When leadership hands you both a clear KPI and a suggested solution, it can feel like a trap. You might worry about jumping straight into delivery without validating if the solution really addresses the real problem. This situation is common, especially in fast-moving businesses with tight timelines. The key is to treat the given solution as a hypothesis, not the final answer.
Why This Matters
Relying solely on what management suggests risks building the wrong product or missing underlying issues. Without proper discovery, you might solve the wrong problem, wasting resources and missing opportunities for impactful change. Plus, KPI metrics like MAU are lagging indicators—they reflect past actions, not future behavior. It’s smarter to focus on leading metrics that predict success and guide development.
How to Approach Discovery in This Context
The first step is to frame the leadership’s solution as a testable hypothesis. Conduct quick, targeted experiments to verify whether it genuinely addresses the core problem. Keep in mind that discovery is an ongoing process, even when a solution seems apparent.
Ask probing questions: Is this solution addressing a real pain point? Are there other ways to solve it more effectively? Use qualitative user feedback and data to challenge assumptions. When evidence suggests the solution won’t work, don’t hesitate to re-negotiate with management—align on findings, not just opinions.
Replacing Lagging with Leading Indicators
Metrics like MAU measure past behavior and can delay decision-making. Instead, focus on leading indicators such as:
- Number of users taking specific actions in the new feature
- Engagement duration on targeted activities
- Frequency of repeat usage over a shorter period
Tracking these signals early helps you pivot quickly if the hypothesis isn’t validating, reducing wasted effort.
Common Pitfalls & How to Avoid Them
- Confirmation Bias: Only look for data that supports the leading idea. Challenge assumptions with critical questions.
- Skipping Validation: Jumping straight into delivery without testing the hypothesis first.
- Overreliance on Lagging KPIs: Use lagging metrics as secondary indicators, not primary success measures.
- Resistance to Re-negotiation: Be prepared to present evidence and rethink the solution if discovery shows misalignment.
Key Patterns for Making “Me-Too” Tools Sticky
To stand out, aim to create a unique value proposition. These patterns help:
- Customization to user needs
- Seamless integration with existing workflows
- Engaging onboarding that demonstrates immediate value
- Ongoing feedback loops for continuous improvement
Final Takeaway
The takeaway is simple: treat every solution as a hypothesis, validate quickly with data, and never be afraid to push back if evidence suggests a better path. This ensures your discovery process remains rigorous, even when directives feel prescriptive. Start with curiosity—then use evidence to guide your product’s success.