1. Managing Organizations Informed decision making as a prerequisite for success Action Vision Mission Organizational Context Policies, Goals, and Objectives Givens Values, Purpose, Structure, Politics, Environment, etc. What should be done ? Analytics, Decision Making When and how ?? Strategic Direction Decision Making Implementation Project Management

2. Managerial Decision Making Information Technology Solutions for Improving Effectiveness Complexity What does it add up to? Uncertainty What can happen? INTELLIGENCECHOICE DESIGN DATAMODELS Variables (Measures and Estimates) Probabilities and Estimates Structuring Relationships Problem Representation Generation of Alternatives Decision Analysis and Influence Diagrams for Visualizing Models and Choices Spreadsheet Models for managing complex relationships and detail

3. Modeling Decision Situations Process for Developing Meaningful and Robust Models Objective Hierarchies Variables and Measures Modeling Relationships Situation Structuring Testing and Validation Implementation and Use DSS Fundamental and Means Objectives (feasible?) Decision, Intermediate, and Outcome Variables Data, Probabilities, Distributions Communicate Influence Diagrams and Decision Trees Spreadsheet Modeling Statistical, OR, Financial, Acctg. Models Values, Goals, Strategies, etc Analyze & Synthesize

4. The Decision Analysis Process Tools for Visualizing and Evaluating Alternatives Identify decision situation and understand objectives Identify alternatives Decompose and model problem structure uncertainty preferences Choose best alternative Sensitivity Analyses Implement Decision Model Representation Deterministic Analysis Probabilistic Analysis Evaluation of Alternatives Decision, Chance, and Consequence Variables Arcs and Relationship Formulas Tornado Diagrams N-way Sensitivity Uncertainty Assessment Risk Profiles EMV, NPV, etc.

5. Model Management Systems Tools for transforming data into information Creates models easily and quickly, either from scratch or from existing models or from building blocks. Allows users to manipulate the models so that they can conduct experiments and sensitivity analysis ranging from "what-if" to "goal seeking".manipulate Stores and manages a wide variety of different types of models in a logical and integrated manner. Accesses and integrates the model building blocks.integrates Catalogs and displays the directory of models for use by several individuals in the organization. Tracks models, data, and application usage. Interrelates models with appropriate linkages through the database. Manages and maintains the model base with management functions analogous to database management: store, access, run, update, link, catalog, and query.

6. Types of Models Tools for transforming data into information Accounting/financial models, most business models are described by accounting and financial relationships. Optimization, such as linear/quadratic programming, used when there is a set of constraints that must be considered before the objective is optimized through a solver. Statistical models for forecasting, used to take historical data and derive relationships in order to predict probabilistic future experience. Used for modeling uncertain relationships. Analog models - simplification of reality. Examples include pie charts, speedometers, and road maps. Symbolic models include Simulation, Algebraic, and Spreadsheet models. These feature easy manipulation and modification, difficult underlying comprehension, however high ease of interpretation.