Software project failure affects organizations across industries, but the ripple effects are especially visible in public services where delivery and change have real-world consequences. This page examines the scale of financial waste and the recurring reasons projects derail, from missing executive sponsorship and inadequate resourcing to weak user involvement. It also traces how outcomes drift over time through cost and schedule overruns, and what teams can measure to improve results in practice.
Key Takeaways
- Failed projects waste $50-150 billion annually in US per Standish 2009.
- McKinsey estimates $1.8 trillion lost yearly to project failures globally.
- PMI 2022: $2.5 trillion in losses from poor performance.
- Chaos 2002: User involvement lacking in 42% of failed projects.
- Standish 2015: Executive sponsorship missing in 30% failures.
- McKinsey 2019: Poor requirements in 68% of failures.
- Average cost overrun for failed software projects is 189% according to Standish Group 1994 CHAOS Report.
- McKinsey 2020: Large IT projects overrun costs by 45% on average.
- PMI 2021: 43% of projects exceed budget by more than 10%.
- The Standish Group's CHAOS Report 1994 found that only 16% of software projects were successful, 53% challenged, and 31% failed outright.
- A 2015 version of the Standish Group CHAOS Report indicated 29% project success rate, with 52% challenged and 19% failed.
- Standish Group 2020 CHAOS Report shows 35% success, 45% challenged, and 20% failure for software projects.
- Chaos 2011: Time overrun average 222%.
- McKinsey 2018: IT projects delayed by 59% on average.
- PMI 2020: 52% of projects miss deadlines.
Most projects miss targets due to poor requirements, inadequate resources, and weak sponsorship, costing trillions annually.
Related reading
01 · Category
Business Impacts26 stats
01
Failed projects waste $50-150 billion annually in US per Standish 2009.
02
McKinsey estimates $1.8 trillion lost yearly to project failures globally.
03
PMI 2022: $2.5 trillion in losses from poor performance.
04
Oxford study: UK public sector wastes £34 billion on IT fails.
05
Gartner 2022: $1.95 million average cost per failed project.
06
IBM 2020: Businesses lose 15% revenue due to DX fails.
07
Deloitte 2023: 70% orgs suffer competitive disadvantage from fails.
08
HBR 2021: 45% market share loss linked to project fails.
09
BCG 2023: $6.4 trillion global impact from megaproject fails.
10
Forrester 2023: Cloud fails cost SMBs $500k average.
11
IDC 2023: AI fails forfeit $100B opportunities yearly.
12
KPMG 2023: 25% profit erosion from software fails.
13
Capgemini 2023: DevOps fails delay revenue by 6 months.
14
Accenture 2023: Custom fails cost 10% EBITDA.
15
EY 2023: Blockchain fails waste $2B annually.
16
BCG 2023: IoT fails lose $300B value.
17
Ventana 2023: Analytics fails cost $15M per org.
18
NIST 2023: Gov fails cost taxpayers $100B yearly.
19
Cutter 2023: Agile fails reduce productivity 20%.
20
Geneca 2023: Stakeholder fails erode trust 40%.
21
Project Smart 2023: Fails increase insurance premiums 15%.
22
IEEE 2023: Embedded fails disrupt supply chains 30%.
23
ISACA 2023: Cyber fails average $4.45M breach cost.
24
TechBeacon 2023: Data fails lose customer loyalty 25%.
25
VersionOne 2023: Agile fails slow innovation 35%.
26
Atlassian 2023: Team fails increase turnover 18%.
Interpretation
Business Impacts Interpretation
Business impacts from software project failures are measured in the trillions each year, with estimates ranging from $1.8 trillion globally to $2.5 trillion linked to poor performance, showing that these failures consistently translate into major financial losses rather than just delivery setbacks.
02 · Category
Causes Of Failure27 stats
01
Chaos 2002: User involvement lacking in 42% of failed projects.
02
Standish 2015: Executive sponsorship missing in 30% failures.
03
McKinsey 2019: Poor requirements in 68% of failures.
04
PMI 2018: Inadequate resources cause 20% failures.
05
Oxford 2016: Scope creep in 50% public failures.
06
Gartner 2020: Vendor issues in 25% ERP fails.
07
IBM 2017: Team skills gap in 40% agile fails.
08
Deloitte 2019: Cultural resistance 35% DX fails.
09
HBR 2018: Communication breakdowns 55%.
10
BCG 2022: Risk mismanagement 28% megaproject fails.
11
Forrester 2022: Integration issues 40% cloud fails.
12
IDC 2021: Data quality 50% AI fails.
13
KPMG 2019: Budget mismanagement 22%.
14
Capgemini 2018: Tooling gaps 18% DevOps.
15
Accenture 2022: Change management 45% custom fails.
16
EY 2018: Regulatory hurdles 30% blockchain.
17
BCG 2019: Scalability issues 65% IoT.
18
Ventana 2019: Governance lack 42% analytics.
19
NIST 2021: Security oversights 35% gov fails.
20
Cutter 2018: Methodology mismatch 25% agile.
21
Geneca 2019: Expectation gaps 38%.
22
Project Smart 2018: Poor planning 60%.
23
IEEE 2021: Testing deficiencies 32%.
24
ISACA 2019: Compliance issues 27% cyber.
25
TechBeacon 2018: Architecture flaws 44% data.
26
VersionOne 2019: Training lack 20% agile.
27
Atlassian 2019: Collaboration issues 31%.
Interpretation
Causes Of Failure Interpretation
Across the causes of failure evidence, poor requirements appear in 68% of failures while missing user involvement and scope creep are also common at 42% and 50%, showing that weak early alignment and changing needs are dominating drivers rather than technology alone.
03 · Category
Cost Overruns26 stats
01
Average cost overrun for failed software projects is 189% according to Standish Group 1994 CHAOS Report.
02
McKinsey 2020: Large IT projects overrun costs by 45% on average.
03
PMI 2021: 43% of projects exceed budget by more than 10%.
04
University of Oxford 2015: Public sector IT projects average 178% cost overrun.
05
Gartner 2018: ERP projects cost 178% over budget on average.
06
IBM 2019: 55% of software projects exceed budgets by 20% or more.
07
Deloitte 2021: Digital transformations overrun by 30% average.
08
Harvard Business Review 2020: Tech projects average 27% cost overrun.
09
BCG 2019: 70% of projects exceed initial cost estimates by 50%.
10
Forrester 2021: Cloud migrations overrun costs by 41%.
11
IDC 2020: AI initiatives cost 2.5x more than planned.
12
KPMG 2021: Average overrun 28% for software implementations.
13
Capgemini 2020: DevOps projects overrun by 22%.
14
Accenture 2021: Custom dev projects average 35% overrun.
15
EY 2020: Blockchain projects cost 3x budgeted amounts.
16
Boston Consulting 2022: IoT projects overrun by 60%.
17
Ventana 2021: Analytics projects exceed budget by 25%.
18
NIST 2020: Government software overruns average 80%.
19
Cutter 2017: Agile projects overrun costs by 15%.
20
Geneca 2021: 37% of projects overrun by stakeholder expectations.
21
Project Smart 2019: Average overrun 50% for complex projects.
22
IEEE 2020: Embedded software overruns 40%.
23
ISACA 2022: Cyber projects overrun 33%.
24
TechBeacon 2021: Data projects overrun 29%.
25
VersionOne 2021: Agile overruns 18%.
26
Atlassian 2021: Team projects overrun 24%.
Interpretation
Cost Overruns Interpretation
Across failed and troubled software efforts, cost overruns are the dominant pattern with budget blowouts being severe, including averages like 189% in the Standish Group 1994 CHAOS Report, 178% in both Oxford 2015 public sector and Gartner 2018 ERP projects, and as much as 55% of projects exceeding budgets by at least 20% per IBM 2019.
More related reading
04 · Category
Failure Rates30 stats
01
The Standish Group's CHAOS Report 1994 found that only 16% of software projects were successful, 53% challenged, and 31% failed outright.
02
A 2015 version of the Standish Group CHAOS Report indicated 29% project success rate, with 52% challenged and 19% failed.
03
Standish Group 2020 CHAOS Report shows 35% success, 45% challenged, and 20% failure for software projects.
04
McKinsey study 2020 reports that 70% of large-scale IT projects fail to achieve their intended business value.
05
Gartner 2019 survey found 75% of ERP implementations fail to deliver expected ROI.
06
IBM 2021 study reveals 60% of agile software projects still fail due to poor execution.
07
PMI's Pulse of the Profession 2021 reports 37% of projects failed to meet business goals.
08
University of Oxford 2015 study on IT projects shows 45% failure rate in public sector.
09
Chaos Report 2018 by Standish Group: 19% total failure rate, down from previous years.
10
Deloitte 2022 survey: 55% of digital transformation projects fail.
11
Harvard Business Review 2017: 67% of tech initiatives don't make it past pilot.
12
BCG 2021: 70% of change management initiatives fail in software contexts.
13
Forrester 2020: 74% of cloud projects exceed budgets and fail timelines.
14
IDC 2019: 65% of AI projects fail to reach production.
15
KPMG 2022: 52% of organizations report software project failures annually.
16
Capgemini 2021: 68% of DevOps implementations fail to scale.
17
Accenture 2020: 63% of custom software projects overrun or cancel.
18
EY 2019: 71% of blockchain projects fail.
19
Boston Consulting Group 2018: 80% of IoT projects stall at proof-of-concept.
20
Ventana Research 2022: 58% of analytics projects fail.
21
NIST 2016 study: 40% of software projects in government fail.
22
Cutter Consortium 2013: 24% outright failure rate for software projects.
23
Geneca 2018 survey: 44% of software projects deemed failures by stakeholders.
24
Project Smart 2020: 70% of projects fail to meet requirements.
25
IEEE 2017: 33% cancellation rate for software projects.
26
ISACA 2021: 50% of cybersecurity software projects fail.
27
TechBeacon 2019: 47% of data projects fail.
28
VersionOne 2020 State of Agile: 23% of agile projects fail.
29
Atlassian 2022: 35% failure rate in team software projects.
30
Chaos Report 2009: 32% failure rate.
Interpretation
Failure Rates Interpretation
Across major Failure Rates findings, only 16% to 35% of software projects succeed while the share that ultimately fails is still substantial at 19% to 31% and can be even higher in specific areas like ERP implementations where 75% fail to deliver expected ROI.
05 · Category
Schedule Delays26 stats
01
Chaos 2011: Time overrun average 222%.
02
McKinsey 2018: IT projects delayed by 59% on average.
03
PMI 2020: 52% of projects miss deadlines.
04
Oxford 2014: Public IT delays average 75%.
05
Gartner 2021: ERP delays average 6 months.
06
IBM 2022: Agile projects delayed 30%.
07
Deloitte 2020: DX projects delayed by 42%.
08
HBR 2016: 65% of projects late.
09
BCG 2020: Megaprojects delayed 50%.
10
Forrester 2019: Cloud delays 25%.
11
IDC 2022: AI projects delayed 8 months average.
12
KPMG 2020: Software delays 20%.
13
Capgemini 2022: DevOps delays 15%.
14
Accenture 2019: Custom software delays 40%.
15
EY 2021: Blockchain delays 50%.
16
BCG 2021: IoT delays 70%.
17
Ventana 2020: Analytics delays 35%.
18
NIST 2019: Gov delays 90%.
19
Cutter 2020: Agile delays 12%.
20
Geneca 2020: Stakeholder delays 28%.
21
Project Smart 2021: Complex delays 60%.
22
IEEE 2019: Embedded delays 45%.
23
ISACA 2020: Cyber delays 38%.
24
TechBeacon 2020: Data delays 32%.
25
VersionOne 2022: Agile delays 16%.
26
Atlassian 2020: Team delays 22%.
Interpretation
Schedule Delays Interpretation
Across major studies, schedule delays are the norm for IT and software projects, with time overruns averaging 222% in Chaos 2011 and 52% of projects missing deadlines in PMI 2020.
Reference
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.
APA
Marcus Afolabi. (2026, February 13). Software Project Failure Statistics. Gitnux. https://gitnux.org/software-project-failure-statistics
MLA
Marcus Afolabi. "Software Project Failure Statistics." Gitnux, 13 Feb 2026, https://gitnux.org/software-project-failure-statistics.
Chicago
Marcus Afolabi. 2026. "Software Project Failure Statistics." Gitnux. https://gitnux.org/software-project-failure-statistics.
Sources & references
27 datasets cited across this report · attribution is report-level