1. CHAPTER ELEVEN MANAGING KNOWLEGE

2. Objectives We have been through some of this already Role of knowledge management Types of knowledge management systems Providing value through knowledge management Business benefits

3. Dimensions of Knowledge Data is transformed into information, which is transformed into knowledge Undocumented knowledge is called tacit knowledge Document codified knowledge is explicit knowledge Collective knowledge is transformed into wisdom

4. Dimensions of Knowledge Knowledge is an asset that requires resources to manage Value increases as more people (inside and outside the organization) share it Knowledge involves How-to, craft, skill, knowing why, understanding procedures Process of change and knowledge management is called organizational learning

5. Steps Toward Knowledge Management Acquire From data warehouse (data mining and AI) From external data stores (Government databases) It’s BI again Store In content management systems and knowledge database (SharePoint) Expert systems to mimic the knowledge of subject experts

6. Steps Toward Knowledge Management Disseminate Through portals and search engines Through e-mail and social tools Apply Through DSS (BI) systems and enterprise applications Provides actionable decision-making tools And finally collaborate Communities of practice

7. Types of Knowledge Management Systems Enterprise KMS Systems to collect, store, organize, and distribute structured and unstructured information Knowledge work systems Specialized systems to discover and create new knowledge Intelligent techniques This is the domain of artificial intelligence

8. Types of Enterprise Knowledge Management Systems Content management systems Drupal Joomla WordPress Tasks Capture information Tag it for retrieval Change management

9. Learning Management Systems Tools for employee learning and training Online courses (MOOCS) Lynda.com We have to throw in Ted talks

10. Types of Knowledge Work Systems Computer-aided design (CAD) Additive manufacturing (3-D printing) Virtual reality systems Augmented reality Virtual Reality Modeling Language (VRML)

11. AND NOW ON TO THE WORLD OF ARTIFICIAL INTELLIGENCE Artificial intelligence simulates human intelligence such as the ability to reason and learn.

12. Expert Systems (Introduction) Systems that capture knowledge of skilled employees that can be used by others in an organization Limitation Works well when decision variables are limited Works poorly when there are too many decision options

13. Operation of an Expert System A knowledge base (database) stores knowledge often represented as a set of rules There may be hundreds or thousands of rules Types Forward chaining Start with user data and apply rules Backward chaining Start with null hypothesis Then apply rules and ask questions until we get an answer

14. Applications Freight routing Pharmacological interaction

15. Case-based Reasoning Based on historical cases (examples) Use historical cases to determine if this case is applicable Used in medical logical

16. Fuzzy Logic Rule based system that can represent imprecision or ambiguity (near, far, close, warm, cold) Autofocus in a camera Positioning of an automatic welding robot

17. Neural Networks How these work internally is beyond the scope of this course Basically we create software that tires to Learn Mimic the human brain Characteristics Sift through large amounts of data Find patterns in that data Software learns and makes corrections over time

18. Genetic Algorithms We keep looking at many solutions Discarding suboptimal solutions Keeping optimal ones until the best solution is found

19. Intelligent Agents They carry out work without human intervention Deleting junk mail Detecting spam Excel figures out graph types based on data heuristics Siri Adapts to user preferences