Reconcile Security Tags Against Sales in Under 60 Lines of Python
If you have ever built software for a shop, you know the bugs that cost real money are rarely in the code. They live in the gap between what the system says happened and what happened on the floor. Here is a small, practical example from retail operations: checking whether the hard security tags removed at the register actually match the tagged items that were sold. The problem Many clothing and…
In retail operations, hard security tags attached to clothing and accessory products can lead to discrepancies between what the system records and what actually happens on the sales floor. The script focuses on reconciling these security tags against sales by joining three CSV files: tagged_skus.csv, sales.csv, and tag_counts.csv.
The script loads tagged SKUs from tagged_skus.csv, calculates the expected tags based on sales data, and counts the tags recorded at closing from tag_counts.csv. It then compares the expected tags with the counted tags for each register and SKU, generating a report of discrepancies. The report includes the date, register, expected tags, actual tags, difference, and status (OK, SHORT, or OVER) for each comparison.
By automating this reconciliation process, managers can quickly identify and address issues such as tags being left with customers, dropped or pocketed, or incorrect sales records.
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