Inventoryops400

 

 Inventory Management and Warehouse Operations.


 

 Inventory Accuracy Measurement

  By Dave Piasecki  

 Inventory accuracy measurement is generally calculated from the results of a cycle-count program or a physical inventory count. There are several ways of calculating accuracy and none of them alone provide a clear picture of your accuracy.

Good-count-bad-count.

Good-count-bad-count has become the de facto standard for measurement in cycle-count programs. I’m not saying this is a good thing, only stating that it has become very common. The basic calculation is to divide the number of Good Counts by the total number of counts. Therefore, if you count 100 items and 90 match the system inventory, then your Good-Count-Bad-Count Accuracy percentage would be 90% (90 good counts divided by 100 total counts).

This would be a pure Good-count-bad-count measurement. Things get more complicated when tolerances are used. Let’s say you are supposed to have 10,000 little sheet metal screws, but your count comes up one short (you count 9,999). Do you really want to designate that as a “Bad Count”? Most people would agree that 9,999 is “close enough”. In fact, if they counted these 3 times by 3 people, they would likely get 3 different counts. So, one reason to use tolerances is to account for limitations of counting (such as counting scale accuracy). Another reason has to do with operational impact. It’s unlikely being short 1 screw out of 10,000 is going to create an operational problem, and you really don’t care if you are short 1.

The problem arises when you try to determine where to set the tolerance. No matter where you set it, there will always be a 1-piece difference between a good count and a bad count. Unfortunately, the typical tolerance is set at 5%. 5% is way too high (in my opinion). If I’m supposed to have 22 televisions in stock and only count 21, I’m short a television, and there is no way I feel comfortable calling that a “good count.

Alternatively, you can use a flat dollar amount as your tolerance. For example, if the value of the variance is less than $3.00, you count it as good.  Some companies will use a combination of percentages and flat dollar amounts to get something that feels appropriate to their needs.

I don’t particularly like tolerances, but I don’t particularly like good-count-bad-count either. With pure good-count-bad-count, counts are either good or bad. It doesn’t make a difference if you are short 1 sheet metal screw or 20 televisions. So, I see tolerances as a necessary evil to make this measurement more useful.

Net Dollar Accuracy.

Net dollar variance is calculated by taking the total value of your inventory counted (actual inventory) and dividing that by the total value of the system inventory (expected inventory).

Therefore, if your inventory counts totaled $9,900,000.00 in value and your system inventory expected you to have $10,000,000.00 in value, you have a Net Dollar Accuracy of 99%. This is the measurement financial people are most interested in because they want to know that if you are reporting you have ten million dollars in inventory that you actually have something close to that.

The problem with net dollar accuracy is that the “netting” can mask significant inaccuracies at the item level. So, if you are short $5,000 of item A and over $5,000 of item B, this nets out to a variance of Zero, even though these are significant variances.

The “netting” is important, though, because if your variances are due to normal random mistakes made in your operation, you should have a similar amount of plus and minus variances, and therefore, your Net Accuracy number should always be close to 100%. If your net accuracy is consistently low (mostly shortages) or high(mostly overages), that is not normal and is a signal of some other operational problem, such as problems with scrap reporting in manufacturing.

Net Piece Accuracy.

This is calculated in the same way as net dollar accuracy, except you use pieces in place of the dollar value. The big problem with Net Piece accuracy is that it will net regardless of value; therefore, if you are short 5 Televisions and over 5 sheet metal screws, those net out to Zero in a net-piece measurement.  Due primarily to this, I would not suggest using Net Piece Accuracy in your accuracy measurement.

Absolute Dollar Accuracy.

Unlike Net Dollar Accuracy, Absolute Dollar Accuracy measurement does not “net” anything. To calculate, you take the absolute value of all variances, subtract this from the total expected value of the items counted, and divide this by the total expected value of the items counted.

So if you are short $5,000 of item A and over $5,000  of item B, this results in an Absolute Variance of $10,000 and if the total value of both these items was $50,000, that would result in an Absolute Dollar Accuracy of 80%.

You can see that your absolute dollar accuracy measurement will almost always be lower (sometimes significantly lower) than your net dollar accuracy measurement. That is why it is not used that often. But it does help to show what net accuracy measurements don’t show. You may have a net accuracy of 99.9% and an absolute accuracy of 70%, and knowing both of these gives you a much better idea of where your accuracy is.

Absolute Piece Accuracy.

Calculated like Absolute Dollar Accuracy except using pieces in place of Dollars. What should you use? I like to see multiple measurements because each tells me something different. However, I’m well aware that I’m not in the majority on this one. I think you at least need to use Net Dollar Accuracy because financial people will expect it. I used to suggest creating a weighted composite measurement if you want to have one number to track over time. For example, weight 50% of Net Dollar Accuracy, 25% of Good-Count-Bad-Count, and 25% of Absolute Piece Accuracy.  The problem with a composite score is you have to deal with the blank stares you get when you try to explain it to others. And, when you observe a change in the composite score over time, you will still need to go back to the original scores to see what caused the change. One comment I would make is to make sure that if you are using tolerances, they are clearly communicated with the measurement.   People generally view accuracy measurement within the context of the previous operation they worked in, yet if you ask them specific questions, you’ll likely find that they don’t know how that was calculated. Alternatives to Accuracy Measurement based on Cycle Counts or Physical Inventories. Accuracy Audits. An Accuracy Audit is really just a small physical inventory that counts a representative sampling of your inventory. This is commonly used by auditors who don’t trust the numbers you are providing to them. But there is no reason you can’t do Accuracy Audits yourself. Just choose a list of Items that represent the overall inventory. So you’ll want fast movers and slow movers, items with significant inventory investment and less expensive items, items used in manufacturing, and items that are just sold. You then do a physical count of just those items. The measurement you would apply to the Audits would be the same as those previously covered. Consumption-based Measurement. I’ve used this in manufacturing operations previously where scrap reporting of components is a suspected problem. The way I used this was to total all miscellaneous adjustments (cycle counts, physical inventories, etc) for a year and also to calculate manufacturing consumption for the entire year. Then, by dividing the total of the adjustments by the total consumption, you have a percentage that represents the variances relative to consumption rather than to a snap-shot-in-time quantity on hand. If you notice consistency among items within a product group, you may need to change the BOMs to support this level of scrap.

What should you use?


I like to see multiple measurements because each tells me something different. However, I’m well aware that I’m not in the majority on this one. I think you at least need to use Net Dollar Accuracy because financial people will expect it. I used to suggest creating a weighted composite measurement if you want to have one number to track over time. For example, weight 50% of Net Dollar Accuracy, 25% of Good-Count-Bad-Count, and 25% of Absolute Piece Accuracy.  The problem with a composite score is you have to deal with the blank stares you get when you try to explain it to others. And, when you observe a change in the composite score over time, you will still need to go back to the original scores to see what caused the change. One comment I would make is to make sure that if you are using tolerances, they are clearly communicated with the measurement.   People generally view accuracy measurement within the context of the previous operation they worked in, yet if you ask them specific questions, you’ll likely find that they don’t know how that was calculated.

AccuracyMeasurement

The image above shows some of the accuracy measurements discussed here. At the top is the raw data, the lower area shows the results of the calculations. 


Alternatives to Accuracy Measurement based on Cycle Counts or Physical Inventories.

Accuracy Audits.

An Accuracy Audit is really just a small physical inventory that counts a representative sampling of your inventory. This is commonly used by auditors who don’t trust the numbers you are providing to them. But there is no reason you can’t do Accuracy Audits yourself. Just choose a list of Items that represent the overall inventory. So you’ll want fast movers and slow movers, items with significant inventory investment and less expensive items, items used in manufacturing, and items that are just sold. You then do a physical count of just those items. The measurement you would apply to the Audits would be the same as those previously covered.

Consumption-based Measurement.

I’ve used this in manufacturing operations previously where scrap reporting of components is a suspected problem. The way I used this was to total all miscellaneous adjustments (cycle counts, physical inventories, etc) for a year and also to calculate manufacturing consumption for the entire year. Then, by dividing the total of the adjustments by the total consumption, you have a percentage that represents the variances relative to consumption rather than to a snap-shot-in-time quantity on hand. If you notice consistency among items within a product group, you may need to change the BOMs to support this level of scrap.

 More Articles by Dave Piasecki.

Dave Piasecki, is owner/operator of Inventory Operations Consulting LLC, a consulting firm providing services related to inventory management, material handling, and warehouse operations. He has over 25 years experience in operations management and can be reached through his website (https://www.inventoryops.com), where he maintains additional relevant information.