Knowledge Management
Knowledge Management (KM) is a multidisciplinary practice spanning fields such as information systems and business administration. It has many applications in industry. Knowledge Management focuses on identifying, employing, storing, and distributing available resources on a project to generate expertise, insight, and information during the development of a product, service, or model. The process of KM incorporates elements of knowledge acquisition, its creation, and its transition into the information stores of society (Phoha, 2001). Studies indicate that the effects of a changing, diverse, and mobile workforce result in companies having an increasingly difficult time retaining knowledgeable employees (Ryan, 2000). The integration of Human Factors in Knowledge Management entails capturing and retrieving information relevant to human capabilities and limitations to build new knowledge or extend current knowledge. This process is inextricably bound and inseparable from human cognition, introducing all sorts of bias. It is a classic problem of psychology, where the cognitive agent must study its own workings, complete with biases, limitations, and perceptual qualities.
Therefore, the management of knowledge occurs within a biased behavioral, cultural, and personal context. This context may vary greatly between individuals. Past research in KM has revealed the importance of considering human cognitive and physical factors when designing knowledge management systems. Human factors practitioners study and apply knowledge relative to human physical, cognitive, and sensory capabilities and limitations to design better products, processes and interfaces (Karwowski, 2006a). KM is especially important in situations where tacit (as opposed to implicit) knowledge exists. Tacit knowledge is not consciously known or recallable by a subject performing a task (he or she “just knows how to do it”), while implicit knowledge is knowledge which is easily transferred by the subject to others, and thus, can be easily documented (Alavi & Leidner, 2001). The advantages of adopting KM practices include:
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Rapid formation of subjective, objective, and empirical knowledge
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Knowledge integration
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Accessibility and conductivity to collaborative problem solving
Human Systems Integration (HSI) is pertinent to systems engineering, specifically, the human component of every system. HSI aims to prevent system designs that do not adequately consider human capabilities and limitations. Thus, HSI is the choice interdisciplinary process for integrating human capabilities and limitations within and across all system elements, i.e. an essential enabler to systems engineering practice. The goal of HSI is to optimize total system performance while accommodating both select and general characteristics of the end user population that will operate, maintain, and support the system in an effort to minimize overall system lifecycle costs and enhance human-system compatibility (Folds et al., 2008). Throughout system design, development, fielding, sustainment, and retirement processes, HSI experts work to ensure the consideration and accommodation of human capabilities and limitations. Within systems engineering, the human is recognized as an integral element of each system through the HSI component, which ensures that human factors have a prominent place throughout the total system lifecycle. Good design practices include the human element within requirements, reliability, and maintainability processes.
The attention to HSI in system development programs have resulted in hundreds of human-centered design improvements and enhanced human-system compatibility. Efforts were concentrated on maximizing total system performance through improvements in workload management, safety, maintenance, and reliability. These efforts resulted in billions of dollars saved and the prevention of hundreds of possible system related safety issues (Booher and Minninger, 2003).
Karwowski (2000) stated that system-human compatibility should be considered at all levels, including physical, perceptual, cognitive, emotional, social, organizational, and environmental considerations. This requires quantification of the inputs and outputs that characterize a set of system-human interactions. Karwowski (2000) stated “at the present time, no universal matrix for measurement of such compatibility exists”. A new science deemed ‘Symvatology’ has been introduced based on investigations of human-system compatibility. Symvatology was proposed to help to advance the progress of the ergonomics discipline by providing a methodology for system design for compatibility.
The Human Factors Engineering (HFE) field of study is concerned with studying human capabilities and limitations to improve work performance, safety, and efficiency (Dempsey et al., 2006) (Karwowski, 2006). The array of work human factors and ergonomics professionals perform has been discussed in detail by Karwowski (2005; 2006) and Salvendy (2006). The primary focus for HFE is to consider human capabilities and limitations within system design to achieve optimal levels of total system performance across factors such as operation, maintenance, repair, and disposal. Comprehensive task analysis are utilized by HFE to help define system functions and, in turn, allocate those functions to meet system requirements.