Do you actually know how many days it takes for an invoice to be balanced / paid in your company? You don’t? Or whether you may have missed the opportunity to benefit from cash discounts? You don’t know that either? Then you should definitely not miss this blog article under any circumstances.
Part IV of the series: “Payment terms in vendor master data”
1. Are you failing to benefit from cash discounts due to poorly maintained payment terms in SAP?
2. Two steps to analyze bad payment terms in SAP
3. Revised terms of payment: How to clean up your vendor master data
4. How to analyze your own payment behavior in SAP
In previous blog posts, we have shown you how to analyze payment terms in SAP and to clean them up in order to investigate payment terms that make little or no sense. Now that we have cleaned up the vendor master data, we can take a look at the cash discounts which are actually being lost in this article and keep an eye out for lost potential with regard to payment terms.
How can the difference between the baseline date for due date calculation and the clearing date be calculated?
The baseline date (ZFBDT field) from the BSEG table (Accounting Document Segment) is usually the starting date of the payment conditions (unless otherwise specified in SAP Customizing). If we take the clearing date (AUGDT field) from the BSEG table into account, by looking at the difference, we can see how many days it has taken for an invoice to be balanced in your company.
How can the difference be examined in SAP?
On this question, there are two ways to proceed. Of course, there is the possibility to generate a report using the SAP transaction “SE16N” for the BSEG table and the corresponding fields, but here we, as usual, come up against the restriction that not all documents can be exported to Excel, or that the export takes a very long time. I therefore opt to go for the faster procedure of using an SQL query to analyze the differences. If you also want to follow this shortcut and perform the analysis directly via the “Go” command, you will find the guide to the procedure to follow including the SQL Query you need here:
Once you have executed the SQL Query, you will obtain a table with the corresponding payment terms (ZTERM), its values (ZBD **), the sum of the document items (SUM (DMBTR)), the difference between the baseline and clearing date, as well as the absolute frequency (COUNT (*)).
At this point, can you already guess what the first results of the analysis are going to be? I had a similar situation with the test data set.
What are the results of the evaluation?
For example, take the penultimate line before the “…”. The payment condition “ZB01” makes provision for a cash discount of 3% for payment within 14 days and one of 2% for payment within 30 days. Otherwise, the full invoice amount is due. If we take a look at the “DAY_DIFFERENCE” column, we can see that the invoice was paid exactly one day too late in 9 cases and therefore no discounts were obtained. If we take the 2% discount on the amount of more than 300 million euros alone, we would have had a cash discount of over 6 million euros. That’s a nice saving for payment just one day earlier, right?
Now it’s time for you to use your professional judgment
Would you also like to know exactly which documents are concerned, so that you can discuss the specific cases with your departments to ensure that you do not miss out on any further discounts in the future? If so, don’t hesitate to contact us here.
The method for analyzing “lost discounts” is already integrated into zap Audit, so you do not have to check any document types, posting data or anything like that manually. Furthermore, our analysis is more mature, comes equipped with business intelligence methods and is being continually improved. This allows you to be effective in reducing false positives while leaving it to zap Audit to automate everything that can be automated. So you can use your valuable time to audit what needs to be audited. Do you have any questions about zap Audit? Please contact us here.