Productivity Loss Claim Lacking Baseline Data
A mechanical contractor on a 20-month wastewater plant project claims $1.9M in lost labor productivity caused by 1,400 owner-directed change orders and pervasive out-of-sequence work. The contractor supports the claim with the 'measured mile' method, comparing a clean 3-month window early in the project to a disrupted 3-month window late in the project. The clean window had 42 workers and 55,000 earned labor hours; the disrupted window had 61 workers and 48,000 earned hours with 71,000 actual hours. The owner's forensic consultant notes the two windows used different crews, different scopes, and that the clean window preceded major design changes. There is no contemporaneous productivity baseline or daily reporting of disruption.
1. Assess whether the measured-mile comparison is a reliable basis for the claim and identify the methodological defects.
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The measured mile is conceptually valid but this application is weak. First, the two windows are not comparable: different crews, scopes, and the clean window predates design changes, so the comparison may capture scope-mix differences rather than disruption. Second, the contractor lacks contemporaneous baseline productivity data and daily disruption records, undermining causation. Third, the windows are small relative to a 20-month project. The productivity loss implied is (71,000/48,000) vs (55,000/55,000) - i.e., 1.48 actual vs 1.0 baseline - a 48% loss, which is high and requires strong corroboration. The claim should be discounted or rejected as presented unless the contractor can establish comparable work, contemporaneous records, and a credible cause-and-effect link between the owner's changes and the loss.
2. What alternative or supplementary approaches should the forensic consultant recommend to test the $1.9M figure?
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Recommend (1) an earned-value-based approach comparing planned vs. earned hours by period; (2) a modified total cost or industry-factor approach (e.g., MCAA/Mechanical Contractors Association factors) as a reasonableness cross-check, not as primary proof; (3) a cause-and-effect analysis tying specific change orders and out-of-sequence events to discrete work packages with contemporaneous daily reports, timesheets, and supervisor logs; (4) a jury/industry benchmark comparison; and (5) validation that the claimed loss is not double-counted in change order pricing. Triangulation across methods strengthens or undermines the $1.9M. Without contemporaneous records, the claim likely fails the burden of proving causation and amount with reasonable certainty.