Revision

Mintzberg’s 10 Management Roles Interpersonal – Figurehead : symbolic head – Leader : Responsible for the motivation and activation of subordinates; responsible for staffing, training, and associated duties. – Liaison: Maintains self-developed network of outside contact and informers who provide favors and information. Informational – Monitor :Seeks and receives a wide variety of special information (much of it current) to develop a thorough understanding of the organization and environment. – Disseminator: Transmits information received from outsiders or from subordinates to members of the organization. – Spokesperson: Transmits information to outsiders on the organization’s plans, policies, actions, results and so forth; serves as an expert on the organization’s industry

Mintzberg’s 10 Management Roles Decisional –Entrepreneur: Searches the organization and its environment for opportunities and initiates improvement projects to bring about change; supervises design of certain projects –Disturbance Handler: Responsible for corrective action when the organization faces important, unexpected disturbances –Resource Allocation: Responsible for the allocation of organization resources of all kinds –Negotiator: Responsible for representing the organization at major negotiations

Technologies for Decision-Making Processes Type of DecisionTechnology Support Needed Structured (Programmed) MIS, Management Science Models, Transaction Processing SemistructuredDSS, KMS, GSS, CRM, SCM Unstructured (Unprogrammed) GSS, KMS, ES, Neural networks

What each Phase consists of? The Intelligence Phase consists of: - Organizational objectives. - Search and scanning procedures. - Data collection. - Problem identification. - Problem ownership. - Problem classification. - Problem statement. The Design Phase consists of: - Formulate a model. - Set criteria for choice. - Search for alternatives. - Predict and measure outcomes. The Choice Phase consists of: - Solution to the model. - Selection of the best (good) alternative (s). - Plan for implementation.

Decision Support Systems Choice Phase – Identification of best alternative – Identification of good enough alternative – What-if analysis – Goal-seeking analysis – May use KMS, GSS, CRM, ERP, and SCM systems

Decision Support Systems Implementation Phase – Improved communications – Collaboration – Training – Supported by KMS, expert systems, GSS

Data Integration

Database Models Hierarchical – Top down, like inverted tree – Fields have only one “parent”, each “parent” can have multiple “children” – Fast used in transaction (insert, delete, update) processing. Network – Relationships created through linked lists, using pointers – “Children” can have multiple “parents” – Greater flexibility, substantial overhead

Database Models Relational – Flat, two-dimensional tables with multiple access queries – Examines relations between multiple tables – Flexible, quick, and extendable with data independence – Best used in retrieving data. Object oriented – Data analyzed at conceptual level – Inheritance, abstraction, encapsulation

Data Warehouse

Data Mining Data mining solving these classes of problems – Classification – Clustering – Association – Sequencing // like association but over a period of time. – Regression // form of estimation. – Forecasting – Others Hypothesis (we assume a situation & start investigation) or discovery driven (it come from the facts).

Static & Dynamic Models A decision to make or buy a product is static in nature. In which static model take a static single snapshot of a situation so it has a single interval. It is presumed to be repeated with identical conditions. Dynamic model represent scenarios that change over time. It is time dependent they used to generate trends. © 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-15

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-16 Decision-Making Certainty – Assume complete knowledge – All potential outcomes known – Easy to develop – Resolution determined easily – Can be very complex

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-17 Decision-Making Uncertainty – Several outcomes for each decision – Probability of occurrence of each outcome unknown – Insufficient information – Assess risk and willingness to take it – Pessimistic / optimistic approaches

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-18 MSS Mathematical Models Link decision variables, uncontrollable variables, and result variables together decision variables, uncontrollable variables are the parameters while result variables are the outcomes which considered as dependent variables.

© 2005 Prentice Hall, Decision Support Systems and Intelligent Systems, 7th Edition, Turban, Aronson, and Liang 4-19 MSS Mathematical Models – Decision variables describe alternative choices they could be people, time and schedules. – Uncontrollable variables are outside decision-maker’s control these factors can be fixed, in which case they are called parameters and they can vary. – Fixed factors are parameters. – Intermediate outcomes produce intermediate result variables. – Result variables are dependent on chosen solution and uncontrollable variables.