What we can do

Full Aviation Human Factors Training
Checklist development to provide a flexible structure for enhanced communication and both normal and non-normal event management
Bow-tie Risk Analysis and Mitigation
All services available as one-off deliverables or as iterative development projects that maximise the improvements that are generated by continuous data analysis

Optimised Decision Making

The world of aviation has been dealing with the issues of variability in human decision making for the last 50 years. Stemming from aircraft accident analysis, Aviation Human Factors training (Team Resource Management) has been used to minimise the risk from the human element in dealing with time critical situations on the flight deck. That is why commercial aviation has the best safety record of any form of transport. These techniques have been employed in arenas from spaceflight to frontline medicine, but have been slow to be adopted elsewhere.

Recent research into this variability has provided a more detailed understanding and named the key culprits: Cognitive Bias and Noise. This has allowed the development of more nuanced techniques to permit increased effectiveness in tackling this variability, not only within aviation but across all industries that rely on human decisions.

Cogntive Bias

What is Cogntive Bias? The term was introduced by Amos Tversky and Daniel Kahneman in 1974 to describe systematic errors in human thinking that arise when we try and simplify the highly complex world around us. These subconcious errors occur in memory, attention and sensory perception which affect the accuracy and rationaltiy of our decisions making. Research has shown (Orzan et al., 2012) that the human mind can only process less than 0.001% of all the bits of information we receive per second - which ultimately requires us to make shortcuts in how we build our internal model of the world. These 'shortcuts' or 'heuristics' increase the speed with which we can operate but are prone to errors. In some situations, these errors are easy to manage and can be taken lightly. However, in time critical or safety related industries they can lead to catastrophic results, despite that Cognitive Bias is well undertsood and broadly predictable.

Noise

Noise is the 'Unwanted Variability in Professional Judgements' as defined by Prof. Olivier Sibony, an academic and author in Strategic Thinking and Decision Processes. Several studies have shown that, even when the variables or cases are identical, professionals often contradict their previous judgements and make decisions that differ widely from their peers, even when alledgedly following rules or guidelines. This variability gives rise to sub-optimal outcomes in a range of discisplines, which can result in loss of reputation and revenue. In aviation, it can result in much worse.

Team Resource Management

Although the terms of Cognitive Bias and Noise are relatievly modern, aviation has been aware of the risks associated with inconsistent Decision Making since the advent of flight. David Beaty, an RAF and BOAC pilot, is considered to be the pioneer of 'Human Factors' in aviaiton, publishing his first book on the subject in 1969. Since then, the industry has been refining the technqiues used to minimse the risks caused by both Bias and Noise in the flight deck. This has been called Crew Resource Management (CRM) and has since been adapted for wider adoption as Team Resource Management (TRM).

Team Resource Management is defined as a team-oriented concept of fault management that originated in the aviation industry but is ideally suited to other dynamic, high-risk and high-stress environments.

This system is based on the goal of improving outcomes through acknowledgement of human contributions to fault management and the implementation of effective strategies for resource utilisation.

TRM solutions are intended to nurture intrinsic social, interpersonal and cognitive skills within a team and combine them with technical protocols to produce an optimised management of non-normal situations.

However, the key to the technique's effectiveness are the iterative improvements achieved from each activation of the protocol. Data captured during this process is fed back into the design to ensure the opportunity to learn and improve is never wasted.