Mango's Inventory Accuracy Scorecard is your primary tool to gauge Operational Levels in your store. It is divided into three sections:

• Top Line Chart - displays monthly Count Sheet Completion (green), IRA (red) and Other Count Types accuracy (blue) trendlines.
• Middle Count Sheet Results - shows numerical results of your store's three-month Count Sheet metrics; the right-hand section shows diagnostics helpful to understand Efficiency, Dollar Accuracy and Shrink.
• Bottom - Your store's Operational Level metrics, alerts, and help links.

• Green Line: this is your store's monthly Count Sheet Level 0 - Completion plot and trend line.
  Red Line: the monthly Random Count (RC Count Type) plot and trend line making up Level 1 - IRA .
  Blue Line: this is your store's Good Counts plot for all Other Count Types (TI, XX, MC, WD, OT). 
  
  These three lines indicate how completely your store is processing its Count Sheets (green line), your inventory accuracy when randomly sampled (red line) and your store's accuracy when high-risk SKUs are counted (blue line). The difference between your store's blue line (accuracy in high-risk SKUs) and it's red line (accuracy for the typical SKU) indicates how much SKU clutter remains in your inventory file. For stores new to Mango, there may be significant clutter which will be cleaned up as your store processes its Count Sheets. As your store processes its Count Sheets you will see the blue line converge with the red IRA line; this indicates better accuracy between noisy high-risk SKUs and the typical SKU. That is, file clutter is getting cleaned up!

• The middle section of your Count Sheets contains a lot of numbers, enough to make even the most analytical person dizzy! Let's simplify things by breaking it into two pieces.

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    This section sums up three months worth of Count Sheet processing and displays the results in two separate columns: Random Count and Other Count Types.

    • 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. 

    The row Total SKUs Counted simply lists the number of SKUs Counted from your store's Count Sheets over the past three months. In the example above, 165 Random SKUs were counted and 661 SKUs were counted from the other Count Types.

    The row Total Dollars Counted row sums up the total inventory dollar value counted (at Replacement Cost). For example, the 661 Other Count Type SKUs counted represented $64,638 in inventory value (quantity-on-hand times cost for each SKU counted).

    The Net Dollar Variance row sums up the net dollar variance (QOH variance times cost) for the SKUs counted. Dollar Accuracy uses a net variance so that inventory shrink and swell net themselves out: some SKU's QOH's go up when counted (swell) some SKUs go down (shrink). This net variance is then divided by the total dollars counted to determine a Net Dollar Variance metric both for Random Samples and the Other Count Types. This metric is used along with your Boundary Accuracy to determine your store's Operational Level 2 - Dollar Accuracy.

    The Good Counts row shows the number of SKUs that were accurate when counted during Count Sheet processing. The number of Good Counts divided by SKUs Counted in the Random Counts column is your Operational Level 1 - IRA metric (showing 82% above). The Good Counts row in the Other Count Type column is plotted along the blue line in the chart above and represents the accuracy in your high-risk inventory population.

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    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 were 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 far 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 a 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.

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  The bottom of the Inventory Accuracy Scorecard shows progress towards your Operational Level goals!

This alert indicates that Mango's accuracy system has substituted an internally calculated IRA sample for your store's Count Sheet Random Count (RC Count Type) sample. This can happen for one of two reasons:

1. Count Sheet Completion is inadequate.
                   -or-
2. There is a mismatch between the Count Sheet Sample and Mango's internally calculated sample.

• If your store's Count Sheet Completion is not sufficient to make a good IRA sample then it will be substituted with an internally calculated IRA.

  

  In the example above we Random Count completion (47 counted out of 165) too low to achieve a statistically significant sample. In this case, IRA is estimated by Mango as indicated by an open diamond (IRA substituted) on the IRA (red) trend line. This can happen when a store stops processing their Count Sheets due to a store remodel, staffing change, etc.

  Steps to correct
  1. Work on Level 0 - Completion

• In the example below, there is high enough Completion for a good IRA sample, however, there was a mismatch between the sample counted and its expected value. Mango calculates it own internal IRA (based on the percentage of SKUs rung to negative quantity-on-hand at checkout) and compares it to the Count Sheet sample returned. If the mismatch is big enough then it a substitution alert will show and the store's counted IRA will be substituted with Mango's calculated IRA. The substituted sample(s) will be shown as an open diamond in the red IRA trendline. This behavior helps protect stores from measuring an incorrect IRA caused by lack of quantity-on-hand variance research or, in some cases, lazy (lunchroom counts) or "optimistic" counting to pad IRA. Sometimes a validation alert can be caused by other factors.

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  How to investigate IRA validation issues
  
  

  1.  Locate your Review Report Email (sent around the 2nd of each month)
  2.  Open the attachment titled "Charts.pdf"
  3.  Scroll to the Inventory Accuracy Scorecard (Page 3) and verify the IRA Substituted stamp is present

  The most common reason for IRA substitution is due to a high negative QOH percentage coupled with very high reported accuracy. In the example above, the store reported an accuracy of 96% on the 55 Random Count SKU (53 of 55 with no variance) but is experiencing a high negative QOH percentage, 10%. It's very hard to say you're a store that's 96% accurate but also having so many SKUs go negative.

  Research Negative QOH

  1. Navigate to your Online Report portal and login
  2. Download the IRA Validation Excel report available in the store's Excel folder.
  3. Look at your Negative QOH worksheet tab and see if there is a rhyme or reason these SKUs went negative last month. SKUs that have gone negative multiple times in the previous month are easier to spot patterns on.

  If the negative quantity-on-hand SKUs all look reasonable then continue to the next step. If there is a lot of noise in your negative QOH's then try to resolve the receiving issue or other store procedure causing the negative QOH's.
  

  1. Look at your RC Count Type tab
  2. Have another person (other than the person who initially counted) carefully re-count the listed RC Count Types from last month. 

  If you find a handful of counts that were off then this is likely the cause of your validation issue. Count Sheet processing requires very careful counting coupled with variance research to ensure a good count! It might be a good idea to review the Operational Level 1 - IRA Checklist.
  
  If nearly all the counts matched then drop us a line: support@mangoreport.com

A Theft Alert showing on your Inventory Accuracy Scorecard means Mango has picked up on a theft-for-cash signature in your store. WD Rtn Count Type on your Count Sheets is auditing SKUs recently returned that were a. not purchased in a long time and/or b. are expensive items. If there is shrinkage when these SKUs are counted it fits a theft-for-cash signature. If enough of these audits show this signature then you will see the Theft Alert in your Inventory Accuracy Scorecard!

SKU-level detail of alerted SKUs can be found in your Shrink Report.pdf (Review Reports email). Many of these will be in your Variance Worksheet, the remainder of alerted SKUs will be in your Adjusted Shrink section. These SKUs will say CS WD Alert in the Research Hint column.

In the example above, we see two faucet stems that were returned (returned to stock, type R) at the register and when audited on Mango's Count Sheets (WD Rtn. Count Type) were short by the amount returned! Furthermore, you see the last sale of both these SKUs is "never". Clearly, theft-for-cash has to be ruled out and further research should be performed:

A Boundary Alert indicates an issue with a store's Inventory Value impacting Dollar Accuracy (Operational Level 2). The problem area(s) are reported on the store's Exception Report.pdf (Pages 1 - 3 typically). These are called "Boundary" reports because the affected SKUs are not reported on Mango's Count Sheets.pdf and their inventory value is excluded from Mango's Chart reports and metrics. Therefore, these SKUs are outside Mango's "boundary". However, they are inside your store's POS system and most likely impacting your store's ability to report accurate financial information and track shrinkage accurately.

Generally speaking, these are impactful easy-to-fix errors and should be treated as a high priority. Boundary errors are divided into three classes:

Three classes of Boundary Exceptions
1) Cost/QOH Errors
2) Store Supply/Coupon Errors
3) Negative Value Errors

**Warning - significant swings in inventory value can impact your store's reported Gross Profit. Please make corrections with your owner's / CPA's knowledge.

1) Boundary Cost Errors Exception (click for more information)

In the example above, one SKU is (falsely) creating $7,000 of inventory value (QOH x Cost). Until corrected, this error creates an imbalance between what the store paid and the resultant inventory value. The net result will falsely create $7,000 of taxable gross profit. The source of the error should be investigated and the error be undone using the same source. For example, if it was a purchasing error then the error should be corrected in the purchasing system rather than through PIP, etc.

2) Boundary Store Supply Exception (click for more information)

The example above shows items contributing to a store's ending Inventory Value (QOH x Cost), however this class of "inventory" is not available for sale and really should not be classified as such (and incorporated into your store's ending inventory/balance sheet). The solution is to zero-out the SKU's QOH so that it does not contribute to ending inventory value. There are several ways to zero out the SKU's QOH: PIP/IMU, Keep Stock Info=N, or a Credit PO. The recommended ongoing method is to utilize a Credit PO. If the value is significant, please make sure your owner and/or CPA approves the method and knows the total dollar amount corrected and which method was used to zero out QOH as some sort of general ledger adjustment may be necessary.

3) Boundary Negative Value Exception (click for more information)

The example above identifies SKUs in your system that have significant negative value or have negative quantity on hand month after month. This condition can indicate a purchasing issue or a Keep Stock Info misconfiguration. Significant negative value in ending inventory can obscure dollar value and can cause erroneous shrinkage to be reported. Generally, stores exclude negative value from their reported ending inventory by utilizing an option within their RIV report. However, this option is not consistently set across stores or even within the same store (different options for month-end and year-end). Because of these adverse accounting risks, negative value should be minimized. This report is part of Level 2 - Dollar Accuracy Boundary reports.

Dollar Accuracy Count Sheet Completion Alert
If Count Sheet Completion for your stores falls below 75% for the twelve trailing months (TTM) then you will see this alert on your Inventory Accuracy Scorecard and your Dollar Accuracy metric will be reported as ??. 

Why?
For Mango to report an accurate and Dollar Accuracy figure, SKUs on its monthly Count Sheets must be counted thoroughly each month. Each Count Sheet contains tens of thousands of dollars of Top Inventory and Phantom Inventory to process and if these SKUs are skipped in sufficient quantities, Mango's ability to report on Dollar Accuracy is compromised. Stores will see this alert if they have stopped processing Count Sheets for a period due to a store remodel, relocation or when Count Sheets are otherwise not processed routinely. 

To resolve this alert
Work on achieving 100% Count Sheet Completion each month and your Dollar Accuracy will start reporting once your twelve-month completion popps above 75% (9 months of good completion out of 12).

Above, this example store shows low Count Sheet Completion November through March (green line in the chart) due to a store remodel. After the remodel was completed, the store resumed its Count Sheet processing and will see a resumption in its Dollar Accuracy metric next month (9 out of 12 months with good completion).