A lot of the value-added enterprise knowledge is owned by individual employees. (SMEs) have knowledge that is crucial to decision-making. The challenge often comes in codifying this knowledge in a way that makes it accessible to others within an organization. To make more informed decisions, SME knowledge needs to be effectively captured and centralized across the enterprise for companies to seamlessly integrate it into machine learning findings and, in effect, make more informed decisions.
Another issue that raises complications is the fragmentation of knowledge in organizations. This is attributed to the myriad of apps individually used by employees. Data is often on multiple denmark whatsapp number data applications that work on incongruous platforms and systems, further complicating the process of centralizing it for knowledge sharing. In fact, it is estimated that 175 apps are installed on the average large enterprise employee’s computer. Expectedly, companies often don’t even know what data they are missing, so the process of extracting knowledge is daunting and overwhelming.
Additionally, when knowledge is inherently owned by employees as opposed to organizations, this means that it also has the same level of transience. It also becomes lost whenever the employee leaves their position and whenever corporate structures shift. This fleeting nature of knowledge also manifests itself in daily situations.