• Random Count - IRA - shows results for the RC Count Types only, these are your random samples representing the typical SKU in your store. If Completion is 100% then you will see 165 SKUs Counted in this column (55 RC Counts per month for three months). The Good Count row corresponds with your Operational Level 1 - IRA metric.
  
  
• Other Count Types - the Other Count Types column shows results for all the other Count Types on your Count Sheets. These include Top Inventory (TI), Double-x (XX), Watchdog (WD) and others. This is your expensive and noisy high-risk SKU population. The Good Count row corresponds with the blue line in your chart above. The Net Dollar Variance row is a major component in your Operational Level 2 - Dollar Accuracy metric. 

This section sheds light on your Operational Level metrics: IRA, Dollar Accuracy, Shrink, and Efficiency.  

SKUs Counted (TTM) - shows the percentage of SKUs Counted (received an updated Last Physical Inventory Date) within the twelve trailing months (TTM). This metric excludes counts to fasteners, live goods, bulk classes, keys and store supply. As part of achieving Operational Level 4 - Efficiency, stores should be counting 40% or less of their store SKUs annually.

SKU's Changed (TTM) - shows the percentage of SKUs that have received a quantity-on-hand variance over the past year. This metric excludes counts to fasteners, live goods, bulk classes, keys, store supply and closeouts (Store Closeout = Y). Along with SKUs Counted above, SKUs Changed is a component of your store's Efficiency metric. The target for this metric is 15% or less.  If a store needs to change QOH's on more than 15% of its SKUs on an annual basis then there is likely an accuracy leak somewhere.

More help on how SKUs Counted and SKUs Changed make up your Operational Level 4 - Efficiency metric.

Median Monthly Counts - Similar to the SKUs Counted (TTM) metric above, but this time we are looking at the the percentage of SKUs counted in a typical (median) month.  Your store should be counting between 1% and 3% of its SKUs each month while processing Count Sheets, Shooting Outs, and other miscellaneous counting your store might do throughout the month. 

Median Monthly Changes - Similar to the SKUs Changed (TTM) metric above but this time we are looking at the percentage of SKUs changed in a typical (median) month.  A store engaged in regular Cycle Counting will exhibit higher metrics here.  Stores still doing annual physical inventories will show a low Median Monthly metric but high SKUs Counted (TTM) above.  Your store should be targeting around 1% to indicate it's keeping up on finding/fixing errors and catching theft every month.  

Shooting Outs - This metric gauges how thoroughly and frequently your store is shooting outs. Your metric shows the percentage of countable outs that were physically counted during the month. A SKU must be at zero on hand for 7 (or more) consecutive days to be included as "countable".  Assuming a store is shooting outs weekly then (in a perfect world) 100% of countable SKUs would receive a Last Physical Inventory date update. A listing of countable SKUs not counted is available online in your MEGA Report Shooting Outs tab. Your best practice is to shoot outs thoroughly each week.

Targets: 
0% - 14% - No regular shooting outs procedure.
15% - 24% - Monthly or bi monthly shooting outs.
25% - 34% - Almost weekly shooting outs.
35% - 100% - Weekly and thorough shooting outs. 

Swell Percent - Swell is a quantity-on-hand (QOH) variance where QOH is changed upward. The percentage of swell variances vs. total variances is your Swell Percent (three-month average). For example, if a store logged 10 variances while counting, and 4 of the variances were swell (the other 6 where shrink) then the store's Swell Percent would be 4/10 or 40%.  The typical store exhibits a Swell Percent just shy of 40% and is very consistent from store to store. This metric is one of the keys to understanding why uncontrolled and unresearched counting has little effect on a store's accuracy: unless your customers are frequently stealing from your competitors and secretly putting inventory on your shelves, a swell variance is an indication of an error. It's either a cashiering, receiving, or counting error, and it's difficult to model a scenario where cashiering and receiving can be this farr off.  Therefore, to see 40% of variances come through as swell is an indication that perhaps much of our our time counting is spent making and fixing errors. This metric is why we suggest focusing on root accuracy processes and controlled counting practices rather than massive counting as a means to accuracy! Stores should expect this metric to be between 33% and 40%. If your store's metric is lower then it can point to shrinkage issues, and if your metric is much higher than 40% then it can point to a potential receiving issue (or uncontrolled annual physical inventories performed by an outside company).  The further this measure drifts from 37% (all-store median) the more this metric matters to your store.

Neg.QOH - There is a correlation between a store's true IRA and the percentage of regular SKUs that turn negative when scanned at checkout.  When this Neg. QOH percentage gets out-of-whack with the store's counted IRA percentage then an IRA Substituted alert is thrown and the store's IRA count is invalidated and substituted with Mango's internally calculated value. This metric should correspond with your store's counted IRA metric, where a higher counted IRA percentage should result in lower Neg. QOH percentage. 

Boundary Accuracy (Current Month) - This measures the amount of inventory errors impacting your store's Inventory Value.  A value under 99% will trigger a Boundary Alert.