Standard Operating Procedure for Data Governance Framework

Purpose

The purpose of this SOP is to establish a comprehensive Data Governance Framework within the pharmaceutical manufacturing facility. This framework aims to ensure the effective management, integrity, security, and compliance of data throughout its lifecycle.

Scope

This SOP applies to all personnel involved in data generation, processing, management, and decision-making processes, including operators, IT personnel, quality control personnel, and quality assurance personnel.

Responsibilities

Data Governance Officer: Responsible for coordinating and overseeing the implementation of the Data Governance Framework, including policy development, communication, and monitoring of compliance.
Department Supervisors: Responsible for enforcing data governance policies within their respective departments and ensuring compliance with the framework.
Data Stewards: Appointed individuals responsible for the quality, security, and compliance of data within specific datasets or processes. Collaborate with Data Governance Officer to address data-related issues.

Procedure

Data Governance Policy Development: Develop and document a Data Governance Policy that outlines the principles, objectives, and responsibilities of the Data Governance Framework. Ensure alignment with regulatory requirements and industry best practices.
Appointment of Data Stewards: Identify and appoint Data Stewards for specific datasets or processes. Clearly define their roles, responsibilities, and authority in maintaining the quality, security, and compliance of the assigned data.
Data Classification: Implement a data classification system that categorizes data based on its sensitivity, criticality, and regulatory requirements. Clearly communicate the handling and security measures associated with each classification level.
Data Access and Security Controls: Establish access controls and security measures to ensure that only authorized personnel have access to specific datasets. Implement encryption, user authentication, and audit trails to enhance data security.
Data Quality Standards: Define and document data quality standards for accuracy, completeness, consistency, and timeliness. Implement measures to monitor and report data quality issues. Establish corrective and preventive actions for addressing identified issues.
Change Management: Implement a change management process for data-related changes, including modifications to data structures, data dictionaries, and data processing workflows. Ensure that changes are documented, reviewed, and approved before implementation.
Data Lifecycle Management: Develop procedures for the systematic management of data throughout its lifecycle, from creation and processing to archival or deletion. Clearly define responsibilities for data owners, data custodians, and data archivists.
Monitoring and Auditing: Establish monitoring and auditing mechanisms to assess compliance with data governance policies. Conduct periodic audits of data access logs, data quality reports, and data handling practices. Address identified non-compliance promptly.
Communication and Training: Communicate the Data Governance Framework and associated policies to all relevant personnel. Provide training on data governance principles, procedures, and the importance of maintaining data integrity and security.
Continuous Improvement: Conduct periodic reviews of the Data Governance Framework to assess its effectiveness. Solicit feedback from stakeholders and make improvements as necessary to adapt to changes in regulatory requirements or organizational needs.

Abbreviations

No abbreviations are used in this SOP.

Documents

Data Governance Policy
Data Stewardship Guidelines
Data Classification Matrix
Change Management Records
Monitoring and Auditing Reports
Training Materials

SOP for Data Governance Framework