Project team evaluation data analysis

The EPA developed a document titled Guidance for Data Quality Assessment, Practical Methods for Data Analysis, EPA QA/G-9 (EPA, 1997a) as a tool for project teams for assessing the type, quality, and quantity of data collected for projects under the EPA oversight. This document summarizes a variety of statistical analysis techniques and is used primarily by statisticians. DQA, however, is not just a statistical evaluation of the collected data. It is a broad assessment of the data in the context of the project DQOs and the intended use of the data, which requires a... 

Essential components of CQI problem solving include the project work team, a structured method to study the problem, collected data, and data analysis tools to evaluate outcomes. 

Clinical trials always have detailed plans and protocols that describe the objectives, hypotheses, assumptions, data collection methods, data analysis methods, and so on. In like manner, the simulation plan describes a simulation process that is agreed to by the simulation team. The plan describes the work to be done, records to be maintained, and reports to be written. This plan should be written in enough detail so that another researcher could pick it up and execute the simulation with corresponding results. The plan must be critiqued and modihed if needed. The preparation of the plan also provides an opportunity to evaluate objectives, assumptions, methods, and goals of the project. 

The aim of project evaluation is to use the available data to provide information which will assist decision making on the future of the project. Use of sensitivity analysis and risk analysis techniques point up areas where uncertainty in the input data has greatest effect and indicates the effects of these uncertainties on the project outcome. Such evaluation does not eliminate the need for skilled judgement in the management team nor does it necessarily make the decision process any easier. However, it does ensure that a complete view of the project is available and makes clear the need for definitive company policy on risk and profitability criteria. 

When performing either a HAZOP study or a what-if analysis, it is essential that all necessary reference data be available for review and evaluation. Any and every type of data pertaining to the system or project under analysis should be examined to ensure that the review team is fuUy cognizant of all design criteria, functional intent, and operational requirements of the system. Once these elements are clearly established and understood, the consequences of any potential deviations (intended or otherwise) can be more fully explored and evaluated. 

As, according to our literature analysis, no statistically relevant amount of empirical data about lEMI events was available, risk had to be determined by estimation. For this purpose, an analysis team comprising all relevant stakeholders (including personnel of the Cl operator) should evaluate the risks in analysis meetings. However, effort in the magnitude of person-weeks or even person-months would have to be spent for this purpose. For a first validation, this effort-consuming involvement of Cl operators, who were themselves not project partners, should be avoided. For this reason, the estimation was performed by personnel of the research institute AIT only. For the concrete RPN tables obtained in the validation, we therefore have to state that the values are provisional and should be seen as examples only. 

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