The demonstration of disruptions incurred by the contractor necessitates the application of rigorous analytical methods and techniques. These methodologies should enable the evaluation and quantification of productivity losses. The analysis cannot be a mere comparison between the actual occurrences and the initial plans.
The primary aim of conducting a disruption analysis is to showcase the extent of lost productivity, consequently showing additional expenses and losses attributed to events for which the employer bears responsibility. Several factors contributing to diminished productivity fall under the contractor’s responsibility and, therefore, do not justify compensation. Some examples include:
- Inadequate coordination among subcontractors.
- Insufficient supervision and planning.
- Rework necessitated by defects.
- Overly optimistic planning.
- Resource shortages.
- Mechanical issues with the contractor’s machinery and tools.
The SCL Delay and Disruption Protocol provides detailed guidance on various methodologies for calculating productivity loss stemming from diverse disruptive events. These methodologies can be broadly categorized as:
Productivity-Based Methods: These rely on actual or theoretical productivity measurements. They aim to quantify the productivity losses in the resources utilized and subsequently assign a monetary value to these losses.
Cost-Based Methods: These involve an analysis of planned and actual resource expenditures. Their primary objective is to directly determine the variance between the actual and planned costs, without prior measurement of productivity losses in the resources employed.
Productivity-Based Methods
Productivity-based methods can be classified into three general categories, listed below in order of preference based on their reliability and widespread acceptance:
Specific Analysis of the Project
Measured Mile Analysis: This method involves comparing the productivity achieved in areas or time periods affected by disruptive events with the productivity achieved in similar activities during periods unaffected by these events. While this method is widely accepted, it is intricate and demands substantial documentation. Furthermore, it necessitates the existence of periods free from any disruptive events for comparison.
Earned Value Analysis: This approach identifies the man-hours reasonably allocated in the budget for completing specific activities and contrasts them with the actual man-hours expended to complete those activities. Often, specialized software is employed to facilitate the calculation of earned value for each activity.
Job Sampling: This method relies on contemporaneous records of direct job observations and event documentation to assess productivity.
Dynamic Modeling System: This approach involves the analysis of a simulation using specialized software to create a detailed model of the project. The model is then resimulated without interruption events, allowing for a comparison of results. Essentially, it is an advanced version of the “Collapse As-Built” method, this approach focuses exclusively on customer-responsible outage events. The robustness of the conclusions drawn from this analysis hinges upon several factors:
- The accuracy of data and the completeness of progress and event records.
- The expertise and judgment of the analyst in constructing the model.
- The transparency of the analytical process executed by the specialized software.
Due to the challenges, intricacies, and associated costs, this method is less commonly employed for calculating lost productivity when compared to other available techniques.
Comparison analysis of similar projects
They are used when there are not enough records available to carry out a specific study of the project. Productivity on the affected project is compared to similar projects within the same industry where the disruption events did not occur.
Industry studies
When there is insufficient contemporaneous documentation for a specific project study or comparative studies are not available, an estimate of lost productivity based on data developed from research studies conducted across the industry can be used. Factors generated from these studies are applied to the actual resource losses on the affected project to determine if the measured level of loss matches the factors determined in those studies. It is important to note that these methods vary in their reliability and depend on the availability of relevant records and data.
Conclusion
All the methods described above are technically acceptable. However, project-specific analyzes are by far the most reliable and accurate. The method used depends mainly on the availability of documentation and the particular circumstances of each particular case.