Data
Software development statistics for 2026
The most-cited numbers on software project success, cost and time overruns, and why builds fail — each with its source. Sobering context for anyone deciding whether, and how, to build.
These figures come from long-running industry research — chiefly the Standish Group's CHAOS reports and the McKinsey–Oxford study of large IT projects. The exact percentages vary by year and methodology, but the direction is consistent: most projects overrun, and smaller, tightly-scoped builds are far safer.
Project outcomes
~29%
of software projects fully succeed — on time, on budget, with the planned features.
52%
are 'challenged' — late, over budget, or missing features.
19%
are cancelled outright before ever delivering.
Cost & time overruns
189%
is the average cost overrun across projects — nearly double the original estimate.
222%
is the average schedule overrun — projects run more than twice as long as planned.
45%
over budget on average is what large IT projects run — while delivering 56% less value than predicted.
Why projects fail
39%
of failures trace back to unclear or incomplete requirements — the single biggest cause.
33%
are driven by scope creep as requirements expand mid-build.
34% vs 6%
is the failure rate of large ($10M+) projects versus small ones — smaller, scoped builds are far safer.
What this means for your build
The throughline across these 9 statistics: software fails on scope, not on code. Unclear requirements, scope creep and oversized projects are what blow budgets — while small, fixed-scope builds with clear priorities succeed far more often.
That's exactly how to de-risk a build: scope tightly, ship a focused first version fast, and iterate. See the honest math in build vs buy software, or how a fixed-scope custom software project avoids these traps.
Build without the overruns
Fixed scope, a quote in 24 hours, and a focused first version live in weeks.