Abstract
The wave of big data is fundamentally transforming many activities and companies. The field of process safety is not spared, with many applications that seem very promising to detect weak signals from industrial processes and in particular mining the ocean of data generated in real-time by the various instrumented systems which would be predictive of future deviations that could lead to a major accident.
The purpose of this paper is to remind readers that in process safety the devil is often in the detail, and we must be careful regarding little rather than big data, the needle in the haystack, which is often the one that is necessary to make the right decision to make the operation safe.
Through case studies of accidents that we have investigated in various sectors of the process industry, we will illustrate situations where the absence of some basic data, sometimes even a single essential data missing or misinterpreted by lack of competence or the lack of recognition of weak signals or patterns, led to explosions and process accidents.
