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Rethinking Data Assumptions: The Power of Skepticism

Time zones, verification technique, and the errors that survive review.

We live in an age where data is everywhere. It’s a commodity, a tool, and often, the very foundation of major decisions. But here’s the truth: even the most reliable data needs scrutiny. To make data truly valuable, we need to ask more questions, challenge more assumptions, and—above all—suspend judgment.

My colleague, Hunter McMahon, recently published a Forbes article emphasizing the importance of curiosity as the role of AI continues to expand in our data-centric world.  Curiosity drives us to ask questions, to dig deeper—but paired with a dose of skepticism, it ensures we don’t just accept answers at face value. Instead, we verify, challenge assumptions, and refine our understanding.

Trust, But Verify: Why Data Needs Skepticism

As data professionals, we know the drill: data arrives, pressure mounts, and the instinct is to dive in and dissect the details as quickly as possible. But that rush can lead you astray. Seasoned professionals understand the importance of hitting pause to gain clarity on the context before moving forward. The mantra here is simple: “trust, but verify.” Understanding the data through client conversations and documentation is crucial, but it’s just as important to challenge assumptions and dig deeper, using your own observations to shape conclusions.

You set up that call with the client. They explain the data, answer your questions, and you’re feeling confident, right? Not so fast. Before you proceed, there’s one thing left to do: question everything with a healthy dose of skepticism.

Why? Because humans make mistakes. Knowledge gets lost, assumptions creep in. Your job isn’t just to analyze data—it’s to interrogate it. Ask the tough questions. Double-check everything.

Time Zone Dilemma: A Case Study in Data Skepticism

Let me give you an example. I worked on a case recently where I received an email metadata report for a single employee pulled from Outlook archives by a third-party vendor. The task? To determine when this employee was sending emails, essentially pinpointing their working hours and whether they were burning the midnight oil.

The vendor claimed the time stamps were processed in the employee’s local time—Eastern Standard Time (EST). The client passed this along to me. Case closed, right?

Wrong.

Rather than taking it at face value, I dug deeper. I created a histogram of the email timestamps, analyzing the volume of emails sent at each hour of the day. What did I find? Email activity started around 1pm, peaked at 5pm, and tapered off by 9pm. But that didn’t line up with other data sources, which indicated the activity should have started at 9am, peaked at 1pm, and faded by 5pm.

Something was off.

Assumptions around data are rarely as solid as they seem. By cross-referencing my findings with other data points, I realized the email data was skewed by 4-5 hours. The culprit? Time zones. The data had been exported in UTC (Coordinated Universal Time), not the Eastern Standard Time as originally claimed.

I went back to the client, asking them to double-check with the vendor. Sure enough, the vendor admitted they made a mistake: the data had been captured in UTC, not EST. Once we corrected the time stamps, the employee’s late-night work hours made much more sense.

This small but crucial adjustment changed the entire narrative of the case. And it only took a few hours of thoughtful, skeptical analysis.

The Data Is Only as Good as the Questions You Ask

The moral of the story? Never assume you have all the answers upfront. A little skepticism, a willingness to question assumptions, and a commitment to verifying facts can make all the difference. It saves time, money, and—most importantly—ensures your analysis holds up under scrutiny.

In a world flooded with data, it’s not about the quantity of information you receive. It’s about how well you understand it and how diligently you approach it. So, the next time you’re handed a dataset, don’t just dive in. Pause. Ask the right questions. Challenge the answers. Because in the end, it’s the questions you ask and the answers you verify that make the data truly meaningful.

The data is only as good as the questions you ask. And trust me—your clients will thank you for it.


iDS provides consultative data solutions to corporations and law firms around the world, giving them a decisive advantage – both in and out of the courtroom. iDS’s subject matter experts and data strategists specialize in finding solutions to complex evidence challenges, ensuring data can be leveraged as an asset, not a liability. To learn more, visit idsinc.com.

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