The Overlooked Gap in Estimating Conversations: Understanding Estimate Classification and Accuracy
- Roger Farish
- Nov 25, 2025
- 2 min read
Updated: Dec 1, 2025
Why Clear Distinction Builds Stronger Estimate Credibility | ROMAN Consulting Group
In capital project estimating, few topics are more misunderstood than estimate classification and accuracy. They often appear side by side in reports, yet they measure completely different things. Confusing the two can mislead teams about how reliable an estimate really is, especially in early project phases when confidence drives key investment decisions.

Estimate Classification measures scope maturity, not precision. It answers the question, “How well do we understand the scope behind this number?”
According to AACE International Recommended Practice 18R-97, estimates are categorized from Class 5 (conceptual) to Class 1 (definitive), each representing a higher level of definition. Misclassifications often occur when teams assign classes based on purpose rather than scope maturity or assume more line items equal higher definition.

Estimate Accuracy, by contrast, quantifies uncertainty. It describes how much actual cost could deviate from the estimate, reflecting the variability in data quality, assumptions, and scope maturity.
True accuracy should come from quantitative risk analysis, such as Monte Carlo simulation, rather than fixed ranges.
Keeping the distinction clear between classification as scope maturity and accuracy as uncertainty builds transparency and improves how project teams communicate cost confidence. Both dimensions together define estimate credibility, shaping investment confidence and informed decision making.
At ROMAN Consulting Group, we help teams strengthen estimate credibility by ensuring classification reflects true scope maturity and that accuracy is grounded in quantified uncertainty. Through independent estimate reviews, FEL support, and cost risk analysis, we provide decision makers with clearer transparency into what is known, what remains uncertain, and how much confidence they can place in the estimate.
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