-
Subscribe to Blog:
SEARCH THE BLOG
CATEGORIES
- Aerospace
- Asset Maintenance
- Automotive
- Blog
- Building Products
- Case Studies
- Chemical Processing
- Consulting
- Food & Beverage
- Forestry Products
- Hospitals & Healthcare
- Knowledge Transfer
- Lean Manufacturing
- Life Sciences
- Logistics
- Manufacturing
- Material Utilization
- Metals
- Mining
- News
- Office Politics
- Oil & Gas
- Plastics
- Private Equity
- Process Improvement
- Project Management
- Spend Management
- Supply Chain
- Uncategorized
- Utilities
- Whitepapers
BLOG ARCHIVES
- July 2025 (1)
- June 2025 (4)
- May 2025 (1)
- April 2025 (1)
- March 2025 (1)
- February 2025 (4)
- January 2025 (4)
- December 2024 (4)
- November 2024 (2)
- October 2024 (6)
- September 2024 (5)
- August 2024 (5)
- July 2024 (6)
- June 2024 (3)
- May 2024 (3)
- April 2024 (4)
- March 2024 (3)
- February 2024 (4)
- January 2024 (5)
- December 2023 (2)
- November 2023 (1)
- October 2023 (6)
- September 2023 (3)
- August 2023 (4)
- July 2023 (2)
- June 2023 (3)
- May 2023 (7)
- April 2023 (3)
- March 2023 (3)
- February 2023 (5)
- January 2023 (6)
- December 2022 (2)
- November 2022 (5)
- October 2022 (5)
- September 2022 (5)
- August 2022 (6)
- July 2022 (3)
- June 2022 (4)
- May 2022 (5)
- April 2022 (3)
- March 2022 (5)
- February 2022 (4)
- January 2022 (7)
- December 2021 (3)
- November 2021 (5)
- October 2021 (3)
- September 2021 (2)
- August 2021 (6)
- July 2021 (2)
- June 2021 (10)
- May 2021 (4)
- April 2021 (5)
- March 2021 (5)
- February 2021 (3)
- January 2021 (4)
- December 2020 (3)
- November 2020 (3)
- October 2020 (3)
- September 2020 (3)
- August 2020 (4)
- July 2020 (3)
- June 2020 (5)
- May 2020 (3)
- April 2020 (3)
- March 2020 (4)
- February 2020 (4)
- January 2020 (4)
- December 2019 (3)
- November 2019 (2)
- October 2019 (4)
- September 2019 (2)
- August 2019 (4)
- July 2019 (3)
- June 2019 (4)
- May 2019 (2)
- April 2019 (4)
- March 2019 (4)
- February 2019 (5)
- January 2019 (5)
- December 2018 (2)
- November 2018 (2)
- October 2018 (5)
- September 2018 (4)
- August 2018 (3)
- July 2018 (2)
- June 2018 (4)
- May 2018 (3)
- April 2018 (3)
- March 2018 (2)
- February 2018 (2)
- January 2018 (1)
- December 2017 (1)
- November 2017 (2)
- October 2017 (2)
- September 2017 (1)
- August 2017 (2)
- July 2017 (2)
- June 2017 (1)
- April 2017 (3)
- March 2017 (3)
- February 2017 (2)
- January 2017 (2)
- December 2016 (2)
- November 2016 (4)
- October 2016 (4)
- September 2016 (3)
- August 2016 (6)
- July 2016 (4)
- June 2016 (4)
- May 2016 (1)
- April 2016 (3)
- March 2016 (4)
- February 2016 (2)
- January 2016 (4)
- December 2015 (3)
- November 2015 (3)
- October 2015 (1)
- September 2015 (1)
- August 2015 (4)
- July 2015 (6)
- June 2015 (4)
- May 2015 (7)
- April 2015 (6)
- March 2015 (6)
- February 2015 (4)
- January 2015 (3)
CONNECT WITH US
Tag Archives: Data Classification
In industrial operations, Maintenance, Repair, and Operations (MRO) functions are essential but often overlooked as a source of inefficiency. While MRO spend typically accounts for less than 10% of a company’s total procurement, it can represent up to 80% of its transactional activity. The root of this imbalance?
Poor data.
Bad MRO data is more than a technical issue, it’s a strategic liability. Duplicate part numbers, inconsistent naming conventions, missing attributes, and obsolete records all combine to slow down procurement, increase errors, and inflate costs. The problem is so pervasive that some studies estimate up to 26% of all purchase orders require rework due to bad data.
How Poor Data Inflates Transaction Costs
Economists refer to the hidden friction in business processes as transaction costs-the overhead incurred not from the value of goods themselves, but from the effort required to find, negotiate, and manage those goods.
In MRO, transaction costs are driven by three main issues:
- Search & Information Costs: Technicians spend hours searching for parts due to inconsistent or missing descriptions. Inventory may be in stock but not findable due to duplicates or poor categorization.
- Bargaining & Decision Costs: Without a standardized view of item-level data, procurement can’t consolidate purchases, compare prices, or analyze spend across suppliers, weakening negotiation power.
- Policing & Enforcement Costs: Mismatches between purchase orders, invoices, and goods receipts arise from inaccurate data, creating labor-intensive reconciliation and delays in payment or fulfillment.
These costs don’t just reduce efficiency, they erode trust in systems and waste valuable labor hours across procurement, maintenance, and finance teams.
The Power of a Clean, Structured MRO Dataset
Fixing these problems starts with building a clean, enriched, and standardized MRO data foundation. That means:
- Removing duplicate entries and normalizing naming conventions
- Enriching descriptions with missing attributes like dimensions, materials, and manufacturer part numbers
- Assigning consistent classifications using global taxonomies such as UNSPSC or eCl@ss
When data is standardized and machine-readable, organizations can streamline part identification, automate procurement, and unlock powerful analytics. They can also reduce inventory costs, prevent emergency orders, and improve supplier performance tracking.
Automating the Solution with AI
The scale and complexity of MRO datasets make manual data cleansing and classification impractical. That’s where AICA’s Product Data Intelligence platform plays a pivotal role.
AICA automates the process of data classification, cleansing, and enrichment by applying domain-specific machine learning models trained on millions of MRO records. It can:
- Detect and merge duplicates
- Normalize inconsistent formats
- Assign accurate UNSPSC GPC, or eCl@ss codes
- Enrich missing product attributes
The result is a reliable, structured material master that integrates directly into ERP, EAM, and procurement systems, serving as a “single source of truth” for all MRO items.
How USC Consulting Group and AICA Work Together
We’ve partnered with AICA enabling us to deliver rapid, scalable improvements in material master quality for our clients, unlocking cost savings, productivity gains, and strategic sourcing capabilities.
Together, USC and AICA help organizations move beyond firefighting and toward a future of proactive, data-driven operations, where every transaction is faster, smarter, and more reliable.
Start your product data transformation today, get in touch with us to find out more.
One of USC Consulting Group’s partners, AICA, has developed a groundbreaking Agentic AI Classification Tool that automates UNSPSC classification, leveraging advanced AI solutions to transform product data management, procurement optimization, inventory management, spend analysis, compliance auditing, and overall operational efficiency.
This innovative tool represents a significant leap forward in data classification technology and has already begun to reshape how organizations approach the classification of products and services.
What is Agentic AI?
Agentic AI refers to advanced artificial intelligence systems that operate autonomously, executing tasks with minimal or no human intervention. Unlike traditional AI models that require constant oversight, agentic AI adapts to predefined goals and delivers results independently, maintaining high levels of accuracy and efficiency.
This approach reduces reliance on manual processes and human input, enabling faster execution, lower costs, and fewer errors.
Why This Tool is Transformative
The Agentic AI Classification Tool is a breakthrough in automating the classification of products and services using the United Nations Standard Products and Services Code (UNSPSC). Here’s why this technology stands out:
- Fully Automated Classification: The tool autonomously handles the entire UNSPSC classification process, eliminating the need for manual intervention and significantly reducing time and labor requirements.
- Exceptional Accuracy and Speed: With unparalleled precision, the tool processes data faster than traditional methods, ensuring reliable and actionable results.
- Cost-Effectiveness: By minimizing the need for manual classification, businesses can achieve substantial cost savings.
- Versatility Across Systems: While designed for UNSPSC, the tool’s adaptable architecture can support other classification systems, extending its application across industries.
- Built-In Quality Assurance: Quality scoring features allow businesses to identify areas where human verification may be beneficial, ensuring data integrity.
Key Features
The Agentic AI Classification Tool includes several advanced features:
- Autonomous Classification: Fully automates classification tasks, streamlining workflows.
- API Integration: Seamlessly integrates with enterprise systems and can be implemented in weeks.
- Scalability: Efficiently processes large datasets, making it ideal for high-volume data management.
- Customizable Applications: Capable of adapting to various classification systems to meet industry-specific needs.
- Quality Feedback Loop: Provides quality scores to monitor and maintain accuracy.
Use Cases
The technology offers solutions across a variety of business functions, including:
Procurement Optimization: Improved supplier management and purchasing efficiency through accurate product classifications.
Inventory Management: Enhanced stock control by reducing categorization errors.
Spend Analysis: More accurate financial reporting and budgeting through precise spend data classification.
Compliance and Auditing: Support for regulatory requirements with standardized and auditable product classifications.
A Transformative Impact on Data Management
This Agentic AI tool enables businesses to reduce classification times, cut labor costs, and achieve higher levels of accuracy and reliability than traditional manual methods. It also supports organizations in scaling their operations to handle increasing data volumes effortlessly.
Looking Ahead
As one of USC Consulting Group’s trusted partners, AICA continues to lead the way in AI-powered solutions for data classification. Their Agentic AI technology exemplifies how innovation can drive efficiency and improve outcomes for businesses managing complex data systems.
By leveraging tools like this, organizations can focus their resources on strategic goals, leaving routine and labor-intensive tasks to advanced AI solutions.