Things No One Tells You About Failed Experiments and Learning Velocity

Things No One Tells You About Failed Experiments and Learning Velocity

Ever feel like you're chasing success but missing the real insights? You're not alone. Focusing solely on winning experiments might seem smart, but it can actually lead you down a blind alley. The real gold lies in understanding the failures—those unexpected twists that teach us what not to do next time. This blog dives into why embracing failure can accelerate learning and ultimately lead to smarter decisions.

Let's break down the why and how of learning from failed experiments. We'll explore practical steps to harness these insights and shift from just running tests fast to learning fast. So grab your coffee and settle in; this could change the way you think about experimentation.

Why focusing only on success can be misleading

Chasing only the wins? You might be missing the point. Null or negative results often offer the clearest insights. Yet, teams tend to skip over them, leading to skewed strategies and repeated mistakes. Failed experiments aren't just throwaways—they're first-class data points. Dive into what these tests actually reveal to see hidden truths. For more on this, check out how failed experiments are analyzed on Statsig.

Winning doesn't always explain why things work; null results often do. Reliable metrics and causality trump vague vibes, forming the backbone of mature experimentation programs. The team at Towards Data Science highlights the importance of structured learning in their experimentation gap article.

Here’s how to extract lessons quickly:

• Validate guardrail metrics early to avoid false wins. Explore more in HBR's article.

• Track nulls and negatives systematically.

• Codify hypotheses in a Center of Excellence to enforce governance. Learn more about this in Statsig's guide on experimentation centers.

Pushing for speed without insight just creates noise. Pair velocity with rigor and thorough post-test reviews. For a deeper dive, read about the balance between speed and insight on Statsig's experiment velocity.

How failure fuels deeper insights

Failed experiments can shine a light on broken assumptions, revealing unexpected patterns that might just outshine quick wins. Delve into each misstep to uncover root causes and refine both process and product. Documenting surprises builds a knowledge base for future work, steering teams clear of repeated mistakes.

Openly sharing failures boosts collaboration, speeding up team learning and keeping everyone off dead-end paths. For insights on leveraging failed experiments, explore Statsig’s perspective.

Accelerate progress by embracing these lessons:

• Capture and share failed experiments openly.

• Use this knowledge to guide smarter iterations.

• Encourage everyone to learn from what didn’t work.

This approach fosters innovation and keeps teams focused on genuine progress. For more, check out the importance of learning velocity on Statsig’s experiment velocity page.

Shifting from experiment velocity to learning velocity

Rushing through shallow experiments? You might miss the real insights. Running numerous tests without value leads to a pile of data with little direction. Focus on what you learn, not just how fast you run tests.

Failed experiments can offer as much insight as successful ones. They highlight gaps in assumptions, helping sharpen questions and direct next steps. Shift your team’s mindset to value experiments that challenge beliefs and guide roadmap decisions. Measure progress by clarity gained, not just test count.

Prioritize quality over quantity:

• Design experiments that answer significant questions.

• Use data to update your strategy.

• Capture lessons from every outcome, including failures.

For more on intentional experimentation, explore The experimentation gap and HBR's online experiments.

Balancing speed and rigor for long-term growth

Sure, fast results are tempting, but cutting corners leads to unreliable data. Establish clear processes to prevent wasted time and resources. Shared guidelines set expectations for timelines, quality checks, and documentation.

A disciplined approach ensures team alignment on metrics and methods. This reduces confusion and enhances learning from both successes and failures. Even when outcomes aren't as expected, you gain valuable insights.

Set rules for experimentation:

• Use a checklist to ensure data quality before starting.

• Define success criteria before launching.

• Schedule regular reviews to catch errors early.

Balancing speed with rigor unlocks higher test velocity without sacrificing insight. This approach helps spot problems quickly and avoid common pitfalls. Explore more on failed experiments analysis on Statsig’s perspective.

Closing thoughts

Embracing failed experiments as opportunities for learning can transform how your team innovates and progresses. By focusing on learning velocity over simple experiment velocity, you create a culture that values insights and drives smarter decisions.

For further reading, check out resources on Statsig's perspectives. Hope you find this useful!