From Gatekeeper to Strategic Advisor: Elevating the Role of Testing in Engineering
Shifting Testing from a Checkpoint to a Continuous Feedback Loop for Better Decision-Making
This post is part of a series aimed at engineering leaders. It focuses on elevating the role of testers and testing by understanding their true purpose. Testing isn’t just about finding bugs—it’s about providing critical insights that drive informed decisions.
As an engineering leader, you rely on data to assess risks, prioritize investments, and guide product direction. You wouldn’t navigate a complex project without a roadmap, just as you wouldn’t build a bridge without thoroughly testing its structural integrity. Yet, testing is often reduced to a gatekeeping function—a final checkpoint rather than an ongoing feedback mechanism.
If your team treats testing as an afterthought or a box to check, you’re missing a crucial opportunity. Testing, when done right, is a strategic enabler that helps improve decision-making, enhance software quality, and ensure engineering efforts align with business objectives.
Testing Is About Information, Not Just Defects
We can debate testing methodologies, the value of testers learning to code, what to automate, and how testing fits within Agile or DevOps. However, one thing we can’t debate is the core purpose of testing: providing information.
Testing exists to gather and share information—not just about defects but about system behavior, risks, usability, and performance. The way we test and report findings should help leaders make informed trade-offs: Is this release stable enough to ship? Do we need more time? Where are our biggest risks?
The format and depth of information may vary depending on the audience—detailed logs for engineers, risk summaries for executives—but the goal remains the same: testing is a continuous feedback mechanism, not just a final checkpoint.
Engineering Leaders Need Testers Who Can Tell the Right Story
Raw data without context is meaningless. As an engineering leader, you need more than test results—you need stories that inform decision-making. A good tester doesn’t just say, “There are five critical bugs.” They explain:
✅ Context: What were we testing, and why? And sometimes more importantly, what didn’t we test.
✅ Findings: What did we discover, and how does it impact the user experience?
✅ Risk Assessment: What happens if we proceed with these issues?
✅ Recommendations: What trade-offs should we consider? Note that testers can provide recommendations, but it is not their role to gatekeep the release. I wrote more about this in a previous post: Why Good Testers Ship Bad Software.
Think of testing like a business intelligence function—it’s not about drowning in metrics but about surfacing the right insights at the right time to guide product and engineering strategy.
The Risk of Assumptions in Testing and Leadership
One of the most dangerous phrases an engineer—or a leader—can say is: “I just assumed…” Assumptions are silent risk multipliers. They can lead to poor product decisions, hidden technical debt, and frustrated customers. The problem isn’t just that assumptions exist—it’s that they often go unnoticed until they cause real damage.
Consider these common (and costly) testing and leadership assumptions:
Assumptions About Test Coverage
Assumption: “Our automation test suite is robust enough to catch all critical issues.”
Reality: Automated test suites often prioritize what’s easy to test rather than what’s most critical to the business. If coverage isn't continuously assessed against evolving risks, gaps can emerge—leading to undetected regressions, security vulnerabilities, or performance bottlenecks.
✅ Solution: Define test coverage based on business impact, not just code coverage percentages. Engage product teams, developers, and testers in risk analysis exercises to ensure critical scenarios are covered.
Assumptions About User Behavior
Assumption: “Users will interact with our product exactly as we designed it.”
Reality: Real users take unpredictable paths, misuse features, and rely on workarounds in ways teams never expected. A feature that works perfectly under controlled testing may fail in real-world usage.
✅ Solution: Use real user data, analytics, and skilled exploratory testing to validate assumptions about workflows. Test under real-world conditions, including accessibility challenges, slow networks, and different device types.
How Leaders Can Shift from Assumptions to Evidence-Based Decision-Making
Great engineering leaders foster a culture of clarity, validation, and continuous learning by encouraging teams to:
🔹 State and document assumptions before making decisions—whether about testing, architecture, or user behavior.
🔹 Challenge assumptions through data, experiments, and diverse perspectives rather than relying on gut feelings or past experiences.
🔹 Align test coverage and engineering priorities with actual business risks, ensuring that testing efforts focus on what matters most.
🔹 Invest in observability and monitoring, enabling real-time insights that validate system behavior in production.
By shifting the focus from assumptions to evidence, you empower your teams to build more reliable, scalable, and user-centric software—and ultimately, to make better engineering decisions that drive business success.
The best engineering teams treat testing as an integrated feedback loop, helping drive product direction and business success—not just catching bugs.
As a leader, how do you ensure that testing provides real value to your organization? Do your teams see testing as a core function of engineering or as an isolated step in the pipeline? What changes have you made to improve the way your organization gathers and shares quality insights?
Other posts in this series: