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Case Study #155 — 300 Software Failure Case Studies

New York City 911 system upgrade failures

New York City's project to unify and modernize its 911 emergency dispatch systems ran years behind schedule and roughly $1 billion over its original budget, drawing sharp criticism after dispatch delays during major incidents.

2004-2011
When it happened
Government
Sector
#155 of 300
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

New York City's project to unify and modernize its 911 emergency dispatch systems ran years behind schedule and roughly $1 billion over its original budget, drawing sharp criticism after dispatch delays during major incidents.

Government
Sector affected
2004-2011
Date of the event
#155
Rank in the 300 Software Failure Case Studies
3
Distinct root-cause clauses identified below
02 — The Root Cause

What the software actually got wrong

The Emergency Communications Transformation Program's software was repeatedly redesigned amid shifting requirements and poor project oversight, and integrating it with the city's existing, disparate police, fire, and EMS dispatch software proved far more complex than planned.

01Root Cause

The Emergency Communications Transformation Program's software was repeatedly redesigned...

What Happened

The Emergency Communications Transformation Program's software was repeatedly redesigned amid shifting requirements and poor project oversight

How Requs AI Catches This

Requs AI Edge Case flags this exact pattern at the requirements and architecture stage — before a single line of code implementing it exists — so the assumption behind it gets challenged while it is still cheap to fix.

02Root Cause

Integrating it with the city's existing, disparate police, fire

What Happened

integrating it with the city's existing, disparate police, fire

How Requs AI Catches This

Requs AI Software FMEA traces this failure mode back to the system-level hazard it feeds, tagging it against the Common Defect Enumeration so it surfaces in review instead of in the field.

03Root Cause

EMS dispatch software proved far more complex than planned

What Happened

EMS dispatch software proved far more complex than planned

How Requs AI Catches This

Requs AI Edge Case and Software FMEA together treat this as a known, catalogued defect pattern — not a novel surprise — so it gets tested for deliberately rather than discovered after deployment.

03 — How This Gets Caught Before It Happens

Beyond code coverage and "shall" testing

Root causes like this one rarely show up in code coverage or requirements-compliance testing, because nobody wrote a requirement anticipating the specific edge case that broke. Requs AI Edge Case and Requs AI Software FMEA are built to surface exactly this class of overlooked failure mode — before the software is written.

Requs AI Edge Case

Surfaces this before code exists

Identifies edge cases like this one at requirements and architecture time, using the Common Defect Enumeration to catalog failure patterns seen across hundreds of real-world software failures — including this one.

Requs AI Software FMEA

Connects the failure mode to the hazard

Traces this class of root cause directly to the system-level hazard it can produce, so a defect pattern like this one gets flagged during design review instead of after it ships.

Find the overlooked root causes before they ship.

Schedule a demonstration, or explore how Requs AI Edge Case and Software FMEA use the Common Defect Enumeration.