Navigating the Maze of Manual Data Management
When GIS customers provide extensive Excel files containing descriptions of C-class items they wish to purchase, sourcing specialists must manually clean, review, and update these lists. This labor-intensive process is not only time-consuming but also prone to human error. Proper categorization of items is crucial for approaching the right vendors, consolidating demand, and negotiating better deals. The manual process hampers GIS's ability to efficiently serve their growing customer base.
Unlocking Faster Onboarding and Improved Supplier Matching
By automating item categorization and enhancing data quality, GIS can significantly reduce onboarding time for customers and improve product matching with suppliers' offerings. This will lead to increased customer satisfaction, streamlined procurement processes, and the capacity to handle a larger volume of clients without compromising on efficiency or quality.
Combining AI and Human Expertise for Optimal Categorization
An effective solution must automate the task of item categorization with high accuracy, minimize manual workload, and continuously improve the performance of the models over time. This will enable GIS to efficiently manage an increasing number of clients and suppliers, ultimately contributing to the company's growth and success.

Faktion's IDQO – An AutoML Platform to automate data quality optimization
Faktion's IDQO is an autoML platform designed to automate manual data quality tasks, such as product data classification, product matching, data enrichment, and data quality validation. By leveraging this powerful solution, GIS International can optimize data quality and streamline their operations to better serve their clients and suppliers.
AI-Powered Categorization, Data Enrichment, and Active Learning
Faktion collaborated with GIS to automate item categorization, achieving a baseline accuracy of 88% for 12 main categories and their respective sub-categories. To further increase accuracy by 5%, input features were augmented with data enrichment using both the Bing search API for relevant keywords (used when abstract item codes are encountered) and a 'GPT in the loop' feature for text summaries (applied when items have a lot of unstructured metadata). Human annotators participated in the training phase through active learning, significantly reducing labeling time. A co-pilot of the ML models was also built, providing a trust score during inference with configurable thresholds.
Resulting in a Transformative Partnership for Optimized Procurement
The implementation of the automated item categorization solution has dramatically improved efficiency and accuracy. Domain experts manually validate tasks that do not meet the set threshold, further enhancing the models' performance over time. This collaboration has revolutionized GIS International's operations, providing better customer experiences, more effective supplier matching, and the ability to handle a greater volume of clients without sacrificing quality or speed.
Expanding the Partnership to Tackle New Data Quality Challenges and Opportunities
As GIS International and Faktion continue to build on the success of their collaboration, they aim to address other data quality challenges and opportunities in the procurement process. By leveraging the IDQO platform and the power of AI, they plan to tackle issues such as item matching, supply chain data, and more. This ongoing partnership will ensure that GIS stays at the forefront of procurement innovation, continually optimizing and streamlining their processes to better serve their clients and suppliers. The collaboration is poised to set new industry standards and reshape the future of C-class item procurement.
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