NASA Requirements vs Cost Overrun: The 5-10% vs 20% Curve
One of the strongest pieces of evidence for "invest early to save late": NASA found that spending 5-10% of effort on requirements yields ~50% overrun, while spending 20% holds overrun to ~10%.
The curve in full
| Definition spend (Phase A/B) as % of total program cost | Cost overrun observed |
|---|---|
| under 5% | about 80% to over 200% |
| 5-10% | about 50% |
| 10-15% | about 30% |
| 15-20% | about 10% |
| 20% or more | close to 0% |
Approximate banding read off Werner Gruhl's scatter chart "Effect of Requirements Definition Investment on Program Costs" (Werner M. Gruhl, Chief, Cost & Economic Analysis Branch, NASA Headquarters). Gruhl plotted roughly 30 individual NASA programs, not averaged bands, and the y-axis is cost overrun only. The lowest-definition programs (under ~5% spent on Phase A/B) ran 100-200%+ over budget; only a handful of well-defined programs finished on budget.
Why the curve is so steep at the low end
The intuition is that requirements errors discovered late are vastly more expensive to fix than requirements errors discovered early. Boehm and Basili (IEEE Computer, 2001) put the escalation at roughly 100x on large projects for a problem caught after delivery versus in requirements and design, and nearer 5:1 on small ones. (The tidy per-phase “1 : 10 : 100” chart often quoted alongside this is unsourced folklore; the direction is sound, the exact multipliers are not.) NASA's requirements-vs-overrun curve is essentially the same cost-of-change effect applied at the project level: starve the requirements phase and you bake in expensive rework.
For project managers, the practical reading is: budgets that allocate only 5-10% of effort to discovery and requirements are not lean. They are pre-committing to 30-50% cost overrun. The cheapest insurance against overrun is to fund the front of the project properly.
How to cite
The chart is widely reproduced in systems-engineering literature; see the discussion in the SEBoK "Economic Value of Systems Engineering" article and the NASA Systems Engineering Handbook. Gruhl's underlying per-program data was never published as an open dataset.
Related references on this site
Frequently Asked Questions
What is the NASA requirements vs cost overrun finding?
Werner Gruhl, then Chief of the Cost and Economic Analysis Branch at NASA Headquarters, plotted roughly 30 NASA programs and found a strong inverse relationship between the share of total program cost spent on definition (Phase A/B) and final cost overrun. Programs investing only about 5% of total cost in definition typically ran 80% to 200%+ over budget, while programs investing 15% to 20% held overruns to roughly 10% or less. The analysis was first run in the 1980s, repeated in the 1990s, and presented at the 1998 INCOSE Systems Engineering Seminar.
Where can I find the original NASA data?
The chart is Werner Gruhl's 'Effect of Requirements Definition Investment on Program Costs' (Cost and Economic Analysis Branch, NASA Headquarters), presented at the 1998 INCOSE Systems Engineering Seminar and widely reproduced in systems-engineering literature, including the SEBoK 'Economic Value of Systems Engineering' article. Gruhl's underlying per-program data was never released as an open dataset, so the published versions are the scatter chart itself rather than a raw table.
Does this requirements-effort finding apply outside aerospace?
Adjacent work in software engineering (Boehm, Cone of Uncertainty) and large IT projects (McKinsey-Oxford 2012) supports the same direction: more rigorous early definition correlates with lower late-stage overrun. The exact percentages vary by domain. For commercial software the equivalent inflection is usually around 15% of effort in discovery and architecture; for hardware-software systems closer to NASA's 20%.