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“Risk management involves establishing an appropriate infrastructure and culture and applying a logical and systematic method of establishing the context, identifying, analyzing, evaluating, treating, monitoring and communicating risks associated with any activity, function or process in a way that will enable organizations to minimize losses and maximize gains” (AS/NZS 4360-2004)
The system safeguard (control mechanism) linked to the level one trajectory trigger

operational fatigue risk and fatigue countermeasure application and manage tactical and strategic change (organisational learning and memory) as part of a continuous improvement cycle within an SMS framework. To compete effectively easyJet as a low cost airline seeks safe optimisation and efficiencies within its rostering practices and, therefore have to know the boundaries within which they can operate safely (operating close to the limits set by the regulatory authorities -in flight time limitations for example). Prompted by a serious fatigue-related incident, a study was undertaken to establish the parameters of fatigue within the existing roster system (Stewart & Abboud, 2005).
S. Stewart, F. Koornneef, R. Akselsson, and C. Turner  - HILAS 2009
1.13 System Integrated Risk Assessment (SIRA)
System Integrated Risk Assessment (SIRA) (Figure 8) is easyJet’s risk management framework (Stewart et al, 2006; HILAS SMS Book 3, Ch 4: Stewart et al, 2009). It is driven by a clear commercial requirement to manage the operational risks the airline faces in a proactive manner.  Starting with a range of event inputs (from individual errors to commercial threats), a ‘system sensory net’ gathers a wide range of technical, human performance and system data which is then fed into an intelligence process, classifying and analysing causal patterns. In turn this drives decision-making, intervention design, risk mitigation and monitoring. The cycle then continues.

This model was applied to the easyJet fatigue related risk problem. A very wide range of evidence was collected over an extended period – not only routine technical and human performance data, but also specific surveys and additional in-flight performance measures were sampled (Stewart & Abboud, 2005a&b). All this data was then analysed with the benefit of a fatigue and rostering model (Fatigue Audit Interdyne: FAID, Fletcher & Dawson, 1998) which helped identify areas of vulnerability due to human circadian periodicity. This evidence clearly identified high-risk areas (e.g., transitions from early to late shifts and insufficient post duty rest and recovery). This then enabled the redesign to the rostering system to eliminate these problems. This required a special derogation from
S. Stewart, F. Koornneef, R. Akselsson, and C. Turner  - HILAS 2009
the Civil Aviation Authority’s Flight-time Limitations regulations. The new rostering system was justified and approved in the light of the evidence presented. The revised rostering schedule was implemented and the monitoring continued. The evidence then demonstrated a significant improvement on all safety related indices. Also important from the point of view of implementation and acceptance of the new roster system was that the new system was both more popular with the pilots and delivered greater operability to the company. Section 1.9 discussed this from the perspective of the evolution from a single roster study to a strategic change process of monitoring and continuous improvement with an increasing focus in the background and contextual
　
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