Risk Based Surveillance as a concept is gaining interest and momentum in the international aviation arena. Its principles are central to the new ICAO Annex 19 and are often the subject of safety conferences and collaboration group publications. Regulatory bodies and industry groups welcome the concept recognising the need to move towards risk-based approaches and data-driven decisions. We are however in an exploratory phase where many States are devising strategies to move from prescriptive regulation to outcome-driven rules, whilst others are trialling performance based principles in their surveillance programmes.
Effective safety management as described in Annex 19 requires that information is systematically collected, analysed and monitored to identify risks and measure progress against outcomes. Data is pivotal in this process. As a result the desire to identify useful and relevant data sources is becoming increasingly important. To be positioned to make decisions based on intelligence, we need to expand the existing knowledge spectrum and enrich the current evidence base. Inevitably, to assemble an integrated total system picture we will need to look beyond the conventional compliance and occurrence reporting data, and include broad type of information alongside expert judgement.
To enable development of a total risk picture, the breadth of data needs to encompass both hard data, such as accident reports and compliance data, and softer cultural and organisational indicators. Such elements may include: organisation health checks, resource and staffing levels, compliance and complexity of the aviation system and SMS maturity.
This turns towards data acquisition and information gathering is facilitated and expedited by current technology. The increase in computing power and the widespread use of the internet promote sharing, exchange and visualisation of information and data in a rapid straightforward manner.
Whilst advances in information technology can have catalytic effects in enhancing data, there is a danger of cultivating a data farming culture, utilising data that is convenient as opposed to being important or relevant. Regulators should carefully govern the use of data to match the scope and the nature of their role. They should tailor their data feeds according to the size, maturity, and complexity of the aviation industry they regulate. It is unlikely that a small Aviation Authority would have the same requirements in terms of data volume, granularity, resource, capacity or IT system sophistication as a large Aviation Authority across different organisations and industry
Irrespective of the regulatory scope, the challenges in handling the volume and diversity of data still remain. We need to be best prepared and equipped – both in terms of technical expertise and technological means – to store, filter, clean and generally manage and process the gathered information. Failure to recognise and address the limitations and the idiosyncrasies of the collected data will result in flawed analysis outputs, and consequently to misleading conclusions.
As considerable quantities of data are becoming accessible, the risk of inadequate data management compromising the delivery of the required outcomes is also growing. The key to success is to identify and account for the different data attributes when designing flexible processes and tools to administer the data streams.
A consistent systematic data management approach is required involving categorisation, harmonisation and consolidation of multiple data sources onto a common platform. This enables reliable processing, analysis and monitoring. Analysts then have access to a wide range of data where they can aggregate, compare and calculate metrics to measure and track safety performance. Safety and key performance (leading and lagging) indicators are good examples of analysed data. They can be used as monitoring metrics to measure effectiveness of actions and, when considered in combination with other indicators, can provide a broader and more comprehensive picture.
It is important that performance indicators and other outputs of data analysis are combined with expert judgement to generate compelling evidence. The subject matter experts, using their expertise and field experience, are in a position to verify and complement the outputs derived from data analysis. Such a process results in developing thorough, balanced views on issues that matter, ultimately creating pictures of intelligence which become the basis of useful conclusions and informed decisions. When these elements are combined they set the foundations for a proactive approach in managing risk and a performance based, data-driven regulatory system.
Data is a key enabler of Risk Based Surveillance (RBS). Aviation Authorities aspiring to embark on RBS should establish data management approaches suitable to their needs and regulatory ambitions.
