MANAGING KNOWLEDGE &
ENHANCING DECISION-MAKING
Role of knowledge management systems in business
Systems used for knowledge management
Types of knowledge work system
Intelligent techniques for knowledge management
Knowledge is a cognitive, even a physiological, event that takes place inside people’s heads
Tacit knowledge: Has not been documented
Knowledge management: Set of business processes developed in an organization to create, store, transfer, and apply knowledge
Explicit knowledge: Has been documented
Knowledge acquisition
Knowledge storage
Knowledge dissemination
Knowledge application
Enterprise content management (ECM) systems help organization manage structured & unstructured knowledge
Locating & sharing expertise so it's accessible for everyone in organization
Learning management systems (LMS) provides tools for management, delivery, tracking, & assessment of various types of employee learning & training,
e.g. MOOC
Knowledge workers: Researchers, designers, engineers who create knowledge
- Keeping org current in knowledge
- Internal consultants
- Change agents
Requirements of KWS: Sufficient computing power to handle sophisticated graphics/complex calculations
e.g.
- Computer-aided design (CAD)
- 3D printing
- Virtual reality systems
- Augmented reality
Expert systems: Intelligent technique for capturing tacit knowledge in a very specific and limited domain of human expertise
Expert systems model human knowledge as a set of rules called knowledge base
Inference engine: Strategy used to search through the knowledge base
- Forward chaining: Inference engine begins with the info entered by the user and searches the rule base to arrive a a conclusion
- Backward chaining: Starts with hypothesis and proceeds by asking the user questions about selected facts until hypothesis is confirmed/disproved
Case-based reasoning (CBR): Descriptions of past cases, are documented and stored in a database for later retrieval when the user encounters a new case with similar parameters
Fuzzy logic systems: Rule-based tech that represent imprecision by creating rules that use approximate or subjective values
Machine learning: How computer programs can improve their performance without explicit programming
Neural networks “learn” patterns from large quantities of data by sifting through data, searching for relationships, building models, and correcting over and over again the model’s own mistakes
Genetic algorithms searches a population of randomly generated strings of binary digits to identify the right string representing the best possible solution for the problem
Intelligent agents: Software programs that work without direct human intervention to carry out specific tasks for an individual user, business process, or software application
Hybrid AI systems: Genetic algorithms, fuzzy logic, neural networks, and expert systems can be
integrated into a single application to take advantage of the best features
Decisions & Decision-making
Information systems & Management decision making
Business intelligence & business analytics
The use of business intelligence & role of information systems
Types of decisions
Unstructured decisions: Decision maker must provide judgment, evaluation, and insight to solve the problem
Structured decisions: Repetitive and routine, and they involve a definite procedure for handling them
Semi-structured: Only part of the problem has
a clear-cut answer provided by an accepted procedure
Decision-making process
Intelligence: Identifying why a problem exists, where, and
what effects it is having on the firm
Design involves identifying and exploring various solutions to the problem
Choice consists of choosing among solution alternatives
Implementation involves making the chosen alternative work and continuing to monitor how well the solution is working.
Managerial Roles
Interpersonal role: Figureheads for the organization when they represent their companies to the outside world and perform symbolic duties
Informational role: Receiving the most concrete, up-to date information and redistributing it to those who need to be aware of it
Decisional role: Act as entrepreneurs by initiating new kinds of activities, they handle disturbances arising in the organization, they allocate resources to staff members who need them, and they negotiate conflicts and mediate between conflicting groups
Real-world decision making
Information quality: High-quality decisions require high quality information
Management filters: Managers absorb information through a series of filters to make sense of the world around them
Organizational inertia & politics: When environments change and businesses need to adopt new business models to survive, strong forces within organizations resist making decisions calling for major change
Business intelligence: infrastructure for warehousing, integrating, reporting, and analyzing data that come from the business environment, including big data
Business analytics: Tools and techniques for analyzing and understanding data, e.g. OLAP, statistics, models, data mining
Predictive analytics use statistical analysis, data mining techniques, historical data, and assumptions about future conditions to predict future trends and behavior patterns
Operational intelligence: Decisions that deal with how to run the business on daily basis
Geographic information systems: tools to help decision makers visualize problems that benefit from mapping
Sensitivity analysis models ask what-if questions repeatedly to predict a range of outcomes when one or more variables are changed multiple times
Decision support for senior management
Balanced score card
Key performance indicators
Business performance management
Fadhila Abidah
09111840000092
SIB Q