Logistics and supply chainBI, AI and ML for the business
Supplier punctuality and OTIF
Receipt 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.
Illustrative scenario: it describes a typical case, not a customer project.
A negotiation with a supplier starts from a number both sides can dispute.
OTIF, delivered on time and in full, is the number purchasing negotiates on. But receipt lines hold impossible dates, negative quantities and orders with no promised date, and a few of them are enough to argue about the data instead of the supplier.
Before measuring, you need rules on the data, declared and visible. Then an OTIF worked out the same way every time, delivery by delivery, and a ranking that shows who is slipping and since when.
- Who it's for
- Purchasing, buyers and category managers, supply chain and supplier quality managers.
In Muvia, step by step
Real product screens, recorded on a project with sample data.
The video · Receipt 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.
What you get
- Argue about the supplier, not the data
- The rules on the data are declared and visible: whoever reads OTIF knows which rows were set aside and why.
- One definition of OTIF
- On time and in full are worked out the same way for every supplier and every meeting.
- The decline has a date
- The ranking and the trend show when a supplier started delivering late or short, before the warehouse says so.
- Numbers ready for the negotiation
- The report reaches purchasing already up to date, with the deliveries behind it.
For the technical team
How it is built in Muvia
- 1
Connect orders and receipts
The ERP and the warehouse become sources copied every night, incrementally and over an encrypted connection; the supplier master arrives as a file. Every source becomes a table.
- 2
Declare rules on the data
Put Data Checks on the receipts query: impossible dates, negative quantities, missing promised dates, late or incomplete deliveries. Some rules quarantine the rows, others only flag them, and each says how many rows it found.
- 3
Work out OTIF in steps
A step-built query compares promised dates and quantities with what was received and marks each delivery as on time, in full or both. The result becomes a dataset with stable fields.
- 4
Build the ranking
A dashboard lines up suppliers by OTIF, with the week-by-week trend and a heatmap by supplier and family: you see who is slipping and from which day.
- 5
Bring the number to the table
A notebook with the ranking and each supplier's deliveries becomes a monthly PDF for purchasing. With Athena, a buyer asks for a supplier's details and sees the query it ran.
- The data it needs
- Purchase orders with promised dates and quantities, from the ERP on SQL Server
- Receipts with actual dates and quantities, from the warehouse database on PostgreSQL
- Supplier master and product families, from an Excel file
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.
- Delivery times and carrier punctualityEvery 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.
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