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Figure 4 is an IPA shortage chart. A linear trendline with R2 of 0.67 is used. Weeks A & B, with their high service levels, both had high coverage (low shortage). Week C had low service level and low cover­age (high shortage). We were able to hit our 95 percent service level objective with about 93 percent coverage, or 7 percent shortage.

Figure 5 is an IPA excess chart. A linear trendline is used, with a very high R2 of 0.837. Note weeks A and C, with low excess and low MOH, and week B with high excess and high MOH. Remember from figure 4 that it took 2.5 MOH to achieve a service level of 95 percent, but with 2.5 MOH, we had 115 percent excess inventory. We could have cut our total inventory in half and still met our service level ob­jective! IPA can be used to identify excess inventory and to monitor inventory reduction programs.

The purpose of the parallel study was to see if IPA shortage was a better indicator of service level than MOH. As seen in figure 6, each of the seven products in our study had a higher correlation between IPA shortage and service level than for MOH and service level. The study confirmed our hypothesis: inventory profile analysis is a better indicator of service level than months on hand analysis. In addition,
 

we discovered a very high correlation of MOH to excess inventory. In other words, within the study range, high MOH inventories had a greater likelihood of more excess inventory than of superior service levels.

The correlation between excess inventory and service level is not shown in figure 6 because product/weeks with high excess inventory also tended to have high coverage and therefore high service levels. The objective of inventory management is to achieve high service lev­els with less, not more, inventory.

You can implement IPA using Microsoft Excel. Initial decisions include the product hierarchy, data source and reporting frequency. For forecasts, you need to include both the download date and the fore­casted date. Include any other relevant information such as the name of the person responsible for the product. Enter the downloaded actual and target quantities at the SKU level. For each SKU, calculate the coverage (or shortage) and the excess. Sum the target, coverage, and excess quantities. Coverage is the total coverage quantity divided by the total target quantity. Excess is the total excess quantity divided by the total target quantity. You can use the Excel ChartWizard to create a combination chart showing coverage, target and excess. Use a scatter (x, y) chart, with linear trendline, to compare coverage to service level.

We have seen that inventory turnover is a poor choice for internal analysis because it converts SKU data to cost data. MOH is an im­provement because it uses units, but it still aggregates shortage and excess into a single value. Inventory profile analysis distinguishes be­tween shortage and excess at the SKU level. IPA coverage, or short­age, is a good indicator of service level. IPA excess can be used to identify waste and monitor inventory reduction programs. IPA can be implemented with Microsoft Excel using downloads from your inven­tory system and reported as coverage and excess indexes or displayed graphically.

The question, "How much inventory should we have?" became "Which ratio should we use?" Inventory profile analysis is the answer to the second question, and it will provide the answer to the first.


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