Case 05Dairy & Agri-tech
Allocating product against test results, not spreadsheets
An automated allocation system joining sales, logistics and laboratory testing data — roughly 10 hours of manual calculation removed each week, with delivery accuracy at 99%.
Client
South Island dairy processor
Year
2022
The Problem
Dairy export allocation is a constraint problem wearing a spreadsheet. Each market carries its own specification, each batch carries its own laboratory results, and the match between them decides what can ship where.
Done manually, the work is slow enough that it can only be run once, which means the answer is the first feasible allocation rather than a good one — and inventory carries the difference.
What We Did
- Integrated sales, logistics and laboratory testing data into a single allocation dataset.
- Automated the allocation itself, optimising against customer and country-specific requirements while minimising inventory held.
- Built Python web applications consolidating sales data, so sales managers could validate customer requirements and check inventory availability before submitting an order.
- Designed Power BI reporting on a structured fact and dimension model, giving the operation self-service analytics instead of a weekly report cycle.
The Result
- Approximately 10 hours per week of manual calculation eliminated.
- Delivery accuracy improved to 99%.
- DIFOT performance improved and dispatch errors reduced through better operational visibility.
- Sales decisions moved upstream of order submission, maximising profit per sale.
Also Delivered
- Health and safety records migrated from Excel to a structured database, integrated with the KaiNexus platform over REST/JSON using Power Automate and Python.
- Order management and returns processing automated with UiPath RPA in Microsoft Dynamics AX.
Technology
PythonPower BIDAXFact and dimension modellingPower AutomateUiPathMicrosoft Dynamics AXREST APIs
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