IntermediateBEHAVIORAL
Describe a situation where your risk planning prevented a problem from becoming a major issue. What specific risks did you identify up front, and how did your mitigation plan play out during execution?
Custom Role
General

Sample Answer

On a data migration project for about 1.5M customer records, I was worried about two things from day one: data quality issues from legacy systems and potential downtime during cutover. In the risk log, I quantified both: we estimated up to 8–10% of records might be incomplete, and even a one-hour outage could impact roughly $150k in transactions. We built in three mitigations: a pre-migration data profiling pass, a staged migration with 10%/30%/60% cohorts, and a rollback plan with read-only mode. During the first 10% cohort, we actually hit 9% bad records, mostly due to legacy formatting. Because we’d planned for it, we paused, ran automated cleanup scripts we’d already prepared, and re-ran that batch overnight with zero customer-visible impact. By the time we did the full cutover, error rates were under 1% and we stayed within a 10-minute read-only window instead of a full outage.

Keywords

Identified concrete risks with quantified impact (data quality and downtime costs)Created specific, actionable mitigations: profiling, staged rollout, rollback planRisk actually materialized but was absorbed with no major customer impactUsed early cohorts to drive learning and reduce risk before full cutover