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Techniques Technique is the way in which humans apply technology or tools consisting of software and/or hardware. Proficiency in the application of technique is considered to be a measure of skill signifying that different people can apply the same technique and attain different levels of achievement. Best practice in the identification of the most appropriate decision analysis models involves a reiterative decision analysis cycle. But optimised decision analysis models often combine well-established analytical techniques1 with the unqiue features, relationships, algorithms and structural logic relating to the specific system of concern to a decision-maker and the decision-maker's preferences. The decision analysis cycle Model building has the purpose of maximising the transparency of all critical factor relationships which determine decision outcomes while minimising the potential for errors arising from inadequate model design and information used. The decision analysis cycle is a design refinement approach based upon a proactive evolution in the quality of three specific types of information:
1. The information and knowledge used to construct a model which encapsulates the understanding of the relationships between the critical factors which determine decision outcomes (deterministic). 2. The confidence in the applicability of the model rests upon the probabilities of critical events, not all of them under the control of the decision-maker (probabilistic). 3. The utility of the model finally depends upon the availability and quality of the information (data) used to predict outcomes (informational). A decision analysis model is deemed to represent an acceptable standard when sufficient confidence has been attained that the deterministic, probabilistic and informational dimensions cannot be refined further have attained an acceptable level of uncertainty2. How we help We assist customers in the development of appropriate decision analysis models according to the specific scope of the decision tasks they wish to automate. We take customers through the deterministic, probabilistic and informational phases and review every step of model building. This reiterative process continues until the model specification satisfies all appropriate criteria. When new information is made available it is sometimes necessary to review a decision analysis model by embarking on further decision analysis cycles; in reality model building is an ongoing process of refinement according to the advance of knowledge and events. 1 such as calculations, goal seeking, optimization, logical deduction and simulation 2 where resources are limited, the marginal costs of collecting better quality information can impose limits on what is considered to be an acceptable level of uncertainty. |
