2.2 How the Brain Processes Information to Make Decisions: Reflective and Reactive Systems
3 min read•june 24, 2024
Our brains have two decision-making systems: reflective and reactive. The is slow and deliberate, using rational analysis for complex problems. The is fast and automatic, relying on instincts and emotions for quick decisions.
Emotions play a big role in how we make choices. Positive emotions can boost creativity and risk-taking, while negative emotions can make us more cautious. Managers need to balance both systems, using reflection for important decisions and trusting instincts when time is short.
Brain's Decision-Making Systems
Reflective vs reactive decision-making
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Frontiers | The Neural Correlates of Consciousness and Attention: Two Sister Processes of the Brain View original
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Biology of Emotion | Boundless Psychology View original
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Top images from around the web for Reflective vs reactive decision-making
Frontiers | The Neural Correlates of Consciousness and Attention: Two Sister Processes of the Brain View original
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Structure and Function of the Brain | Boundless Psychology View original
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Biology of Emotion | Boundless Psychology View original
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Frontiers | The Neural Correlates of Consciousness and Attention: Two Sister Processes of the Brain View original
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Structure and Function of the Brain | Boundless Psychology View original
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Reflective system engages in slow, deliberate, and conscious processing of information (complex problem-solving)
Conducts rational analysis of available data and options
Considers potential long-term consequences and implications
Involves higher primarily in the
Utilizes to plan, organize, and regulate behavior
Reactive system operates through fast, automatic, and unconscious processing ()
Relies heavily on , mental shortcuts, and intuitive judgments
Focuses on immediate rewards and short-term outcomes ()
Driven by emotions, instincts, and learned associations
Involves structures such as the (fear response)
Emotions in decision processes
Emotions can bias decision-making by overriding rational analysis in favor of gut feelings (fear leading to )
Amplify the perceived benefits and desirability of short-term rewards
Minimize the perceived risks and potential negative consequences
Positive emotions (excitement, optimism) can lead to:
Increased risk-taking behavior and boldness in choices
Greater creativity, openness to new ideas, and willingness to explore alternatives
Enhanced problem-solving abilities and
Negative emotions (anxiety, anger) can result in:
Avoidance of risk and preference for safer, more conservative options
Narrowed focus, tunnel vision, and reduced capacity for creative thinking
Impaired decision-making quality, accuracy, and outcomes
Dual-Process Theory and Cognitive Biases
explains decision-making through
System 1: Fast, intuitive, and automatic (reactive system)
System 2: Slow, deliberate, and analytical (reflective system)
can influence decision-making processes
These mental shortcuts can lead to systematic deviations from rational judgment
Examples include confirmation bias, anchoring, and availability heuristic
allows the brain to adapt and change decision-making patterns over time
can occur after making many decisions, leading to poorer quality choices
Managerial Applications
Managerial use of decision approaches
Reflective decision-making is best suited for complex, high-stakes decisions with long-term implications ()
Situations where ample time, information, and resources are available
Systematic problem-solving, , and forecasting
Reactive decision-making can be effective in time-sensitive situations requiring quick action ()
Familiar or routine decision contexts where past experience is relevant
Circumstances where limited information or cognitive resources are available
Managers should strive to balance reflective and reactive approaches by:
Recognizing their own emotional biases and how they impact decisions
Deliberately engaging the reflective system for important choices
Trusting instincts when appropriate, but not relying on them exclusively
Seeking diverse perspectives to challenge assumptions and blind spots (team input)
Continuously learning from past decisions to refine future decision-making processes