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Compare shipment contribution and transit reliability by customer and lane using matched revenue, carrier-cost, and delivery records. A worked US freight example shows the calculations, reconciliations, and decisions behind the comparison.
Data analytics in logistics compares shipment contribution and transit reliability using the same customer, lane, and reporting definitions. Start with matched shipment, revenue, carrier-cost, and delivery records. A profitable lane with repeated delivery failures needs a different response from a reliable lane whose accessorial costs absorb its margin.
For an illustrative US freight broker, the unit of analysis is one completed shipment. The reporting period follows delivery date, with revenue and costs assigned to those shipments even when an invoice arrives later. Open shipments remain in a separate reconciliation until their outcomes are known.
Define a lane as origin area, destination area, direction, and service class. Chicago to Atlanta is distinct from Atlanta to Chicago. Consolidate spelling variants into one customer name, but retain the underlying shipment IDs so the totals can be checked.
Use net customer revenue after credits. Define variable costs before calculating contribution: purchased carriage, shipment-specific accessorials, and variable handling costs in this example. Fixed office salaries and rent stay outside that measure. OpenStax's contribution-margin explanation identifies the amount remaining after variable costs as available to cover fixed costs and profit.
If a report deducts allocated fixed costs too, give that result a different name. The distinction between gross margin, contribution margin, and net margin prevents a shipment comparison from becoming an unsupported statement about company profitability.
The broker's completed-shipment file contains the following records. Chicago is the origin of both lanes. All cost fields are net of recorded carrier credits, and the accessorial column excludes charges already included in purchased carriage.
| Shipment | Customer | Destination | Revenue (USD) | Carriage (USD) | Accessorials (USD) | Variable handling (USD) | Contribution (USD) |
|---|---|---|---|---|---|---|---|
| S1 | A | Atlanta | 1,200 | 850 | 100 | 50 | 200 |
| S2 | A | Atlanta | 1,000 | 780 | 70 | 50 | 100 |
| S3 | B | Dallas | 1,500 | 1,050 | 180 | 70 | 200 |
| S4 | B | Dallas | 1,300 | 950 | 100 | 50 | 200 |
| S5 | A | Dallas | 1,400 | 1,000 | 80 | 70 | 250 |
| S6 | B | Atlanta | 1,100 | 800 | 60 | 40 | 200 |
| Total | 7,500 | 5,430 | 590 | 330 | 1,150 |
Shipment contribution = Net shipment revenue - Purchased carriage - Accessorials - Variable handling
Contribution margin = Shipment contribution / Net shipment revenue
S1 contributes 1,200 - 850 - 100 - 50 = $200. Across all shipments, variable costs are 5,430 + 590 + 330 = $6,350, leaving 7,500 - 6,350 = $1,150. The overall contribution margin is 1,150 / 7,500 = 15.3%, rounded to one decimal place.
The control is an identity: revenue of $7,500 equals variable costs of $6,350 plus contribution of $1,150. Separately tie customer revenue to the invoice register and carrier charges to the payable register, including documented accruals for unbilled services. A correct subtraction does not prove that all invoices were included.
Measure elapsed transit from the agreed pickup event to delivery confirmation, using one time zone or properly converted timestamps. Preserve the original customer deadline. This example expresses that deadline as elapsed hours after pickup and treats arrival exactly at the deadline as on time.
| Shipment | Agreed deadline after pickup, hours | Actual transit hours | On time? |
|---|---|---|---|
| S1 | 24 | 30 | No |
| S2 | 24 | 24 | Yes |
| S3 | 36 | 42 | No |
| S4 | 36 | 34 | Yes |
| S5 | 36 | 36 | Yes |
| S6 | 24 | 26 | No |
| Total | 3 of 6 |
On-time delivery rate = Shipments delivered by their agreed deadline / Eligible completed shipments
The total is 3 / 6 = 50.0%. Both the numerator and denominator refer to the same completed shipments used for contribution. Flag missing confirmations rather than treating a blank timestamp as an on-time delivery.
The Federal Highway Administration describes travel-time reliability as consistency or dependability in travel times, and explains why an average alone misses difficult days. For this business comparison, deadline compliance makes the service question explicit; the detailed transit hours remain available to investigate variation. The broader logistics KPI guide covers other delivery and warehouse measures.
Group the same shipment IDs in different ways. Each grouping must independently add back to the company total; customer and lane totals must never be added to each other.
| View | Shipments | Revenue (USD) | Variable costs (USD) | Contribution (USD) | Contribution margin | On-time delivery |
|---|---|---|---|---|---|---|
| Customer A | 3 | 3,600 | 3,050 | 550 | 15.3% | 2 / 3 = 66.7% |
| Customer B | 3 | 3,900 | 3,300 | 600 | 15.4% | 1 / 3 = 33.3% |
| Customer total | 6 | 7,500 | 6,350 | 1,150 | 15.3% | 3 / 6 = 50.0% |
| Chicago-Atlanta | 3 | 3,300 | 2,800 | 500 | 15.2% | 1 / 3 = 33.3% |
| Chicago-Dallas | 3 | 4,200 | 3,550 | 650 | 15.5% | 2 / 3 = 66.7% |
| Lane total | 6 | 7,500 | 6,350 | 1,150 | 15.3% | 3 / 6 = 50.0% |
Percentages use unrounded amounts and are displayed to one decimal place. Customer B contributes more dollars than A but misses more commitments. Chicago-Atlanta also needs service review. Neither observation proves a cause: examine the underlying late shipments before changing a carrier agreement or customer promise.
Finance owns cost classification and the invoice reconciliation. Transportation owns pickup and delivery definitions. Account management owns the customer commitment and the response when service falls short. Review the combined table together so a service improvement is evaluated alongside its cost.
Suppose a documented carrier credit reduces S3 accessorials from $180 to $60. The reduction is $120, so S3 contribution rises from $200 to $320. Company variable costs fall from $6,350 to $6,230, and company contribution rises from $1,150 to $1,270.
The revised contribution margin is 1,270 / 7,500 = 16.9%. Delivery outcomes remain 3 / 6 = 50.0% because no service record changed. The check is 6,230 + 1,270 = $7,500. A better financial result alone does not establish better transit reliability.
This is descriptive analysis of completed work. Use predictive analytics for logistics when the question becomes whether a forecast anticipated future volume or transit outcomes accurately.
Bring your shipment, invoice, carrier-cost, and delivery export as a file or Google Sheet; Covirage maps the columns, and its tools compute and check the figures. The external AI model explains the customer and lane comparisons with every figure traced to its rows. Create a free Covirage account and bring a sample of your own data.
See Covirage for shipping and logistics for the industry context.
Start with shipment records, customer invoices and credits, carrier charges, and delivery confirmations. Use shipment IDs to connect the records. Keep the original delivery commitment, lane, service class, and a clear reporting cutoff so costs and service describe the same completed work.
No. Shipment contribution subtracts the variable costs defined for the analysis from shipment revenue. It shows what remains toward fixed costs and profit. Corporate salaries, rent, and other fixed expenses still need to be covered before the company earns net profit.
Only with context. Different distances, service classes, and customer commitments create different expected transit times. Compare actual performance against each shipment's agreed deadline, then investigate transit variation within comparable lanes rather than interpreting a shorter overall average as better service.