Data governance, the practice of managing the availability, usability, integrity, and security of data in enterprise systems, is often touted as a critical component of modern business.

Yet, many data governance implementations fail to deliver on their promises, becoming bogged down in bureaucracy, generating little tangible value, or simply fading into irrelevance.

A significant contributing factor to these failures lies in a fundamental misunderstanding of the nature of data governance itself: is it a sustaining or a disruptive technology?  

1. Sustaining vs. Disruptive: A Quick Recap
2. The Misclassification of Data Governance
3. Data Governance as a Disruptive Force
4. The Solution: Embracing Disruption
   1. Reference:

Sustaining vs. Disruptive: A Quick Recap

As Clayton Christensen outlined in The Innovator’s Dilemma, sustaining innovations improve existing products or services for current customers, often through incremental enhancements.

Conversely, disruptive innovations introduce simpler, more affordable, or more accessible offerings that initially target niche markets or create entirely new ones, eventually displacing established players.  

The Misclassification of Data Governance

Many organizations approach data governance as a sustaining innovation.

They view it as a way to improve existing data management practices, enhance data quality within existing systems, and ensure compliance with existing regulations. This leads to implementations characterized by:

• Top-down, centralized control: A large, dedicated team defines rigid policies and procedures, often without sufficient input from business users.
• Focus on compliance and risk mitigation: The primary goal is to avoid penalties and minimize risks, rather than to enable new opportunities or drive business value.
• Emphasis on existing systems and processes: Data governance is implemented as an overlay on existing IT infrastructure, with little consideration for fundamental changes in how data is used and managed.

This “sustaining” approach often fails because it doesn’t address the underlying challenges that hinder effective data utilization. It adds complexity and bureaucracy without creating new value or empowering data users.

Data Governance as a Disruptive Force

In reality, effective data governance is often disruptive. It requires significant changes in:

• Organizational culture: Shifting from data silos and individual ownership to a shared responsibility for data quality and accessibility.  
• Business processes: Implementing new workflows for data creation, validation, and usage.
• Technology infrastructure: Potentially requiring new tools and platforms to support data governance processes.  
• Roles and responsibilities: Creating new roles like data stewards and data owners, and redefining existing roles to incorporate data governance responsibilities.  

When organizations fail to recognize this disruptive nature, they attempt to implement data governance using existing organizational structures and processes, which are ill-equipped to handle the necessary changes. This leads to resistance from business users, lack of adoption, and ultimately, failure.

The Solution: Embracing Disruption

To successfully implement data governance, organizations need to embrace its disruptive nature and adopt a different approach:

• Start small and iterate: Begin with a pilot project in a specific business area, focusing on a specific business problem. This allows for experimentation and learning without disrupting the entire organization.
• Empower business users: Involve business users in the design and implementation of data governance processes. This ensures that the processes are relevant and practical, and fosters a sense of ownership.
• Focus on value creation: Emphasize the benefits of data governance, such as improved decision-making, increased efficiency, and new business opportunities. This helps to overcome resistance and gain buy-in from stakeholders.  
• Build a “heavyweight” team for process creation: As discussed in relation to Christensen’s work, a dedicated, cross-functional team is needed to establish new processes and capabilities. This team should act as “general managers” for data, making trade-offs and decisions for the good of the overall data governance program.

By recognizing data governance as a potentially disruptive force and adopting a more agile, iterative, and business-focused approach, organizations can increase the likelihood of successful implementation and unlock the true value of their data. Ignoring this disruptive nature, however, sets the stage for yet another failed data governance initiative.

Reference:

Christensen, C. M. (1997), The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail, Boston, MA: Harvard Business School Press