Management Process Model linking management desired processes functions conditions Planning Manager Communications Organizing Coordination Goals Decision Making Leading Adaptation Controlling

Models of Decision Making Rational Model (Classical) Complete information about alternatives Complete information about consequences of each alternative Objective analysis of facts Goal: maximize, minimize, optimize

Factors that affect our ability to make rational decisions Limited cognitive capacity and time Emotions/intuition Framing Information Processing Biases all of the perceptual biases Decision Context Biases escalation of commitment groupthink org. impediments

Models of Decision Making: continued Nonrational Models Administrative Model Bounded Rationality Incremental Model Intuition Political Model

Limited available information Limited search for additional Bounded Rationality Limited available information Limited search for additional information Limited cognitive capacity “Satisficing” solutions

Nonprogrammed decisions Types of Decisions Programmed Decisions Nonprogrammed decisions

Decision Making Environments Decision making under certainty Decision making under risk Decision making under uncertainty

Decision Making Techniques Depends on how much, and the quality of, information available; which is a function of The environment in which decision making is to take place The ability to forecast that environment

Forecasting Techniques Forecasting the external environment Economic forces Technological forces Sociocultural forces Governmental forces Forecasting the internal environment Sales forecasting

Sales Forecasting Techniques Forecasts based on what people say they will do. Jury of Executive Opinion Salesforce Composite User Expectation Forecasts based on what people are doing. Test marketing Forecasts based on what people have done in the past. Time Series Analysis Correlation analysis Econometric Models

Decision Making Techniques Under Certainty Habit SOPs Linear Programming Waiting Line Analysis (Queuing Theory)

Decision Making Techniques under Risk Decision Tree Analysis Payoff Matrices

The true meaning of Probabilities Objective versus Subjective probabilities 1.0 .8 .6 .4 .2 Probability Of Success Low Size of Commitment High Statistical averages (Objective probabilities) Risk Averter Gambler

Decision Tree Analysis Our Price Competitor’s Price Profits 50 30 10 55 40 25 100 80 60 High (.40) Medium (.50) Low (.10) High (.10) Medium (.60) Low (.30) Medium (.20) Low (.70) 36 High Medium Low 49.6 Market Do not market Competition .80 No competition .20 37 37 34 High Low 100 Medium

How big of a plant to build? Depends on demand Payoff Matrices How big of a plant to build? Depends on demand Decision Strategies Small Plant Medium Plant Large Plant Product Demand Low Medium High (.50) (.30) (.20) 30 -14 -30 30 68 28 30 68 100

Decision Making Techniques Under Uncertainty Decision Matrices without probabilities Possible States of Nature (Demand) Alternatives 100,000 200,000 300,000 400,000 Labor Intensive Labor Machine Automated 10 8 9 11 12 8 6 7 20 10 6 4

Summary Decision Decision Decision Decision Decision Type Environ. Model Technique Goal Programmed Certainty Rational Habit Maximize SOPs Minimize Risk Classical Calculation Optimize Operations Research Non- Nonrational Programmed Uncertainty Administrative Judgement Satisfice Political Negotiation Compromise Intuition Inspiration Relativity

Group Decision Making Techniques Ordinary Criteria Groups Brainstorming NGT Delphi # ideas Low Medium High High Quality of ideas Low Medium High High Conflict Potential High Low Medium Low Time/Cost Medium Low Low High Task Orientation Low High High High Sense of Accomplishment High to Low High High Medium Commit. To Solution High n.a. Medium Low Cohesiveness High High Medium Low