Since first gaining significant traction from the Government and the private sector, Knowledge Management has evolved substantially. New mental models, new methodologies and technologies are deciding the relevance of Knowledge Management’s relevance. So what does the future hold for the knowledge base cluster of capabilities?
Benefits of a Knowledge Base
Since it has already been demonstrated over the past twenty years, Knowledge Management confers a range of benefits to organizations. These benefits fall into five broad categories:
- KM helps organizations to share valuable insights
- Reduce call ticket numbers by empowering self-serve
- Reduce operating costs through continuous productivity gains
- Facilitate access to scarce expertise and knowledge globally
- Reduce training time for employees
Based on these benefits, knowledge Management’s core attraction for organizations can be summarized as:
“In a time of disruptive innovations across an industry, a firm’s competitive advantage depends more than ever on its knowledge: on what it knows, how it uses what it knows, and how fast it can acquire new knowledge.”
As large areas of the global trade in goods and services migrate to knowledge-based economies, the increased competition is driving the quest for continuous innovation.
A knowledge base sits at the heart of any innovation effort. When innovation is increasingly the only sustainable competitive advantage, that innovation effort is largely determined by how effective the enterprise is at creating, sharing, managing and utilizing knowledge.
The Organic Age of Knowledge Management
A new wave of Knowledge Management based on complexity theory and the idea of organizations as complex adaptive entities where learning is a continuous cycle has effectively replaced our machine-based ideas of society, organizations, communities and other institutions.
This outmoded mechanistic perspective struggled to provide meaningful context around knowledge parameters and had limited real life impact. By contrast, the organic perspective explores complex dynamics that rely on probabilities rather than certainties, on sense-making rather than reduction-ism, on facilitating interaction and collaboration of social entities and human beings rather than command and control.
In this scenario, web-based knowledge base software has emerged as the confluence between knowledge management’s twin enablers; change management and system transformation.
System improvement and change management in return have recognized that the most effective way to impact complex social systems is to by gaining an understanding of the system and its interactions and dynamics as a whole, thus identifying opportunities, possibilities and potentials.
The Future Is Mobile (Almost)
Mobile technology has become a primary means of accessing the Internet for both personal and professional reasons. Mobile devices save both money and time, and as a result, mobile technology and web-based knowledge base software are increasingly inseparable. Geographically dispersed or embedded staff requires access to an organization’s knowledge management system while they’re on the go, or working remotely. Vendors are wiring their social intranet software with smartphones and tablets to display options in response to this demand.
Increasingly Social
Social media has revolutionized the way we use the Internet. The emergence of inbound marketing to attract an audience and promote brands, products and services on social media channels such as Instagram, Facebook and Twitter has proven to be highly effective and extremely easy to use. As a result, the “social” is being increasingly integrated with web-based knowledge base software. As social media elements are blended with knowledge base software, barriers to collaboration and sharing are coming down. Staff can communicate more intuitively and engage more effectively, as social elements are increasingly “second nature.”
Technology Focus
Emerging technology will continue to reshape and underpin the future face of Knowledge Management. Breakthrough technologies focus on four dimensions:
- Cognitive technology
- Robotics
- Artificial Intelligence
- 3D printing
Cognitive Technology & Robotics: Developments such as IBM´s Watson integrate natural language processing and machine learning to generate insights from a fusion of data sources. These technologies merge natural language understanding with statistical analysis of epic volumes of unstructured content via artificial intelligence.
3D Printing: 3D printing has the potential to totally transform how we share and co-create tacit knowledge transfer. For example, geographically dispersed team members can collaborate & co-create prototypes remotely as they share experiences and information. This means that you can touch and feel the outcome of the shared knowledge, which originated and was modified in a knowledge base.
Virtual Reality: Not only can we facilitate the transfer of tacit knowledge using 3D printing but when combined with recent advances in virtual reality, we may potentially experience learning in a completely new manner. Microsoft has combined virtual reality with hologram technology enabling users to actually interact with the objects they see. This represents a step-change in knowledge transfer sessions.
Anti-Fragility: The twenty-first century is defined by the social and technical hazards we face. Organizations and the complex adaptive systems they inhabit can vary in their ability to withstand these stress events. Anti-fragility is a concept developed by professor, former trader and former hedge fund manager Nassim Nicholas Taleb. Anti-fragility goes beyond robustness; it means that something does not merely withstand a shock but actually improves because of it.
Some organizations benefit from shocks; they thrive and grow when exposed to volatility, randomness, disorder, and stressors and love adventure, risk, and uncertainty. A key part of any organization’s coping mechanisms in developing its approach to anti-fragility is its knowledge base. With its blend of access to expertise, its structured and unstructured dynamic content, knowledge bases are determining the boundaries between systematic non-predictive decision making where there is randomness, unpredictability, opacity or incomplete understanding.
Conclusion
Knowledge management has matured significantly from its early obsession with storing information. Advances in finding, sharing and this knowledge soon followed. The goal of Knowledge Management programs solidified around the use of knowledge for clear and specific organizational purposes.
Much of the future manifestations of knowledge bases revolve around connecting people, processes and technology by managing the right technologies with the right people using the right processes. This approach helps ensure the continual flow of knowledge through an organization. Web-based knowledge base software is the platform from which knowledge is continually created, shared, utilized and importantly, leveraged for organizational success.
