Classifying large catalogues of products and services according to the UNSPSC can be an overwhelming, time-consuming, and costly process. A leading industrial supplier faced this challenge with their vast catalogue of items, realising that manual classification was not only inefficient but also expensive. They turned to AICA’s AI-powered classification solution, which drastically improved speed, reduced operational costs, and enhanced overall efficiency.
In this article, we explore how AICA transformed the supplier’s classification process, achieving significant time and cost savings by utilising cutting-edge AI technology.
The Challenge: A Daunting Task
The industrial supplier’s catalogue consisted of 145,000 items, all requiring precise UNSPSC classification. Manual methods, as projected, would take around 1,209 days to complete, given that each item would take about 4 minutes to classify, working an 8-hour day.
With such a massive time and cost commitment, the company sought a more efficient, scalable solution—this is where AICA came in.
The AICA Advantage in UNSPSC
AICA introduced its advanced AI-powered classification solution, specifically designed to tackle the inefficiencies of manual classification. Leveraging machine learning algorithms, AICA automated the classification process with high accuracy, significantly reducing both the time and cost needed to complete the task.
Implementation and Impact
Speed
Using AICA’s AI, the entire catalogue of 145,000 items was classified in just 20 days—a vast improvement over the 1,209 days initially estimated for manual work. The ability of the AI to classify items swiftly enabled the supplier to dramatically speed up the process without sacrificing accuracy.
Accuracy
AICA’s AI achieved a confidence score of over 90% for 78% of the items, meaning only 22% of the catalogue required further manual review. This high accuracy rate reduced the number of items that needed human intervention, cutting down the workload and allowing the supplier to focus on a smaller subset of items.
Cost Efficiency
Using AICA’s AI-powered classification solution resulted in a significant cost reduction, amounting to roughly one-third of the cost compared to manual classification methods.
Although the AI handled the bulk of the classification work, AICA’s QA/QC team played a vital role in ensuring the highest levels of accuracy for the remaining items. Our team managed the manual classification of items flagged by the AI and conducted quality control checks to ensure consistency and reliability throughout the project. This collaboration between AI and human expertise allowed for a seamless and efficient classification process.
Conclusion
By leveraging AI technology and combining it with a skilled team for quality control, AICA successfully transformed the supplier’s product classification process. The result was not only faster completion times but also considerable cost savings. This case study demonstrates how AI can redefine industry standards by offering scalable, efficient, and cost-effective data classification solutions.
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