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If you were told there would be no math, that’s a shame – because there’s a formulaic approach to ensuring your retail organization has accurate inventory records and is making the most of your opportunity to boost that bottom line.
To discuss retail inventory record accuracy and the formula you can use to calculate it, Herb Billings, Vice President, Technology Strategy at Datascan, is back alongside host Tyler Kern for another episode of Herb’s Hot Takes.
Many retailers are aware of inventory accuracy percentage – but it doesn’t tell the entire story. It can be misleading, because, as time increases between counts, system records become less and less accurate.
A monthly degradation percentage, then, can give retailers a clearer picture and equalize the timeframe between counts, delivering more actionable insights.
You calculate that monthly degradation by taking the inventory inaccuracy percentage (100% – inventory accuracy %) and dividing by the number of months since the previous count. Datascan gets a standardized month by dividing the number of days between counts by 365, then multiplying by 12.
While this method still isn’t perfect, as many factors impact the actual level of inventory accuracy, this monthly approach can help retailers be more informed between counts.
By Datascan5
11 ratings
If you were told there would be no math, that’s a shame – because there’s a formulaic approach to ensuring your retail organization has accurate inventory records and is making the most of your opportunity to boost that bottom line.
To discuss retail inventory record accuracy and the formula you can use to calculate it, Herb Billings, Vice President, Technology Strategy at Datascan, is back alongside host Tyler Kern for another episode of Herb’s Hot Takes.
Many retailers are aware of inventory accuracy percentage – but it doesn’t tell the entire story. It can be misleading, because, as time increases between counts, system records become less and less accurate.
A monthly degradation percentage, then, can give retailers a clearer picture and equalize the timeframe between counts, delivering more actionable insights.
You calculate that monthly degradation by taking the inventory inaccuracy percentage (100% – inventory accuracy %) and dividing by the number of months since the previous count. Datascan gets a standardized month by dividing the number of days between counts by 365, then multiplying by 12.
While this method still isn’t perfect, as many factors impact the actual level of inventory accuracy, this monthly approach can help retailers be more informed between counts.