MAKING BUSINESS DECISIONS
1) Managerial decision-making challenges are analyze large amounts of information, apply sophisticated analysis techniques and make decision quickly.
2) There are six decision making process :
- Problem identification
- Data collection
- Solution generation
- Solution test
- Solution selection
- Solution implementation
THE DECISION MAKING ESSENTIAL
1) Operational decision making – employees develop, control, and maintain core business activities required to run the day-to-day operations.
2) Structured decision – situations where established processes offer potential solutions.
3) Managerial decision making – employees evaluate company operation to identify, adapt to, and leverage changes.
4) Semistructured decisions – occur in situations in which a few established processes helps to evaluate potential solution but not enough to lead to a definite recommended decision.
5) Strategic decision making – managers develop overall strategies, goals and objectives.
6) Unstructured decisions – occurs in situations in which no procedures or rules exists to guide decision makers toward the correct choice.
DECISION SUPPORT SYSTEM (DSS)
1) Decision support system (DSS) – models information to support managers and business professionals during the decision making process.
2) There are three quantitative models used by DSS
- Sensitivity analysis where the study of the impact that changes in one or more parts of the model have on other parts of the model.
- What-if-analysis where checks the impact of a change in an assumption on the proposed solution.
- Goal-seeking analysis where finds the inputs necessary to achieve a goal such as a desired level of outputs.
is the intelligence of machines and robots and the branch of computer science that aims to create it. AI textbooks define the field as "the study and design of intelligent agents" where an intelligent agent is a system that perceives its environment and takes actions that maximize its chances of success. John McCarthy, who coined the term in 1955, defines it as "the science and engineering of making intelligent machines."AI research is highly technical and specialised, deeply divided into subfields.
Expert System – computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems.
An example of expert system in terms of medical…this basic tasks are carried out by medical expert system which is diagnosis, prognosis, treatment, monitoring. In terms of treatment, the patient or physician could access the system through internet. From here, the user could choose from the choice of patient’s databases or patience disease database. Each database would perform the particular task, either from diagnosis module or prediction module. Then the user will received the feedback through internet so that the treatment can be performed.
Neural Network – attempts to emulate the way the human brains works – fuzzy logic – a mathematical method of handling imprecise or subjective information.
An example of neural network which is bank loans….imagine a highly experienced bank manager who must decide which customers will qualify for a loan. His decision is based on a completed application form that contains ten questions. Each question is answered by a number from 1 to 5 ( some responses may be subjective in nature). If we had a large number of loan applications as input, along with the manager’s decision as output, a neural network could be ‘ trained’ on these patterns. The inner workings of the neural network have enough mathematical sophistication to reasonably simulate the expert’s intuition.
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