Traditional Decision-Making Processes and Applications

Origins and Evolution of Decision-Making Research

• Early Academic Context: The foundations of decision-making research were primarily established in college classrooms and laboratories. These settings offered convenient access to participants and controlled environments.

• Participant Demographics: Most early subjects were college students. A significant limitation of this demographic was their lack of expertise regarding the subjects they were asked to make decisions about.

• Environment Disparity: The controlled laboratory settings used in early research were drastically different from the high-risk, high-consequence environments (such as public safety) where decisions have life-altering stakes.

• Example Study: Stock Trading Experiment:

  • Setup: A professor/researcher received a grant and utilized students from an economics class. Students were chosen for their accessibility and low cost (working for modest pay or extra credit).

  • Data Provision: Students received packets for $6$ to $10$ companies. These packets contained historical data, executive biographies, product/service information, financial statements, and stock price trends.

  • The Task: Each student was given a hypothetical amount of money, such as $10,000, to invest. They evaluated companies and traded stocks throughout a semester, tracking transactions and decision-making processes.

  • Researcher Objective: While students aimed to maximize profits (often motivated by rewards like a pizza party for the winner), the researchers' true goal was to understand the underlying mechanics of purchasing and trading decisions.

The Traditional Decision-Making Process

• Nomenclature: This process is known by several names, including:

  • Rational Decision-Making Process: So named because it follows a regimented, step-by-step series of actions.

  • Analytical Decision-Making Process: Named for its heavy reliance on metrics to weigh and evaluate potential options.

  • Traditional Decision-Making Process: The simplified term used to describe this structured approach.

• The Seven-Step Framework:

  1. Define the problem.

  2. Identify the decision-making criteria.

  3. Allocate weights to each of the criteria based on importance.

  4. Develop alternatives for solving the problem.

  5. Evaluate each alternative based on the weighted criteria.

  6. Select the best alternative that maximizes the desired outcome.

  7. Evaluate the effectiveness of the action that was taken.

Step 1: Defining the Problem

• Foundational Importance: Accurate problem definition is critical. An incorrect definition increases the likelihood of a poor decision.

• Symptoms vs. Root Causes: There is a common tendency to focus on symptoms rather than the root problem.

  • Medical Example (EMS): Symptoms like chest pain, shortness of breath, pale/clammy skin, and ST-segment elevation on an EKG are markers. While the field diagnosis may be a "heart attack" to facilitate standard treatment, the root cause requires further clinical investigation.

  • Law Enforcement Example: A driver weaving with slurred speech and fruity-smelling breath displays symptoms of impairment. While it may appear to be intoxication (DUI), the root cause could be a diabetic emergency involving blood sugar regulation.

• Decision Default: In public safety, responders often treat the most dangerous potential root cause as a default (e.g., treating for a heart attack) because field diagnostic tools are limited.

Step 2 & 3: Identifying and Weighting Criteria

• Identification: This involves establishing the metrics used to guide the decision. In stock trading, this might include years in business, profitability over $10$ years, management quality, and $5$-year performance.

• Weighting: Not all criteria are equal. Decision-makers must assign percentages or values to each criterion to reflect its relative importance. For example, is management quality more important than historical profitability?

Step 4, 5, & 6: Alternatives, Evaluation, and Selection

• Developing Alternatives: This involves listing possible choices. To keep the list manageable, filters must be applied.

  • Traded Stock Example: A broker might filter by exchange (e.g., New York Stock Exchange), market capitalization (e.g., blue chip or mid-level capitalized), or sector.

• Evaluating Alternatives: This is a numerical process. Each alternative is scored against the weighted criteria established in previous steps.

• Making the Decision: The alternatives are ranked from highest to lowest score. The highest-scoring option is selected. This is intended to be the easiest step, as the "best" choice is mathematically derived.

The Role of Emotions and Intuition

• The Dilemma: Conflict arises when the logical, highest-ranking alternative does not align with the decision-maker's "gut feeling" or emotional preference.

• Rational vs. Emotional: A student may set criteria that favor a stable company, but their intuition may favor a company they personally like or have high hopes for.

• Balance: There is no definitive rule that a logical decision is always superior to an intuitive one, nor that a blend is always best. However, the plan must ultimately be put into action.

Step 7: Reflection and the Value of Experience

• Evaluation of Effectiveness: After the decision is implemented, the outcome is assessed. Questions include: "How did I do?", "Did things turn out as expected?", and "What were the consequences?"

• Definition of Wisdom: Wisdom is the collection of experiences, successes, failures, and evaluations of lessons learned over time.

• Mentorship in Emergency Services: Seasoned veterans are valuable not merely for their age, but because they have a vast collection of experience-based lessons. This knowledge transfer helps newer responders become better decision-makers.

• Temporal Criticality: In public safety, the timeline for reflection is compressed. High-risk, high-consequence incidents moving at high speed require immediate assessment. Changing course too soon may prevent success; waiting too long can lead to catastrophe.

Case Study Application: Planning a Vacation

• Step 1: Problem: Burnout/Need for vacation.

• Step 2 & 3: Criteria and Weights:

  • Cost = $50\%$

  • Amenities = $20\%$

  • Activities = $15\%$

  • Solitude = $10\%$

  • Weather = $5\%$

• Step 4: Alternatives: Beach, Mountains, Cruise, Theme Park, Visit Relatives.

• Step 5: Ranking for the Cost Criterion (Ranking $1$ to $5$, where $5$ is best/lowest cost):

  1. Theme Park: $4,000 (Rank $1$)

  2. Cruise: $3,500 (Rank $2$)

  3. Beach: $3,000 (Rank $3$)

  4. Mountains: $2,500 (Rank $4$)

  5. Visit Relatives: $1,000 (Rank $5$)

• Step 5 Math (Criterion Weight $\times$ Rank):

  • Theme Park: $50 \times 1 = 50$

  • Cruise: $50 \times 2 = 100$

  • Beach: $50 \times 3 = 150$

  • Mountains: $50 \times 4 = 200$

  • Visit Relatives: $50 \times 5 = 250$

• Final Weighted Totals (Collective Scoring):

  • Beach: $340$ (Winner)

  • Visit Relatives: $335$

  • Mountains: $305$

  • Cruise: $300$

  • Theme Park: $220$

Limitations of the Traditional Model in Public Safety

• Practicality Concerns: While rational and thorough, the traditional process is often incompatible with emergency scenes because of:

  • Lack of time: Responders cannot "hold the incident in abeyance" for $20$ to $30$ minutes to run calculations.

  • Insufficient/Unstable Data: Real-world emergency data is often incomplete or changing too rapidly for analytical assessment.

• Exceptions: The traditional process is appropriate if the incident is stable and time is available, such as a confined hazardous materials spill with no immediate threat to life or property.

• Alternative Models: Experienced public safety personnel under time pressure do not use this rational process; instead, they rely on models more suited for dynamically changing environments, which are discussed in subsequent chapters.