This section may be overly technical for some folks, and that's all right. Please keep in mind, Mango makes it easy to "just fix it" without getting into the weeds of exactly how Dollar Accuracy is measured (and its importance to proper cost of goods accounting). However, we do encourage everyone to read through this section so general concepts like Boundary Accuracy are understood. If you are an owner, auditor, CPA or enjoy the science of retail accounting then this should be fun stuff!

Gross Profit Equation
When working with inventory value, always keep in mind the Gross Profit Equation:

While correcting inventory value issues through your Level 2 Checklist you are affecting your store's ending inventory value, which is linked to gross profit (equation above). If you are changing inventory value without a corresponding sale or purchase then you are also changing your store's Gross Profit dollar-for-dollar. That is, as ending inventory goes up, cost of goods goes down which increases gross profit and vice versa.

Inventory value corrections (and errors) can have a dollar-for-dollar impact on your store's reported (and taxable) gross profit. Make sure significant fixes are reported to your ownership and/or CPA. For example, if you are going to blow away $110,000 in Store Supply inventory value then it will likely reduce your store's reported Gross Profit by $110,000!

• If Operational Level 1 measures quantity-on-hand accuracy (IRA) then why we need to measure Dollar Accuracy as a separate metric? Isn't Dollar and quantity-on-hand accuracy similar? Let's look at some examples to illustrate why they can be significantly different.

  • A customer buys two cans of white spray paint in two different sheens, flat and semi-gloss. An untrained cashier, seeing two similar-looking cans rings up both under the same SKU (a third of untrained cashiers will do it). This creates two quantity-on-hand errors: the flat and semi-gloss SKUs are now inaccurate (one SKU is 1 high and the other is 1 low) and have an IRA of 0%. However, because both cans are worth the same amount in cost dollars, the error "nets out" (e.g. one SKU is $2.31 too high and the other is $2.31 too low so the net change is zero dollars) and inventory dollar accuracy is preserved. This is why a store with 80% IRA can still have very high Dollar Accuracy; because many of our cashiering and counting errors net out in dollar terms (some variances go up and some go down). In fact, about two-thirds of our counting variances net each other out in inventory dollars.
    
    
  • A sandpaper SKU is showing 37 sheets on hand. But the entire box cost is accidently assigned to the individual sheet SKU. The sheet quantity-on-hand matches when counted so IRA is 100%. But, in dollar terms, the SKU is way off. If the box costs $20 then there's a $700 dollar variance in just one SKU—now imagine the entire sandpaper class is set up like this, it might have perfect IRA but be tens of thousands of dollars off in inventory dollar value. It happens more than you would expect!
    
    
  • A store buys bin tags and check-out bags as store supplies from its warehouse. The line-items and costs are broken out separately on its invoice and the bookkeeper makes the appropriate expense-item journal entries. However, the bin tags and check-out-bags are automatically received into the store's inventory (QOH is incremented), a routine and expected occurrence, thereby increasing inventory value, decreasing cost of goods sold and increasing taxable gross profit. Counting these SKUs for IRA purposes is an entirely wasteful process since this errant dollar value should be be eliminated entirely.
    
    
  • A store sells live plants but does not receive the vendor's invoices at the SKU level (does not create PO's) so the plant SKUs incrementally show negative quantity-on-hands. These negative quantity-on-hand SKUs create negative inventory dollar value when multiplied by their corresponding costs. Most stores elect to exclude negative value from ending inventory but many stores do not and some even exclude it in some places (RIV for example) but not in other applications, or some exclude it monthly but not yearly. Furthermore, when quantity-on-hand adjustments are made to "zero out" negative value, it creates a shrinkage imbalance (called swell) which tends to mask true shrinkage and oftentimes (if negative value is excluded from RIV) leaves owners and CPA's scratching their heads because there is a large disconnect between reported shrinkage and corresponding inventory value change. Counting these SKUs and zeroing them out for IRA purposes runs the risk of corrupting shrinkage and cost of goods accounting! 

  The examples above show how quantity-on-hand accuracy (IRA) alone is not an adequate method nor metric for achieving and measuring inventory dollar accuracy. However, having a good IRA at 80% or better (the Level 1 goal) is a prerequisite to achieving Dollar Accuracy. 

Mango's Dollar Accuracy metric is computed by measuring the percentage of "Boundary" issues (cost/quantity errors, store supply inventory and negative value) then subtracting the net dollar variance percentage as your store processes its Count Sheets. Cleaning up any Boundary issues is a big part of achieving Dollar Accuracy in your store because Dollar Accuracy can never be higher than your store's Boundary Accuracy metric.

• Boundary is a Dollar Accuracy concept in Mango that might be best understood with an analogy:
  
  Let's say your profession is a painter and you are called to paint the exterior of an old house. When you get to the job site, you see the 'ole house needs a little more than just paint, it also needs some siding replaced and one side of the house is completely covered in mud. So, before you can even begin to get out the paint and brushes, you have to get out your hammer and saw and a power washer to prep the house for painting. Although this prep work isn't "painting" it is mandatory to ensure a quality paint job.
  
  Dealing with Boundary issues in Mango is similar to dealing with the painting prep work in the analogy above. You will use different tools (Boundary Exception Reports and Inventory Maintenance) to prepare your store's inventory file (if it first needs it) before continuing on with measuring and improving Dollar Accuracy through your Count Sheets.

• Dollar Accuracy is measured using the net dollar variance method as your store processes its Count Sheets. This dollar variance is then subtracted from your store's Boundary accuracy metric to produce a composite Dollar Accuracy figure. Wow, that's a mouth full. First, let's take a look at what we mean by Boundary and and then we will hit Net Dollar Variance.
  
  Boundary
  As we've discussed above, Boundary has to do with errors best fixed through processes other than counting and PIP, these are SKUs with issues your Count Sheets can't fix. Boundary issues come in three flavors:

  • Cost & QOH Errors
  • Store Supply Value
  • Persistent Negative Quantity on Hand (QOH) 

  • 

    Above we see an example Boundary Exception Report dealing with obvious average cost errors which are inflating inventory value and reducing cost of goods sold over $35,000. 

  • 

    The SKUs above are not inventory (they are expenses or capital goods) and do not belong in your store's inventory balance nor cost of goods equation.

  • 

    The SKUs above are persistently (month after month) showing negative on hand. This is a result of a purchasing and receiving issue or the SKUs should be set to Keep Stock Info = N to remove the negative quantity-on-hands.

  Measuring Boundary
  When summed together, the three boundary examples above total $87,248.53.

  

  If our example store's total inventory value is $400,000 then these boundary issues represent 22% of total inventory value and which results in a 78% Boundary Accuracy metric.

  

  Note: the keen observer will notice how negative value counts against boundary accuracy. This might seem punitive for stores excluding negative value from ending inventory, however, we occasionally see of inconsistencies in the way the same organization reports ending inventory value. Exclusions can vary from store-to-store (within the same organization) and from year-end to month-end or from printed reports to on-screen summaries. Furthermore, when a store excludes negative value and then corrects negative value, it creates a dollar-for-dollar imbalance in shrinkage as it relates to cost of goods sold, as negative value changes are not excluded in shrinkage (RPH), but the change from negative value is excluded from inventory value.
  

  In summary, Boundary, the first component in Mango's Dollar Accuracy metric, is the dollar value of errors, store supply and negatives as a percentage of your store's reported system inventory value. Once cleaned up, your store can maintain a 99% - 100% Boundary Accuracy metric.