In materials management, ABC analysis is an inventory categorization technique. ABC analysis divides an inventory into three categories—"A items" with very tight control and accurate records, "B items" with less tightly controlled and good records, and "C items" with the simplest controls possible and minimal records. The ABC analysis provides a mechanism for identifying items that will have a significant impact on overall inventory cost, while also providing a mechanism for identifying different categories of stock that will require different management and controls. The ABC analysis suggests that inventories of an organization are not of equal value. Thus, the inventory is grouped into three categories in order of their estimated importance. 'A' items are very important for an organization. Because of the high value of these 'A' items, frequent value analysis is required. In addition to that, an organization needs to choose an appropriate order pattern to avoid excess capacity. 'B' items are important, but of course less important than 'A' items and more important than 'C' items. Therefore, 'B' items are intergroup items. 'C' items are marginally important.
ABC analysis categories
There are no fixed thresholds for each class, and different proportions can be applied based on objectives and criteria. ABC Analysis is similar to the Pareto principle in that the 'A' items will typically account for a large proportion of the overall value, but a small percentage of the number of items. Examples of ABC class are
A items – 20% of the items accounts for 70% of the annual consumption value of the items
B items – 30% of the items accounts for 25% of the annual consumption value of the items
C items – 50% of the items accounts for 5% of the annual consumption value of the items
Major ERP packages have built-in function of ABC analysis. User can execute ABC analysis based on user defined criteria and system apply ABC code to items.
Mathematical calculation of ABC analysis
Computed ABC analysis delivers a precise mathematical calculation of the limits for the ABC classes. It uses an optimization of cost versus yield. Computed ABC was, for example, applied to feature selection for biomedical data, business process management and bankruptcy prediction.
Example of the application of weighed operation based on ABC class
Actual distribution of ABC class in the electronics manufacturing company with 4,051 active parts.
ABC class
Number of items
Total amount required
A
20％
60％
B
20％
20％
C
60％
20％
Total
100％
100％
Using this distribution of ABC class and change total number of the parts to 14,213.
Uniform purchase
When equal purchasing policy is applied to all 14,213 components, for example weekly delivery and re-order point of two weeks' supply, the factory will have 16,000 deliveries in four weeks and average inventory will be 2½ weeks' supply.
Weighed purchase
In comparison, when weighed purchasing policy is applied based on ABC class, for example C class monthly delivery with re-order point of three weeks' supply, B class bi-weekly delivery with re-order point of 2 weeks' supply, A class weekly delivery with re-order point of 1 week's supply, total number of delivery in 4 weeks will be ++=5,000 and average inventory will be ++=1.925 weeks' supply. a) A class item can be applied much tighter control like JIT daily delivery. If daily delivery with one day stock is applied, delivery frequency will be 4,000 and average inventory level of A class item will be 1.5 days' supply and total inventory level will be 1.025 weeks' supply, a reduction of inventory by 59%. Total delivery frequency is also reduced to half from 16,000 to 8,200.
Result
By applying weighed control based on ABC classification, required man-hours and inventory level are drastically reduced.
Alternate way of finding ABC analysis:-
The ABC concept is based on Pareto's law. If too much inventory is kept, the ABC analysis can be performed on a sample. After obtaining the random sample, the following steps are carried out for the ABC analysis.
Step 1: Compute the annual usage value for every item in the sample by multiplying the annual requirements by the cost per unit.
Step 2: Arrange the items in descending order of the usage value calculated above.
Step 3: Make a cumulative total of the number of items and the usage value.
Step 4: Convert the cumulative total of the number of items and usage values into a percentage of their grand totals.
Step 5: Draw a graph connecting cumulative % items and cumulative % usage value. The graph is divided approximately into three segments, where the curve sharply changes its shape. This indicates the three segments A, B and C.
