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Over the past decade, the rates of serious injuries and fatalities (SIFs) have declined at a much slower rate than less-serious workplace injuries. This problem should raise serious questions and implications for safety leaders at all organizational levels, from the first level of supervision to the senior-most executive and board member, and to the labor leader and government regulator.
Seven multinational corporations sought to develop a better understanding of the causes and correlates of SIFs. These organizations submitted 2 years of incident data related to SIFs, less-serious recordable injuries and near-hits. In total, these data included 1,028 event cases representing approximately 1 million global workers and contractors. This research will ultimately lead to a better understanding of SIF causes and the establishment of new paradigms for SIF prevention.
The Pattern Is Evident
Leaders who closely follow lagging and leading safety performance indicators have seen the national and global data (Figure 1, p. 36) and they know it elicits questions about the effectiveness of current safety management systems (BLS). Nonfatal recordable incidents in the U.S. have declined steadily over the past 2 decades. The rate of nonfatal recordable injuries declined 51% in the past 15 years and 34% just in the past 10. While the fatality rate has also declined, it has been much less dramatic: only 12.5% in the past 10 years and 25.5% in the past 15 (BLS). Data pulled from a sampling of countries with data available through the International Labor Organization (2009) suggest similar experience in many countries (Figure 2, p. 36).
Even at a more granular level, this same pattern is evident. Data from International Association of Oil and Gas Producers (2012) shows similar, unparallel levels of rate reduction among the contractor population across all business functions (Figure 3, p. 37). Many organizations have observed this phenomenon among their own population. For example, Figure 4 (p. 37) presents data from one global organization (identity protected).This article aims to provide insight into factors behind these trends, approaches for data analysis and new conclusions regarding SIF prevention.
Abstract The use of data-driven cognitive solutions represents a major advancement in the management of oil and gas operations. Tools that integrate concepts from disciplines such as informatics, machine learning and predictive analytics can offer powerful solutions to allow improvements in the safety, efficiency and integrity of oil and gas operations. We discuss data systems that enhance traditional, human-based monitoring systems, with the aim of approaching risk-free operations. Ethical decision-making is critical in the management of oil and gas operations. Digital data solutions effectively compensate for the limitations of human-based decision processes when confronted with data overload and multi-dimensional data systems. Increased adoption of data gathering, automation, data analytics and advanced computer-aided process control has already made its mark in the industry. Examples have emerged as for how in areas such as artificial lift, pipeline transportation and offshore operations, these data analytics techniques have helped in failure detection and prediction and smart management of such operations. The incorporation of data-intensive decision-making and smart risk management solutions have resulted in a step change in the improvement of the ethical foundation and the base underlying the industry. Moreover, these digital tools and machine-based cognitive processes for risk-avoidance solutions can help to build and restore the public's faith and trust in the industry. We also discuss how relying on digital solutions alone can have its limitations when it comes to professional ethics and responsibilities.
The construction industry continues to experience a high number of workplace injuries and fatalities as compared to other U.S. industrial sectors. Although this number has been declining over the past 20 years, the rate of decrease has been slowing, and is nearly stagnant in recent years (ILO, 2003). As an industry, construction has averaged 1,010 fatalities per year, indicating that much improvement is still needed to achieve zero injuries, illnesses and fatalities (BLS, 2013a). One such improvement can be found in the collection and measurement of safety data.
Historically, the construction industry has defined safety performance through the measurement and assessment of lagging indicators including injuries, illnesses and fatalities. These lagging indicators are required by OSHA to assess the state of construction safety (BLS, 2013a). One major limitation of assessing safety performance using lagging indicators is that incidents must occur before hazards or unsafe behavior can be identified and mitigated.
Leading indicators are an alternative form of safety metrics that proactively assess safety performance by gauging processes, activities and conditions that define performance and can predict future results (Hinze, Thurman & Wehle, 2013). One such leading indicator is a near-hit, defined as an incident in which no property damage or personal injury occur, but could have occurred given a slight shift in time or position (BLS, 2013a). The major advantage of measuring leading indicators such as near-hits is that data can be collected and analyzed without requiring an injury to occur.
This article presents research products in the development, deployment and effectiveness of using a near-hit management program on construction sites. The authors gathered the information through personal experience, formal research in the Construction Industry Institutes Research Team 301: Using Near Misses to Enhance Safety Performance, and through secondary research and literature review. The goals of this article are to present the near-hit management program and demonstrate its quantitative effect and proof of effectiveness when applied to a multibillion dollar construction project, to encourage the use of this methodology in the field.
This paper was prepared for presentation at the 1999 SPE Offshore Europe Conference held in Aberdeen, Scotland, 7–9 September 1999.
According to the U.S. Bureau of Labor Statistics, “Nearly 3 million nonfatal workplace injuries and illnesses were reported in 2012, with more than 50% involving days away from work, job transfer or restriction.” Lone worker safety is and should be of paramount concern to lone working employees, as it is their safety at stake, and also to organizations who face their own risks and level of liability. In fact, it has been documented that an organization need not have a workplace violence incident to experience its effects, but rather, that in some cases, the mere threat of workplace violence can create unneeded financial outlay. That said, can any organization really afford NOT to protect their staff?
Introduction to Lone Worker Protection
The term ‘lone worker’ may not be a familiar one to you but as workforces for most businesses become more mobile, it’s a term you will likely need to consider if health and safety is your remit. The term ‘lone worker’ was coined in 1986 following the disappearance during work hours of a London, UK based realtor, Suzy Lamplugh. Suzy, like many realtors was called to an appointment to show a potential client a property that was for sale. She disappeared that day and has never been found, she was legally declared dead in 1993. In Suzy’s memory, her parents set up a charitable trust www.suzylamplugh.org to promote good practices relating to personal safety. Advocating better awareness of risks to lone working employees has been a key focus for them over the past 25 years.
There are a number of definitions for ‘lone worker’ but the simple default I tend to use is as follows:
‘A lone worker is any employee who is operating out of sight or sound of other employees’.
Most companies these days will have lone working staff. You may refer to them as remote workers, field staff or road warriors but lone workers can also include those in office or campus environments or more industrial or laboratory type environments. With the advent of mobile technologies such as tablet devices and smartphones, more and more of us can count ourselves as lone workers. It is also important to note that many companies will have employees who are not full-time lone workers, but rather, who work independently away from others during a portion of their day and are exposed to risk during that time.