public sector communitycontinuity planningdisaster resiliencefemahazard mitigation
Complete evaluation framework
What to assess and how to score it
Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.
01
Evaluation factor
Outcomes that landed
30% weight
Ask which resilience plans they authored that were adopted: FEMA hazard mitigation plans, BCA-approved mitigation grants, continuity of operations plans, or flood ordinance updates that changed CRS ratings.
Evidence to listen for
Names programmes or initiatives that were adopted, funded, or delivered
States their own role rather than the department's
Gives measured reach or impact
Distinguishes work that landed from work that stalled, and explains why
Five-point scoring guide
1
Poor
No delivered work; describes intent and process only.
2
Needs Improvement
Involved in initiatives but cannot say what resulted or what they owned.
3
Satisfactory
Real delivery with adequate ownership; impact described loosely.
4
Very Good
Named outcomes with clear personal scope and some measures.
5
Excellent
Names adopted plans, funded mitigation projects with dollar values, and measurable outcomes such as improved CRS class or reduced flood claims.
02
Evaluation factor
Stakeholder facilitation
25% weight
Probe how they ran workshops with emergency managers, floodplain administrators, utilities, tribal councils, and residents, including how they handled conflict over risk maps or buyout proposals.
Evidence to listen for
Brings a real contested case, not a philosophy of engagement
Names the competing interests and the resolution method
Uses concrete engagement formats and can point to input that changed a decision
Treats every group as legitimate
Five-point scoring guide
1
Poor
Diplomacy-speak with no case attached, or contempt for one group.
2
Needs Improvement
Recalls conflict but no method; engagement is a box to check.
3
Satisfactory
Real case and workable approach; resolution thin on specifics.
4
Very Good
Names the tension and method; cites engagement that shaped the outcome.
5
Excellent
Describes structured facilitation of steering committees and public meetings, plus specific instances where opposing stakeholders reached a documented consensus.
03
Evaluation factor
Regulatory and policy command
25% weight
Test command of the Stafford Act, DMA 2000, 44 CFR Part 201, BRIC and HMGP grant cycles, NFIP rules, and state hazard mitigation plan requirements.
Evidence to listen for
Names the statutes, funding rules, and processes they have worked under
Explains how those requirements sequenced their work
Owns the compliance thinking rather than deferring it entirely
Knows where the discretion sits
Five-point scoring guide
1
Poor
Outsources all regulatory thinking; cannot name a framework.
2
Needs Improvement
Generalities about compliance; no sequencing or named rules.
3
Satisfactory
Knows the main frameworks; sequencing described loosely.
4
Very Good
Names relevant frameworks and how they shaped a timeline.
5
Excellent
Cites eligibility rules and deadlines accurately, and explains how regulatory constraints shaped a specific plan or grant application.
04
Evaluation factor
Evidence and reporting
20% weight
Look for use of HAZUS, THIRA/SPR, FEMA Flood Insurance Rate Maps, GIS exposure analysis, and benefit-cost analysis to justify recommendations to councils and funders.
Evidence to listen for
Uses data to choose between options, not to justify a decision already made
Names the sources and methods behind their numbers
Reports to funders, councils, or the public in terms those audiences can use
Tracks whether the intervention worked
Five-point scoring guide
1
Poor
No use of evidence; decisions are assertion.
2
Needs Improvement
Cites data but cannot explain its source or limits.
3
Satisfactory
Uses evidence competently; evaluation after the fact is thin.
4
Very Good
Evidence drives choices and is reported clearly to lay audiences.
5
Excellent
Shows quantified loss estimates and BCA ratios behind recommendations, and explains data limitations without overselling model certainty.
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