Hello Group Members,
A False Positive Result in IDEA is a result that indicates that a given condition is present when in fact it is not.
Let us understand the False Positive Result with two examples commonly encountered in Data Analytic activities.
1. You are performing a Rate Variance Check in Procurement by mapping the actual Buy Rate of various Material Codes against the Lowest Buy Rate for the review period. Now upon completing the testing and impact analysis, you notice many of the Lowest Buy Rates are either 0 or sometimes strangely even negative (very seldom though). This throws up the rate variance with the impact but it is actually a False Positive Result owing to Data Quality Issues in your underlying data imported to IDEA.
2. In yet another common testing arena, we look for Duplicate Vendor Invoice checks in IDEA on the Vendor Payment data dump. On running the duplicate we get more than expected cases owing to common spends like Utilities, Telecom, Rent which are fixed amount spends every month and appear in multiple line items for multi facilities being used. While this appears to be a duplicate (so condition present) but in fact it is not (false positive).
So we can learn to manage False Positive Result states effectively in IDEA by understanding the data better (for data quality issues) and understanding the process better (to tag inclusions and exclusion states like Utility, Telecom and Rent from 2. above).
One feature in IDEA which gets us full benefit on False Positive Result handling is Direct Extraction and / or Criteria in IDEA.
So in 1. above by entering a criteria Net Price > 0 in the Equation Editor while performing the Lowest Buy Rate testing we can exclude False Positives owing to Data Quality Issues.
In 2. above by entering a criteria .NOT. (@isini("rent", narration) .OR. @isini("water", narration) .OR. @isini("telecom", narration) you can suitably exclude these fixed spends before running the Duplicate test within IDEA.
However a word of caution to all of us. While excluding fixed spends like 'rent', 'water', 'telecom' and others make sure that this exclusion is aligned to the business process and is deemed necessary. If you eliminate a genuine duplicate through your exclusion, remember it will never ever surface in any potential duplicate checks on future duplicate runs in IDEA till providence makes one revisit the condition in the future.
Would invite Group Members to share their experiences on False Positive Results handling.
Regards
Group Admin Team