
In the traditional agency conflict, business leaders (agents) make decisions that sometimes diverge from the long-term interests of shareholders (principals). This conflict arises when executives prioritize short-term gains, like bonuses or stock price increases, over the business's long-term health. It’s a classic dilemma that can jeopardize the very core of a company’s mission—sustainable growth.
A parallel exists in today’s data-driven world: the data agency conflict. However, instead of a divide between shareholders and executives, this conflict occurs when an organization’s short-term objectives lead to decisions that harm its most valuable asset—data.
The Core of the Data Agency Conflict
In many organizations, the focus is on agility, speed to market, and delivering products or services to stay competitive. Product owners, business units, and other stakeholders often make decisions that benefit immediate project needs, but they do not understand how those decisions affect the overall data landscape. In the rush to meet these objectives, data assets are often treated carelessly, and long-term impacts on data quality, governance, and architecture are neglected.
In this version of the agency conflict, the problem isn’t just between two groups, like Product Owners and IT—it’s an organizational-wide issue. The overarching focus on speed and short-term wins can undermine the health of the data, leading to a range of problems, including inconsistent data structures, unreliable reporting, and even compliance risks.
Why Does The Data Agency Conflict Happen?
Organizations often fail to recognize data as an asset requiring care, stewardship, and long-term strategy. When business goals overshadow data management practices, the following scenarios tend to play out:
Uncontrolled Data Onboarding: Product owners or other business units onboard new data without consulting the data management group, leading to inconsistencies in data formats, naming conventions, and quality. This approach may work in the short term to meet business needs but results in a chaotic data environment in the long run.
Data Structure Changes Without Governance: As product teams rapidly iterate on new features or services, they may drive changes in the underlying data structures without understanding the downstream impact. This can lead to misaligned data, integration issues, and difficulty maintaining reliable data pipelines.
Lack of Data Governance Knowledge: With little understanding of data governance, architecture, and management principles, business units may make decisions that weaken the integrity of the data ecosystem. Over time, this erodes trust in the data, making it harder for teams to rely on it for decision-making or reporting.
Obliviousness to Data’s Strategic Value: Many organizations fail to treat data as the strategic asset it is. Instead, they see it as a secondary tool or resource used only when needed. As a result, data isn’t handled with the same care as other valuable resources, like financial capital or intellectual property.
The Consequences of a Cavalier Attitude Toward Data

When an organization doesn’t recognize the long-term value of data, several adverse outcomes arise:
Inconsistent and Unreliable Data: Without proper governance and architecture, data becomes inconsistent across different systems. This can lead to unreliable reporting, which can affect decision-making and ultimately cause operational inefficiencies.
Increased Technical Debt: Every time a product team makes a quick fix to a data structure or onboard data without proper integration, they add technical debt. Over time, these shortcuts accumulate, making the data environment more complex and expensive to maintain.
Compliance Risks: Data management isn’t just about efficiency but also security and compliance. When organizations fail to implement proper governance, they risk violating data privacy regulations (like GDPR or CCPA), which could result in legal repercussions and hefty fines.
Loss of Competitive Edge: When properly managed, data provides insights that drive competitive advantage. Companies that can’t trust their data or find themselves bogged down by data quality issues are slower to innovate and miss key market opportunities.
Addressing the Data Agency Conflict
The organization must shift its approach and recognize data as a strategic asset to resolve this conflict. Here are some ways to realign the company’s objectives with the health of its data:
Establish a Data Governance Framework: Implement a governance framework that requires all business units to adhere to data management standards before onboarding new data or changing data structures. This framework should balance agility with long-term data stewardship.
Appoint Data Owners Across Departments: Data owners can act as intermediaries between the business and data management teams, ensuring that data-related decisions meet immediate business needs and long-term governance objectives. They can help make data a shared responsibility.
C-Suite Engagement: Data must be treated as a strategic asset from the top. C-level executives must prioritize data management as part of the organization’s long-term strategy. They can drive cultural change by linking data management efforts to business outcomes, such as improved decision-making or operational efficiency.
Education and Awareness: Business units and product teams must understand the consequences of poor data management. Offering workshops or internal resources that explain the value of data and the risks of neglecting governance can go a long way toward shifting perspectives.
Aligning Data with Business Goals: You can demonstrate the tangible value of good data management practices by directly linking data quality and governance to key business outcomes, such as customer satisfaction, time to market, and operational efficiency.
A Long-Term Solution
Much like resolving traditional agency conflict requires long-term alignment of executive and shareholder interests, solving the data agency conflict requires aligning the organization’s objectives with the long-term health of its data assets. Without this alignment, the organization risks underutilizing one of its most critical resources, ultimately hampering growth, innovation, and competitiveness.
The solution is not to slow down business objectives or innovation. Instead, it’s about embedding data governance and management into the fabric of the organization’s strategy. When data is seen as an asset, it’s protected, cultivated, and used to its full potential—just like any other valuable resource.
Resolving the data agency conflict requires a fundamental shift in how your organization views and manages its data. By recognizing that data is not just a tool but a strategic asset, you can drive better decision-making, safeguard your organization from future risks, and ultimately fuel long-term growth and success.
Explore more data culture insights at the Data Culture Hive Mind!
JM Abrams
Chief Data Culturist
LF01
Σχόλια