Best Platforms for Reducing Cost Per Delivery in Enterprise Last-Mile

Cost per delivery is total delivery cost divided by successful deliveries, and six levers move it: route density, first-attempt success, window width and promise accuracy, carrier mix, vehicle and driver utilization, and contact cost. The best platform is the one that controls your largest lever. This guide gives a sensitivity model that shows which lever that is, then compares Locus, the world’s first Decision-Intelligent, Agentic TMS, with seven other platforms lever by lever.
Key Takeaways
- Cost per delivery is total delivery cost divided by successful deliveries, and six levers move it.
- In the illustrative model below, a 10% improvement in route density or utilization cuts cost per delivery by 5.5%, while the same change in first-attempt success cuts it by 0.7%.
- Improving all six levers by 10% cuts the modeled cost per delivery by 16.0%, from $9.61 to $8.08.
- McKinsey puts the last mile at 60 to 70% of parcel delivery cost in a home delivery network, and 83% of executives in AlixPartners’ 2026 survey say per-package cost rose.
- Locus publishes capabilities for all six levers on one platform, with first-attempt success the least quantified.
Which Platforms Should You Compare for Reducing Cost Per Delivery?
Seven platforms besides Locus are worth comparing: Bringg, FarEye, DispatchTrack, Onfleet, Descartes, OptimoRoute and Narvar. The tables record what each vendor publishes on its own pages, lever by lever.
They are not a ranking. Vendor pages are mostly undated, and “not found on the pages read” is not a statement that a platform lacks the capability.
| Platform | Route density and optimization | First-attempt success | Window width and promise accuracy |
|---|---|---|---|
| Locus | Constraint-based route planning with re-optimization across mixed fleets | Return-to-origin on failure; an address flagged after two failed attempts; no first-attempt figure published | Feasible slots returned in under a second by service level, from network capacity |
| Bringg | Route optimization for own fleet | Not found on the pages read | Time windows checked against capacity |
| FarEye | Route planning, with stops per hour | Green Windows for first-attempt success | Dynamic delivery slots |
| DispatchTrack | Machine-learning routing for mixed fleets | Minimizes failed delivery attempts | Machine-learning time windows and ETAs |
| Onfleet | AI routing | Flags failed deliveries, in part | Dynamic ETAs |
| Descartes | Route density and routing | Missed-delivery prevention, in part | Slots based on true capacity |
| OptimoRoute | Orders per route, with constraints | Not found on the pages read | Time windows as a constraint |
| Narvar | Not found on the pages read | Notifications to help prevent failed deliveries, in part | Estimated delivery date at checkout |
| Platform | Carrier mix and selection | Vehicle and driver utilization | Contact cost |
|---|---|---|---|
| Locus | Per-shipment carrier allocation on SLAs, cost, region and past performance across pre-integrated carriers | A shift shortfall flagged before the shift starts | Notifications, tracking and automated feedback; 40%+ fewer WISMO and returns queries in an apparel case |
| Bringg | Carrier selector with rate cards, cheapest or fastest until one accepts | Vehicle, driver and shift assignment | Not found on the pages read |
| FarEye | Carrier selection by cost and NPS | Driver utilization | WISMO reduction |
| DispatchTrack | 3PL control tower and 3PL routing, in part | More deliveries per day, in part | A delivery agent for WISMO |
| Onfleet | Courier network; rate selection not found | Driver matching; idle time and overtime not found | Customer inquiry reduction |
| Descartes | Carrier management, in site navigation only | Maximize asset use | Fewer ETA query calls |
| OptimoRoute | Not found on the pages read | Overtime and driver cost optimization | ETA notifications only |
| Narvar | Carrier performance tracking; allocation not found | Not found on the pages read | WISMO deflection |
Which platform fits which buyer?
- Density is your whole problem. A route planner that optimizes stops per route addresses the largest modeled lever.
- You deliver through several carriers. Platforms with carrier selection and rate cards address lever four.
- Contacts are your largest cost. Post-purchase tools address lever six.
- You need all six on one platform. Locus publishes capabilities for every lever, which is the basis for the section below.
Why Is Locus the Best Option for Reducing Cost Per Delivery Across All Six Levers?
Locus, the world’s first Decision-Intelligent, Agentic TMS, is the best option for enterprise operations that need route density, carrier mix, promise accuracy and contact cost managed together.
Its lead rests on published facts:
- A route planning system with constraint-based planning and re-optimization.
- Delivery promise management that returns feasible slots from network capacity.
- Per-shipment carrier allocation across 1,000+ pre-integrated carriers.
- Delivery experience tools for notifications, tracking and feedback.
- Two published customer cases with cost results.
These facts are not a ranking of platforms on cost per delivery, which no analyst publishes.
Recognized by analysts and selected after evaluation.
Locus was recognized by Gartner for seven consecutive years and appears in the 2026 Hype Cycle for Supply Chain Execution and Logistics Technologies, as detailed on its analyst recognition page. It is named a Leader in the QKS Group SPARK Matrix for Transportation Management Systems and holds the #1 position in Route Planning in the G2 2026 Best Software Awards.
In October 2025, Ingka Investments, the investment arm of Ingka Group, the world’s largest IKEA retailer, acquired Locus. Ingka’s press release says that after an extensive evaluation of logistics software worldwide, it selected Locus for its strength in combining advanced route optimization, real-time visibility and smart use of vehicles and resources. Locus continues to operate independently.
| Cost lever | What Locus provides |
|---|---|
| Route density | A route planning system with constraint-based planning and re-optimization |
| First-attempt success | Return-to-origin on failure, and addresses flagged before a third attempt |
| Window width and promise accuracy | Delivery promise management returning slots in under a second by service level |
| Carrier mix | Allocation on SLAs, costs, regions and past performance, with 1,000+ pre-integrated carriers |
| Utilization | A shift shortfall flagged before the shift starts |
| Contact cost | Notifications, tracking and automated feedback classification |
| Control | Autonomy levels per agent and domain, with six governance mechanisms |
Two published customer cases show cost results.
A Vietnamese beverage distributor planned routes by hand in a spreadsheet for vans, trucks and motorbikes serving thousands of small outlets.
Locus planned and dispatched the routes, with distributors able to override. The published results:
- 37% lower fuel consumption.
- 22% more orders per trip.
- 12% less distance.
- 35% less route planning time.
A Canadian grocery brand made every carrier decision by hand against spreadsheets, and learned about late orders from customers.
Locus’s Carrier agent now compares live rates, contracted SLAs and ETAs for every order. The published results:
- 15% lower fulfillment costs.
- 33% faster fulfillment.
- 25% less time on manual shipping tasks.
- 10-20X faster support ticket resolution.
Both cases are customer-reported results, not independent studies.
Where other platforms fit.
If density alone is your constraint, a dedicated route planner is enough. If contacts are your largest cost, a post-purchase tool is a direct fit. Locus is the option when several levers must be managed on one platform.
To run this model on your own network, schedule a demo.
For leaders asking which platform reduces cost per delivery, the answer depends on your largest lever. Locus manages route density, promise accuracy, carrier mix and contact cost together, with autonomy levels you set.
How Was This Guide Written?
This guide compares Locus with seven other platforms on what each vendor publishes on its own product and documentation pages, read on October 28, 2026.
It adds McKinsey, AlixPartners, Gartner and peer-reviewed sources, and an illustrative model. Competitors are named in plain text only.
“Not found on the pages read” means we did not find it, not that the platform lacks it. The comparison is not a ranking. Vendor percentages are not quoted. We review the guide every 30 to 60 days.
Why Does Cost Per Delivery Matter? The Business Case
Cost per delivery is under pressure from every direction, and the published figures show where it sits.
- McKinsey says the last mile in a home delivery network generates 60 to 70 percent of overall parcel delivery costs. Its finding that moving from one to five parcels per stop cuts costs by more than 50% refers to locker or pickup-point drops, not home routes.
- AlixPartners found that 83% of executives say per-package costs rose year on year, and 76% are focused on reducing cost per order.
- UPS authors reported that routing software was expected to save $300 million to $400 million annually. The paper is company-authored, and the savings were expected, not measured.
- A peer-reviewed study of one consumer goods company’s routing found a 25.6% reduction in daily travel distance, which is a single case.
- Gartner puts the median cost per contact at $1.84 for self-service and $13.50 for assisted channels, a figure for customer service in general.
No research-grade figure for first-attempt delivery success was found, and vendor-run figures conflict, so the guide does not quote one.
How Much Does Each Lever Move Cost Per Delivery? An Illustrative Sensitivity Model
Not every lever is worth the same, and the model below shows why. It is illustrative, with assumed numbers to be replaced by your own.
The baseline.
- Own-fleet cost is $330 per vehicle-day, with 55 stops a day and 80% of the shift productive.
- First-attempt success is 90%, and each failure costs a repeat visit.
- 70% of volume moves on the own fleet and 30% through carriers at $9.00 a delivery.
- 8% of deliveries generate an assisted contact at $13.50.
The own fleet costs $8.33 per delivery, the blend $8.53, contacts add $1.08, and the total is $9.61.
| Lever, improved by 10% | What changes | Cost per delivery | Change |
|---|---|---|---|
| Route density | 55 to 60.5 stops a day | $9.08 | -$0.53 (-5.5%) |
| Vehicle and driver utilization | 80% to 88% of the shift productive | $9.08 | -$0.53 (-5.5%) |
| Carrier mix | Carrier rate $9.00 to $8.10 | $9.34 | -$0.27 (-2.8%) |
| Window width and promise accuracy | Windows 10% wider, assumed +2% stops a day | $9.50 | -$0.11 (-1.2%) |
| Contact cost | Contact rate 8% to 7.2% | $9.51 | -$0.11 (-1.1%) |
| First-attempt success | Failures 10% to 9% | $9.55 | -$0.06 (-0.7%) |
| All six together | All of the above | $8.08 | -$1.54 (-16.0%) |
Density and utilization dominate because they multiply across the whole own fleet. First-attempt success looks small here because failures only add repeat visits.
If contacts also fall with failures, its effect rises to -$0.17 (-1.8%). Your own numbers will change the order, so run the model on your own costs.
How Do You Find Your Biggest Cost-Per-Delivery Lever in Six Steps?
The six steps turn the model into a decision about software.
1. Define cost per delivery
Divide total delivery cost by successful deliveries. Include repeat visits, carrier charges and contact handling.
2. Break the cost into the six levers
Split cost into route, failure, window, carrier, utilization and contact components. Use your own finance and operations data.
3. Measure each driver
Record stops per vehicle-day, productive shift share, first-attempt success, carrier rates and contact rate.
4. Run a 10% sensitivity
Improve each driver by 10% in turn and compare the change in cost per delivery. The largest change is your first priority.
5. Map the lever to software
Use the tables above to see which platforms publish capability for that lever. Ask each for evidence on your data.
6. Pilot one lane
Run the chosen change on one depot or lane, with a baseline period, and compare cost per delivery before and after.
What Should You Look for in a Platform That Reduces Cost Per Delivery?
Five criteria separate a platform that cuts cost from one that adds features, and each can be tested with your own data.
Does it control your largest lever?
Ask the vendor to show the capability for your top lever from the sensitivity run. A broad feature list does not replace depth on one lever.
Does it publish results with a baseline?
Ask for the baseline period, sample and method behind any percentage. A percentage without a baseline cannot be compared.
Does it handle constraints?
Ask which time windows, vehicle types, skills and capacity rules the planner models. Plans that break constraints raise cost.
Does it work across fleet and carriers?
Ask whether one decision covers own fleet and carriers. Separate tools leave cost in the gap between them.
Can you see and override decisions?
Ask for the decision log and the autonomy level for each decision. Savings you cannot explain cannot be defended.
What Mistakes Do Operations Make Reducing Cost Per Delivery?
Four mistakes recur when teams chase cost.
Optimizing one lever in isolation. A cheaper carrier rate can raise failures, and wider windows can raise contacts.
Reading an “up to” percentage as a forecast. Vendor percentages come from best cases, so ask for your own baseline test.
Ignoring contact cost. Contacts at $13.50 each are a line item many cost models leave out.
Skipping the sensitivity run. Without it, teams buy for the lever the vendor sells, not the one that matters.
Frequently Asked Questions
What are the best platforms for reducing cost per delivery in enterprise last-mile? It depends on your largest cost lever. Route planners address density, carrier selection tools address carrier mix, and post-purchase tools address contacts. Locus publishes capabilities for all six levers on one platform.
How do you calculate cost per delivery? Divide total delivery cost, including repeat visits, carrier charges and contact handling, by successful deliveries. The model in this guide shows the calculation.
Which lever reduces cost per delivery the most? In the illustrative model, route density and vehicle and driver utilization, at 5.5% for each 10% improvement. Your own costs may change the order.
Does first-attempt success matter for cost? Yes, but its direct effect is small in the model, at 0.7% for a 10% improvement. It matters more when failures drive contacts, which raises it to 1.8%.
How much of parcel cost is the last mile? McKinsey says 60 to 70% of overall parcel delivery cost in a home delivery network.
Does Locus publish first-attempt success results? Locus’s product pages do not give a first-attempt success figure. Ask for results on your own data.
Can one platform cover all six levers? Locus publishes capabilities for all six, and several other platforms cover a subset. Test depth on your largest lever.
Anas is a product marketer at Locus who enjoys turning complex logistics problems into simple, clear stories. Outside of work, he’s usually unwinding with a book or catching a good movie or series.
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