Material Master Data Cleansing and Standardization
10 steps to follow to achieve high quality Material Master Data
Material Master Data Cleansing is a process of identifying, correcting, and enhancing the quality of material master data within an organization’s systems. It includes information about the products or materials that an organization buys, produces, stores, and sells. Cleansing and Standardizing this data is essential for maintaining accurate inventory records, improving operational efficiency, and supporting business processes such as procurement, production planning, and sales in your Organization’s ERP system.
Here are the 10 steps typically involved in material master data cleansing and standardization:
- Data Profiling:
Analyze the existing material master data to identify inconsistencies, errors, duplicates, and other data quality issues. Here you can use various Data profiling tools that can help automate this process by examining data patterns, distributions, and anomalies. Or just use Excel to begin.
- Data Cleansing Rules:
Define data cleansing rules and standards based on industry best practices, organizational requirements, and regulatory guidelines. These rules specify criteria for data validation, correction, standardization, and enrichment.
- Duplicate Identification and Resolution:
Identify duplicate material records within the system and consolidate or eliminate redundant entries. Use techniques such as fuzzy matching, similarity scoring, and record linkage to identify potential duplicates and merge or purge them as needed.
- Data Standardization:
Standardize material data attributes such as names, descriptions, units of measure, and classifications to ensure consistency and uniformity across the organization. Apply formatting rules, data validation checks, and reference data sets to standardize data values.
- Data Enrichment:
Enhance material master data by enriching it with additional information or attributes from both internal and external sources. This may include supplier data, product specifications, classifications such as UNSPSC or Eclass, and regulatory compliance data such as HS codes.
- Data Validation and Correction:
Validate material master data against predefined business rules, constraints, and reference data to ensure accuracy and integrity. Correct any data errors, inconsistencies, or inaccuracies identified during the validation process.
- Data Governance with clear roles and responsibilities:
Establish data governance processes and clear roles and responsibilities in relation to master data creation and management. Assign data stewards responsible for managing and maintaining specific material master data settings, enforcing data quality standards, and resolving data-related issues.
- Master Data Auditing:
Implement ongoing monitoring and auditing processes to ensure the continued accuracy and quality of material master data as per set new standards. Regularly audit data quality metrics, address emerging data issues, and update data cleansing rules as needed.
- Data Integration and Synchronization:
Make sure that your material master data management process is integrated with your ERP system, Engineering Drawings Management Systems and possibly in MDG system in case you are using multiple ERP systems in your organization. Ensure that material master data changes are synchronized and propagated across relevant systems in a timely manner.
- User Training and Awareness:
Provide training and guidance to users involved in creating and managing material master data to ensure ongoing data quality awareness and adherence to data governance policies and procedures.
By following the above steps organizations can improve the accuracy, consistency, and reliability of their material master data, leading to better decision-making, operational efficiency, and customer satisfaction.
