Managing Organizations Informed decision making as a prerequisite for success

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

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

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

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

5. Model Management SystemsTools 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". Stores and manages a wide variety of different types of models in a logical and integrated manner. Accesses and integrates the model building blocks. 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 ModelsTools 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.