What is the fourth industrial revolution?

Technology may revolutionize how we live, work, and interact forever. The transformation’s extent, scope, and complexity will be unprecedented in human history. We have no idea how it might turn out. Nonetheless, one thing is sure: a comprehensive and integrated response is necessary, involving all stakeholders in global politics, from government and business to academia and civil society.

Water and steam power we6re harnessed to mechanize production during the First Industrial Revolution. By harnessing electric power, the Second enabled mass production. In the third, electronic and information technologies were used to automate production.

A fourth Industrial Revolution is forming, building on the third, the digital revolution, which began in the mid-nineteenth century. It is characterized by a technological convergence that blurs the lines between the physical, digital, and biological realms.

In addition to its velocity, scope, and system effect, today’s revolutions are not just continuations of the Third Industrial Revolution but are the start of a new one. The Fourth Industrial Revolution progressed exponentially rather than linearly compared to prior industrial revolutions. Furthermore, it is wreaking havoc in almost every industry across the globe. And given the scope and complexity of these changes, a comprehensive redesign of production, management, and governance systems is in the works.

The potential of billions of people connected by mobile devices, with unparalleled processing power, storage capacity, and knowledge access, is limitless. Emerging technological developments in disciplines including artificial intelligence, robots, the Internet of Things, autonomous cars, 3-D printing, nanotechnology, biotechnology, materials science, energy storage, and quantum computing will multiply these possibilities.

Artificial intelligence is now everywhere, from self-driving vehicles and drones to virtual assistants,KM tools for customer service, chatbots, and investment software. From software used to discover new treatments to algorithms used to anticipate our cultural preferences, AI has made impressive progress in recent years, fuelled by exponential gains in processing power and the availability of massive amounts of data. In the meantime, digital fabrication technologies interact with the biological environment regularly.

Engineers, designers, and architects are merging computational design, additive manufacturing, materials engineering, and synthetic biology to create a symbiosis between microbes, our bodies, the goods we consume, and even the structures we live in.

Knowledge management in 4IR

The new Industry 4.0 paradigm is changing industrial processes, how businesses create value, and how they engage with suppliers and customers. Manufacturing firms may now collect massive volumes of data that they can use to adjust production, generate personalized products and services, and increase operational activities in terms of efficiency, productivity, and flexibility thanks to modern technology. Service firms can use customer data to optimize their processes, thus improving customer interactions by providing a personalized and customized solution for each customer.

New digital skills and competencies (e.g., data management) become vital in this new technology context because they can help new knowledge manufacturing enterprises gain a competitive advantage. Such fresh understanding is dependent not only on the deployment of Industry 4.0 technology but also on relationships with suppliers and customers and personnel competency upgrades.

It is vital to build organizational knowledge to adapt the organization to new conditions. Knowledge should be managed and communicated throughout the company once developed. With the automation of the organization system, artificial intelligence will be required to handle the automated systems that have been established and the knowledge base that has been developed. Furthermore, different models for knowledge management may be used by other organizations.

Still, with the changing organizational contexts, new models are needed to enable knowledge mining, management, and dissemination in the digital era. It is also vital to emphasize security, which is critical because the digital age comes with the difficulty of being able to offer people access to information, perhaps jeopardizing the organization’s privacy and corporate secrets.

As a result, digital transformation is altering client expectations dramatically. Customers place expectations on organizations for developing new products and services and developing novel ways to suit their needs due to an organization’s ability to customize products. Organizations must develop new methods to adapt to changing situations due to rising demands from organizational contexts and rapid changes caused by new technologies.

By adapting, the firm develops organizational knowledge, leading to the long-term development of competitiveness.

Is there a one size fits all criteria for Knowledge Management in today’s era?

The demand to increase organization efficiency and effectiveness necessitates the development of a new knowledge management paradigm.

Organizational management is always on the lookout for new models that will allow them to leverage existing organizational knowledge for growth and development. Parallel to the growing need for knowledge management models in organizations, many new models have emerged, focusing on a particular aspect.

Furthermore, organizational knowledge management methods enable the distribution of existing information across all levels of the business. Which model a company chooses is determined by its needs and existing knowledge management strategy. Although knowledge transfer in an organization is a complex process that assumes that knowledge differs depending on the employee’s career stage and can be divided into individual, group, and organizational.

Inter-organizational relationships that relate to understanding partners, suppliers, competitors, and other stakeholders can be divided into individual, group, administrative, and inter-organizational relationships. As a result, the amount of knowledge is determined by one’s career advancement and the information that can be expressed and tacit.

Conclusion

The organization must establish and apply various knowledge management models to secure its growth and development and long-term viability. Different knowledge management models focus on other aspects. Its type and characteristics determine the model that an organization will use. Strategic knowledge management should be given special attention in a disorganized environment since it might allow the business to adapt to new requirements.

One of the issues that today’s businesses face due to environmental changes is the need to generate new IT-based knowledge. Because organizational knowledge can be a competitive advantage, the necessity of having an information system within an organization that will enable the transmission of gained knowledge and data protection in an integrated information system is continually highlighted.