Complexity is an inherent property of socio-technical activities and represents a continuously growing concept in modern project en-vironments (Marle and Vidal, 2016). Complexity is often used to de-scribe those phenomena that cannot be totally understood and kept under control, oppositely to complicatedness (Ulrich and Probst (1988); Dekker et al. (2012)). A joint combination of the two traditional scientific approaches for complexity management (i.e. descriptive and perceived complexity) has been early acknowledged as necessary to cope with nowadays project management issues (Schlindwein and Ison 2005). Since all approaches for describing complex projects are models of reality, they necessarily deal with the limited perception of the analyst, i.e. his/her improper understanding of reality. Therefore, the approaches to deal with project risks are inherently biased, leav-ing room for the emergence of unforeseeable effects (Baccarini, 1996). In the last decade, similar observations have been largely explored in the context of risk and safety management for socio-technical sys-tems, leading to the theory of “Resilience Engineering” (RE) (Flin, 2006; Hollnagel, 2011). Acknowledging the limitations of traditional risk approaches, an effective project management should combine traditional risk management with resilience management, where re-silience is intended as the ability to recover from endogenous or ex-ogenous shocks or disturbances (Patriarca et al., 2018). Based on the assumptions of RE, this research aims to explore the potential benefits of adopting the Functional Resonance Analysis Method (FRAM) (Hollnagel, 2012) for modelling socio-technical properties of projects. The research aims to explain how a RE-based approach may favour an effective resilience management, and conse-quently support the project manager in coping with socio-technical risks.
Favouring resilience in increasingly complex environments. Development of an adaptive approach for Large Engineering Projects Management
FAVARI E
2018-01-01
Abstract
Complexity is an inherent property of socio-technical activities and represents a continuously growing concept in modern project en-vironments (Marle and Vidal, 2016). Complexity is often used to de-scribe those phenomena that cannot be totally understood and kept under control, oppositely to complicatedness (Ulrich and Probst (1988); Dekker et al. (2012)). A joint combination of the two traditional scientific approaches for complexity management (i.e. descriptive and perceived complexity) has been early acknowledged as necessary to cope with nowadays project management issues (Schlindwein and Ison 2005). Since all approaches for describing complex projects are models of reality, they necessarily deal with the limited perception of the analyst, i.e. his/her improper understanding of reality. Therefore, the approaches to deal with project risks are inherently biased, leav-ing room for the emergence of unforeseeable effects (Baccarini, 1996). In the last decade, similar observations have been largely explored in the context of risk and safety management for socio-technical sys-tems, leading to the theory of “Resilience Engineering” (RE) (Flin, 2006; Hollnagel, 2011). Acknowledging the limitations of traditional risk approaches, an effective project management should combine traditional risk management with resilience management, where re-silience is intended as the ability to recover from endogenous or ex-ogenous shocks or disturbances (Patriarca et al., 2018). Based on the assumptions of RE, this research aims to explore the potential benefits of adopting the Functional Resonance Analysis Method (FRAM) (Hollnagel, 2012) for modelling socio-technical properties of projects. The research aims to explain how a RE-based approach may favour an effective resilience management, and conse-quently support the project manager in coping with socio-technical risks.File | Dimensione | Formato | |
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