Flow Assurance technologies are currently experiencing steady progress. Most new technologies are in many ways riskier than older ones, but they are also more efficient. It would be optimal for offshore operators ready to buy some novel technology to select the right offer, given their respective safety policies, from all existing possibilities. But operators hardly know of all these possibilities; the contractors who develop new technology do. But how could the latter optimally select the design option which should be offered to a given operator, to best serve its needs? The present paper deals with this question by connecting technical possibilities with company strategies in an integrated and quantified model: the output data of a physical model are entered as input into a psycho-management risk model. As a result, one can compute optimal characteristics for each operator of a new technology. This helps the contractor sell and monitor its offer under uncertainty. It also induces the operator to buy the innovative technology. We use some specific software developed at GRID (Group of research on Risk, Information and Decision, affiliated to ENSAM) to assess safety policies of operators. A real case is analyzed and presented. We argue that our model produces insight, by revealing knowledge which officers of the contractor company in long lasting contact with a given operator have internally accumulated, but which they are not able to express under any operational format. Such knowledge is ignored by industrial engineering, but often turns out to be richer than what can be extracted from any available data. One difficulty is to manage the software’s session in such a way that officers will answer the questions. The other difficulty is to convince engineering and risk managers that the “Human factor” is much richer than it is given credit for in textbooks and even more accurate than most existing data. Thus, we substantially improve existing industrial management techniques as currently applied to offshore technology, and more generally existing practice in the industry.

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