The old saying "Garbage in, Garbage Out" still applies
Access to the right data is essential, as accurate and properly coded data provides the foundation for category management strategies, including leveraging, pricing agreements, quantity discounts, value analysis, supply base optimization and other important cost management activities. Data Cleansing is actually a process that involves multiple stages.
Data Audit is about reviewing of existing data, Menigma performs various process to analyse the data and provide the detailed report on quantity and quality of master data. This process includes
- Validate that all required fields are included (mandatory vs. optional fields)
- Flag duplicate items
- Provide Content Audit Reports
Cleanse content for a consistent look and feel, product descriptions are normalized as per the rules and standards defined by customers, this step includes
- Standardize punctuation
- Expand abbreviations using standard and commodity-specific abbreviation cross-reference
- Remove special characters
- Standardize UOM
- Re-arrange the characteristics as per the requirement
Menigma provides classifications to the descriptions as per standard or custom schema/taxonomies like UNSPSC, SIC, NAICS, RUS, etc
- Categorize each Items to taxonomy choose by customer
- Identify items that don’t fit into categorization taxonomy
Category-specific attribute value population from existing item descriptions
- Category-specific attributes will be obtained from the taxonomy (e.g. category-specific attributes may be material and length for category “cable ties”).
- Attribute values will be sourced only from the description fields.
- As per defined description rules, generate descriptions by adding category-specific attribute values (e.g., noun, modifier, attribute values) (optional).
Category-specific attribute value sourcing
- Source category-specific attribute values from supplier and manufacturer documents and web sources.
- As per defined description rules, generate description by adding category-specific attribute values (e.g., noun, modifier, attribute values).
Source graphic images in the prescribed format and size from supplier and manufacturer documents and web sources.