Through knowledge management systems companies are able to organize efficiently and promote both internal and external collaboration more effectively, therefore optimizing and realigning their organizational make up and infrastructure.
This is possible thanks to the use of several processes which merge AI and IT/Cloud computing programs together with applications to filter through and distribute relevant information that is pertinent to single or multiple business solutions, or aimed towards the promotion of a specific product or service.
Identification and distribution of specific data are key aspects of knowledge management processes which aim to analyse, cross-reference, process, filter and deliver all the available data on the Internet and the world wide web, make sense of human language and behaviour by imitating the neural pathways of the human brain, and boost productivity while also lowering costs.
For example cloud computing services enable you to store data on the cloud servers of third parties/providers – or installed internally in your IT database infrastructure. This enables save on energy bills, on external drives, multiple computers and other expensive hardware, including cables and fixed work offices.
Knowledge management systems like these primarily help to optimize and promote the sharing and exchange of ideas across all company levels, including open availability of specific data to all departments while boosting the market knowledge potential of any business or organization that employs processes like text/data mining, cognitive intelligence, machine learning, and also RPA (Robotic Process Automation) among others.
It is an evolution of enterprise resource planning software programs which in the past decade and a half have helped companies and small business to increase market visibility and boost growth, and which with the use of external servers hosted by third parties and service providers (i.e. Software as a Service) has been able to not only reduce bureaucracy and increase productive potential, but also improve work efficiency and communication between employees, managerial levels, and CEOs.
New business strategies
More importantly, knowledge management systems have afforded the opportunity to discover previously unknown business strategies and intelligence that can give even start-ups and small business a competitive edge in the markets compared to bigger players and monopolies.
This is done through a cross-disciplinary approach which extracts information from every area of human knowledge and activity. It does this by resorting to the content found in OSINT (Open Source Intelligence) – the wide gamut of data found on the Internet, used also by intelligence agencies and government departments.
Text and data mining are then used to recognize language structure as well as separate and then process structured (fixed in location) and unstructured data (HTML, PDF docs, blog conversations, audio/video files, etc.) to be delivered directly to the appropriate departments.
AI algorithms are able to predict fluctuations in consumer/customer satisfaction, loyalty, and also regulate the supply chain (thus reducing costs) and the cost/risk factor based on their analysis and forecast of changes in customer demand and trends, while providing the appropriate suggestion for solutions. This is much like AI online assistants do when providing answers to customer queries and suggesting related products/services of interest.
Their biggest strength is that they can anticipate future trends by searching through the entire web search history of consumer audiences including their social media accounts as well as virtual libraries, consumer blogs, professional organizations, business reports and academic journals to recommend specific solutions customized to their preference.
Ultimately, knowledge management processes can bring companies and their customers and clients together while also helping organizations to diversify into other business areas and attract multiple new audiences.