Logistics and supply chainBI, AI and ML for the business
Delivery times and carrier punctuality
Every shipment leaves a dispatch time and a delivery time, scattered between the warehouse and the carriers' files. Muvia brings them together: where time is lost between warehouse and customer, which carrier slows down in which area and from which week, and the carrier review already written.
Illustrative scenario: it describes a typical case, not a customer project.
The customer remembers the delay. Whose fault it was, often nobody knows.
A delivery goes through the warehouse, the pickup, the carrier and the last mile. Each stage leaves a timestamp in a different system: the warehouse has the shipment, the carrier has the outcome in a file or on its portal.
Without joining them, the carrier review runs on gut feeling. With every timestamp in one place, the delay has a name: a carrier, an area, a week.
- Who it's for
- Logistics and transport managers, customer service and whoever negotiates carrier contracts.
In Muvia, step by step
Real product screens, recorded on a project with sample data.
The video · Every shipment leaves a dispatch time and a delivery time, scattered between the warehouse and the carriers' files. Muvia brings them together: where time is lost between warehouse and customer, which carrier slows down in which area and from which week, and the carrier review already written.
What you get
- The delay has a name
- Carrier, area and week: you know where time is lost, not just that it is.
- You see since when
- The week-by-week trend shows when a carrier started slowing down, before customers complain.
- The review arrives written
- The carrier notebook goes out on fresh data, with no extracts from the carriers' portals.
- Negotiations on shared numbers
- With the carrier you discuss deliveries measured the same way for everyone.
For the technical team
How it is built in Muvia
- 1
Join shipments and outcomes
The warehouse database is copied every night, incrementally; the carriers' files arrive over SFTP and tracking from a REST API. A query links shipment and outcome on the shipment number and works out the hours from dispatch to delivery.
- 2
Follow the route on the dashboard
A Sankey diagram follows shipments from warehouse to area to carrier, a sunburst shows where the hours of delay pile up and a ranking lines up the carriers by punctuality.
- 3
Drill down week by week
In Analysis, compare the distribution of delivery times week by week, with a box per period, and area by area: you see from which week a carrier started to slow down.
- 4
Write the carrier review
A notebook with text, numbers and charts sums up each carrier's times and punctuality and becomes a scheduled PDF for the logistics manager.
- 5
Set a threshold on punctuality
An alarm opens when a carrier's punctuality in an area falls below the agreed standard; in the register, whoever handles it notes what they asked the carrier.
- The data it needs
- Shipments with dispatch time, warehouse and destination, from the warehouse database on PostgreSQL
- Delivery outcomes and times, carriers' CSV files received over SFTP
- Tracking events read from a carrier's REST API
- Delivery areas and promised times per area, from an Excel file
- Parts of Muvia used
More cases in this line
All use cases- Demand and stock forecastingSales history and stock levels are already in the ERP. Your data scientist builds a forecasting model with scikit-learn; Muvia runs it every night next to the data and puts forecast, actual sales and understock in front of the people who reorder.
- Stock coverage and low-stock alarmsSales and stock by item already live in the ERP and the warehouse system. Muvia works out every day how many days of cover each item has left, opens an alarm when it drops below the threshold and closes it by itself once goods arrive, with who handled it in the register.
- Supplier punctuality and OTIFReceipt lines already tell you who delivers on time and in full, provided the data is clean. In Muvia, rules on the data set aside the impossible rows, OTIF is worked out delivery by delivery, and the supplier ranking shows who is slipping and since when.
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