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Delivery Economics Dashboard

A white-glove delivery operation losing $1,156 on 13 orders — and the fix isn't routing, it's pricing.

White-glove furniture delivery · 13 customers · Bay Area · a national luxury furniture retailer

Service standard is fixed: no split orders · full install + staging + cleanup

Executive Summary

The operation, the loss, and the answer — in one screen.

The finding: this is a pricing problem, not a routing problem. Labor is 92% of cost and happens inside customers' homes, where routing can't touch it. A 20% routing improvement saves $96 against a $1,156 loss.
26,369
cu ft delivered
21
truckloads
7
working days
396
miles
74%
avg utilization
−$1,156
net on the book

What was asked

Optimize routes, truck loading, and the daily schedule for 13 customers — then answer whether flat-rate delivery fees should change, by how much, and why.

What the numbers say

$6,043 in cost against $4,887 in fees. Eight of thirteen customers lose money; the five smallest orders subsidize the rest.

The recommendation

Volume-based pricing at $150 + $0.25/cu ft — or +$88.94 per delivery on flat fees. Bigger truck as the capital lever: it flips the loss into a $508 profit.

Modeling Approach

How the optimization was structured — and what was deliberately not optimized.

Primary objective: minimize total cost. Labor is 92% of cost; fuel is 8%. Optimizing routes affects only the 8%. Therefore the model prioritized minimizing working days over minimizing miles.

Sequencing decisions

1 · Geographic clustering

Group customers by proximity to minimize travel between stops — six Bay Area clusters around the SF SOMA warehouse.

2 · Load packing

Bin-pack orders into the 1,700 cu ft truck without splitting any customer's order across loads.

3 · Day assignment

Assign loads to days inside the 540-minute (9-hour) work window, keeping 3 loads per day.

Trade-off accepted: 74% average utilization rather than 100% — forcing perfect packing would split customer orders across days, degrading the white-glove experience and adding labor cost.

Constraint hierarchy

ConstraintValueBinding?Impact
Daily work window540 min (9 hrs)YESLimits loads to 3 per day
Truck volume1,700 cu ftYESRequires 21 loads for 26,369 cu ft
Truck weight7,000 lbsNOVolume fills first in most loads
Operating daysTue–SatNO7 working days span two weeks
Service standardWhite glove, fixedYESNo split orders, no rushed crews — rules out cost-only moves

Optimization Results

The 7-day schedule: 21 loads, every day inside the work window.

26,369
cu ft · total volume
21
truckloads
7
working days
74%
avg utilization

Daily delivery schedule

DayLoadsTravelServiceTotalMilesBufferStatus
Buffer > 60 min
Can absorb a same-day reschedule
Buffer 30–60 min
Tight but manageable
Buffer < 30 min
Risk of overtime if disrupted

Buffer = 540-minute window minus scheduled travel + service. Days 1–3 run tight — they carry the reschedule risk.

Route Visualization

Six geographic clusters around the SF SOMA warehouse. Select a day to see its route; same-day stops stay inside one cluster.

Geographic clusters

Customer volumes

Cost Analysis

Where the money goes — and what the flat fees cover.

Cost structure

Revenue & profit

Adjust parameters

Defaults are the case-documented values. Every figure on this page recomputes live.

Scenario Comparison

Three alternatives tested against the base case — tune the inputs and watch the verdicts move.

MetricBase caseSpeedLuxuryCapacity

Speed: parallel crews, 10% coordination overhead per truck, 15% deadhead fuel per extra truck. Luxury: 7.5 hrs/day at premium pace. Capacity: fewer trips in a bigger truck.

Pricing Strategy

Should flat-rate fees be reviewed?

Yes.
The problem with flat fees. One customer ordered 3,970 cu ft requiring 3 loads; another ordered 276 cu ft. Both pay $399. The fee ignores the cost driver.

Option A: flat increase

+$88.94 per delivery to break even — local becomes $387.94, extended $487.94. Simple, but it doesn't address the volume disparity.

Option B: volume-based RECOMMENDED

$150 + $0.25/cu ft. A 276 cu ft order pays $219; a 3,970 cu ft order pays $1,143. Aligns price with actual delivery cost.

Impact on actual customers

CustomerVolumeZoneCurrentProposedChange

Operations System

The spreadsheet plans the week. Running the day takes a system — for the dispatcher, the salesperson, and the driver.

The gap: Excel handles weekly planning. Daily operations need real-time decision systems for customer reschedules, traffic delays, no-shows, and instant quotes.

System architecture

+----------------------------------------------------------+
|                  DELIVERY OPERATIONS                 |
+----------------------------------------------------------+
|                                                          |
|  +----------+      +----------+      +----------+        |
|  | PLANNING |      | DISPATCH |      |  SALES   |        |
|  | (weekly) |----->| (daily)  |<---->| (quote)  |        |
|  +----------+      +----------+      +----------+        |
|       |                 |                  |             |
|       +-----------------+------------------+             |
|                         |                                |
|                         v                                |
|  +--------------------------------------------------+    |
|  | SHARED DATABASE                                  |    |
|  | orders · truck GPS · buffer remaining            |    |
|  | pricing rules · reschedule history               |    |
|  +--------------------------------------------------+    |
+----------------------------------------------------------+

Three tools

1 · Sales quoting tool

iPad/POS plugin — salesperson enters cubic feet, gets the price instantly.

$150 + ($0.25 × volume)

Surcharges: stairs +$50 · expedited +$150 · assembly +$100

2 · Dispatch dashboard

Live truck locations, buffer remaining per day, one-click reschedule, overtime alerts.

Buffer signal: >60 min · 30–60 · <30

3 · Driver app

Navigation plus three exception buttons — the driver taps, the system handles the logic.

Traffic delay → ETAs update · No answer → wait timer starts · Reschedule → logged, new slot found

Proposed Operational Design Flow — decision rules, the dispatch live view, the disruption playbook, the no-show live scenario, the cost-impact calculator, and the implementation roadmap.
Open the full design →

Interactive Tools

Working calculators built on the same cost model.

Pricing calculator

–
Current flat fee
–
Proposed price
–
Difference

Labor rounding calculator

–
Rounded hours
–
Billable cost

Rule: 15-minute increments, round up at 7+ minutes. Rate: $104/hr.

Disruption policy

· 1st reschedule: free

· 2nd+ reschedule: $75 concierge fee

· No-show: $75 fee + next available window

Wasted trip cost: $208 (2 hrs × crew rate) — the fee covers a third of it; the rest is the price of the promise.

Key numbers

Total cost: $6,043 · Labor 92% ($5,564) · Fuel 8% ($479)

Loads: 21 · Days: 7 · Miles: 396 · Utilization: 74%

"This is a pricing problem, not a routing problem."

"Delivery is a cost center, not a profit center — at current prices."