复杂社会技术系统的数据管理最佳实践:美国矿业安全与健康管理综述

W. P. Rogers, M. G. Nelson, Amy J. Richins, Ashley Hodgson
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引用次数: 1

摘要

社会技术系统在现代工业世界中无处不在。社会技术系统描述了人类如何在各种过程中与技术相互作用。这些系统普遍存在于现代工业环境中,例如经营矿山。安全和健康管理系统(SHMSs)是复杂的社会技术结构,旨在管理和减少职业风险。美国矿业公司正在自愿采用SHMSs,以补充监管安全合规工作。像所有复杂的社会技术系统一样,围绕SHMS有各种各样的方法和采用哲学。许多SHMSs都存在高度冗余,这种冗余以多种方式表现出来:重复的流程、表单、许可和跟踪机制。这些裁员对整个系统产生了严重影响,并吸收了关键的文化和领导力“能量”。最近由犹他大学发起、阿尔法基金会赞助的一项研究正在调查美国15个不同矿区的SHMSs的有效性。已经收集了大量数据,以帮助表征SHMSs的要素并将其对安全结果的影响联系起来。这项研究评估了许多变量。对本文重要的是描述SHMS社会技术方面稳健性的变量。其中两个变量是SHMS在整个系统中的整体集成以及如何管理数据。在此上下文中,数据管理处理捕获、分析和处理系统内数据的方法。此外,系统是围绕受控的数据共享机制集成的。已经发现,在给定的站点中,已经采取了各种各样的方法来将SHMS集成到治理管理哲学中。本文提出了一系列案例研究,为适当的数据管理和SHMSs集成开发了一些特定的最佳实践。
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Data Management Best Practices of Complex Socio-technical Systems: A Review of U.S. Mining Safety and Health Management
Sociotechnical systems are everywhere in the modern industrial world. Sociotechnical systems describe how humans interact with technology throughout a variety of processes. These systems are prevalent in modern industrial settings, such as operating mines. Safety and health management systems (SHMSs) are complex sociotechnical structures designed with the aim of managing and reducing occupational risk. U.S. mining companies are voluntarily adopting SHMSs to supplement regulatory safety compliance efforts. Like all complex sociotechnical systems there are a wide variety of approaches and adoption philosophies around a SHMS. Many SHMSs suffer from high levels of redundancies, which manifest themselves in diverse ways: duplicate processes, forms, permits, and tracking mechanisms. These redundancies have severe impacts on the overall system and absorb critical culture and leadership “energy”. A recent study initiated by the University of Utah and sponsored by the Alpha Foundation is investigating the effectiveness of SHMSs across 15 different U.S. mining sites. A large amount of data has been captured to help characterize elements of SHMSs and correlate their impacts on safety outcomes. Many variables were assessed in the study. Those of importance to this paper are the variables describing the robustness of the sociotechnical aspects of the SHMS. Two such variables are the overall integration of the SHMS within the whole system and how data is managed. Data management in this context deals with the approach to capturing, analyzing, and acting on data within the system. As well, systems are integrated around controlled, data-sharing mechanisms. It has been found that wide variety of approaches has been taken to integrate the SHMS within the governing management philosophy at a given site. A series of case studies is presented that develop some specific best practices for proper data management and integration of SHMSs.
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