Project Focus ENI Safety Pre-Sense

Eni is not just making sense of safety, it is making “pre-sense”!

Data is everywhere. Today it’s as valuable as money, traded like currency and used to make sense and give reason to what we do and to the decisions we make. You can be sure to always hear the immortal phrase “based on the data” at every meeting, presentation and even office chats we partake in.

A phrase that was first used in the 60’s, “data science” is not only the reigning king of buzzwords but it’s widely considered as the fourth paradigm of science. In turn, the rise of the data scientist is indicative of this phenomenon. Using their analytical expertise they bring to life and transform numbers, spreadsheets and statistics into models and scientific processes, essentially making sense of huge amounts of data.

Data and Safety

When it comes to Health and Safety, data is of vital importance. Eni, one of Italy’s largest organisations, are using data to not just make sense of it, but to make pre-sense. As part of their Open Innovation Strategy, Eni chose the Mathesia crowdsourcing platform to boost its Safety Pre-Sense project, with the objective of providing a comprehensive analysis on safety events worldwide. The network of experts on the platform have been tasked with the creation of a data-driven framework capable of identifying the most relevant and repeating causes and factors of incidence concerning safety. The framework will then act as a decision support system, predicting the risk of future events, performing scenario analysis and prescribing risk mitigation measures.

In explaining that safety in all production plants is of key importance to Eni, data scientist Diletta Milana outlines the inspiration to taking this data driven approach to Health, Safety & Environment (HSE) activity. “At Eni, safety is our top priority. Our HSE teams work tirelessly to understand how to continuously improve the safety of our employees and contractors. However, being a global company involved in frontier technology and complex processes, we need to tackle a number of challenges. As the Eni digital transformation evolves and brings in unprecedented value in every business, we realized that an integrated and meaningful use of data, empowered by the advancements of machine learning techniques, fosters the precious opportunity to bring safety to a whole new level. Our ultimate goal is to build a system able to support and guide our HSE experts in making faster, more aware and more focused decisions”.

Using the pre-qualified data science and mathematical expertise on the Mathesia platform, Eni is accessing new and exciting  ways to find solutions to this challenge. As a keen recogniser of the value of open innovation, Eni is experimenting the collaborative economy that exists in crowdsourcing as part of one of many of its key initiatives.

Check out the Eni “Safety Pre-Sense” challenge