Risk management uncertainty

See also Carcinogen Classification Schemes Dose-Response Relationship Exposure Assessment Exposure Criteria Hazard Identification Risk Assessment, Ecological Risk Based Corrective Action (RBCA) Risk Characterization Risk Communication Risk Management Uncertainty Analysis. 

Risk and uncertainty associated with each venture should translate, ia theory, iato a minimum acceptable net return rate for that venture. Whereas this translation is often accompHshed implicitly by an experienced manager, any formal procedure suffers from the lack of an equation relating the NRR to risk, as well as the lack of suitable risk data. A weaker alternative is the selection of a minimum acceptable net return rate averaged for a class of proposed ventures. The needed database, from a collection of previous process ventures, consists of NPV, iavestment, venture life, inflation, process novelty, decision (acceptance or rejection), and result data. 

The reality of risk assessment in investment for new processes is somewhat more complex than this. The specific innovations are often not discrete and the confidence of success of each item is a probability distribution rather than a single value. Techniques to handle the mathematical aspects have been available for many years [61] and computational tools are now readily available. A detailed coverage of managing uncertainty is beyond the scope of the current text and this simplistic approach suffices to address the key question of how to effectively manage the N-and C-values. 

Managing risk and uncertainty was increasingly seen as a priority in recent conferences, reflected in these comments from R D management interviews ... 

In essence, the earlier components of this overall assessment process are mainly deterministic in character (albeit with some probabilistic elements), whereas the later stages are mainly probabilistic. Not all elements of the process are quantifiable (with any degree of confidence), however and the socicii-political-cultural context of any downstream decision-making process may be intensely uncertain. Such uncertainties make the process of risk communication and debate a complex and sometimes unpredictable undertaking. It is essential therefore that those elements of the risk management process that cein be objectively einalysed and evaluated (either qualitatively or quantitatively, as appropriate) are so assessed. 

A number of EIA theorists believe in incorporating formal RA methods into EIA as a way to cope with uncertainties, especially in impact prediction where a formal framework for ecological risk assessment (EcoRA) is already developed. It includes three generic phases problem formulation, analysis, and risk characterization followed by risk management. The analysis phase includes an exposure assessment and an ecological effects assessment (see, e.g., US EPA (1998)). 

Risk characterization provides a basis for discussions of risk management between risk assessors and risk managers (US EPA 1998). These discussions are held to ensure that results of risk analysis are presented completely and clearly for decision makers, thus allowing any necessary mitigation measures (e.g., monitoring, collecting additional data to reduce uncertainty, etc.). 

Dealing with lack of knowledge and uncertainties - a task for risk management... 

Therefore, in this approach, we develop Risk Model III as a reformulation of Risk Model II by employing the mean-absolute deviation (MAD), in place of variance, as the measure of operational risk imposed by the recourse costs to handle the same three factors of uncertainty (prices, demands, and yields). To the best of our knowledge, this is the first such application of MAD, a widely-used metric in the area of system identification and process control, for risk management in refinery planning. 

Another approach to risk-based decision-making is the precautionary principle. The risk assessment and risk management approach used in the United States places a heavy reliance on the certainty of the data. The precautionary principle emphasizes that there is always some uncertainty and that decisions should be based on recognizing the possibility of harm. When in doubt, be cautious until adequate data are available to show that there is little potential for harm. Action to reduce exposure to hazardous agents should begin even if there is some uncertainty in the data. 

The assessment endpoint should be not only measurable (at least potentially) but also modelable. Defining a modelable endpoint is likely to require close discussion between an assessor (who knows what they can model) and a risk manager (who knows what they want to protect). Sometimes the assessment endpoint is only indirectly related to the management goal, for example, if the assessment endpoint is a risk to individuals, but the aim is to protect population sustainability. In such cases, qualitative inference will be required to interpret the assessment result. This inference will need to be done jointly by the risk assessor and risk manager. It is likely to involve substantial uncertainty, which will have to be taken into account qualitatively when producing a narrative description of the assessment outcome. This step should be identified as part of the conceptual model. 

Should any assessment endpoints be expressed as probabilities Suter (1998) points out that it can be confusing to use the term probability in defining assessment endpoints because it is unclear whether it relates to variability or uncertainty, so it will be helpful to distinguish these in the discussion with the risk manager. 

Einkel, A. M. 1990. Confronting uncertainty in risk management, a guide for decision-makers. 

Irrespective of the risk, assumptions and decisions will have to be made because of uncertainty. Implications of attempting to characterize all variability and uncertainty in the risk assessment need to be considered. For example, exaggerating uncertainties can obscure the scientific basis of risk management decisions, leaving the impression that the decision has been arbitrary in nature (NRC 1989). The purpose of the uncertainty factor together with the type of assessment (e.g., deterministic or probabilistic, protective or best estimate) must be clearly communicated. Uncertainty factors can be described in 3 categories ... 

It has been argued that the use of uncertainty factors is equivalent to having decision making or risk management operating within the risk assessment. Others believe... 

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