Sign in with your Red Cross ArcGIS Online account to model county reassignments within a region.
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Chapter Realignment
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How to use this tool
Pick a region from the dropdown at the top.
The map shows every county in that region, colored by its current chapter assignment.
In the county table, use the dropdown in the last column to move a county to a different chapter.
The chapter cards at the top of the right panel recalculate instantly — population, SVI, NRI, ALICE, income.
Changed counties are outlined in red on the map and highlighted in the table.
Click Save Scenario to store a named version. Reset All clears your changes.
Scenario—
Welcome, Dragon
This tool models county reassignments within a single region — just like the Florida realignment demo, but powered by live AGOL data.
To begin, pick a region from the dropdown at the top. ↑
48 regions · 3,152 counties · 112 metrics per county
Chapter SummaryPick a region to see chapter rollups
County
Pop
SVI
NRI
ALICE
Chapter
No changes
FMAS — Full Strategy Document×
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American Red Cross — Real Estate Strategy
FMAS: Facility Mission Alignment Score
This is the beginning. The Chapter Realignment tool you're using now shows chapter-to-county mapping with community vulnerability and demographic data. The ultimate goal is a facility-level FMAS score (0–100) that tells leadership, objectively, which Red Cross properties are mission-aligned and which need a deeper-dive conversation — based on data, not anecdote.
The Algorithm
Every facility gets a single 0–100 score composed of three weighted pillars. Higher = better aligned. Low scorers become the targeted list for deeper review — alternatives include partnership, right-size, co-locate, or exit. The algorithm surfaces the conversation; people make the decision.
40% of FMAS signal available today (Need pillar). Delivery and Efficiency pillars require internal ARC data feeds — shelter, volunteer, biomedical, disaster, training, facilities, Brivo access, HR headcount.
The Quadrant Map — Where Each Facility Lands
Once all three pillars are scored, every facility plots on a Need × Delivery grid. Dot size represents Efficiency (larger = less efficient). This becomes the picture leadership sees first.
↖ Invest / Partner
High need, low delivery. Real community need but weak mission output — invest or partner to improve.
↗ Protect ★
High need, high delivery. Mission-aligned and performing — protect and potentially expand.
↙ Exit Candidate
Low need, low delivery. Especially if high cost — deeper dive: right-size, relocate, or exit.
↘ Right-Size / Relocate
Low need, high delivery. Mission is happening but community profile doesn't justify footprint.
What This Tool Does Today
Currently, the Chapter Realignment Engine lets you pick a region, move counties between chapters, and see how the region's chapter-level metrics change instantly. The 112-column consolidated database powering it includes the full Need pillar (SVI, NRI, CRCI, ALICE, FLARE, demographics) — we just haven't yet composed them into the FMAS score.
What's Next
Immediate: Add an FMAS Need score column to the county table and chapter cards (0–100, computed from the four components above). This gives chapters an objective "community need" rollup that updates when counties are reassigned.
Then: Identify the internal AGOL layers (or CSV uploads) for the Delivery and Efficiency pillars. As each dataset comes online, add it to the consolidated county layer via the Python pipeline and the scores become richer.
Finally: Layer the facility-level dimension on top — each Red Cross property plotted on the quadrant map with its FMAS score and scorecard, ready for the working-group presentation.