pre-optimization baseline. Any improvement you see after the change is attributable to the change.
Without a baseline, you have no way to know whether the new system is working. You’re flying by impression instead of data.
Track stops per hour by driver, not just in aggregate
Fleet-wide stops per hour averages hide individual variation. A fleet average of 3.2 might include one driver at 4.8 and another at 1.9. Delivery management software that calculates per-driver stops per hour reveals who is performing above fleet average and who needs attention.
The driver at 1.9 might be on routes with longer inter-stop distances. Or they might be spending 20 minutes at every stop. The metric points to the question. Investigation answers it.
Compare stops per hour before and after route optimization changes
When you adjust your routing configuration — change time window settings, add zone restrictions, update stop time estimates — track whether stops per hour improves in the following two weeks. This is how you validate that routing changes are actually producing efficiency gains, not just theoretical improvements.
If stops per hour doesn’t move after a routing change, the change didn’t address the actual bottleneck. Keep investigating.
Building a Stops-Per-Hour Improvement Program
Calculate stops per hour weekly, not monthly. Monthly averages smooth out variation that weekly tracking would reveal. A week where stops per hour drops from 3.4 to 2.6 is a signal worth investigating — it might indicate a routing issue, a driver problem, or an external factor like road construction. Monthly averaging buries that signal.
Separate different route types in your analysis. Don’t average urban and rural routes together. Don’t mix food delivery routes with B2B distribution routes. Each route type has a different expected stops-per-hour range, and mixing them produces a number that’s hard to interpret.
Use stops per hour to evaluate driver performance fairly. A driver consistently below fleet average might be on worse routes, not working more slowly. Compare stops per hour controlling for route type before drawing conclusions about individual driver performance.
Set a quarterly improvement target. If your current stops-per-hour average is 3.1, set a 90-day target of 3.4. Specific targets make optimization efforts concrete — and reveal whether your route planning investment is generating measurable returns.
Frequently Asked Questions
How do you calculate stops per hour and why is it the right metric for evaluating a multi stop route planner?
Stops per hour is total stops completed divided by total driver hours worked — a driver completing 24 stops in 8 hours runs at 3.0. It captures the combined output of routing efficiency, stop execution speed, and driver time management, converting vague impressions about route quality into a trackable number that reveals whether the route planner is actually delivering gains.
What stops per hour benchmarks should operators use when evaluating a multi stop route planner by route type?
Urban food delivery routes typically achieve 4 to 6 stops per hour for well-optimized sequences. Suburban multi-stop routes fall in the 2.5 to 4 range. Rural delivery drops to 1 to 2.5 stops per hour, where miles per stop is often more informative than stops per hour because inter-stop distance dominates the math. Mixing route types in a single average makes the metric nearly uninterpretable.
Why should multi stop route planner performance be measured by individual driver rather than fleet average?
A fleet average of 3.2 might include one driver at 4.8 and another at 1.9, hiding whether the underperforming driver is on structurally inefficient routes or actually executing slowly. Per-driver stops per hour with a multi-stop route planner points to the right question — route structure or driver behavior — so investigation can answer it rather than averaging the signal away.
How should operators establish a baseline before switching multi stop route planners to know if efficiency improved?
Record stops per hour for the 30 days prior to any routing change, broken out by driver and route type. That pre-optimization baseline is the only way to attribute improvement to the new system — without it, any change in the number is indistinguishable from seasonal variation, and you’re evaluating the investment by impression rather than data.
The Metric That Makes Route Planning Accountable
Route planning software either improves your delivery efficiency or it doesn’t. Stops per hour is the measurement that tells you which is true. Track it consistently, break it down by driver and route type, and use it to evaluate every routing change you make.
The operations that improve fastest are the ones that measure carefully. Build the measurement first. The improvement follows.
