Triad Benefits
The Triad approach can accelerate project schedules, reduce overall project costs, and improve project outcomes.
The application of a Triad approach to hazardous waste site characterization and remediation decision-making provides potentially several critical benefits to the overall cleanup process. These include:
- Reduced Data Collection Costs. The Triad recognizes that, with the right quality assurance and quality controls in place, collaborative data sets containing data produced by a mix of analytical methods can achieve decision quality objectives at often significantly reduced costs as compared to data sets derived solely from standard analytical methods employed by fixed laboratories. There are several reasons for these cost savings. First, the types of real-time measurement systems used for sample analyses often have a significantly lower per-analysis cost than their standard analytical counterparts. Second, if one is able to adapt data collection programs in response to real-time results, sampling programs can be kept as focused on decision-making needs as possible, and consequently as efficient as possible. Third, the availability of real-time data allow unexpected results to be addressed in the framework of one field deployment, minimizing the potential need for return visits to the field for additional data collection. This, in turn, eliminates redundant mobilization and demobilization costs, along with the accompanying expenses of work plan and supporting documentation development.
- Expedited Schedules. Timely site closure requires timely decisions. Timely decisions require timely supporting data. With its emphasis on real-time measurement technologies, one of the Triad's strengths is its ability to produce timely data to support hazardous waste site decision-making. With real-time measurement systems, unexpected results during data collection can be resolved during the course of data collection work, provided contingencies have been built into the supporting work plans. This minimizes the potential need for multiple consecutive sampling programs. The Triad also provides the possibility for integrating characterization, remediation, and closure activities into one field mobilization when site conditions and the accompanying regulatory framework allow. For example, a traditional soil remediation effort that involved the removal of contaminated soils would typically require sufficient data to design the excavation completely before remediation began. Using a Triad approach, dynamic work strategies could be implemented for the excavation, allowing work to proceed based on limited initial data, with real-time data collection taking place during the excavation process to guide its progress.
- Enhanced Stakeholder Concurrence. The Triad emphasizes systematic planning, combined with dynamic work strategies. Unlike a traditional work plan where stakeholders know precisely what will be done before work is initiated, in a dynamic work strategy at least some key decisions are deferred until the actual field work takes place. Consequently, stakeholders initially are asked to concur with a process rather than a product. For a Triad approach to be successful requires their involvement at some level with the decisions that are being made in the field as work progresses. This guarantees stakeholder participation in the characterization and/or remediation process that is beyond what has traditionally been the case. This, in turn, generally results in enhanced stakeholder concurrence with the final decisions derived from data produced by dynamic work strategies.
- Improved Site Decision-Making. The ultimate goal of the Triad is improved decision quality. By focusing on reducing decision uncertainty, rather than simply analytical uncertainty, and making use of collaborative data sets combined with a weight of evidence approach to data evaluation, a Triad approach will typically result in much better decisions being made with the same resource investment. With its emphasis on real-time measurement systems, Triad-based data collection programs can pursue data collection activities for an area until decision quality objectives have been attained. That includes responding to and resolving unexpected site conditions that are encountered. In practical terms this means a reduced likelihood that contamination is left undiscovered, or that resources are spent unnecessarily on portions of a site where contamination concerns in fact do not exist. Improved site decision-making also can reduce overall remediation costs through waste stream minimization and adaptive remedial strategies, an important outcome from a site manager's perspective.
