Page 200 - Pipeline Risk Management Manual Ideas, Techniques, and Resources

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Data Management
and Analyses

Contents VI Sconng 81182

er environments 811 83

finitions 81178
Datacollectcon and format 81179 es of central tendency
Point events and continuous data 81179 esofvanation 81’190
Eliminating unnecessary segments 8/ I80 andcharts 81190
Creating categones of measurements 81 Examples 8/192
Assigning zones ofinfluence 811 80
Countable events 81181
Spatial analyses 811 8 1
Data aualitvhncertaintv 811 81
V. SegmkntaGon 8/18I .

1. Background ment process is offered here. Some of these issues may not
be apparent until the later stages of the effort, so advance plan-
Although subsequent chapters discuss possible additions to the ning will help ensure an efficient process. The numerical tech-
risk assessment, many will, at least initially, want to work solely niques that help extract information from data are discussed
with the results of the risk assessment methodology described here. Using that information in decision making is also
in Chapters 3 through 7. Therefore, this chapter discusses some discussed and then more fully detailed in Chapter 15, Risk
data management issues and then begins the natural progres- Management.
sion from risk assessment to risk management.
Risk assessment is, at its core, a measurement process. As
noted in Chapter 1, there is a discipline, perhaps even an “art” II. Introduction
to measuring. This involves a philosophy with a clear under-
standing of the intent ofthe measuring. Furthermore, it requires Risk assessment is a data-intensive process. It synthesizes all
defined processes and structure for performing the measure- available information into new information-risk values, either
ments including all associated data handling efforts. relative or absolute. The philosophy behind data collection is
Having accumulated some risk assessment data, the next discussed in Chapters 1 and 2.
step is to prepare that data for decision making. Guidance on The risk values themselves become information that must be
data management issues that will often arise in the risk assess- managed. All through this book the risk “model” has meant the