The exponential growth of digital data generation and consumption in the past decade has ignited new discussions about the relevance and impact of knowledge management (KM) on individuals and businesses. This chapter presents a literature review examining knowledge management and systems of learning as well as some of the critical factors to be considered in the design, implementation, and evaluation of metrics for KM implementation success. It highlights the role of leadership and the importance of valuing knowledge workers for effective KM and KMS practices, and the design of knowledge metrics focused on learning and growth within the scope of the balanced scorecard framework and the possibilities of a Web 4.0 data processing environment in a competitive globalized market.
TopIntroduction
In an era driven by data and the ability to use information to produce and share knowledge, businesses are significantly impacted by massive data production, the demand for data processing and use, and professionals with the skills to competitively manage data in organizations. Unquestionably, society has shifted from a form of production based on material goods and services, which is based on a concept that involves the logistical distribution and delivery of goods and services to create intellectual capital, defined by many researchers as the knowledge economy (Housel and Bell, 2001). This approach to capitalism attributed economic power to the core existence and understanding of society, the exploitation of labor, and the historically contingent strategic nature of class conflict in production and exchange (Skillman, 1996).
Skillman (1996) argues that “capitalist exploitation is instead best understood in terms of Marx’s historical-materialist theory of profit, which depicts capitalist production relations as a historically contingent strategic response to evolving conditions of class conflict over the creation and distribution of surplus product.” (p. 1). Carchedi (2005) contends that modern capitalism is based on the development of a Marxist theory of production of knowledge, where the theoretical structure accommodates mental production. The idea of production technologies and the future of work often parallel advances in technology, the creation of new machines, and the rise of artificial intelligence (Rifkin, 1995; Karakilic, 2020) which prompts recurring questions about whether machines will ever replace humans in the workplace.
In conjunction with the change in production processes progressively moving from physical labor to the use of intellect, the value of knowledge becomes a key factor in organizations, and the measurement of it becomes critical for performance evaluation and profitability. The notion of intellectual capital and collective intelligence is not new; however, the intensified advance in the production, adoption, and use of smart machines (artificial intelligence, machine learning, IoT, and algorithms, for example) imposes the urge to rethink knowledge production. Pettersen (2018) defends that “knowledge work can be assisted and enhanced, but not replaced, by computers” (p. 8).
Currently, the discussion around data access is marked by the evolution of the internet and how it brought a new paradigm to the communication process on an unimaginable global scale. It is imperative to understand the principles and impact of the evolution of the web as we strive to understand both data management and knowledge management and the impact they have on social and business activities. This insight allows effective creation of practices, policies, and an organizational culture that is designed to allow the rapid flow of information and knowledge in organizations, which impacts efficiency and innovation.
In that context, Aghaei, Nematbakhsh, and Farsani (2012) discuss the evolution of the internet, which the authors define as the “techno-social system that enhances human cognition, communication, and co-operation” (p.1). The authors highlight the evolution from Web 1.0, a readable platform where users had access to content but not the ability to change it, to Web 2.0 where the format was mostly read-write with a community centered approach, and the ability to share content. Then came Web 3.0, which introduced platforms for live-streams, smart applications, and more significant user engagement. Web 4.0, known as the symbiotic web, is an evolving current concept that considers self-learning systems and relates to the interaction between man and machine. (Almeida, 2017).
This chapter will discuss some critical factors for successful knowledge management implementation and metrics, from conceptualizing knowledge management and knowledge management systems to how an organizational culture focused on effective learning innovation will enable the use of performance metrics to track and measure the value of knowledge to organizations that increasingly demand the promotion of a knowledge-based approach to productivity.