In socio-technical work systems, safety can be considered an emergent property, due to non-linear and symbiotic interactions among technical and human aspects of work. A new perspective on socio-technical safety (referred to as Safety-II) pushes the need to assess and gather meaningful knowledge about normal work, and its effect on safety and productivity. This perspective promotes the development of organizational tools to support capturing, understanding, and exploring the inherent complexity of everyday work activities.
This project aims to develop an ontology-based framework for gathering and making interpretive sense of organizational performance, relying on the use of the Functional Resonance Analysis Method (FRAM). In particular, the ontology-based framework will support a formal representation to guide knowledge collection for FRAM analyses, which will overcome traditional top-down theoretical assessment relying on constructivism-oriented artificial varieties of work, i.e. work-as-imagined (WAI), towards a bottom-up approach focused on normal operations, i.e. work-as-done (WAD). The project will rely on an innovative gamified approach for knowledge gathering in order to isolate functional areas of concern, and the need for associated safety performance metrics: the Human-Centred Safety Crowd-Sensitive Indicators, the H(CS)2I. These latter will support sharp-end workers to critically assess their own work activity, helping middle managers and top managers to interpret weak signals (both positive and negative) about system performance to support organisational decision-making at different organizational levels. Validating the indicators’ framework in the process industry domain, the proposed methodological outcome will be then adaptable for different enterprise domains, in line with Directive 2014/95/EU about non-financial reporting, supporting new national procedures and benchmarking.
The overall aim of the project is to develop a framework grounded on
considering safety as an emergent property, and specifically focussed
on front-line workers. The research questions are as follows:
Scientific disciplines: computing/information science
The disseminated framework to define the H(CS)2I
indicators will be beneficial to stakeholders at different
organizational levels and with regulators through provision of a
methodological and decision-support tool for proactive indicators.
The framework supports:
The H(CS)2I project will last 18 months and will consist of five tasks.
Task 1: Project Management (Task Leader: ENEA)
Task 2: Developing Knowledge of Industrial Production Processes – Work as Imagined WAI (Task Leader: Middlesex University London)
Task 3: Gamified Collection of Work-As-Done (WAD) knowledge (Task Leader: ENEA)
Task 4: FRAM analysis: Definition of H(CS)2I indicators (Task Leader: Sapienza University of Rome)
Task 5: Framework validation and dissemination (Task Leader: Middlesex University London)
Antonio Denicola (ENEA, Italy) — project coordinator
Giordano Vicoli (ENEA, Italy)
Maria Luisa Villani (ENEA, Italy)
Maeve O'Loughlin (Centre for Decision Analysis and Risk Management, Middlesex University London, United Kingdom)
Patriarca Riccardo (Sapienza University, Italy)
IOSH (United Kingdom)
Information last updated on 2019-05-14.
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