Answer

Context/Introduction

One of the industries which has historically experienced devastating accidents is the oil and gas industry. In specific, according to the UK Health and Safety Executive’s (HSE), the occupational hygiene data for the oil and gas sector reveals that workers in such industries are exposed to high risks which highly endanger their health and safety (Azizi, 2016, p.23). A majority of the catastrophic accidents experienced in the industry have been attributed to both organisational and operational errors related to human factors. For instance, according to Theophilus et al. (2017, p.168), the 1984 Bhopal toxic release was one of the most catastrophic industrial releases which resulted in not only the injury of 200,000 people but also the death of close to 6,000 people. Upon investigations of the catastrophe, it was established that human factor failings were, directly and indirectly, responsible for the accidents. However, Tamim et al. (2017, p.256) assert that a majority of the instruments and tools deployed in the investigations of the human factor errors to prevent such accidents were not only ineffective but also not robust. As a result, it is vital to move beyond the immediate personnel and focus on factors such as the organisational failures, unsafe acts, and unsafe provisions which might result in the catastrophes.

One of the mechanisms which have been used to effectively mine data relating to the human factor failings which result in accidents is the oil and gas industry is the human factors analysis and classification system for the oil and gas industry (HFACS-OGI). In specific, according to Xi et al. (2010, p.1499), the HFACS was first developed by both Dr Scott Shappell and Dr Doug Wiegman and first deployed in the aviation industry. More specifically, Azizi (2016, p.22) posits that the US Air Force first used it in the quest to investigate and analyse the various human factors which resulted in errors in the aviation industry. The basis for the HFACS is James Reason’s Swiss cheese model (Cohen, Wiegmann, & Shappell, 2015, p.728). The primary purpose of HFACS is to assist in the investigation process and hence foster target training and prevention efforts. With the use of HFACS, investigators are empowered to systematic identify both active and latent failures which leads to the accident (Theophilus et al., 2017, p.167). The principal aim of HFACS is not to apportion blame on any of the human factors in the organisation but rather to gain an in-depth understanding of the causal factors which culminated into an accident.

The use of HFACS is effective in the assessment of the various human factors; especially as they relate to an organisation’s safety culture, management commitment, and an entity’s erosive drift. Theophilus et al. (2017, p.168) add that entities have deployed HFACS to evaluate the technical failures which arise from the ageing equipment and the lack of knowledge and competency by the operators. In the oil and gas industry, HFACS focuses on the prevention of catastrophic accidents especially fires and explosions and toxic releases arising (Xi et al., 2010, p.1500). The HFACS framework describes human errors based on four levels of failures. These include the unsafe actions of the operators, preconditions of any hazardous factors, unsafe supervision, and organisational influences (Miranda, 2018, p.763). Theoretically, at least a failure at either of the four levels will lead to an adverse event. However, Tamim et al. (2017, p.257) claim that if an act leading to the adverse event is corrected, then the adverse event will be prevented. The original HFACS was modified to fit within the oil and gas industry. The modification and changes to the original HFACS involved the prevention of catastrophic accidents, especially toxic releases which are related to the Control of Major Accident Hazards (COMAH) Regulations (1999).

Research demonstrates that the original HFACS has been changed to fit in the operations and systems of the oil and gas industry. However, only a few studies have focused on the examination of the various pieces of information in the HSE database which reflect on the multiple ways in which HFACS can be used in the mining of data related to human factors responsible for the accidents and catastrophes in the oil and gas industry. Many researchers have sought to establish the various ways in which HFACS can be used in the identification of the human factor errors and thus mechanisms and strategies adopted to prevent such errors. Cohen, Wiegmann, and Shappell (2015, p.23) add that the HFACS models which have been adopted have not explicitly been a perfect fit for the oil and gas industry. As such, deploying HFACS-OGI will be valuable data mining of the human factors which have resulted in the accidents and catastrophes which have occurred in the oil and gas sector (Theophilus et al., 2017, p.169). The HSE National Exposure Database (NEDB) can be a vital tool which can be deployed to ensure that organisations can get crucial data on how various human factors result in failings in systems in the oil and gas industry. Conducting a study in the HSE database is critical to establishing the impact of the HFACS-OGI Model in the identification of the various human factor errors and hence adopting appropriate preventive mechanisms to prevent adverse events arising from the errors.

Research Questions

The proposed study will seek to answer the following research questions: –

1. What are the specific human factors responsible for adverse events such as accidents, toxic releases, and fires in the oil and gas industry?
2. What mechanisms have been commonly used in the identification of the human factors in the oil and gas industry?

• What is the overall effectiveness of the use of HFACS-OGI Model in the reduction of accidents and catastrophic events in the oil and gas industry?

Aims and Objectives

The proposed research will aim at achieving the following goals and objectives: –

1. To explore the human factors responsible for adverse events such as accidents, toxic releases, and fires in the oil and gas industry.
2. To evaluate the impact of HFACS-OGI Model in the data mining of human factors based on the HSE database.

• To assess the overall effectiveness of the use of HFACS-OGI Model in the reduction of accidents and catastrophic events in the oil and gas industry

Methodology

The proposed research will deploy a quantitative methodology. In specific, a quantitative research method implements objective measurements as well as of statistics and numerical analysis of data collected via the use of computational techniques. The use of a quantitative methodology is based on various advantages/benefits. One of those is that since the method relies heavily on primary data, then its findings are reliable and credible. Additionally, according to Muijs (2010), it is hard to argue with the results of the quantitative study because it relies on numerical and unbiased data. A case study design will be used with a particular focus on the HSE database. A case study design aims to identify the various human factors using HFACS-OGI based on the case and provide focused solutions/interventions (Yin, 2017, p.56). One of the rationales behind the choice of a case study design is that it allows for a more in-depth and comprehensive collection of information as it only focuses on one case.

Data Collection

            In the proposed research, data will be collected via the examination of the various pieces of primary information contained in the HSE database. Notably, the database contains information related to the multiple exposures to risk in different industries and sectors. The data associated with the various catastrophes in the oil and gas sector and the human factors which cause such failings will be collected. The use of secondary data was chosen because of multiple benefits. One of those is that it will be less costly for the researcher to rely on data from a single source compared to collecting primary data which is not only expensive but also time-consuming (Runeson et al., 2012, p.67).

Data Analysis

            Data collected from the HSE database will be analysed using IBM’s Statistical Package for the Social Sciences (SPSS). In specific, the data mined on human factors causing accidents and catastrophes will be analysed to establish the key areas of failure and errors and hence ensure effective decision making as to the efficiency of  HFACS-OGI. The choice of SPSS is pegged on its ability to give the researcher advanced tools which can enable the efficient and effective management and analysis of data (Muijs, 2010, p.98). Additionally, SPSS is easy to learn and use as it includes a full range of data, management systems, and even editing tools. The in-depth statistical capabilities in SPSS enables a researcher to conduct a complete plotting, reporting, and presentation of data. The SPSS will be used to analyze the common human factors responsible for adverse events in the oil and gas industry based on HSE data. Additionally, the primary mechanisms; apart from HFACS-OGI, which are used by organizations to mine data as to the huamn factors will be analyzed. Finally, SPSS will be vital in assesing the effectiveness of HFACS-OGI through the analysis of the times that it has prevented adverse events against when it has not.