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Interestingly, another study done on oil and gas sector is “known as three multiple regression models respectively that capture the forecast mechanism of yearly total observation (YTO) of Man-Hour Worked for accident, man-hour lost for cost reduction, maintenance trend and Cost Reduction linear Programming (LP) Model at Kaduna Refining and Petroleum Company (KRPC)”(Oladejo and Macauley,2014). These methods were discussed and applied using collated data to identify employee turnover and absenteeism from active work due to occupational health and safety issues at the workplace. Data from responsible departments such as (Oladejo and Macauley, 2014) “Safety and Environments Department (HSED, Planning Budget and Monitoring Department (PBMD) of KRPC” were generated, gathered, documented and categorized for investigation. Nevertheless, multiple regression model was favoured and ranged best option in this study to do forecasting on annual surveillance (Oladejo and Macauley, 2014) “man-hour worked as a result of accident in the system, man-hour lost as a result of accident which will assist the management in putting resources in place that will reduce cost in the system and maintenance models that will inform progressive routine maintenance plan in the system”. System of cost reduction by predicting yearly total observation using multiple regression models to find out about total number of man-hour worked because of industrial accident in oil and gas industry and exclusively identify preservation and significantly real time in terms of man-hour lost for cost reduction. All calculation methods used to determine avoidable turnover directly impact an organisation when health and safety issues were not taken seriously and addressed thoroughly accordingly. The negative result business face due to injury, there was a failure of employees to report to work when they were scheduled to do so. Occasionally the lost time injury, a severe job-related injury that causes an employee to be absent from the job, further affect the work output, productivity decrease and strategic business objectives not met as scheduled. The alignment of all these three case studies will further be elaborated in a similar case experienced in the petroleum sector and discussed in Papua New Guinea Liquefied Natural Gas (PNG LNG) context.

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