Knowledge Sharing: The Foundation of a Competitive Edge

In every organization, classroom, or economy, there is one resource that never depletes when it is used – knowledge. Unlike oil, land, or capital, knowledge grows when it is shared. This simple but powerful idea underpins what experts call the knowledge-sharing economy, where the systematic exchange of information becomes the most valuable source of competitive advantage. Understanding how knowledge is shared – and what types of knowledge exist – is essential for anyone working in media, education, communication, or development.

What is knowledge sharing? 🔗

Knowledge sharing is the deliberate exchange of information, expertise, or insight between individuals, teams, or institutions. Research confirms that when knowledge is shared within an organization, its collective memory is enhanced, leading directly to better performance and innovation. Crucially, knowledge sharing creates value that is intangible – it cannot be easily counted or placed on a balance sheet, yet it consistently outperforms physical assets as a source of sustained competitive advantage.

To fully appreciate knowledge sharing, it helps to understand that not all knowledge is the same. Knowledge broadly falls into two major categories: tacit knowledge and explicit (or embedded) knowledge. How each type is shared differs considerably, and getting this distinction right has major implications for organizations and nations alike.

Tacit vs. embedded knowledge sharing 🔗

Tacit knowledge: the knowledge inside people 🔗

According to researchers in the Journal of Knowledge Management, tacit knowledge is the type of knowledge embedded in an individual’s brain or experience – it exists as know-how, skills, and intuition rather than written instructions. It is the accumulated judgment of a surgeon who knows when to adjust a technique, the editorial instinct of a veteran journalist, or the negotiation skill of an experienced diplomat. Tacit knowledge is deeply personal, hard to articulate, and even harder to transfer.

Studies estimate that tacit knowledge accounts for a significant majority of an organization’s total knowledge base, making it the most valuable – and most elusive – organizational asset. It is shared primarily through socialisation: direct interaction, mentorship, apprenticeships, communities of practice, and on-the-job experiences. Because it resides in people’s minds and manifests through their behaviors and value judgments, it cannot simply be emailed or uploaded to a database.

The SECI model by Nonaka and Takeuchi – one of the most influential frameworks in knowledge management – describes socialisation as the first mode of knowledge creation: tacit-to-tacit transfer between individuals through shared experience. When a senior editor guides a junior reporter through an investigative story, or when a professor mentors a doctoral student in research methodology, tacit knowledge is being transferred in real time.

A key challenge is that tacit knowledge often goes unnoticed until it disappears – when a key employee retires or leaves, taking decades of institutional knowledge with them. Organizations with strong knowledge-sharing cultures address this by actively creating opportunities for experienced staff to interact with newer team members, rather than relying solely on documentation.

Embedded (explicit) knowledge: the knowledge in systems 🔗

Embedded knowledge – also referred to as explicit knowledge – is the type that has been codified, structured, and stored in a tangible form. This includes manuals, standard operating procedures, databases, published research, policy documents, product designs, and organizational routines. Unlike tacit knowledge, embedded knowledge can be easily shared through writing or digital means and stored in formats that workforces can readily access.

Where tacit knowledge is shared through socialisation, embedded knowledge is shared through what Nonaka and Takeuchi describe as combination – organizing and synthesizing existing explicit knowledge into new forms. This happens every time a news organization publishes its editorial guidelines, a government releases a policy report, or a university updates its curriculum. The knowledge is delineated – set out in defined, communicable products or routines – rather than locked inside someone’s experience.

Research from PwC highlights that companies with strong knowledge-sharing cultures achieve measurably higher productivity, underscoring why organizations invest in centralized knowledge repositories, knowledge management systems, and structured documentation practices. Digital tools like shared databases and collaborative platforms have made the distribution of embedded knowledge faster and more scalable than ever before.

Why both types matter equally 🔗

A common mistake is treating explicit/embedded knowledge as “real” knowledge while dismissing tacit knowledge as informal or subjective. A 2025 systematic review from the European Conference on Knowledge Management found that effective organizational performance relies on a dual approach – fostering informal, tacit knowledge sharing alongside formal mechanisms for capturing and disseminating explicit knowledge. Prioritizing one at the expense of the other creates blind spots: over-reliance on documentation misses the nuanced judgment of experienced practitioners, while failing to codify knowledge means lessons are lost every time staff turn over.

Additionally, IEEE research shows a behavioral distinction worth noting: explicit knowledge sharing responds to both external incentives (rewards, recognition) and internal motivation, while tacit knowledge sharing is driven by intrinsic motivation alone. This means you cannot simply incentivize people with bonuses to share their deepest expertise – the organizational culture and trust environment must genuinely support it.

Building knowledge-based economies with digital technology 🔗

The logic of knowledge sharing scales beyond individual organizations to entire national economies. A knowledge-based economy (KBE) is one in which the primary driver of growth, wealth creation, and employment is the production and application of knowledge – rather than the extraction of natural resources or cheap labor. Harvard Business School’s Michael Porter argued that today’s most competitive economies are those making the most productive use of their inputs through continual innovation – not those simply endowed with more raw materials.

This shift is especially consequential for developing countries. According to the Asian Development Bank, developing economies that build knowledge-based systems become less reliant on natural resources and labor-cost advantages, which are increasingly unsustainable as wages rise and resources diminish. The path forward involves expanding higher education, growing the pool of skilled professionals, and enabling ICT-based teaching and learning.

Research across 15 Southern African Development Community countries reinforces this point: knowledge-based economy pillars – including education, innovation systems, and ICT infrastructure – have a significant and positive long-run impact on economic growth. For nations with scarce natural resources, investment in knowledge infrastructure is not optional – it is the primary route to prosperity and global competitiveness.

The role of ICT and digital tools 🔗

Digital technology is the infrastructure of the knowledge economy. The World Bank’s knowledge economy framework identifies ICT infrastructure as one of four essential pillars – alongside education, innovation systems, and institutional environment – that determine a country’s capacity to produce and apply knowledge competitively. ICT enables knowledge to move across borders, disciplines, and communities at low cost, dramatically expanding who can participate in knowledge creation and exchange.

Advances in artificial intelligence, machine learning, and collaborative digital platforms are making it easier to capture, organize, and circulate explicit knowledge at scale. These technologies are particularly effective at surfacing and organizing explicit knowledge, reducing the time teams spend searching for information and improving access across organizations and institutions. However, technology alone is not sufficient – as knowledge management research repeatedly shows, the human and cultural dimensions of knowledge sharing are just as critical as the tools.

Media and information literacy as the connective tissue 🔗

For knowledge sharing to actually drive economic and social development, people must be equipped to access, evaluate, and use information critically. This is precisely where Media and Information Literacy (MIL) becomes indispensable. UNESCO describes MIL as empowering individuals to discern truth from misinformation and navigate digital environments responsibly – including fostering the digital competencies needed to bridge knowledge divides.

UNESCO’s Institute for Information Technologies in Education defines MIL as a composite set of knowledge, skills, and practices that allow people to effectively access, analyze, critically evaluate, interpret, use, create, and disseminate information. In other words, MIL is what enables citizens and professionals to move beyond passive consumption of information toward the active, systematic exchange of knowledge that generates new insight and drives development.

This connection between MIL and knowledge sharing is especially vital in developing countries. Without the capacity to critically evaluate information sources, use digital platforms effectively, and communicate knowledge across communities, even the best ICT infrastructure will fall short of building a genuine knowledge economy. MIL skills allow individuals to participate in the information ecosystem – consuming, creating, and sharing knowledge responsibly – which is the foundation of any competitive, knowledge-driven society.

Higher education as a knowledge-sharing engine 🔗

Universities and higher education institutions play a central role in all of this. They are the spaces where tacit knowledge is transferred through mentorship and peer learning, where embedded knowledge is produced and published, and where digital tools are integrated into systematic knowledge exchange. Research in the Future Business Journal confirms that education and innovation are among the most important indicators of knowledge economy development, directly impacting a country’s ability to compete globally and reduce unemployment.

When universities integrate MIL into their curricula, they do more than teach media skills – they equip graduates to be active contributors to a knowledge-based economy. A systematic review in Education and Information Technologies found that the curricular integration of MIL is crucial for cultivating informed, critical, and engaged citizens in contemporary society, and that political will combined with teacher activism are key factors in making it happen.

From competitive advantage to national development 🔗

The thread connecting tacit knowledge, embedded knowledge, digital technology, and MIL is this: competitive advantage – whether for a business, a team, or a nation – now flows from how well knowledge is shared, not just how much of it exists. As knowledge management scholars Nonaka and Takeuchi observed, creating and renewing knowledge would become the key to sustaining competitive advantage for organizations and economies in the future. That future is now.

For developing countries, the strategic implication is clear. As development organizations like Helvetas note, a company’s – and by extension, a nation’s – ability to adapt processes and products to new information is increasingly crucial to maintaining competitive standing. The knowledge economy does not reward those who hoard information; it rewards those who build systems, cultures, and capacities that turn information into shared, actionable knowledge.

What do you think? If tacit knowledge is the most valuable yet hardest-to-transfer type of knowledge in any organization, what practical steps should educational institutions take to ensure it is systematically passed on before experienced educators and professionals retire? And as developing countries work to build knowledge-based economies, how central should Media and Information Literacy be in national education policy – is it a basic skill on par with reading and mathematics?

References

1. https://researchleap.com/the-value-of-knowledge-sharing-impact-of-tacit-and-explicit-knowledge-sharing-on-team-performance-of-scientists/
2. https://www.emerald.com/jkm/article/29/4/1248/1242026/Impact-of-knowledge-sharing-culture-on
3. https://bloomfire.com/blog/implicit-tacit-explicit-knowledge/
4. https://info.aiim.org/aiim-blog/tacit-knowledge-vs-explicit-knowledge
5. https://training.safetyculture.com/blog/tacit-vs-explicit-knowledge/
6. https://slick.plus/blog/explicit-vs-tacit-knowledge-understanding-the-differences-and-their-impact-on-organizations/
7. https://papers.academic-conferences.org/index.php/eckm/article/view/3740
8. https://ieeexplore.ieee.org/document/5998951/
9. https://en.wikipedia.org/wiki/Knowledge_economy
10. https://development.asia/explainer/advancing-knowledge-economies-through-education-and-skills
11. https://www.mdpi.com/2071-1050/13/5/2890
12. https://www.mdpi.com/2071-1050/14/8/4774
13. https://www.unesco.org/en/articles/media-and-information-literacy-and-digital-competencies
14. https://iite.unesco.org/mil/
15. https://link.springer.com/article/10.1186/s43093-021-00112-6
16. https://link.springer.com/article/10.1007/s10639-023-12154-0
17. https://pmc.ncbi.nlm.nih.gov/articles/PMC7995391/
18. https://www.helvetas.org/en/switzerland/how-you-can-help/follow-us/blog/inclusive-systems/knowledge-management-knowledge-economies