Flag on the play: lazy troubleshooting!
In the world of DevOps and InfoTech, every day is a puzzle of interconnected systems, configurations, and software components. The pace of change is fast, the stakes are high, and the pressure to quickly resolve issues can be intense. When facing a critical outage or a performance bottleneck, it’s easy to latch onto the most recent change and assume it’s the culprit. This mental shortcut—the idea that if something happened right after any event, the event must have caused it—is known as the “Post Hoc, Ergo Propter Hoc” Logical fallacy. See also: Correlation does not imply causation.
This Latin phrase, "Post Hoc, Ergo Propter Hoc" translates to “after this, therefore because of this,” and it’s a classic logical misstep that can even send seasoned IT professionals down the wrong path.
Understanding the Post Hoc Fallacy
“Post Hoc” reasoning occurs when someone concludes that because one thing followed another, the first thing must have caused the second. It’s a hallmark of faulty logic that can appear almost anywhere, from casual water-cooler chat to high-level strategic planning. For example, suppose you finish rolling out a Windows security patch and shortly thereafter notice a spike in CPU usage on your application server. You might be tempted to say, “The patch caused the CPU spike.” While it could be true, making that assumption outright is risky. Without proper analysis, you might overlook other underlying causes: a scheduled background job, a spike in user traffic, a faulty hardware component, or even a different patch installed weeks before that only just revealed its latent impact.
Like any good conspiracy theory, logical fallacies provde a simple and easy explanation almost never rooted in truth or accuracy. They are empty calories: the easy and, yes, sometimes lazy path to trobleshooting root cause of anything.
How the Fallacy Arises
In an enterprise environment, the complexity of systems magnifies the risk of this logical trap:
- Constant Change and Updates:
IT departments operate in a state of perpetual motion. Software updates, new policies, network configuration tweaks, and vendor patches roll out regularly. As a result, it’s often not hard to find something that “changed” recently when a problem surfaces. - High Pressure and Urgency:
When critical systems falter—email servers glitch, database queries slow to a crawl, or a global VPN stutters—time is of the essence. The pressure from stakeholders to find the root cause is immense. In a high-stress environment, it’s tempting to reach for the nearest “obvious” explanation to stop the bleeding. - Bias Toward the Recent:
Human memory and perception are biased toward recent events. When faced with an issue, we instinctively recall what’s top-of-mind -- particularly the last known change -— to anchor our reasoning. This natural cognitive bias can nudge us into making unwarranted causal connections.
Why This Matters
Falling victim to the Post Hoc fallacy can lead IT teams down expensive and time-consuming dead ends. If you incorrectly blame the wrong cause, you might waste hours (or days) backtracking on that change, rolling it back, or tweaking it unnecessarily—only to find the real culprit still lurking in the shadows. Worse yet, repeatedly falling into this pattern erodes trust within the organization. Stakeholders might question your troubleshooting prowess if each “sure thing” fix doesn’t solve the problem.
Adopting Structured Troubleshooting Methodologies
To avoid the Post Hoc trap, it’s essential to embrace a more disciplined and systematic approach to troubleshooting. Borrowing from the Scientific Method and other structured methodologies can help you remain objective and open-minded:
- Form a Hypothesis (Don’t assume it’s true): Instead of declaring, “The recent switch firmware upgrade caused the packet loss,” frame it as a hypothesis: “I suspect the switch firmware upgrade might be contributing to the packet loss.” This subtle shift in language keeps your mind open to alternative explanations.
- Gather and Analyze Data: Look beyond the temporal association. Collect logs, performance metrics, system health reports, and application traces. Compare system behavior before and after the suspected change. Often, a more thorough examination will reveal patterns or confounding variables you overlooked.
- Test Multiple Theories: Have a short list of possible causes, not just one. If the firmware upgrade isn’t panning out as the culprit, consider other factors: changes in network traffic patterns, a newly added VLAN, a load-balancer configuration tweak, or even environmental factors like a failing hard drive.
- Controlled Experiments: If possible, isolate variables. Roll back the suspected change in a controlled environment, like a test lab or a single subset of endpoints, to see if the issue disappears. If it does not, you have evidence that the cause lies elsewhere. A methodical, measurable test is much more reliable than a hunch.
- Documentation and Peer Review: Document your hypotheses, tests, findings, and outcomes. Share these with a colleague for a sanity check. A second set of eyes might catch a detail you’ve missed or suggest an alternative line of inquiry.
Staying Vigilant and Open-Minded
In enterprise IT, complexity and constant flux are the norms. To thrive in this environment, cultivate a mindset that’s skeptical of quick conclusions and open to exploring every angle. When you find yourself gravitating toward a cause simply because it’s the most recent change you’ve implemented, pause and question that line of thinking. With a structured, evidence-based troubleshooting approach, you can sidestep the pitfalls of Post Hoc reasoning and deliver better, more reliable solutions to your users and your team.
The Take-Away
If you remember nothing else I ever write on this blog, remember this: the Post Hoc, Ergo Propter Hoc fallacy ensnares people and increases outage windows every single day. Even the most experienced IT professionals get sidelined by it. However, by recognizing this cognitive trap and countering it with structured, data-driven troubleshooting methodologies, you can reduce downtime, increase accuracy, and ultimately build greater trust and credibility within your organization. In a world where “what changed?” may be the simplest question, remember that “what changed most recently?” is not always the right answer.
