Decision-Making Process

Introduction

• All managers are characterized as decision-makers.
• Managers must understand decision-making processes and have knowledge of available decision-making tools to achieve organizational goals.
• The quality of decisions significantly impacts the success or failure of individuals and companies.

The Decision Process

• Define the problem and influencing factors clearly and concisely.
• Establish specific and measurable decision criteria and goals.
• Create a model showing a clear relationship between goals and variables.
• Models should contain one or more variables.
• Variables consist of measurable quantities subject to change.
• Generate as many solutions to the problem as possible, and as rapidly as possible when identifying and evaluating alternatives.
• Select the best alternative that best satisfies and aligns with the stated goals.
• Implement the chosen decision while understanding that this is the most challenging stage; involving task assignments and a timetable for implementation.

Decision Theory

• Decision theory is an analytical approach to selecting the optimal alternative or action.
• Decision Theory is useful in several management situations:
• New product analysis
• Location planning
• Equipment selection
• Scheduling
• Maintenance planning

Conditions of Decision-Making

• There are some conditions related to decision making that are separated into three categories based on the degree of certainty regarding potential outcomes, and consequences.
• The three main classifications:
• Certainty
• Risk
• Uncertainty

Certainty

• It is the condition where the decision-maker knows with certainty the consequence or outcome of any alternative or decision choice.
• For example, knowing exactly how much a $1000 purchase of treasury bills will yield upon maturity.
• The decision-maker chooses the alternative that yields the most favorable outcome.

Risk

• The decision-maker knows the probability of occurrence of the outcomes or consequences for each choice.
  • For example, it may be known that the probability of rain tomorrow is 0.3.
• The decision-maker under risky conditions seeks to maximize the expected monetary value.

Uncertainty

• The decision-maker does not know the probability of occurrence of the outcomes for each alternative.
• Decision-making criteria under uncertainty include:
• Maximax
• Maximin
• Equally likely or Laplace

Maximax

• This criterion aims to find the alternative that maximizes the maximum outcome or consequence for every alternative.
• The procedure that is undertaken begins with identifying the maximum outcome in every alternative.
• Then, pick the plan with the maximum number.
• This decision criterion locates the alternative with the highest possible gain, and hence is called an "optimistic" decision criterion.

Maximin

• Maximin locates the alternative that maximizes the minimum outcome or consequence for every alternative.
• First, find the minimum outcome within every alternative.
• Pick the alternative with the maximum number.
• This decision criterion locates the alternative that has the least possible loss, and hence is called a "pessimistic" decision criterion.

Equally Likely or Laplace

• Finds the alternative with the highest equally likely or average outcome.
• First, calculate the average outcome for every alternative by summing all outcomes divided by the number of outcomes.
• Pick the alternative with the maximum number.
• The equally likely approach assumes that all probabilities of occurrence for the states of nature are equal and thus each state of nature is equally likely.

Fundamentals of Decision Theory

• All decision-makers face alternatives and states of nature, regardless of the decision's complexity.
• All possible alternatives may not be stated, and not all states of nature will be known in an uncertain situation.

Terms

• Alternative is a course of action or a strategy that may be chosen by a decision-maker.
  • For example, not carrying an umbrella tomorrow
• The state of nature is an occurrence or a situation over which the decision-maker has little or no control.
  • For example, tomorrow's weather

Decision-Making Tools: Decision Tables

• Managerial decision-making can be represented using decision trees and decision tables.
• Decision trees are more effective tools than decision tables when a sequence of decisions must be made.
• Symbols for decision trees:
• A decision node is a point from which one of several alternatives may be selected.
• A state of nature node is a point out of which one state of nature will occur.

Decision Tables

• List all alternatives down the left side of the table.
• List states of nature (occurrence) across the top of the table.
• For any alternative and a particular state of nature, there is a matching consequence or outcome, and it is usually expressed as a monetary value.
• This is called a conditional value.
• Conditional values (payoffs) are in the body of the decision table.

Decision Making Under Risk

• Decision-making in risky conditions is essentially a probabilistic decision situation.
• Several possible states of nature may materialize, each with a given probability.
• The expected monetary value (EMV) for each alternative can be determined using a decision table with given conditional values ​​along with probability assessments for all states of nature.

Expected Monetary Value (EMV)

• If the decision were repeated a large number of times, the result would be the average number of monetary returns on each alternative.
• One of the most commonly used decision criterion when selecting alternatives involves picking the maximum EMV available.
• The sum of possible payoffs of an alternative, each adjusted by the probability of occurrence for the given payoff for the various alternatives.
• EMV = (Payoff of 1st state of nature) x (Probability of 1st state of nature) + (Payoff of 2nd state of nature) x (Probability of 2nd state of nature) + ... + (Payoff of last state of nature) x (Probability of last state of nature)

EMV Criteria

• Calculate the best decision from the probabilities associated with each decision.

Decisions Under Uncertainty Criteria

• Decisions under each uncertainty criteria should include consideration of favourable markets, unfavourable markets, maximum in row, minimum in row, and the row averages.
• The maximax choice is to construct a large plant to find the maximum payoff and select it.
• The maximin choice is to do nothing to find the minimum payoff of each alternative and select minimum.
• The equally likely choice is to construct a small plant.
• This is the maximum of the average outcome of each alternative.

Complex Decision Trees

• Includes consideration for GETZ Products (or similar companies) to make two decisions, with the second one dependent on the first. Includes deciding whether to build a new plant, and if the company has the option to conduct a marketing research survey, at a certain cost. The information from the survey could help decide whether to build a large plant, a small plant, or not to build at all.

Uses of Decision Analysis

• Decision trees and tables are valuable for making decisions under risk and uncertainty.
• Decision theory can analyze investments in research and development, plant and equipment, and new buildings and structures.
• Decision theory also applies in other areas such as inventory control, aggregate planning, maintenance, scheduling, and production control.

Explore the decision-making process crucial for managers. Understand defining problems, setting criteria, and creating models. Learn to generate solutions, select the best alternatives, and implement decisions effectively for organizational success.