What are the best practices for creating and maintaining master data governance policies and procedures?

1 Define master data domains and attributes

The first step in master data governance is to identify and define the master data domains and attributes that are relevant and critical for your organization. A domain is a category of master data, such as customer or product, and an attribute is a specific property or characteristic of a domain, such as name or price. You should document the definitions, descriptions, formats, and sources of each domain and attribute, as well as the relationships and dependencies among them. This will help you to establish a common understanding and vocabulary of master data across the organization, and to avoid duplication and inconsistency.

2 Establish roles and responsibilities

The second step in master data governance is to assign roles and responsibilities for the creation, maintenance, and usage of master data. You should define who is the owner, steward, custodian, and consumer of each master data domain and attribute, and what are their rights and obligations. The owner is the person or department who has the authority and accountability for the quality and integrity of a master data domain. The steward is the person or team who is responsible for ensuring the compliance with the governance policies and procedures, and for resolving any issues or conflicts. The custodian is the person or system who performs the technical tasks of creating, updating, deleting, and storing master data. The consumer is the person or system who uses master data for business purposes.

3 Implement data quality rules and controls

The third step in master data governance is to implement data quality rules and controls that ensure the validity, completeness, accuracy, timeliness, and consistency of master data. You should define the criteria and metrics for measuring and monitoring data quality, such as accuracy rate, completeness rate, duplication rate, and timeliness rate. You should also establish the processes and tools for validating, cleansing, enriching, and standardizing master data, such as data quality software, workflows, and checklists. You should also define the procedures and escalation paths for handling data quality issues and exceptions, such as error reporting, correction, and prevention.

4 Enable data access and security

The fourth step in master data governance is to enable data access and security that ensure the availability, confidentiality, and integrity of master data. You should define the policies and rules for granting, revoking, and auditing access rights to master data, based on the roles and responsibilities of the users and the sensitivity of the data. You should also implement the technical measures and safeguards for protecting master data from unauthorized access, modification, or loss, such as encryption, authentication, authorization, backup, and recovery.

5 Align data governance with business strategy

The fifth step in master data governance is to align data governance with business strategy that ensure the relevance, value, and alignment of master data with the business goals and objectives. You should communicate and collaborate with the business stakeholders and users to understand their needs and expectations from master data, and to solicit their feedback and input on the governance policies and procedures. You should also align the data governance objectives and initiatives with the business strategy and priorities, and demonstrate the benefits and outcomes of data governance for the business performance and value.

6 Continuously monitor and improve data governance

The sixth step in master data governance is to continuously monitor and improve data governance that ensure the effectiveness, efficiency, and maturity of data governance. You should measure and report on the data quality indicators and metrics, and identify the root causes and impacts of data quality issues. You should also evaluate and audit the compliance and adherence to the data governance policies and procedures, and identify the gaps and risks. You should also review and update the data governance policies and procedures based on the changing business needs and requirements, and implement the best practices and lessons learned from the data governance activities.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?