Having spent considerable time overseeing accounts payable automation projects firsthand, I possess a detailed understanding of the hurdles associated with aligning invoice line data with corresponding order and receipt line data.
Among our ongoing developmental tasks, remains improving our ‘Assistive Matching’ service. This service’s primary objective is employing innovative methods to match line data effectively. It’s great to see it in action.
Consider this scenario: an invoice presents the following invoice line data:
- Quantity: 2
- Unit Price (Nett Each): £850.57
- Line Total (Total GBP): £1326.89
Upon examining the order line data, we find:
- Quantity: 2
- Unit Price (Nett Each): £663.446
- Discount: -22
- Line Total (Total GBP): £1326.89
Assistive matching operates through various approaches, one of which involves utilising a combination of quantities and pricing from the order and receipt lines. In this instance, despite the absence of the unit price post-discount from the supplier on the invoice, one might anticipate a failed match. However, through the calculations performed by assistive matching, the match is successfully made, and the correct post-discount unit price is backfilled.
What’s even more remarkable is its capability to function seamlessly even in scenarios where the discount percentage is absent from the dataset.
To clarify, this method does not rely on product code matching. Instead, it leverages unit price and quantities, incorporating built-in logic to accommodate discounts, rounding discrepancies, differences in unit of measure, and pricing tolerances.