Gobbling Up Assumptions: Ben Franklin’s Turkey Tale Reveals About Data Governance

You know that Ben Franklin turkey story? Sure, it’s a quirky story, but it teaches us something crucial about decision-making: false assumptions can shape our beliefs, sometimes for centuries. In the world of data governance, these misconceptions can do far more than spark a debate over national birds; they can lead to costly mistakes, missed opportunities, and even disaster. Learning from Franklin’s misunderstood fowl will enable us to spot the dangers of assumption and embrace best practices that keep our data (and our organizations) on solid ground.

Setting the Scene: Turkeys, Eagles, and the Power of a Good Story

You’ve probably heard the tale about Benjamin Franklin, the ever-inventive statesman, who supposedly lobbied for the turkey to be the United States’ national bird, only to be overruled by those who preferred the bald eagle. This story has been passed around dinner tables, classrooms, and trivia nights for generations. But here’s the twist: Franklin never actually made such a proposal.

Here’s the real story: In January 1784, Benjamin Franklin wrote to his daughter Sarah, reflecting on the new nation’s choice of the bald eagle as its symbol. “For my own part I wish the bald eagle had not been chosen as the representative of our country. He is a bird of bad moral character. He does not get his living honestly,” Franklin observed. Instead, he praised the turkey as “a much more respectable bird, and withal a true original native of America… a bird of courage.”

As you can clearly see, Franklin never seriously suggested swapping the eagle for the turkey as the nation’s symbol. The real focus of his letter to his daughter was a critique of hereditary privilege, not a campaign for poultry pride.

So, how did a tongue-in-cheek aside become a national legend? The answer lies in the power of false assumptions. A single misreading, repeated often enough, can become accepted truth. If a myth about a turkey can endure for centuries, imagine what unchecked assumptions can do in the high-stakes world of data governance.

Franklin’s words, though satirical and aimed at critiquing the Society of the Cincinnati’s embrace of aristocratic traditions, offer a surprisingly apt metaphor for today’s data governance landscape. The eagle, impressive but opportunistic, could be said to stand for organizations that cut corners or chase appearances. The turkey, less glamorous but authentic and courageous, could be said to represent those who build their foundations on integrity and substance.

The Four Horsemen of Data Governance Apocalypse

False assumptions are like the background music in a cartoon theme song—easy to overlook, but they shape the entire experience. Sometimes they’re harmless, like mishearing the lyrics to the Flintstones theme (“through the courtesy of Fred’s two feet”). Other times, they’re the branch you trust while climbing a tree, only to find yourself tumbling to the ground. In data governance, these missteps can be costly, leading to compliance failures, data breaches, and operational chaos.

Let’s break down four of the most common dangers that arise from false assumptions in data governance, and pair each with a best practice to keep your organization on the right path.

1. Segregate: The Danger of Data Silos

Danger: Many organizations fall into the trap of thinking data governance belongs solely to the IT department. The logic goes: “They manage the systems, so they must own the data.” This approach creates silos, disconnects governance from business objectives, and leaves critical decisions in the hands of those who may not fully understand the data’s business context.

When organizations segregate data (i.e., hoarding it in departmental silos), they lose sight of the bigger picture. Each team optimizes for its own needs, but the organization as a whole becomes blind to risks and opportunities. Data silos make it nearly impossible to spot patterns, enforce consistent policies, or respond quickly to threats.

Real-World Consequence: When data governance is left to IT alone, business units may bypass controls, leading to shadow data practices and inconsistent data quality.

Best Practice – Enable Cross-Functional Collaboration: Effective data governance is a team sport. Break down silos by building a unified data architecture. Centralize governance policies so that sensitive information is protected no matter where it lives. Form cross-functional governance councils with representatives from IT, security, legal, and business units. Maintain an enterprise-wide data inventory and standardize access controls. When segmentation is necessary, use logical controls, not physical separation, to ensure visibility and consistency. This approach ensures policies are practical, aligned with business goals, and widely adopted.

2. Skimp: The Danger of Inadequate Investment

Danger: Another widespread assumption is that data governance is just about ticking the compliance and security boxes. Organizations focus on meeting the minimum requirements for regulations like GDPR or HIPAA, believing that once the paperwork is filed, the job is done. Nothing could be further from the truth.

Skimping on data governance is a false economy. Organizations that treat governance as a box-ticking exercise or a cost to be minimized end up with outdated technology, understaffed teams, and employees who aren’t prepared to spot or stop threats. The result? Gaps that attackers and regulators are all too happy to exploit.

Real-World Consequence: This narrow view leaves organizations vulnerable as regulations evolve and new risks emerge. The real problem: treating data governance like a to-do list instead of something that needs constant attention and adaptation.

Best Practice – Broaden the Scope Beyond Compliance: Data governance should encompass data quality, consistency, usability, and value creation; not just compliance. Embedding governance into everyday business processes and focusing on data as a strategic asset will enable organizations to drive better decision-making and innovation while staying ahead of regulatory changes.

Treat data governance and cybersecurity as strategic investments. Regularly assess risks and compare the cost of prevention to the potential cost of a breach. Invest in comprehensive staff training in addition to annual compliance modules. Run simulation exercises to test both technical and human responses. Set clear metrics for security operations (like response times and vulnerability remediation) and hold teams accountable for meeting them.

3. Stagnate: The Danger of Outdated Practices

Danger: Some organizations treat data governance as a one-time project. They launch an initiative, roll out new policies, and then move on, assuming the job is finished. This mindset ignores the reality that data, technology, and regulations are constantly evolving.

Stagnation happens when organizations fail to adapt their governance practices to new technologies, regulations, and threats. Legacy systems and policies may have worked in the past, but today’s environment demands constant evolution. When organizations cling to outdated frameworks, they create compliance gaps and security blind spots.

Real-World Consequence: When governance is treated as a project with an end date, controls become outdated, and new risks go unaddressed. The lesson? Failing to keep up with regulatory changes can have billion-euro consequences.

Best Practice – Treat Data Governance as an Ongoing Program: Make governance evolution a formal, ongoing process. Conduct regular maturity assessments to identify gaps between current practices and emerging standards. Review regulatory developments quarterly and update policies annually. Use automated compliance monitoring tools to flag violations in real time. Test both technical controls and policy effectiveness through regular security assessments and penetration testing.

4. Strangle: The Danger of Operational Paralysis

Danger: There’s a persistent belief that data governance is all about restricting access; that is, locking down data so tightly that only a select few can use it. While security is vital, overzealous controls can stifle innovation and frustrate employees who need data to do their jobs.

Furthermore, some organizations, in an effort to be secure, go too far: strangling business operations with excessive bureaucracy and rigid controls. When governance becomes a bottleneck, employees find workarounds, creating shadow IT and new vulnerabilities. Overly restrictive policies can stifle innovation and slow response times, making the organization less secure, not more.

Real-World Consequence: When access is too tightly controlled, employees may resort to workarounds, such as downloading data to personal devices or using unauthorized apps. This shadow IT creates new vulnerabilities and undermines the very controls governance is meant to enforce.

Best Practice – Balance Accessibility and Security: Design governance frameworks that balance protection with agility. Apply stringent controls where they’re truly needed, but streamline processes for routine business activities. Involve stakeholders in policy design and test procedures under real-world conditions. Survey employees to identify pain points and workarounds, then adjust policies to remove unnecessary friction. The goal is to empower users while safeguarding data.

Storytelling as a Safeguard: Why Myths Matter

Why spend so much time on a story about Ben Franklin and a turkey? Because stories are sticky. They help us remember, reflect, and, most importantly, question what we think we know. The Franklin turkey myth is a perfect illustration of how a single, misunderstood remark can become accepted wisdom, shaping beliefs and behaviors for generations.

In data governance, the stakes are higher than a Thanksgiving centerpiece. False assumptions can cost millions, erode trust, and derail even the most promising initiatives. But we can spot these myths before they take root when we embrace a culture of curiosity, critical thinking, and collaboration.

The Courage of the Turkey: Building Resilient Data Governance

Beyond a symbol of American authenticity, Franklin’s turkey was a metaphor for courage and substance. “He is besides… a bird of courage, and would not hesitate to attack a grenadier of the British guards who should presume to invade his farm yard with a red coat on,” Franklin wrote. In data governance, the turkey’s courage means investing in the right controls, adapting to new threats, and empowering people to do their best work.

But organizations that choose the turkey’s path (i.e., prioritizing substance over style, collaboration over silos, and evolution over stagnation) are better equipped to weather the storm. They build trust with customers, satisfy regulators, and create a culture where data is both protected and put to work.

Bringing It Home: Lessons from Franklin’s Feathered Fable

So, the next time you hear a story that sounds just a little too neat, or a colleague insists that “this is how we’ve always done it,” channel your inner Franklin. Ask questions. Dig deeper. And remember: the real danger isn’t in the turkey or the eagle. The real risk comes from letting assumptions fly unchecked.

Perhaps Franklin was onto something: sometimes the “obvious” choice deserves a second look. In our data-driven world, the most dangerous phrase isn’t “I don’t know;” it’s “everyone knows that.” Question your assumptions, validate your sources, and always consider the turkey.