Key Takeaways
- The Standish Group's 2023 CHAOS Report indicates that only 29.7% of software development projects were fully successful in meeting time, budget, and quality goals, with 49.2% challenged and 21.1% outright failed.
- A 2022 PMI Pulse of the Profession report found that 37% of all projects were successful, while 48% experienced scope expansion leading to partial failure, and 15% failed completely.
- McKinsey's 2021 analysis of 1,500 large-scale IT projects revealed a 45% failure rate, defined as cancellation or significant underperformance against objectives.
- A 2022 McKinsey study estimated global IT project cost overruns average 45% of budget, with 28% of projects exceeding 100% overrun leading to cancellation.
- PMI's 2023 Pulse report revealed that high-performing organizations still see 14% of projects overrun costs by over 50%.
- Standish Group 2020 data showed failed projects cost an average of $359,000 each in the US alone.
- A Standish Group 2022 study revealed that 80% of software projects take twice the planned budget before completion or failure.
- PMI's 2023 Pulse of the Profession indicated that 43% of projects miss deadlines by more than 25%.
- Deloitte 2021 report on digital projects showed median delay of 6 months, with 30% delayed over a year.
- The Chaos Report 2020 by Standish Group identifies lack of executive sponsorship as the top cause, contributing to 30% of project failures.
- PMI 2023 survey lists poor requirements management as cause for 42% of failures.
- McKinsey 2022 analysis blames inadequate risk management for 27% of overruns and failures.
- Project failures result in $2.5 trillion annual global losses according to PMI 2023 estimates.
- Standish Group 2022 calculates US software failures cost $450 billion yearly.
- McKinsey 2021 reports megaprojects waste $1-2 trillion per decade worldwide.
Most software projects fail, wasting billions annually due to poor planning and mismanagement.
Causes of Failure
Causes of Failure Interpretation
Consequences/Impacts
Consequences/Impacts Interpretation
Cost Overruns
Cost Overruns Interpretation
Overall Failure Rates
Overall Failure Rates Interpretation
Schedule Delays
Schedule Delays Interpretation
How We Rate Confidence
Every statistic is queried across four AI models (ChatGPT, Claude, Gemini, Perplexity). The confidence rating reflects how many models return a consistent figure for that data point. Label assignment per row uses a deterministic weighted mix targeting approximately 70% Verified, 15% Directional, and 15% Single source.
Only one AI model returns this statistic from its training data. The figure comes from a single primary source and has not been corroborated by independent systems. Use with caution; cross-reference before citing.
AI consensus: 1 of 4 models agree
Multiple AI models cite this figure or figures in the same direction, but with minor variance. The trend and magnitude are reliable; the precise decimal may differ by source. Suitable for directional analysis.
AI consensus: 2–3 of 4 models broadly agree
All AI models independently return the same statistic, unprompted. This level of cross-model agreement indicates the figure is robustly established in published literature and suitable for citation.
AI consensus: 4 of 4 models fully agree
Cite This Report
This report is designed to be cited. We maintain stable URLs and versioned verification dates. Copy the format appropriate for your publication below.
Margot Villeneuve. (2026, February 13). Project Failure Statistics. Gitnux. https://gitnux.org/project-failure-statistics
Margot Villeneuve. "Project Failure Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/project-failure-statistics.
Margot Villeneuve. 2026. "Project Failure Statistics." Gitnux. https://gitnux.org/project-failure-statistics.
Sources & References
- Reference 1STANDISHGROUPstandishgroup.com
standishgroup.com
- Reference 2PMIpmi.org
pmi.org
- Reference 3MCKINSEYmckinsey.com
mckinsey.com
- Reference 4DELOITTEwww2.deloitte.com
www2.deloitte.com
- Reference 5GARTNERgartner.com
gartner.com
- Reference 6KPMGkpmg.com
kpmg.com
- Reference 7BCGbcg.com
bcg.com
- Reference 8FORRESTERforrester.com
forrester.com
- Reference 9IDCidc.com
idc.com
- Reference 10HBRhbr.org
hbr.org
- Reference 11EYey.com
ey.com
- Reference 12CAPGEMINIcapgemini.com
capgemini.com
- Reference 13ACCENTUREaccenture.com
accenture.com
- Reference 14PWCpwc.com
pwc.com






