Abstract
Designing food processes and keep them updated at the pace of innovation to face competition, consumers’ trends and sustainability precepts is all but an easy task to accomplish. The complexity is steadily increasing and, with it, the need to adopt a systemic, as well as systematic, approach in designing and maintaining food processes to avoid compromising their survival and to guarantee their steady efficiency. The use of scenarios to exploring the uncertainty associated with that complexity becomes essential to support designers and, even more broadly, all decision makers involved in the design and operation of a technological process. Risk engineering can play an important role in that direction as it allows to account for hazards and threats associated with the identified opportunities. In the food industry hazards related to the safety of food production are identified and assessed through the well-known, widely used and regulated methodology “Hazards Analysis and Critical Control Point (HACCP)”, whose application is nowadays fostered by the international standard ISO 22000. Yet, the HACCP, as many other methodologies applied in other sectors, fails to capture the complexity associated with food processes, thus leaving space for grey zones where inter-functional risks can grow and manifest.
The manuscript presents how the Holistic Risk Analysis and Modelling (HoRAM) method can be conveniently applied to provide decision makers with the necessary information (scenario analysis) by assessing the technological element jointly with the human and organizational ones (i.e., a systemic approach). Further, the manuscript also explains how HoRAM allows to systemically and systematically account for the consequences that might be generated by each scenario and for the entire universe as a whole, thus allowing to include in the decision both the possibility of the unwanted outcomes and the associated effort needed to make them less likely or less severe. Finally, it explains how the scenarios produced can be managed at different level of abstraction to allow the analyst better understanding the problem analysed and the decision-maker the profile of the opportunity to pursue.
