October 26, 2016

How to Improve Your Invoice Data Quality

by Digitalization, Accounts Payable Optimization, Invoice Process Automation

Developments in invoice processing have made the practice much easier and faster than before, but have also made it more challenging for accounts payable to improve at the same pace. This is because of the many inter-dependencies in the purchase-to-pay process.

One question I often get asked is whether it is beneficial to interpret invoice rows on paper invoices, or if interpretation on the invoice header level is good enough (invoice header level meaning e.g. invoice number, total amount, currency, due date, etc.). The answer is that it depends on what you want to achieve.

Let me give you an example. Let’s say that you want to manage your invoices with as little manual input as possible, meaning that a certain predefined level of deviation between the order and the invoice is acceptable. Perhaps you expect a surcharge on freight, for example. In this case it would be sufficient to match the invoice only on the header level, and to automate the inspection and approval process (provided the deviating net amount is within predefined tolerance limits). Thus, there would be no need to interpret the rows from the invoice.

However, if you would want to check for all the inconsistencies between the rows in the order, the goods you have received, and what has been specified on the invoice, then you would need to interpret the invoice rows. In this situation, the quality of the invoice data becomes essential in order to avoid unnecessary manual work, or to investigate deviations that might turn out to be incorrect interpretations (OCR) of the invoice data, and not actual errors in the invoice.

Personally I always recommend that customers who want to use row level data should consider increasing their usage of e-invoicing, instead of trying to interpret invoice rows from paper invoices. I recommend this as the e-invoice will provide you with a higher quality of data overall, as the data doesn’t need to be interpreted (OCR) and manually verified from paper.

Taking all the different types of invoice processing into account, the answer is even more complex. This is because specific types of invoices correlate to different types of purchases, some of which are easier to automate the invoices for than others. But the common denominator across the entire invoice handling process is invoice data quality.

Improving your invoice data quality

In conclusion, I generally tell our customers that there is no conflict when it comes to header or row level interpretation. They complement each other and improve efficiency in the invoice process. But your e-invoicing ratio is important – especially if you are prone to using row level data. This is a closely watched KPI in top performing organizations, with the best always having it in the green.

Tobias Wikstrom

Tobias Wikström

Tobias Wikström has more than 15 years’ experience in purchase-to-pay and cash management operations. He has supported hundreds of customers in their strategic alignment initiatives through invoice automation, supply chain and cash flow automation projects – gaining valuable cross-vertical knowledge in the process. During recent years, cloud services and operations have also been within his focus areas. A strong believer in LEAN and continuous improvements, Tobias supports pragmatic approaches to complex challenges.

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