Non-Invasive Data Governance: Why Should You Care About It?
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Non-invasive data governance (NDG) is a model of data governance that advocates for the least amount of disruption while still effectively managing and ensuring the quality, privacy, and protection of data in an organization.
The term ‘non-invasive data governance’ is associated with Robert S. Seiner, who presented it in his book “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success”.
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This model operates under the principle that data governance is a necessary function of business operations. And as such, it should be integrated seamlessly into the business without causing unnecessary disruption to daily tasks.
Let’s dive in!
Table of contents
- What is non-invasive data governance?
- What are the key principles of non-invasive data governance?
- When was the term “Non-invasive data governance” coined and by whom?
- How to create a non-invasive data governance framework?
- Strategies for implementing non-invasive data governance
- Challenges and their solutions in non-invasive data governance
- Rounding it up all together
- Non-invasive data governance: Related reads
What is non-invasive data governance?
Non-invasive Data Governance (NDG) represents a significant shift from traditional governance models. At its core, NDG is about integrating data governance practices seamlessly into existing processes, without disrupting them.
It emphasizes empowering individuals who are already handling the data – often called data stewards – to make governance-related decisions. This approach stands in contrast to traditional methods, which often involve imposing governance through a centralized, top-down structure.
The benefits of adopting a non-invasive approach are manifold.
- It reduces resistance to data governance initiatives, as it does not interfere drastically with existing workflows.
- It fosters a sense of ownership and responsibility among those directly working with the data, leading to more accurate and timely governance.
- NDG aligns closely with agile methodologies, making it particularly suitable for organizations that value flexibility and rapid adaptability.
Understanding NDG is key to realizing why more organizations are moving away from conventional, often cumbersome, governance models. By integrating governance organically into business processes, NDG not only ensures compliance and data quality but also supports a dynamic and evolving data strategy that aligns with business objectives.
What are the key principles of non-invasive data governance?
The term “non-invasive” implies that data governance should naturally happen as part of day-to-day operations and should not be seen as a separate, burdensome process. It should be formal, yet not invasive or rigid.
The key principles of non-invasive data governance include:
- Recognition of existing governance
- Roles and responsibilities
- Incremental implementation
- Proactive control
Let us understand each of them in a bit of detail:
1. Recognition of existing governance
NDG assumes that some form of governance already exists in the organization, whether formal or informal. This approach recognizes and leverages this fact instead of attempting to impose a completely new structure.
2. Roles and responsibilities
The non-invasive model assigns roles, responsibilities, and accountabilities based on people’s existing jobs and relationships to data. This way, people are doing what they’ve always been doing. However now with recognized responsibilities and a formal title associated with their governance-related activities.
Data stewards play a crucial role in the non-invasive model. They are often the ones handling the data directly. The stewardship roles are formalized, and these individuals are given responsibilities to ensure:
- Data’s accuracy
- Data privacy
- Data security
- Data value
4. Incremental implementation
NIDG promotes an incremental approach to implementation rather than trying to apply governance to all data elements at once. The focus is on the most critical data elements that have a significant impact on business operations and decision-making.
5. Proactive control
The non-invasive model emphasizes proactive control over reactive control, focusing on preventing data issues rather than responding to them after they occur.
This model encourages communication and collaboration across the organization. It aims to make everyone in the organization a data steward in their own right by incorporating data governance into their roles.
By adopting a non-invasive data governance model, organizations can make the most of their data without drastically changing the way they operate. This model can help an organization like yours, with a federated dataops model, to integrate various data silos effectively without disrupting the existing structure and workflows.
When was the term “non-invasive data governance” coined and by whom?
The term “non-invasive data governance” was coined by Robert S. Seiner, a well-known expert in the field of data governance.
- He introduced the concept in his book “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success,” which was published in 2014. Seiner’s work in data governance extends back several decades.
- Before writing his book on non-invasive data governance, he contributed significantly to the data governance field through his consulting work, presentations, and articles. He is also known as the publisher of the Data Administration Newsletter (TDAN.com), which is an acclaimed online publication in the field of data management.
- His approach to non-invasive data governance arose from his experiences working with different organizations on their data governance strategies. He observed that many traditional data governance programs failed because they were too disruptive, difficult to implement, or seen as overly bureaucratic.
In response, he developed the concept of non-invasive data governance as a way to formalize existing data-related roles, responsibilities, and practices in a way that was less disruptive and more effective.
His approach recognizes that most organizations already have some informal data governance practices in place - they may just not label them as “data governance.” The goal of non-invasive data governance, then, is to identify and leverage these existing practices.
This helps in providing a framework for formalizing and improving them without the need for a significant organizational overhaul.
How to create a non-invasive data governance framework?
Creating a non-invasive data governance (NDG) framework requires a thoughtful approach that respects existing processes and roles.
Here’s a step-by-step actionable guide:
- Understanding the current state
- Defining the data governance goals
- Establishing a data governance office (DGO)
- Recognizing and formalizing existing roles
- Training and supporting data stewards
- Developing policies and procedures
- Implementing in an incremental manner
- Setting up metrics and KPIs
- Continual communication and improvement
Now, let us understand each of the above steps in detail:
1. Understanding the current state
Before any governance framework is implemented, it’s important to understand the current state of data governance in your organization. Look for existing processes that involve:
- Data creation
- Data storage
- Data management
- Data usage
Identify individuals who are already handling these processes and understand their relationship to data.
2. Defining the data governance goals
Based on your organization’s strategic objectives, define clear goals for your data governance initiative. This might involve ensuring data quality, improving data security, achieving regulatory compliance, enabling better decision-making, or other objectives specific to your organization.
3. Establishing a data governance office (DGO)
While NDG is non-invasive, a centralized body like a DGO can help coordinate and guide the program. The DGO can develop policies, offer guidance, coordinate among different departments, and track the progress of the governance initiative.
4. Recognizing and formalizing existing roles
Identify the individuals who are already performing data management tasks, and formalize their roles as data stewards. Assign responsibilities based on their existing relationship with the data. This may include data creators, custodians, users, and processors.
5. Training and supporting data stewards
Provide the necessary training and support to your data stewards so they can effectively perform their roles. This could involve training on:
- Data management best practices
- Privacy regulations
- The use of any tools or systems used in the governance program
6. Developing policies and procedures
Develop clear policies and procedures to guide the management of data in your organization. This should cover all aspects of data governance, including data quality, data privacy, data access, data lifecycle management, and more. These policies and procedures should be integrated into existing workflows as much as possible.
7. Implementing in an incremental manner
Start by applying the governance framework to the most critical data elements. As the program matures, gradually extend its scope to cover other data elements. This incremental approach allows for early wins and helps build support for the program.
8. Setting up metrics and KPIs
Establish metrics and Key Performance Indicators (KPIs) to measure the effectiveness of the data governance program. This might involve tracking improvements in data quality, reductions in data breaches, improved compliance levels, or other metrics relevant to your goals.
9. Continual communication and improvement
Communicate the progress and successes of the data governance program to stakeholders regularly. Use feedback and metrics to continually improve the program. By following these steps, you can establish a non-invasive data governance framework that is tailored to your organization’s needs and culture, maximizing the chances of success.
Strategies for implementing non-invasive data governance
Implementing non-invasive data governance requires a comprehensive and nuanced approach, combining cultural change, strategic empowerment of data stewards, seamless technology integration, adaptive policy development, and a feedback-driven system for continuous improvement.
The following are some of the key strategies for implementing NDG:
- Cultural change
- Empowering data stewards
- Technology integration
- Policy development and enforcement
- Feedback and continuous improvement
Let’s understand them in detail:
1. Cultural change
It forms the bedrock of NDG. It involves shifting the organization’s mindset to value data as a strategic asset. This cultural shift is initiated through educational programs and regular communication, emphasizing the importance of data governance.
Training programs and real-life scenarios help in illustrating how proper data handling can drive business success. Regular updates via newsletters or intranet posts keep data governance a key focus in the organization.
2. Empowering data stewards
Empowering data stewards is crucial in the NDG framework. It starts with selecting individuals who have a deep understanding of the data and its business context. These data stewards are then given specialized training and the authority to make governance-related decisions.
This decentralization not only fosters a sense of ownership but also accountability. Additionally, creating support networks or communities of practice for data stewards encourages the sharing of insights and best practices, further strengthening the governance framework.
3. Technology integration
Integrating latest technologies is critical in NDG. The key lies in selecting governance tools that blend seamlessly with existing systems to minimize disruption to workflows. These tools should be user-friendly, catering to the tasks of data quality management, metadata management, and data lineage tracking.
The integration of these tools into daily operations ensures that governance becomes an integral part of business processes, enhancing efficiency and compliance without adding complexity.
4. Policy development and enforcement
Developing and enforcing policies in NDG requires developing clear, concise, and flexible governance policies. These policies should be easily understandable and adaptable to the ever-changing business environment.
The enforcement of these policies is crucial but should be implemented in a way that it becomes a part of regular business operations, ensuring compliance in a non-disruptive manner.
5. Feedback and continuous improvement
The implementation of NDG is an evolving process, necessitating a feedback and continuous improvement mechanism. This involves setting up channels for employees to provide feedback on how data governance practices affect their work.
Such feedback is invaluable for continuously monitoring, refining, and adjusting the NDG approach to align with both the organization’s and employees’ needs.
Challenges and their solutions in non-invasive data governance
Implementing non-invasive data governance, while beneficial, comes with its unique set of challenges. Understanding these challenges and preparing solutions is key to a successful implementation.
- Resistance to change
- Lack of understanding
- Balancing flexibility and control
- Integrating technology
- Measuring success
Let’s explore them in detail:
1. Resistance to change
A common challenge is the inherent resistance to change within organizations. Employees may be wary of new processes, fearing increased workload or a shift in their responsibilities.
To counter this, it’s crucial to communicate the long-term benefits of non-invasive data governance clearly. Demonstrating how this approach can simplify their work and improve overall data quality can help in gaining their buy-in. Involving employees in the planning stages and addressing their concerns directly can also ease the transition.
2. Lack of understanding
Another significant hurdle is a lack of understanding or misconceptions about what non-invasive data governance entails.
This can be overcome through comprehensive training and education programs. Providing resources, workshops, and hands-on training sessions can help demystify the concepts and show the practical applications of NDG in everyday work.
3. Balancing flexibility and control
Striking the right balance between flexibility in data handling and maintaining control over governance processes is often challenging.
This requires a well-thought-out strategy that empowers data stewards while still having clear policies and guidelines in place. Regular reviews and audits can help ensure that flexibility does not lead to lax governance practices.
4. Integrating technology
Choosing and integrating the right technology for NDG can be daunting, especially in complex IT environments.
It’s important to select tools that are compatible with existing systems and intuitive to use. Seeking input from IT professionals and end-users during the selection process can lead to better technology choices that support NDG principles.
5. Measuring success
Lastly, determining the success of NDG initiatives can be difficult, as the benefits are often qualitative and long-term.
Establishing clear metrics and KPIs early in the implementation process can help in tracking progress. Regularly reviewing these metrics ensures that the NDG strategy remains aligned with organizational goals.
By addressing these challenges with well-thought-out solutions, organizations can effectively implement non-invasive data governance and reap its benefits.
Rounding it up all together
NDG is a model of data governance that emphasizes minimal disruption, assigning data-related roles, based on people’s existing jobs and relationships to data. It aims to formalize and improve the existing data practices, assuming some form of governance already exists, whether formal or informal.
The term “non-invasive data governance” was coined by Robert S. Seiner, a prominent expert in the data governance field. He introduced the concept in his book, “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success,” published in 2014.
By implementing a NDG model, organizations can achieve effective data governance that integrates seamlessly into existing business operations, ultimately enhancing the quality, privacy, and protection of data.
Non-invasive data governance: Related reads
- What is Data Governance? Its Importance, Principles & How to Get Started?
- Snowflake Data Governance Features, Frameworks & Best Practices
- How to implement data governance? Steps, Prerequisites, Essential Factors & Business Case
- 7 Best Practices for Data Governance to Follow in 2023
- Automated Data Governance: How Does It Help You Manage Access, Security & More at Scale?
- Data Governance and Compliance: Act of Checks & Balances
- Data Governance vs. Data Management: What’s the Difference?
- How to Improve Data Governance? Steps, Tips & Template
- 7 Steps to Simplify Data Governance for Your Entire Organization
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