Steps to Take When Your Project Suffers Productivity Loss
The measured mile analysis is a widely recognized and preferred method for quantifying productivity loss in construction claims. It estimates damages resulting from lost productivity by comparing activities during a period of disrupted performance to identical or substantially similar activities during a period of unaffected performance. The unaffected performance period represents the “measured mile,” which serves as a basis for comparing impacted labor productivity and determining lost man-hours for the impacted activities. The procedure for implementing a measured mile analysis is as follows:
Identify and Track Impacted Activities
Once a potential disruption event is identified, the project site personnel should identify and closely monitor the activities that could potentially be impacted.
Compile and Analyze Labor Productivity Data
After identifying disruption events and impacted activities, labor productivity data should be compiled and analyzed. Labor productivity data can be extracted from contemporaneous project documents such as daily reports, weekly reports, progress records, payment applications and certified payroll. Analysis of labor productivity data should include the validation and reconciliation of project documentation.
Identify Measured Mile and Calculate Lost Man-Hours
Once labor productivity data is compiled and analyzed, results should be scrutinized to identify trends over a project’s timeline. Non-impacted periods of a project should be marked and labor productivity during these time periods should be calculated. The measured mile is the progress of activities, or production recorded, over an unimpacted period of a project. The labor productivity of the measured mile is a benchmark for comparing labor productivity recorded during an impacted period. However, finding an unimpacted period of performance (e.g. a measured mile) is often a significant challenge. In this case, a period of performance that is the least impacted by the disruption event can be used as a basis for determining productivity loss. A graphical representation of labor productivity throughout the project is helpful to determine the impacted and unimpacted periods of performance. Figure 1 depicts an example of labor productivity and the measured mile for a construction project.
Figure 1 – Labor Productivity and Measured Mile Example
Once a measured mile is determined, labor productivity during the impacted period of performance can be compared to the labor productivity of the measured mile to calculate the lost man-hours.
Summarize Lost Productivity Information
and Quantify Total Damages
A summary depicting the impacted activities and corresponding lost man-hours is prepared. The hourly labor rates are factored in to quantify the total damages incurred as a result of lost productivity. The summary should include sections related to liability and causation. The liability section explains entitlement of the affected party based on particular contract clauses that justify the application for damages. The causation section explains the relationship between disruption impacts and disruption events, which occurred as a result of the other party’s actions and/or inactions. This section is essential to apportion responsibility based on the actions and/or inactions of stakeholders.
The measured mile analysis has proven to be a useful and preferred method for the quantification of lost productivity due to disruptions as it relies on productivity actually achieved during the project. However, it should be carefully used to quantify damages and support claims successfully. Common mistakes in implementing a measured mile analysis include the use of erroneous or inconsistent data, the use of incorrect productivity measurement, the use of different scopes of work in comparing labor productivity, and the lack of/or incorrect causation.
Authored By: Nour Bouhou, PhD, PSP
Information extracted from Quantifying Disruption in Power Projects Using the Measured Mile Analysis by Anthony Gonzales, Jesus Schuldes, PSP and Adrian G. Saldanha.