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MODULE 0: Executive Functioning
1. Introduction to Decision-Making and Executive Functions
Decision-making is a complex cognitive process requiring evaluation, planning, inhibition, selection of options, and monitoring outcomes. One of the primary cognitive systems enabling efficient decision-making is the set of Executive Functions (EF).
2. Definition of Executive Functions (EF)
Executive Functions are higher-order cognitive processes responsible for regulating thoughts, behaviors, and emotions. They enable individuals to plan, initiate, monitor, and adapt goal‑directed behaviors (Welsh et al., 1991).
According to the slides (p.4), EF constitute a complex cognitive construct supporting many daily-life activities.
2.1 Core Abilities of EF
- Ability to control and regulate other cognitive functions and behavior (Welsh et al., 1991).
- Ability to selectively process relevant information while inhibiting irrelevant stimuli.
- Ability to plan and schedule sequences of actions to achieve goals (Pennington & Ozonoff, 1996; Friedman et al., 2006).
2.2 Executive Functions as Goal-Oriented Skills
According to Welsh & Pennington (2009), EF are essential for planning, implementing, and successfully completing strategic actions. They include both cognitive and self-regulation processes.
These involve monitoring thoughts, correcting errors, inhibiting impulses, and adapting behavior to changing demands.
3. When Are Executive Functions Used?
Executive Functions are activated especially when familiar responses or automatic routines are insufficient.
3.1 Situations activating EF
- When previously learned patterns are no longer functional (p.7).
- When new solutions must be created for a problem.
- When learning new actions.
- When performing decision‑making or planning tasks.
- When correcting errors.
- When executing a new sequence of behaviors (p.8).
- When constant self‑monitoring is required.
- When overcoming habitual responses or resisting impulsive actions.
4. Subdomains of Executive Functions
The literature identifies three relatively independent EF components (p.9):
- Inhibition
- Working Memory
- Cognitive Flexibility (Shifting)
4.1 Inhibition
Inhibition is the ability to suppress irrelevant stimuli, control automatic responses, and choose appropriate actions.
It allows individuals to filter out distractions and maintain focus toward goal achievement (p.10).
4.1.1 Selective Attention
Selective attention is a key mechanism of inhibition. It consists of selecting relevant information and suppressing irrelevant input (p.11).
The slides illustrate this with the Cocktail Party Effect (p.12): the ability to focus on one voice in a noisy room.
4.2 Working Memory (WM)
Working Memory is an active system responsible for holding and manipulating information simultaneously (p.13).
WM coordinates both maintenance (holding information) and processing (reasoning, updating, switching).
4.2.1 Relation Between WM and Inhibition
Inhibition and Working Memory are interdependent (p.14). Individuals must maintain clear goals in WM in order to inhibit irrelevant stimuli.
Diamond (2013) emphasizes that minimizing external distractions is essential for effective goal pursuit.
4.3 Cognitive Flexibility (Shifting)
Cognitive flexibility is the ability to adapt behavior based on changing environmental demands (p.15).
It involves shifting mental sets, updating strategies, and adjusting actions according to feedback.
Deficits lead to perseveration—repeating inappropriate responses despite negative outcomes.
5. Decision-Making and Its Relationship with Executive Functions
Decision-making relies heavily on EF because it requires evaluating alternatives, inhibiting impulsive choices, holding information in mind, predicting outcomes, adapting to changes, and monitoring errors.
5.1 EF Contributions to Decision-Making
- Inhibition prevents impulsive or risky decisions.
- Working Memory allows simultaneous comparison of alternatives.
MODULE 1
1. Understanding the Decision-Making Process
1.1 Defining the Decision Context
- Every decision takes place within a specific organizational environment shaped by goals, resources, constraints, culture, and external factors.
- Internal factors: resources, values, policies, organizational climate.
- External factors: competition, regulations, market trends.
- Clarifying urgency and importance is essential for proper prioritization. Example: HR team designing a recruitment strategy must consider labor market, company image, and diversity targets.
1.2 Recognizing the Need for a Decision
- DM begins when a gap appears between the current state and the desired state.
- Triggers: declining engagement, customer complaints, emerging market opportunities.
- Not all problems require immediate action; sometimes delaying is strategically beneficial when information is insufficient.
1.3 Gathering and Organizing Information
- Decision quality depends on accuracy and relevance of data.
- Sources: internal reports, KPIs, employee feedback, performance reviews, market analysis.
- Combine quantitative (metrics) and qualitative (experience, perceptions) data.
- Beware of information overload and confirmation bias.
1.4 Identifying and Generating Alternatives
- Good decision-making relies on creating multiple feasible options.
- Methods: brainstorming, creative problem solving, mind-mapping.
- Avoid groupthink by encouraging diverse perspectives. Example: for high turnover, consider salary review, career pathways, flexible working.
1.5 Evaluating Alternatives
- Alternatives assessed via feasibility, cost, risk, alignment with organizational values.
- Tools: decision matrices, cost–benefit analysis, risk models.
- Combine rational assessment with emotional and ethical considerations.
1.6 Choosing the Best Alternative
- Selection may be rational or bounded by limited information.
- In group decisions, leadership clarity is essential to avoid dominance or stalemate.
1.7 Implementing the Decision
- Translate the chosen option into an action plan.
- Assign responsibilities, deadlines, communication channels.
- Anticipate resistance — plan change-management strategies.
1.8 Monitoring and Reviewing Outcomes
- Use predefined success indicators.
- Detect early failure or unintended consequences.
- Apply lessons learned to future decision cycles.
2. Types of Decisions and Decision Environments
2.1 Strategic Decisions
- Long-term impact; shape organizational direction.
- Examples: restructuring, entering new markets.
- Require vision, uncertainty tolerance, strong stakeholder coordination.
2.2 Tactical Decisions
- Medium-term, departmental-level decisions.
- Examples: introducing HR systems, adjusting marketing strategies.
- Balance analysis with adaptability; often cross-functional.
2.3 Operational Decisions
- Day-to-day decisions; efficiency-focused.
- Examples: shift planning, approving leave.
- Typically individual; speed matters.
2.4 Decision Environments: Individual Decision-Making
Advantages:
- Speed in urgent decisions.
- Clear responsibility.
- No need for coordination.
Risks:
- Narrow perspective.
- Confirmation bias and overconfidence.
- Pressure of carrying responsibility alone.
2.5 Decision Environments: Team Decision-Making
Advantages:
- Diverse perspectives → creativity, accuracy.
- Shared accountability and higher commitment.
- Better implementation quality.
Risks:
- Time-consuming.
- Conflicts and coordination issues.
- Groupthink and social loafing.
2.6 Matching Decision Type to Environment
- Strategic → Best in teams (cross-functional, diverse expertise).
- Tactical → Team or individual with consultation.
- Operational → Individual for speed.
- Crisis → Individual or small expert group (fast response required).
2.7 Work Psychology Perspective
- Decision environments shape behavior, culture, and responsibility patterns.
- Individual DM requires resilience and self-regulation.
- Team DM requires psychological safety, facilitation skills, and conflict resolution.
- Optimize environments via bias training, constructive dissent, and role clarity.
3. The Decision Cycle – Eight Key Phases
According to slides (pp. 26–34), the decision cycle ensures structured progression from recognizing the problem to evaluating outcomes.
3.1 Phase 1 – Problem Recognition & Framing
MODULE 2
1. Introduction: Anatomy of a Decision
Module 2 focuses on deconstructing a decision into its fundamental psychological components. A decision is not a single act of choosing; rather, it is the product of cognitive, emotional, and social processes that interact dynamically. Work psychologists analyse these components to understand how decisions are made, why they sometimes fail, and how they can be improved in organizational settings.
2. Components of a Decision
According to the slides (pages 4–7), a decision in Work and Organizational Psychology refers to the conclusion an individual or group reaches after evaluating alternatives, consequences, and contextual constraints.
2.1 Core Cognitive Processes
- Identifying alternatives — generating possible courses of action.
- Evaluating consequences — assessing outcomes, risks, and impacts.
- Selecting the most suitable option — choosing the alternative aligned with goals and contextual demands. These processes are shown visually on slide 4, where a sequence of ‘Option 1, Option 2, Option 3’ illustrates the analysis required before choosing.
2.2 Decision-Making Is Not Purely Logical
Slides 5–6 emphasise that decision-making is not merely rational. It emerges from a complex interaction between:
- Cognitive elements
- Emotional responses
- Social processes These interact with past experiences, cognitive biases, stress, group dynamics, organizational culture, and the availability of information.
2.3 Influencing Factors
Slide 6 presents five critical influences:
- Past experiences and learning
- Cognitive biases and heuristics
- Group dynamics and organizational culture
- Time pressure and stress
- Availability of information These factors shape how alternatives are perceived, how consequences are evaluated, and how confident decision-makers feel.
2.4 Work Psychology Perspective
Work psychologists study decisions to understand:
- how workplace choices are made,
- how and why poor decisions arise, and
- how decisions can be improved to enhance individual and organizational performance. (Slide 7)
3. Framing a Choice
Slides 9–19 expand on the concept of framing — the idea that the same decision can be perceived differently depending on how it is presented.
3.1 Definition of Framing
Framing refers to presenting, describing, or contextualizing a choice in a way that emphasises certain aspects while minimising others. It highlights that objective facts matter less than how those facts are interpreted.
3.2 Why Framing Matters
According to slide 10, people respond not to facts but to the meaning they assign to them. Framing activates cognitive biases and emotional reactions, often leading to decisions that deviate from rational predictions.
3.3 The Cognitive–Emotional–Behavioural Loop
Slides 11–13 illustrate how perception shapes emotion, which then drives behaviour. Examples include fear (e.g., growling dog interpreted as danger) and tenderness (e.g., calm puppy).
3.4 Types of Framing Effects
The slides (14–16) and the course summary identify three primary framing effects:
a) Gain vs. Loss Framing (Prospect Theory)
- People prefer avoiding losses to acquiring equivalent gains.
- Example from slide 14: “You will save 200 jobs” vs. “400 jobs will be lost.”
b) Attribute Framing
- Highlighting a positive or negative attribute of the same fact.
- Example: “75% competent” vs. “25% lacking competence.”
c) Risk Framing
- Describing options in terms of risk vs. safety influences perception.
- Example from HR (slide 16): “Flexible work reduces burnout” vs. “Rigid schedules increase turnover.”
3.5 Workplace Application of Framing
Slide 17 provides a clear example: presenting a new performance evaluation system as a tool for employee growth (positive frame) vs. as a system to identify poor performers (negative frame).
3.6 Work Psychology Insight on Framing
Framing shapes motivation, resistance, and behavioural outcomes (slide 18). Ethical framing is crucial: the goal is influence, not manipulation.
4. The Decision Context
Module 2 (slides 21–27) introduces the concept of decision context — the environment in which choices are made and implemented.
4.1 Core Definition
The context is the set of organizational, social, cultural, and psychological conditions that influence:
- how a decision is made (the process), and
- how it is received and executed (implementation). Slide 21 uses the metaphor of ‘soil’: the same seed (decision) will flourish or fail depending on the environment.
4.2 Elements of the Decision Environment
Slides 22–25 outline five essential contextual elements:
MODULE 3
1. Introduction: Normative vs Behavioural Approaches
Module 3 examines two major traditions in decision-making research: normative theories, which prescribe how decisions should be made by perfectly rational agents, and behavioural theories, which explain how real humans actually decide in everyday organisational settings. The contrast between ideal rationality and human limitations is the foundation for all modern work in applied decision-making psychology.
2. Normative Decision-Making Theories
Normative theories outline how decisions should be made under conditions of full rationality, stable preferences, full information, and unlimited cognitive capacity. They serve as benchmarks for rational behaviour and provide structured, mathematical or procedural models for identifying optimal choices.
2.1 The Rational Decision-Making Model
This foundational model assumes that individuals evaluate all alternatives systematically and select the one that maximises utility or outcomes. Steps include: problem identification, information gathering, option generation, evaluation, selection, and implementation.
Strengths: clarity, structure, logic, applicability in stable contexts, usefulness in training. Limitations: unrealistic assumptions, bounded rationality, time consumption, neglect of emotions and politics, implementation gap.
2.2 Expected Utility Theory (EUT)
A formal mathematical model by Von Neumann & Morgenstern (1944), prescribing that rational decision-makers choose the option with the highest expected utility (probability × outcome value).
Strengths: normative benchmark, clear axioms, mathematical rigour, foundation for later theories. Limitations: unrealistic assumptions, descriptive inaccuracy, neglect of psychological factors, inability to explain loss aversion, overly mathematical for workplace decisions.
2.3 Bayesian Decision Theory
Bayesian theory describes rational belief-updating under uncertainty using Bayes’ Rule. Savage established the modern framework integrating subjective probabilities and utilities.
Strengths: coherent updating mechanism, flexibility, inclusion of prior knowledge, normative ideal for inference. Limitations: dependence on subjective priors, cognitive unrealism, computational demands, need for high-quality data.
2.4 Multi-Attribute Utility Theory (MAUT)
Used for decisions involving multiple criteria (e.g., hiring, investments). Decision-makers assign weights to attributes and compute total utility scores.
Strengths: systematic structure, explicit trade-offs, transparency, applicability across sectors. Limitations: high cognitive and data demands, subjectivity in weighting, oversimplification, descriptive weakness.
2.5 Multi-Criteria Decision Analysis (MCDA)
A family of practical tools (AHP, ELECTRE, TOPSIS) integrating qualitative and quantitative criteria. Less strictly normative than MAUT, focusing instead on usable decision-support tools.
Strengths: flexibility, ability to handle subjective judgements. Limitations: dependent on methods and weighting approaches.
2.6 Game Theory
Models strategic interactions where outcomes depend on multiple decision-makers. Assumes perfect rationality, complete knowledge, and optimisation of self-interest.
Strengths: strategic insight, equilibrium analysis, applicability in negotiation and organisational strategy. Limitations: unrealistic assumptions, complexity, multiple equilibria, descriptive inaccuracy, neglect of psychology.
3. Behavioural Decision-Making Theories
Behavioural theories describe how real people make choices, highlighting cognitive limitations, emotional influences, social pressures, and imperfect information. They emerged as a corrective to normative theories, explaining systematic departures from rational models.
3.1 Bounded Rationality (Simon, 1957)
Humans are not fully rational. Due to limited information, time, and cognitive resources, people satisfice—choose the first acceptable option rather than optimise.
3.2 Prospect Theory (Kahneman & Tversky, 1979)
People evaluate outcomes relative to a reference point rather than in absolute terms. Key components:
- Loss aversion — losses feel worse than equivalent gains feel good.
- Probability weighting — overweighting unlikely events and underweighting likely ones.
- Explains risk-averse and risk-seeking behaviour in workplace decisions.
3.3 Heuristics and Biases (Tversky & Kahneman, 1974)
Mental shortcuts help simplify complex decisions but cause predictable errors.
- Availability heuristic — judging likelihood based on ease of recall.
- Representativeness — relying on stereotypes instead of data.
- Anchoring — overreliance on initial information.
3.4 Dual-Process Theory
Describes two systems of thinking:
- System 1: fast, intuitive, automatic, emotional.
- System 2: slow, analytical, effortful, logical. Most workplace decisions rely on System 1 unless reflective thinking is deliberately activated.
3.5 Naturalistic Decision-Making (NDM)
Explores decisions in high-pressure, real-world environments (firefighting, military, healthcare). Experts rely on pattern recognition, not formal analysis — recognition-primed decision-making.
3.6 Escalation of Commitment (Staw, 1976)
People continue investing in failing courses of action due to sunk costs, self-justification, and social pressures.
MODULE 4
1. Introduction: Creativity in Organisational Decision-Making
Creativity is presented as a vital complement to analytical reasoning, especially in environments where routine solutions fail. In modern organisations facing volatility, uncertainty, and competition, creativity enhances adaptability, innovation, and problem-solving.
2. Why Creativity Matters in Decision-Making
2.1 Adaptation in a Complex, Changing Environment
- Many organisational challenges are non-routine and cannot be solved using standard procedures.
- Creativity allows decision-makers to design novel responses to unprecedented situations.
- Example: During COVID-19, organisations creatively redesigned operations such as remote work and digital service delivery.
2.2 Expanding the Range of Possible Solutions
- Analytical thinking tends to focus on predictable, conventional options.
- Creativity widens the solution space, enabling unconventional but potentially superior strategies.
- Example: Recruiting internationally to solve talent shortages rather than competing locally.
2.3 Innovation as a Competitive Advantage
- Creative decision-making drives innovation in products, processes, and services.
- Without creativity, decision-making becomes reactive instead of strategic.
- Example: Apple combining usability, design, and technology.
2.4 Overcoming Cognitive and Organizational Biases
- Creativity challenges habitual thinking, functional fixedness, and status quo bias.
- It reframes problems and disrupts assumptions.
- Example: Turning manufacturing waste into a commercial product.
2.5 Enhancing Employee Engagement and Ownership
- Involving teams in creative decision-making strengthens empowerment and motivation.
- Creative involvement increases acceptance of implemented solutions.
2.6 Work Psychology Perspective
Work psychologists design conditions that enable creativity:
- Structured brainstorming free of premature judgment,
- Cross-disciplinary collaboration,
- Rewarding experimentation and learning from failure.
2.7 Case Study: Creative Decision-Making in Employee Retention
A software company facing high turnover applied a creative decision-making workshop instead of standard HR fixes. Process followed the divergent–convergent cycle:
- Preparation – data review and benchmarking.
- Incubation – individual reflection.
- Illumination – breakthrough ideas such as Project Rotation and Innovation Sprints.
- Evaluation – feasibility and cost analysis.
- Implementation – piloting new systems.
Results:
- 40% reduction in turnover,
- Higher engagement,
- New client-ready innovations.
3. Creativity as a Complement to Analytical Thinking
3.1 Understanding the Two Modes
Analytical thinking:
- Logical, structured, linear
- Used for evaluating evidence and narrowing choices Creative thinking:
- Non-linear, associative, imaginative
- Used for generating new possibilities
3.2 Why They Work Best Together
- Creativity without structure → unrealistic ideas.
- Analysis without creativity → predictable, unoriginal solutions.
- Ideal cycle: Divergent thinking → Convergent thinking → Iteration.
3.3 Workplace Examples
Marketing:
- Creative brainstorming → bold campaign ideas.
- Analytical review → selection based on ROI.
HR:
- Creative ideas for employee wellbeing.
- Analytical forecasting of impact on turnover.
3.4 Work Psychology Insight
Teams skilled in switching between divergent and convergent thinking achieve:
- More innovative and feasible outcomes,
- Lower conflict,
- Higher satisfaction with solutions.
3.5 Organisational Applications
- Separate idea-generation from evaluation sessions,
- Combine imaginative and analytical team members,
- Encourage exploratory phases followed by structured planning.
4. Types of Decisions that Benefit from Creativity
4.1 Strategic Decisions
Creative thinking helps envision new markets, products, and long-term opportunities.
4.2 Crisis Problem-Solving
Creativity allows unconventional resource use under constraints.
4.3 Process Improvement
Reimagining workflows and borrowing ideas from unrelated sectors (cross-pollination).
4.4 Employee Engagement
8.2 Brainwriting
Silent idea generation reduces dominance and increases inclusion.
8.3 Mind Mapping
Visual linking enhances associative thinking.
8.4 SCAMPER
Structured prompts to break thinking routines.
8.5 Role Storming / Role Play
Encourages perspective-taking and empathy.
8.6 Incubation
Allow unconscious processing to produce insights.
9. Structured Methods to Generate Innovative Options
9.1 Design Thinking
Empathise → Define → Ideate → Prototype → Test.
9.2 Six Thinking Hats
Systematically separate cognitive roles to prevent groupthink.
9.3 TRIZ
Uses innovation patterns and contradiction resolution.
9.4 Nominal Group Technique
Ensures equal participation and prioritisation.
9.5 Delphi Method
Anonymous expert rounds until consensus is reached.
