Large Industrials

XSB participates in the development of Parts Management Standards for the Government. This, coupled with a dozen years of experience, and more than 100 parts data management projects completed in support of DoD has given us high visibility into the pervasive data quality issues in this space.  Due to the size and complexity of the enterprise and its supply chain, the parts management challenge facing many of the large industrials in the A&D market is not unlike that faced by the DoD.  Duplicate and obsolete parts are frequently described differently across multiple divisions of the same company, complicating the development of common parts libraries and resulting in multiple enterprise wide inefficiencies.  Studies by XSB, DoD and Deloitte show that standardizing enterprise part data can reveal ways to reduce total parts by 10 to 15% with concurrent reductions in direct and indirect costs associated with these items. XSB is uniquely positioned to address these problems.

XSB has invested $20 million in developing patented parts management technologies to standardize data and identify common parts from the 100M+ items in the A&D supply chain. Our major focus is automated product data understanding to solve the following problems:

• Automated discovery of product data in online catalogs and

• Precise interpretation of product characteristics and

• Their aggregation across multiple internal and external data sources for the same part

These capabilities require semantic understanding of product data. XSB relies on an ontology-driven infrastructure that describes classes of products from more general to specific and various characteristics applicable in those classes. Unlike many other commercial solutions in the MDM universe, the XSB system is finely tuned and narrowly focused for the discovery and understanding of product data only.  The result of these processes is clean, usable data that is available across the entire enterprise and facilitates efficient search, attribute-based product comparison, spend analysis, and a variety of other uses.