In this episode of Lokad TV, we discuss ABC analysis, an inventory categorisation method that has its roots in Pareto’s 80-20 rule. The method works by splitting up a catalog based on its perceived worth.
The Pareto principle was formulated by Italian economist Vilfredo Pareto; it dates back to the late 19th century and states that 80% of the overall consumption value is based on only 20% of total items. In other words, demand is not evenly distributed between items and top sellers vastly outperform the rest.
We discover how ABC analysis works and examine both the positive and negative sides of it. We see that despite the fact that it has been around for multiple decades and that it’s majorly incorporated into many major ERP packages - not to mention widely adopted by the supply chain industry as a whole - it fails to embrace a more modern approach and make the most of easily available software that can automate the bulk of inventory management. One of the major issues of ABC analysis is its over-simplification of products, which leads to instability over time.
We learn more about this ABC approach, its underlying problems and what can be improved upon, so that you can take care of the most important products in a catalogue, without classifying them.
To finish up the episode, we also debate in further depth Lokad’s unique approach to inventory management and the philosophy behind it: focus on the ROI, where every product is optimized against its own fine-grained properties.
00:24 Can you explain a little more about what ABC analysis actually is?
02:02 How does it work?
03:05 Is ABC analysis something that is being used by companies on a daily basis?
06:04 Why categorizing products according to their importance is not so relevant for you?
08:58 What are the problems with the ABC approach?
13:01 How can we approach things in a better way? If you’re not classifying your products, how do you know you are taking care of the most important items in your catalogue?
18:59 Isn’t Lokad just a more sophisticated version of ABC analysis, just at a much more granular, finer grain level? What are the key differences?
21:37 There must be some positives to take from this approach. What are the benefits of an ABC approach?