To resolve conflicting opinions on bug severity, apply a structured framework: first, define severity criteria based on user, system, and business impact. Engage stakeholders in cross-functional discussions, leveraging data like bug frequency and financial impact. Build consensus through compromise or provisional fixes, and continuously review and iterate after implementation to ensure improvements. This process balances technical and business priorities while fostering collaboration and data-driven decision-making.

1/ Stack rank your factors. Your ability to understand and operate the system is top, customer impact is next, your money is 3rd or lower. 2/ measure the impact, how many people, for how long. How much money/time/information? 3/ quantify how bad it is for the impacted groups, are you stealing their money? Giving away your stock? Leaking personal data? Perhaps it's a missed opportunity, whatever, quantify it. Write some tenets. Read your bugs. Break your rules. Thoughtfully.

Just make sure who is responsible for what in the project. Example: ❗ Testers report defects with Severity as one of its attributes. ↕️ Product Owner (PO) prioritizes defects and stories using another attribute -- Priority. Then, the PO can prepare a product backlog using known Priorities. This way, information about reported defect's severity is not lost, and correct prioritization information is set for the team.

Follow the organization’s framework on defining severity levels. Propose framework update if necessary. Call for brainstorming and facilitate discussion (use planning poker technique) to come to a common understanding.

When opinions differ on bug severity, grounding decisions in objective criteria is essential. I establish a clear framework that ranks bugs based on their impact on functionality, user experience, and system stability. For example, in a recent case, conflicting views arose on a radar software bug’s priority. By using a structured rubric that rated the bug’s impact on operational safety and mission-critical functions, we reached consensus quickly. This method lets team members see the rationale behind each decision, reducing subjective debate and ensuring that high-impact issues get prioritized efficiently.