Part IX of the series: “Digitization of auditing SAP Fixed Asset and Inventory Processes”
Data and process analytics have the potential to bring great benefit to auditing. Nonetheless the questions are: how is it possible to pursue and analyze the enormous and extensive results? Does one have to pursue each and every case that emerges from data analytics? Often, there are way too many results and false positives! Frequently auditors are overwhelmed by the amount of results. In the following, I would like to explain how to proceed.
1. Auditing SAP processes in fixed asset and inventory
2. Master Data audit of SAP fixed assets
3. How to audit fixed assets procurement in SAP
4. SAP data analytics for fixed asset depreciation
5. Auditing fixed asset retirement in SAP
6. Process analytics for SAP current asset transactions
7. Segregation of Duties in SAP asset management
8. Fixed asset data structure in SAP
9. Professional Judgement in auditing SAP fixed assets
Divide et Impera
"Divide and rule" – says the Latin scholar. This simply means: when a task is too difficult, one can divide it into subgroups and deal with the easier subgroups until all of them have been processed.
How does this affect the interpretation of data analysis results by the auditor?
In total I have implemented 125 indicators for process weaknesses(about every process: purchase, order to cash, fixed assets and inventory, as well as cross process indicators). In this series different indicators in the area of fixed assets and inventories have been introduced. During the implementation, the described problem of too many results arose and because of that a solution needed to be constructed.
I will elaborate this on the following example - let’s take the following indicator:
P&L loss at retirement or sale of asset
This indicator is associated with the audit objective of saving opportunities.
There is a risk that asset retirement or sale to company stakeholders below actual value.
The criterion for this indicator is:
The document has been marked because a P&L loss is accounted for at time of sale or retirement of a fixed asset.
Let us suppose that 347 documents are affected by this indicator. Quickly, the auditor comes up with the thought that he would never have done the data analytics! How to pursue 347 indications?
To encounter this problem, I have devised the concept of "profile", which was consistently implemented at zapliance. It's pretty simple: each document marked by an indicator is automatically sorted into a certain result group. How these result groups are build differs for each indicator and is related to the professional analytics target of the indicator. The purpose is that you only have to look at the result groups and not at all the individual documents in the groups.
Let's follow the example with the indicator "P&L loss at retirement or sale of asset". This indicator maps its profiles according to the criterion "asset class". That means all documents with reference to asset accounting and with the same asset class are assigned to a profile. For example, three profiles are formed: "car pool", "office equipment" and "machinery".
The auditor can then concentrate on the profile, which he considers particularly relevant or valuable for fixed asset retirement. Certainly vehicles and machines, compared to office equipment, would be interesting here. Through the profiles a special focus is placed on the highest risks or most interesting cases. Following this approach, random samples lose methodological value.
It is no longer necessary to audit individual cases, but case groups, which makes the audit much more efficient and leads to a very good understanding of the audited entity.
In the example given, the question must therefore be considered:
Fixed assets of which asset classes have a high residual value when the asset is disposed of, which could not be redeemed by the asset retirement?
... and the examination of the indicator would be completed.