As the practice of pipeline risk assessment continues to advance, we can also focus on the next steps: how do I make sense out of large sets of numbers? what is this risk assessment telling me? Here’s a recent article with some advice: PIN Article: Analyzing Risk Estimates
Armed with a modern risk assessment, risk management becomes much more transparent and even exciting. Seeing cost/benefits of proposed risk reduction actions provides clarity and, often, some ‘ah-ha!’ moments. Please click this link to read the pdf file of this article.
Risk Concepts sometimes harbor challenges in understanding and communications. This means that we must employ extra care in our choice of language when discussing risk issues. Read the article (pdf file)
A rather common issue these days is decision making involving comparisons between In Line Inspection (ILI) vs Direct Assessment (DA, and, in particular, External Corrosion DA or ECDA). You may need to research these techniques, if not already familiar to you, since we will assume the reader is fairly familiar with both. Both are acceptable […]
Quantifying potential consequences with a common scale can be challenging. Using a measure such as cost—the monetized loss associated with the damages—forces some difficult judgments to be made among various receptor damages. For example, not only must a value be assigned to a statistical human life, but also to various injury types, environmental damage, damage […]
In an earlier article, we noted that risk management is, in effect, often unintentionally delegated to decision-makers occupying the lower portions of the corporate org chart. In many companies, the field personnel are essentially setting corporate risk levels via their choices in day-to-day activities and their perceptions of priorities. While we noted some advantages of […]
Many statistical investigation techniques, used for decades in numerous applications, will also help us understand pipeline risk. Financial market analyses tools are a good example. The same types of charts, summary statistics, and other analytical tools used there will be appropriate for our data sets.