Home Forums Kamanja Forums Use Cases & Samples New Use Case – Retail Produce Auto-Correct

This topic contains 0 replies, has 1 voice, and was last updated by  Solomon de los Reyes 2 years ago.

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    Solomon de los Reyes

    Large volumes of data are generated at retail cash registers every day.  Most products are scanned via UPC code. Produce is not scanned with a UPC code, grocery clerks are expected to identify produce and enter in 1 of 200+ memorized produce codes or use some register lookup tool. Misidentification can be costly. Misidentifications also include classifying an organic item as non-organic.

    For example the Gala apple has a PLU Code of 4132, not to be confused with a Fuji apple 4131. Too many misidentifications of the Fuji apple could result in lower prices and an incorrect order because the shipment thinks its low.

    A continuous decisioning engine could take into account current quantities, the employees behaviors specifically propensity to default to known PLU codes and very quickly adjust the codes or prompt the checker to do so. If a checker rings up 8 orders of an item every 8 hour shift, which costs the company 50 cents this use case doesn’t not seem very worthwhile. However if you multiply on average 20 checkers a day time 5000 stores across the country you get $18,250,000 dollars lost a year.

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