In a landscape where data underpins every strategic decision, data governance policies are crucial for ensuring accuracy, compliance, and strategic value in your organization’s data management strategy. Data governance policies are formal documents or sets of rules that outline how an organization collects, stores, manages, shares, and disposes of data. They are designed to ensure that data is handled with security, efficiency, and compliance.

While data governance policies are key for leveraging data as a strategic asset, it is important to acknowledge that policies can not effectively inform or enforce behavior independently.

Although these carefully crafted legal documents play a significant role, they do not substitute for practical, real-life data guardrails that impact individuals at the point of data entry and use. Before we dive deeper into the intricacies of data governance and the practical tools that support it, let's clearly define what data policies are.  

DEFINING DATA POLICY AND DATA GOVERNANCE 

1. Data Policy: A data policy is a set of principles and guidelines that dictate how data should be governed within an organization. Policies cover data quality, access, security, and compliance with legal and regulatory standards. 
2. Data Governance: This refers to the overall management of the availability, usability, integrity, and security of the data employed in an organization. Data governance encompasses data policies, as well as the processes and people that ensure effective data management. 

CREATING DATA GUARDRAILS THROUGH DATA MANAGEMENT POLICY

The best data management guardrails are business rules, data validations, and informed employees who are properly incentivized. It is essential to incorporate practical measures into the creation of data policy to ensure the outlined policy principles are actually implemented and adhered to at the ground level.

Focus on these three components when mapping out practical data guardrails for your data management policy: 

1. Business Rules: These specific, actionable directives guide how data should be handled in various scenarios. They translate the broader policy into everyday actions. 
2. Data Validations: When data entry or data use occurs, validations serve as checkpoints to ensure that the data meets the policy’s quality and integrity standards.
3. Informed Employees: Training and incentives are key to helping employees understand that data governance is “with and for” them rather than being done “to” them, so they can take ownership of and follow policy. Buy-in from team members is crucial for successful data governance policies. 

IMPLEMENTING DATA GOVERNANCE POLICIES THROUGH DATA CONTRACTS 

Data contracts are an effective way to facilitate the practical, daily use of data governance policies. 

Data contracts take data policy a step further to structure how data is exchanged between two parties, whether in data pipelines, between applications, or file transfers. 

Our experience shows that data contracts encourage businesses to invest in their data ownership and quality, while also providing technology with specific, simple instructions to inform their needs. Data contracts are crucial for the business and technology relationship, embodying the principles of the data governance policy in an actionable format. Writing a data contract with embedded data governance clauses provides clarity on security and privacy constraints, allowing you to verify your data products’ adherence to relevant standards. 

For example, a data contract could require the practice of anonymizing or masking certain attributes, which dictates their permissible uses. Any Personal Healthcare Information (PHI) or Personally Identifiable Information (PII) contained within the product would also be required to be managed in accordance with stringent data privacy and security regulations such as GDPR, HIPAA, PCI DSS, among others. 

Data governance guidelines in a data contract typically cover the following areas: 

• Designated user roles with authorization to access a data product 
• Duration of authorized access to a data product 
• Specific columns or fields that have restricted access or visibility
• Columns or fields that contain sensitive data
• The manner in which sensitive data is depicted within the dataset 

Additional details such as the data contract’s version and the names and contacts of data stewards or owners serve as living documentation for your enterprise. 

THE LIMITATIONS OF DATA GOVERNANCE POLICIES 

Kenway’s experience with the data policies of diverse organizations has revealed key pitfalls that frequently arise during their adoption and execution: 

• Single-Motivation Policies: If an individual leader or department creates data management policies for the entire company, there is a good chance that the policies will not fully encompass the day-to-day realities of data governance across all teams. This issue can be avoided by creating data management policies with a group of stakeholders who can together provide a comprehensive understanding of the organization.
• Lack of Updates: A “set-it-and-forget-it” mindset when creating data policies will quickly lead to an ineffective and irrelevant set of rules. It is important to treat your data policy as a living document so it doesn’t lag behind the fast-paced evolution of data technologies and practices. 

THE BENEFITS OF DATA GOVERNANCE POLICIES

• Protecting Privacy and Security: By establishing clear guidelines, data policies protect the privacy and security of sensitive information.
• Ensuring Compliance: Data policies help organizations adhere to laws, regulations, and industry standards.
• Enhancing Data Quality: Setting agreed-on data collection and management standards ensures that data is always accurate and useful.
• Facilitating Data-Driven Decision-Making: Good data governance policies foster an environment where quality data is accessible and usable, leading to better decision-making. 

BRIDGING POLICY AND PRACTICE 

While a data governance policy lays the vision and framework for data management, it is the real-world guardrails — business rules, data validations, informed employees, and data contracts — that bring the policy to life. These data guardrails ensure that the policy doesn’t just exist on paper but is woven into the fabric of the organization’s daily operations. By bridging the gap between policy and practice, organizations can ensure that their data is both managed according to the highest standards while also being also leveraged to its full potential. 

If you’re ready to take the next step in the implementation of data governance policies or have questions about how data contracts could benefit your company, connect with one of our consultants to learn more.

DATA GOVERNANCE POLICY FAQs

What is data model governance policy?

Governance for data models includes policies that guide the use of particular data sets. 

What are some data governance policies?

An example of a data governance policy is outlining how to classify different types of data, defining different types of data users and their roles, and who has access to sensitive data.

What are data governance procedures?

Data governance procedures are the steps taken to ensure data governance is being accomplished in regards to people, processes, and technology. Examples of data governance procedures are data policies and data contracts. 

What are the policies of information governance?

Information governance policies typically include rules and guardrails surrounding the proper intake, organization, use, and disposal of information and data.