1. Chapter 11 Managing Knowledge

2. Dimensions of Knowledge

3.  Knowledge Management – business processes developed in an organization/create, store, transfer, apply knowledge  Acquisition  Storage  Dissemination  Application  Communities of practice (COP) – informal social networks/ people with similar work related interests and activities Terms

4.  Manage knowledge in your organization  Enterprise-wide (general purpose; collect, store, distribute, and apply digital content and knowledge)  Knowledge work systems (specialized systems; engineers, scientists, etc; discovering and creating new knowledge)  Intelligent Techniques (data mining, expert systems, neural networks, fuzzy logic, etc.) Knowledge Management Systems (KMS)

5.  Types of knowledge  Structured (explicit and formal)  Semistructured (email, chat rooms, etc)  Unstructured (in head – tacit)  Enterprise content management systems  Hold all three types of knowledge  80 percent of organization’s knowledge is semistructured or unstructured  Can help create a classification scheme (taxonomy) Enterprise-wide KMS

6.  Digital asset management systems (work with digital objects)  Knowledge network systems (expertise location and management system; hold information from experts in the firm)  Collaboration tools and learning management systems (LMS) (tools for various types of learning and training)  Social bookmarking  Folksonomies Enterprise-wide (cont)

7.  Knowledge workers (create knowledge for organization)  Knowledge work systems (specialized systems for knowledge workers)  Sufficient computing power  Require links to external knowledge bases  Give the worker quick and easy access to databases  Workstations optimized for specific tasks performed Types:  Computer aided design (CAD)  Virtual reality Virtual reality  Programs for web Use VRML  Augmented Reality Augmented Reality Knowledge Work Systems

8. For Tacit knowledge  Expert systems  Case-based reasoning  Fuzzy logic For Knowledge discovery  Neural Networks  Data Mining Artificial Intelligence (computer-based/attempt to emulate human behavior) Power of AI People Power App Intelligent Techniques

9.  Expert Systems (tacit knowledge/specific and limited domain of human expertise)  Knowledge base (rules)  Inference engine (search)  Forward chaining (Info entered by user; searches rule base for conclusion)  Backward chaining (starts with hypothesis; try to confirm or disprove)  Case based reasoning (CBR) (past experiences of human specialists/organizational knowledge/stored in database/look for similar parameters) Intelligent Techniques (cont)

10.  Fuzzy Logic (rule based/approximate or subjective values/for imprecise info)  Neural networks (look for patterns and relationships in data)  Genetic algorithms (finding optimal solution/based on evolutionary biology techniques)  Hybrid AI systems (integrate genetic algorithms, fuzzy logic, neural networks, expert systems)  Intelligent agents (software programs/work in background/carry out tasks for user)  Agent-based modeling (model behavior of humans) Intelligent Techniques (cont)