What is Actual Time of Departure (ATD)?
Actual Time of Departure (ATD) is the exact time when a vehicle, vessel, aircraft, train, or shipment physically leaves its origin point. It replaces the planned or scheduled departure time once the movement has actually started and is recorded in the transport or terminal system as a real event.
In logistics, ATD is a core milestone for tracking performance, calculating lead times, and updating customers or partners. It is often used together with ETA / ATA (Estimated / Actual Time of Arrival) to measure how reliably carriers and logistics providers execute their promises.
ATD in the Context of ETD, ETA, and ATA
1. Planned vs Actual Times
ETD (Estimated Time of Departure): The planned or forecast time when a shipment is expected to depart. Used in booking, scheduling, and initial customer communication.
ATD (Actual Time of Departure): The real departure timestamp when the vehicle or shipment has left the terminal, port, or warehouse.
ETA (Estimated Time of Arrival): The forecast time when a shipment is expected to arrive at the next node or final destination.
ATA (Actual Time of Arrival): The real arrival timestamp, recorded when the shipment physically arrives and is registered in the system.
2. Why ATD and ATA Matter Together
ATD and ATA form the actual transit-time window between two points in the network. Comparing this actual transit time with the planned transit time (ETD/ETA) reveals how well the transport network is performing.
Analysing the gap between ATD–ETD and ATA–ETA helps identify where delays originate: at origin (late departure), in transit (slower movement), or at destination (congestion, handling queues).
How ATD is Captured in Logistics Operations
1. Terminal and Port Systems
What it is: At seaports, airports, and rail terminals, ATD is typically generated by terminal operating systems (TOS) when a vessel, aircraft, or train passes a specific gate or status change.
Example events: “Gate out”, “Wheels up”, “Departed berth”, or “Train departed yard” can all trigger ATD updates depending on the mode.
2. Warehouse and Fulfilment Centres
What it is: In warehouses, ATD often corresponds to the time when a truck leaves the loading bay with all assigned shipments loaded and confirmed.
Typical process: The transport management system (TMS) or warehouse management system (WMS) records ATD after the final loading scan and gate confirmation, replacing the scheduled departure time.
3. Carrier and Parcel Networks
What it is: Parcel and express carriers record ATD when linehaul trailers or aircraft depart sorting hubs or depots. These events feed into tracking pages and APIs.
Impact: Customers often see status messages like “Departed facility” or “In transit”, which are based on actual departure scans and timestamps.
4. IoT and Telematics Data
What it is: For road freight, ATD can be derived from telematics and GPS data when a truck leaves a defined geo-fence around the warehouse or terminal.
Benefit: This avoids manual updates, improving accuracy and providing richer data for real-time visibility platforms.
Using ATD and ATA for Performance and Planning
1. Transit Time Measurement
What it is: Transit time between two points is calculated as the difference between ATD (origin) and ATA (destination).
Usage: Comparing actual transit time with agreed service levels (for example “48 hours door to door”) shows whether carriers and lanes are performing as promised.
2. Schedule Reliability and Delay Analysis
What it is: Analysing the difference between ETD and ATD at origin, and ETA and ATA at destination.
Patterns:
- Large gaps between ETD and ATD indicate origin-side issues (late loading, documentation problems, port congestion).
- Large gaps between ETA and ATA with on-time ATD indicate in-transit or arrival-side issues (weather, routing, destination congestion).
3. Customer Communication and Promises
What it is: ATD events trigger updated ETAs and customer notifications (“Your order has left the warehouse”). ATA events confirm delivery to the next node or final customer.
Value: Using real ATD and dynamic ETA calculations improves the accuracy of delivery estimates and reduces “Where is my order?” contacts.
4. Inventory and Planning Accuracy
What it is: Inbound ATD and ATA timestamps feed into available-to-promise (ATP), safety stock calculations, and production or sales planning.
Impact: Reliable actual times reduce the need for extra buffers and help planners trust the data when making inventory and allocation decisions.
Comparing Planned and Actual Times
| Term | Meaning | Type | Typical Use |
|---|---|---|---|
| ETD | Estimated Time of Departure | Planned / forecast | Booking, scheduling, capacity planning |
| ATD | Actual Time of Departure | Recorded event | Transit-time calculation, performance, visibility |
| ETA | Estimated Time of Arrival | Planned / dynamic forecast | Customer updates, resource planning at destination |
| ATA | Actual Time of Arrival | Recorded event | Lead-time measurement, demurrage/detention, billing |
ATD and ATA in Different Transport Modes
1. Ocean Freight
ATD: Time when the vessel leaves the port berth or pilot station. Used for freight invoicing triggers, transit measurement, and downstream ETA updates.
ATA: Time when the vessel arrives at the next port, often used to start free-time counters for demurrage and detention, and to plan container pick-up.
2. Air Freight
ATD: “Wheels up” time when the aircraft actually takes off, replacing scheduled departure time in airline and forwarder systems.
ATA: Landing time or “on block” time when the aircraft reaches the gate, used to estimate when cargo will be available in the warehouse.
3. Road Freight
ATD: Time when a truck leaves the shipper’s site, cross-dock, or hub, recorded manually or via geo-fence.
ATA: Time when the truck arrives at consignee or next hub, often paired with proof of delivery (POD) events.
4. Parcel and Last-Mile
ATD: Departure time from sorting centre or local depot, often represented as “Departed facility” in tracking.
ATA: Arrival at destination depot or final delivery event; in last mile, ATA often coincides with the delivery scan at the door.
Good Practices for Managing ATD and ATA Data
Standardise Event Definitions: Make sure all carriers and partners use consistent meanings for ATD and ATA (for example gate-out vs wheels-up) to avoid confusion.
Integrate Systems: Connect WMS, TMS, carrier systems, and visibility platforms so ATD and ATA updates flow automatically and in real time.
Use ATD to Refresh ETA: Update estimated arrival times whenever an actual departure occurs, rather than relying on static schedules.
Monitor Data Quality: Regularly check for missing, duplicated, or inconsistent ATD/ATA events and work with carriers to improve accuracy.
Link to Contracts and KPIs: Build KPIs like on-time departure and on-time arrival around ATD and ATA, and tie them to performance reviews and incentives.
Common Issues with ATD and ATA
Despite being simple timestamps, ATD and ATA can cause headaches if not managed carefully.
- Inconsistent time zones: Different systems storing local vs UTC times can make transit times look incorrect.
- Manual updates: Human-entered times may be late, rounded, or inaccurate, especially in busy terminals.
- Different event triggers: One carrier may log ATD at “gate out”, another at “departed yard”, leading to non-comparable data.
- Missing events: ATD or ATA not captured for some shipments, breaking KPI calculations and visibility.
- Delayed data feeds: Events recorded on time but sent in batches, which reduces real-time usefulness for customers and planners.
Measuring Performance with ATD and ATA
When used consistently, ATD and ATA underpin robust performance measurement across the end-to-end network.
- On-time departure rate (ATD vs ETD) by lane, carrier, and mode
- On-time arrival rate (ATA vs ETA) at hubs and final destinations
- Average transit time (ATA – ATD) and its variability
- Impact of late ATD on missed connections, late deliveries, and extra costs
- Customer promise adherence (delivered by promised date/time)
Conclusion
Actual Time of Departure (ATD) and Actual Time of Arrival (ATA) look like simple timestamps, but they are fundamental building blocks of reliable logistics. They turn planned schedules into measurable reality, enable honest performance reporting, and power accurate ETAs for customers.
By standardising how ATD and ATA are captured, integrating them across systems, and using them in KPIs and planning, supply chain teams gain a far clearer view of what is really happening between origin and destination – and where to improve next.
FAQ about Actual Time of Departure (ATD)
What is Actual Time of Departure (ATD) in simple terms?
ATD is the exact time when a shipment or vehicle really leaves a warehouse, terminal, port, or hub. It replaces the planned departure time once the movement has actually started.
How is ATD different from ETD?
ETD is the estimatedactual departure time recorded by the system when the shipment really departs.
What is ATA and how does it relate to ATD?
ATA (Actual Time of Arrival) is the real arrival time at the next node or final destination. Together, ATD at origin and ATA at destination define the actual transit time between two points in the network.
Why is ATD important for e-commerce brands?
ATD events trigger more accurate ETAs for customers (“Your order has left the warehouse”), help track carrier performance, and support planning for downstream hubs and delivery routes.
Who records ATD and ATA?
They are typically recorded by terminals, warehouses, carriers, or transport management systems – sometimes automatically via scanners or telematics, sometimes manually by staff.
How can ATD and ATA improve delivery estimates?
When a system knows the real departure time (ATD), it can recompute ETA based on live conditions and historical transit times, rather than relying on static schedules.
Can ATD be wrong?
Yes, if updated manually, delayed, or recorded in the wrong time zone. That is why standard definitions, automation, and data quality checks are important for ATD/ATA events.
How do companies typically use ATD/ATA data?
They use it to measure on-time performance, calculate transit times, manage carrier scorecards, support customer notifications, and feed analytics or AI models that optimise routes and inventory.
