(52av) Transforming a Major Hazard Management System into a Digital Model: A Case Study Presentation and a Scientific Questioning Around Human Factor Issues

Based on several case studies where we have accompanied operators over several years, and particularly thanks to a close 7-year partnership with the Service National des Oléoducs Interalliés (SNOI)[1], we have designed a computer application dedicated to the management of major industrial risks.

Firstly, we propose to present the pragmatic results of this work:

• Rationale for an integrated web-based risk management tool in the SNOI. In a problem-based way, we will list the reasons which led this industrial operator to redouble their efforts to improve the management of their environmental and major hazard issues.
• Rationale of the developed solution:

1. A risk assessment able to support decisions and provide the rationale to justify operator choices also if questioned by the regulator and its own management staff. This rationale informed the very foundation of the way the IT system was designed and realized in the easiest way as much as possible.. Above all we wanted the risk assessment to be the foundation of a live picture shared across all levels to provide transparency on the risk faced and the impact that the unavailability or the unreliability of tasks or equipment can have on accident scenarios plants are exposed to.
2. A monitoring process to:
   1. Support the improvement of the risk assessment,
   2. Demonstrate the congruence between the risk control means considered in the analyses and the resources efficiently managed on the sites,
   3. Monitor that the evolution of the criticality of the hazardous phenomena remains acceptable over time.
3. A management system of:
   1. All the type of requests and demands received from different inspectors (including updates to risk studies), with a classification according to how clear and easy or not to do they are to realize,
   2. How are best to address them so that recurrent similar request can be dealt in a consistent standardized way (especially in risk studies),
   3. The lists of evidences that proof the operator correctly daily answer to requests.

• Concrete examples, explained with screenshots, in order to give the practical vision behind the use of this solution.

In a second step, we would like to go much further in our presentation, to show that, behind this digital technology, the challenge is to address fundamental Human Factors issues. The digital transformation of a risk management system is not just about simplifying work, speeding up processes, facilitating change, saving stress and financial expenditure. These are significant side-effects. But it would be a serious mistake to take them as the ultimate goal. No! the really important issue is to fight against the lack of confidence of managers and regulators to take decisions because of the discrepancies between risk studies and the reality of installations and practices.

Our digital approach aims to combat: 1. inconsistencies within the studies, 2. the lack of correspondence between the data used in the studies and the reality of the installations and practices, 3. the lack of legibility of the dynamics from the point of view of the risk acceptability criteria. To do this, it is necessary to combat i) the cognitive biases of the many actors in charge of these studies, from the field operators to the site operators, via the various engineering fields, ii) sociological game-playing that sustains them. Basically, we intend to show how the digital knowledge management process support this combat, when it is used essentially as a tool for criticizing the modelling processes, i.e. to control the intelligibility and acceptability of engineering models in a mastered scientific approach. We want to show how some critical human factors issues are well managed when digital technology favors the back and forth between proposals and reality, the confrontation of daily operational data (production, maintenance, logistics) with the modelling hypotheses, the construction of a common representation of the risks that each actor, from his own point of view, with his feedback, must criticize.

[1] ) SNOI is responsible for the French part of the NATO pipeline network in Central Europe (CEPS), known as the Common Defense Pipeline (ODC). It thus operates a network of 2,300 km of pipelines and 14 SEVESO depots, including 7 classified as high threshold, for a total capacity of 500,000 m3 distributed among more than 80 buried tanks.