Industry: FMCG and Consumer Goods
Master Data Cleansing and Governance at Mondelez International
About Mondelez International
Mondelez International is an American multinational confectionery, food, and beverage company based in Illinois and is the world’s largest snacks companies. They operate in variety of confectionaries and ready to eat food items and have large holdings in the retail industry.
- Large no. of products.
- New catalyst system leads to a lot of duplication and inconsistent material data.
- No existing duplicity check.
- No mass extend of materials in various plants.
- No existing workflow process for material master.
- No standard way to generate description according to specific material naming convention.
- User enters wrong values in fields as there is no criteria to check the values.
- No approval process and real time business validations are in place.
- No data Extraction functionality.
Through cleansing and standardization process, MDO removed about 6750 duplicate records out of 45000 existing records making the data free of duplicity and redundancy. This was further enhanced with MDO Governance implemented in parallel for long term sustainability. MDO standardized various MRO spare parts and other materials using nouns, modifiers and business validations creating short and long descriptions for the same.
- Technical workers can easily identify materials at a plant or across plants for maintenance.
- Inventory and reporting became efficient leading to effective Maintenance.
- Inventory is not duplicated or stored in multiple locations leading to Cost/Storage Control and ease of Stocktakes.
- Inventory is standardised and optimised.
- Identification of baskets of goods per category for procurement allows economies of scale.
- Accurate spend analysis and directed procurement.
- Approval for increases in stock holdings of new materials are justified with duplicate searching ensuring minimum increases in Cost hence Inventory Control.
- Ensures a Governance process for clean and consistent master data across all plants.