The Application, Utility and Acceptability of Data Analytics in Safety Risk Management of Airline Operations



Published Jun 29, 2022
Washington Mhangami Stephen King David Barry


One area the aviation industry is grappling with is the quantification of the probability of occurrence of safety incidents. Currently, aviation professionals involved in safety risk management mostly rely on collective experience to determine probability of incident occurrences and apply it to the International Civil Aviation Organisation (ICAO) matrix or equivalent to evaluate the risk. A number of limitations linked to the use of risk matrices will be explored in this paper. It is the aim of this paper to explore statistical methods that can be used to determine the probability of safety occurrences and come up with an algorithm that can be used by airlines using available safety data. The novelty of this research is that it combines the exploration of use of statistical techniques to quantitatively assess risk using Flight Data Monitoring (FDM) and other data, with acceptability of Safety Risk Management (SRM) data analytics by operational personnel. The paper also explores the contributory factors leading to the reluctance of operational personnel to use data analytics to inform their risk assessments despite the increasing availability of operational data and advancement in technology.

How to Cite

Mhangami, W., King, S., & Barry, D. (2022). The Application, Utility and Acceptability of Data Analytics in Safety Risk Management of Airline Operations. PHM Society European Conference, 7(1), 580–582.
Abstract 991 | PDF Downloads 310



Airline operational safety, Flight data monitoring, Statistical techniques

Barry, D. J. (2021). Estimating Runway Veer-off Risk Using a Bayesian Network with Flight Data. Transportation Research Part C: Emerging Technologies 128:103180. doi: 10.1016/j.trc.2021.103180
Civil Aviation Authority (CAA) (2013). CAP 739 - Flight Data Monitoring. Available at: (Accessed: 8 June 2022).
Cox, L.A. (2008). What’s wrong with risk matrices? Risk Analysis. 28 (2), 497–512 doi: 10.1111/j.1539-6924.2008.01030.x.
Hubbard, D.W. (2009). The failure of risk management. Hoboken, NJ: John Wiley & Sons, Inc
International Civil Aviation Organisation (ICAO) (2018). Safety Management Manual (SMM). 4th ed. International Civil Aviation Organisation.
Li, L., Hansman, R.J., Palacios, R., & Welsch, R. (2016). Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring. Transportation Research Part C: Emerging. Technologies. 64 (Supplement C), 45–57.
Malatji,W.R., Van Eck,R.,& Zuva,T. (2020) Understanding the Usage, Modifications, Limitations and Criticisms of Technology Acceptance Model (TAM). Advances in Science, Technology and Engineering Systems Journal, vol.5, no. 6, 2020, pp.113-17. doi:10.25046/aj050612
Rezaei, M., & Borjalilu, N. (2018). A dynamic risk assessment modeling based on fuzzy ANP for safety management systems. Aviation, 22(4), 143-155. doi:10.3846/aviation.2018.6983
Venkatesh, V., & Hillol, B. (2008). ‘Technology Acceptance Model 3 and a Research Agenda on Interventions’. Decision Sciences 39(2):273–315. doi: 10.1111/j.1540-5915.2008
Doctoral Symposium