Improving Organizational Knowledge Control with the use of NLP

Knowledge management has emerged as a key enabler of organisational learning and innovation in the digital era. Over Data helps organizations to collect, transform and act upon these insights towards process innovation and decision victory. Rooted in a dynamic capability lens of organizational learning, this study extends theory and practice by illustrating how knowledge management systems, powered by NLP, can provide transformational impact in terms of guiding organizational learning to achieve competitive advantage in the midst of evolving business scopes. Failure to capture, share and innovate organizational learning allows an organisation to learn from its best practices and adequately adapt to change. Traditional KM approaches have been biased to the codification of explicit knowledge which, by and large, have focused on the codification of explicit knowledge, in general, they did not pay much attention to tacit knowledge embedded in extracted information from the organization communication, documents, and external data stores. NLP technologies help fill this vacuum by enabling organizations to work with both structured and unstructured data in a manner capable of uncovering previously opaque patterns, insights and knowledge. Leveraging essential NLP techniques such as sentiment analysis, topic modeling, entity recognition, and text summarization, organizations can generate insights from vast datasets. As a few examples, qualitative analysis can be used to to measure employee satisfaction or customer feedback using sentiment analysis etc. or topic modeling can work to surface new trends or areas of knowledge that are critical for strategic initiatives. Entity recognition also facilitates the identification of key players, relations and resources, which streamlines the decision-making process. When paired with machine learning algorithms, this kind of NLP tooling provides insight into key topics in real time, automating repetitive tasks and enabling adaptive learning processes throughout the organisation. Intelligent knowledge repositories Similarly, another important application of NLP in KM. These repositories utilize NLP techniques to structure, tag, and pull up information dynamically, so that the moment when employees need the information, they land on the right information at the right time. This ability promotes collaboration and minimizes knowledge silos-one of the greatest impediments to effective learning. NLP is also an enabler for conversational AI applications such as the chatbots or virtual assistants where employees can query knowledge bases using natural language, which will help bring knowledge to the hands of employees, to perform easier retrieval.