LP Cycle Counts Part 3 (Predictive Analytics for Loss Prevention Series)

In parts 1 & 2 of LP Cycle Counts we outlined the components of a robust program and the advantages of an analytic-based LP cycle counts over a cycle count for inventory adjustment program. The discipline applied to timely analysis of the LP cycle count results and follow-up for outliers is critical. The whole point of the program is to take appropriate action for the few locations that have issues, and leave the others to continue their excellent work uninterrupted. An effective program becomes a “lens” to focus your management and oversight resources on issues before they mushroom into huge losses.

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LP Cycle Counts Part 2 (Predictive Analytics for Loss Prevention Series)

In Part 1 of LP Cycle Counts I described a robust program and the related benefits. The cornerstone of the LP program is cycle counts of all units in a Product Category and comparison to the units per the perpetual inventory system. Over the years since program implementation and despite the success, several operational or financial managers have asked why we do not support making adjustments to inventory based on this program. There are many reasons why inventory adjustments cannot be recorded based on the LP program and why implementing a program with the rigor to support inventory adjustments is not operationally or cost beneficial.

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LP Cycle Counts Part 1 (Predictive Analytics for Loss Prevention Series)

Requirements of a Robust Cycle Count Program

Loss Prevention (LP) cycle counts are quick counts of all the units of a product category/class/department in a retail store. This unit count is then compared to the total units on-hand per the perpetual inventory system and a shrink (in units) percentage is calculated.

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