Supply Chain Data Governance Checklist
Unlock the full potential of your supply chain data! This Supply Chain Data Governance Checklist ensures accuracy, security, and compliance, minimizing risk and maximizing efficiency. Download now and transform your data into a strategic asset.
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Data Ownership & Accountability
Defines roles and responsibilities for data quality, security, and compliance within the supply chain.
Who is the Data Owner for Product Master Data?
Who is accountable for data quality within the transportation network?
Contact Name of Primary Data Steward
Number of dedicated data stewards
Describe how data ownership responsibilities are communicated to relevant personnel.
Date of Last Data Ownership Review
Data Quality Standards
Outlines criteria for data accuracy, completeness, consistency, and timeliness.
Data Accuracy Rate (%)
Data Completeness Rate (%)
Data Consistency Score (1-10)
Last Data Quality Validation Date
Data Validation Method
Description of Data Validation Rules
Data Source Accuracy Rating
Data Security & Access Controls
Ensures appropriate data security measures and access controls are in place to protect sensitive information.
Encryption Method Used (Data at Rest)
Authentication Method
Minimum Password Length (Characters)
Access Control Model
Data Access Restricted by:
Last Review Date of Access Controls
Data Integration & Interoperability
Evaluates the effectiveness of data integration processes between supply chain partners and systems.
Number of Integration Points
Integration Method (e.g., EDI, API, Flat File)
Description of Data Formats Used
Protocols Used (e.g., AS2, SFTP, HTTPS)
Date of Last Integration Testing
Description of any Integration Errors Encountered & Resolution
Data Retention & Archiving
Addresses data retention policies, archiving procedures, and compliance with relevant regulations.
Data Retention Period (Years)
Archiving Method
Last Data Archiving Review Date
Justification for Retention Period
Data Format for Archival
Sample Archival File (for review)
Storage Capacity Required (GB)
Master Data Management (MDM)
Reviews the processes and tools used to manage critical master data elements (e.g., product, supplier, customer).
MDM System in Use?
Number of Master Data Domains Managed
Data Stewardship Model?
Last MDM Data Quality Review Date
Summary of Key MDM Challenges
Data Sources feeding into MDM?
Data Synchronization Frequency?
Data Compliance & Regulatory Requirements
Verifies adherence to relevant data privacy laws (e.g., GDPR, CCPA) and industry regulations.
Applicable Data Privacy Regulations?
Specific Regulatory Requirements (e.g., specific data fields, consent requirements)
Date of Last Regulatory Compliance Review
Number of Data Subject Access Requests (DSARs) Received in Last Year
Supporting Documentation (e.g., consent forms, compliance reports)
Data Transfer Agreements (if applicable)
Data Monitoring & Auditing
Establishes mechanisms for monitoring data quality, identifying anomalies, and conducting periodic audits.
Frequency of Data Quality Checks
Last Data Quality Audit Date
Monitoring Tools Used
Summary of Recent Data Anomalies Detected
Number of Data Quality Exceptions Identified in Last Period
Audit Trail Status
Data Training & Awareness
Assesses the level of data governance awareness and training among supply chain personnel.
Number of employees who have completed data governance training
Primary training delivery method (select one)
Date of last data governance training update
Briefly describe the content of the data governance training program
Which topics are covered in the data governance training? (Select all that apply)
Method for assessing training effectiveness (select one)
Data Incident Response
Defines procedures for responding to data breaches and other data-related incidents.
Description of Incident
Incident Date & Time
Incident Severity Level
Initial Response Actions Taken
Estimated Financial Impact (USD)
Supporting Documentation (Logs, Screenshots)
Incident Status
Root Cause Analysis Summary
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