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Industry · Air cargo

“How much of what we booked actually flew?”

A cargo team asks how much of what was booked actually flew. The answer depends on the agreed rule: which booking cohort counts, when it is frozen, and which weight is compared. Duodata captures that definition once, with an owner, and puts it to work in your platform.

For cargo operations and commercial teams · Cargo operations · Commercial planning · Finance

3:53 · English captions
Duodata overview — air cargo. Illustrative demonstration with fictional data.
Worked example

Booked-to-flown gross weight, defined precisely

Booked-to-flown gross weight realization compares one frozen booking cohort at two moments: the gross freight mass of distinct confirmed booking pieces, frozen 24 hours before the original departure (UTC), against the gross mass that actually flew from that same cohort — linked by the original piece IDs and counted once per route segment. It is not load factor (capacity utilisation) and not recognized revenue — it answers whether booked demand materialised.

“How much of what we booked actually flew?”

Definition A · original departure

Gross mass flown ÷ gross mass booked, cohort frozen at T-24h before the original departure

Original departure cohort

Cancelled and waitlisted bookings are excluded at the cutoff. A shipment keeps its original departure assignment even if it is later cancelled or split.

Definition B · 48-hour measurement window

Same frozen cohort, flown mass counted within a 48-hour measurement window

Measurement-window cohort

A deliberate change of definition: the cohort is the same, the window in which flown mass counts is not. The change is recorded with an owner — it is not an operational improvement.

The AI answer and the operational and commercial decision behind it depend on which definition is agreed. Duodata records the rule once — the cohort, the cutoff, the piece-level link and the window — so the number AI gives is the number the business decided to use.

Illustrative example with fictional data. Not a measured customer result.

Platforms

Put this meaning to work in your platform.

Databricks

The agreed definition deploys as Unity Catalog metric views, answered by AI/BI Genie.

Snowflake

The agreed definition deploys as Semantic Views, answered by Cortex Analyst.

Free pilot

Start a free pilot

We work through one business question with you: agree its meaning, map it to the relevant data and review how it works on Snowflake or Databricks. We agree the scope together before we start.