In materials management, ABC analysis is an inventory categorization technique dividing stock into three groups: 'A' items, which require very tight control and accurate records due to their high value; 'B' items, with moderate controls and importance; and 'C' items, having the simplest controls and minimal records. This method helps identify items impacting overall inventory cost and tailors management approaches accordingly. Since inventories vary in value, 'A' items demand frequent value analysis and strategies like just-in-time ordering to avoid excess capacity. 'B' items are moderately important, while 'C' items are the least critical, enabling organizations to prioritize resources effectively across different stock categories.
ABC analysis categories
There are no fixed thresholds for each class, and different proportions can be applied based on objectives and criteria which vary between companies.3 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.4 Examples of ABC class are:
- 'A' items – 20% of the items account for 70% of the annual consumption value of the items
- 'B' items – 30% of the items account for 25% of the annual consumption value of the items
- 'C' items – 50% of the items account for 5% of the annual consumption value of the items
Another recommended breakdown of ABC classes:5
- "A" approximately 10% of items or 66.6% of value
- "B" approximately 20% of items or 23.3% of value
- "C" approximately 70% of items or 10.1% of value of the items
ABC analysis in ERP packages
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 (parts).
In the absence of an ERP system, ABC Analysis can also be done in MS Excel.
Mathematical calculation of ABC analysis
Computed (calculated) ABC analysis delivers a precise mathematical calculation of the limits for the ABC classes.6 It uses an optimization of cost (i.e. number of items) versus yield (i.e. sum of their estimated importance). Computed ABC was, for example, applied to feature selection for biomedical data,7 business process management8 and bankruptcy prediction.9
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.
Distribution of ABC class| 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 (safety stock) of two weeks' supply, the factory will have 16,000 deliveries in four weeks and average inventory will be 2+1⁄2 weeks' supply.
Application of weighed purchasing condition| Uniform condition | Weighed condition | ||
|---|---|---|---|
| Items | Conditions | Items | Conditions |
| All items 14,213 | Re-order point=2 weeks' supplyDelivery frequency=weekly | A-class items 200 | Re-order point=1 week's supplyDelivery frequency=weekly |
| B-class items 400 | Re-order point=2 weeks' supplyDelivery frequency=bi-weekly | ||
| C-class items 3,400 | Re-order point=3 weeks' supplyDelivery frequency=every 4 weeks | ||
- Weighed purchase
In comparison, when weighed purchasing policy is applied based on ABC class, for example C class monthly (every four weeks) 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 (A 200×4=800)+(B 400×2=800)+(C 3,400×1=3,400)=5,000 and average inventory will be (A 75%×1.5weeks)+(B 15%x3 weeks)+(C 10%×3.5 weeks)=1.925 weeks' supply.
Comparison of "equal" and "weighed" purchase (4 weeks span)| ABC class | No of items | % of total value | Equal purchase | Weighed purchase | note | ||
|---|---|---|---|---|---|---|---|
| No of delivery in 4 weeks | average supply level | No of delivery in 4 weeks | average supply level | ||||
| A | 200 | 75% | 800 | 2.5 weeks | 800 | 1.5 weeksa | same delivery frequency, safety stock reduced from 2.5 to 1.5 weeksa, require tighter control with more man-hours. |
| B | 400 | 15% | 1600 | 2.5 weeks | 800 | 3 weeks | increased safety stock level by 20%, delivery frequency reduced to half. Fewer man-hours required. |
| C | 3400 | 10% | 13,600 | 2.5 weeks | 3,400 | 3.5 weeks | increased safety stock from 2.5 to 3.5 weeks' supply, delivery frequency is one quarter. Drastically reduced man-hour requirement. |
| Total | 4,000 | 100% | 16,000 | 2.5 weeks | 5,000 | 1.925 weeks | average inventory value reduced by 23%, delivery frequency reduced by 69%. Overall reduction of man-hour requirement. |
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.10 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.
See also
External links
- SAP library ABC Analysis
- Oracle Overview of ABC Analysis
- ABC Analysis in MS Excel
- ABC Analysis in R
References
Thomas E. Vollmann, Manufacturing planning and control systems for supply chain management ↩
Lun, Lai, Cheng (2010) Shipping and Logistics Management, p. 158 ↩
Wong, C., Using ABC Analysis for Inventory Control, APICS Redwood Empire Chapter, last updated on 10 February 2006, archived on 26 August 2009, accessed on 14 July 2024 https://web.archive.org/web/20090826174905/http://www.apics-redwood.org/articles/art0302BCW.htm ↩
Purchasing and Supply Chain Management By Kenneth Lysons, Brian Farrington ↩
Wild, T., Best Practice in Inventory Management, (2nd Ed., p. 40) ↩
Ultsch, Alfred, Jörn Lötsch. "Computed ABC analysis for rational selection of most informative variables in multivariate data." PLOS One 10.6 (2015): e0129767. ↩
Kringel, D., Ultsch, A., Zimmermann, M., Jansen, J. P., Ilias, W., Freynhagen, R., ... & Resch, E. (2016). Emergent biomarker derived from next-generation sequencing to identify pain patients requiring uncommonly high opioid doses. The pharmacogenomics journal. ↩
Iovanella, A.: Vital few e trivial many, Il Punto, pp 10-13, July, 2017. ↩
Barbara Pawelek, Jozef Pociecha, Mateusz Baryla, ABC Anal-ysis in Corporate Bankruptcy Prediction, Abstracts of the IFCS Conference, p 17, Tokyo, Japan,2017 ↩
Pareto's law in this example is that a few high usage value items constitute a major part of the capital invested in inventories whereas a large number of items having low usage value constitute an insignificant part of the capital. ↩