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Case Study #169 — 300 Software Failure Case Studies

Target Canada supply-chain software failure

Target's expansion into Canada collapsed within two years, with the company closing all 133 Canadian stores and taking a loss of more than $2 billion (US), one of the most expensive retail failures in North American history.

2013-2015
When it happened
Retail
Sector
#169 of 300
Ranked by documented impact
01 — What Happened

The damage was public. The root cause was preventable.

Target's expansion into Canada collapsed within two years, with the company closing all 133 Canadian stores and taking a loss of more than $2 billion (US), one of the most expensive retail failures in North American history.

Retail
Sector affected
2013-2015
Date of the event
#169
Rank in the 300 Software Failure Case Studies
1
Distinct root-cause clause identified below
02 — The Root Cause

What the software actually got wrong

A new, unfamiliar SAP-based supply-chain and inventory system produced inaccurate inventory data across the new Canadian stores, leaving many shelves empty of popular items while warehouses were overstocked with unsellable goods, a core operational failure that Target could not fix quickly enough to save the venture.

01Root Cause

A new, unfamiliar SAP-based supply-chain and inventory system produced...

What Happened

A new, unfamiliar SAP-based supply-chain and inventory system produced inaccurate inventory data across the new Canadian stores, leaving many shelves empty of popular items while warehouses were overstocked with unsellable goods, a core operational failure that Target could not fix quickly enough to save the venture.

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.

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.