MRO Material Data Cleansing, Enrichment, and Classification - A Case Study

About Client

The client, Chemtrade Logistics, is a publicly traded chemical manufacturing company headquartered in Toronto, Canada with operations across North America and Brazil. Chemtrade approached us to cleanse, enrich and classify its MRO inventory materials data. Chemtrade uses SAP ERP system and the scope of the cleansing project included processing 31,000 materials in the first phase and continuous support as and when new material would be purchased.

Data Challenges

• Duplicate material entries were created and maintained in SAP.
• Little or no standardization in naming convention - material name, specification values and in unit of modifiers.
• Materials with insufficient description to identify the material and its type.
• Missing mandatory technical attributes to uniquely identify a material.
• Many supplier details were listed out in manufacturer’s name and part number.

Project Scope

The entire project scope broadly constituted the following major activities.

• Input data analysis
• Material sourcing
• Validate and standardize manufacturer’s/supplier’s name and part numbers
• Noun-Modifier assignment & schema mapping/ development
• Values capture – Data capture guidelines and UoM standards.
• Description generation
• De-duplication
• UNSPSC classification

Input Data Analysis

Client sent the data extract to SoftNis in an Excel file format in the English language. An initial analysis was performed on the input data to ensure that it had the necessary information to identify the product, such as the manufacturer's/supplier's name, part number, or description.

Material Sourcing

The materials were sourced as per the following hierarchy:

Manufacturer’s website/catalogs: As a first step we tried to source the material information from the actual manufacturer’s website to obtain authenticated, reliable and precise results.

Vendor's website/catalogs: In the absence of product listing or any required information on the manufacturer’s page, we extracted the material information from the client’s vendor pages as the next logical step.

Third party supplier’s websites/catalogs: When the product information was not found either in the manufacturer’s or vendor’s pages, we sourced it from the material third party pages.

Not Found: When product listing or product details or any relevant information was absolutely not found even after an exhaustive search, we concluded that the material was not found.

Validate and Standardize Manufacturer's/Vendor’s Name and Part numbers

We identified and validated the manufacturer’s/vendor’s name and part numbers available in the input description (or in any other provided input columns) and populated it in separate columns. All manufacturer’s/ vendor’s name and part numbers were standardized to one format as per the actual legal name of the manufacturer/vendors and their part number representation.

Noun-Modifier(NM) Assignment & Schema Mapping/Development

Our subject matter experts (SME) identified each material by defining the noun-modifier. The noun-modifiers were defined based on the input description and sourced (if) information. Once the noun-modifier were defined, it was mapped to SoftNis dictionary for attribute templates. Currently, SoftNis has more than 5,000 unique noun -modifier combinations in the dictionary.

Populate Attribute Values

Values were captured as per the attributes defined for a noun-modifier.

Found materials: For all the sourced materials the input information was validated and missing values were captured from the respective sourced websites/catalogs.

Not found materials: For all the not found materials, attribute values were captured from the input description.

Duplicate Material Identification

The exact duplicates were identified to know if both the materials have the same manufacturer’s name and part number. For materials where manufacturer’s/supplier’s name, part numbers, were not available in the input data, potential duplicates were identified based on the long description.

UNSPSC Classification

The latest UNSPSC version - 23.0701 was used for classification. A complete UNSPSC classification was provided including Segment, Family, Class, and Commodity, with both text definitions of each along with the corresponding codes.

Benefit to Customer

• Reduced inventory by direct 10%, through duplicate material detection.
• Provided sufficient information to identify the material uniquely and improve the purchase process.
• Improved procurement spend visibility with UNSPSC hierarchy.
• Consistent, standardized and enriched Material Master data helped our client to identify business and technology gaps.
• Standardized and validated separate list of manufacturers and vendors helped to optimize supply chain operations.

Testimonial

“SoftNis helped us to cleanse and classify our 31,000 MRO materials’ data in just 6 weeks. I am pleased with the data quality and the duplicate materials which they identified during the process.”

-Tejinder Kaushik, Vice President, Head of IT, Chemtrade Logistics Inc. Canada.

Proof of Concept (PoC) - No Cost, No Obligation

We are pleased to work on your data samples as proof of concept that comes with no strings attached. Send us your data samples at [email protected] for POC.