Zero-Risk Bias
A cognitive bias where people prefer the option that seems to eliminate risk entirely, even if another option offers a greater overall benefit. Important for understanding decision-making and designing risk communication for users.
235 topics found for:
“decision-making process”
Optimism Bias
A cognitive bias that causes people to believe they are less likely to experience negative events and more likely to experience positive events than others. Crucial for understanding user risk perception and designing systems that account for unrealistic optimism.
Regressive Bias
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
Bye-Now Effect
The tendency for people to defer purchasing decisions to a later time, often leading to procrastination. Important for understanding consumer behavior and optimizing sales strategies.
Informational Influence
The change in opinions or behavior that occurs when individuals conform to the information provided by others. Important for understanding social dynamics and designing systems that leverage social proof and peer influence.
Design Tradeoffs
The compromises made between different design options, balancing various factors like usability, aesthetics, and functionality. Essential for making informed decisions that optimize overall design effectiveness.
Reference Dependence
A cognitive bias where individuals evaluate outcomes relative to a reference point rather than on an absolute scale. Essential for understanding decision-making and consumer behavior.
Fallacy of Composition
A logical fallacy that occurs when one assumes that what is true for a part is also true for the whole. Important for avoiding incorrect assumptions in design and decision-making.
Digital Twin
A digital replica of a physical entity, used to simulate, analyze, and optimize real-world operations. Essential for improving operational efficiency and decision-making.
Moral Luck
A phenomenon where the success or failure of a design or business outcome is influenced by external factors beyond the control of the decision-makers, akin to serendipity. Important for recognizing and accounting for external influences in performance evaluations to ensure fair assessments and informed decisions.
Decoy Effect
A cognitive bias where consumers change their preference between two options when presented with a third, less attractive option. Useful for designers to create choice architectures that effectively influence user decisions.
HITL
Human in the Loop (HITL) integrates human judgment into the decision-making process of AI systems. Crucial for ensuring AI reliability and alignment with human values.
Business Analytics
The process of using statistical analysis and modeling to explore and interpret business data to make informed decisions. Essential for improving business performance, identifying opportunities for growth, and driving strategic planning.
Expectation Bias
A cognitive bias where individuals' expectations influence their perceptions and judgments. Relevant for understanding how expectations skew perceptions and decisions among users.
Pessimism Bias
A cognitive bias that causes people to overestimate the likelihood of negative outcomes. Important for understanding user risk perception and designing systems that address irrational pessimism.
Organizational Goals
The strategic objectives that an organization aims to achieve, guiding its operations and decision-making processes. Important for aligning digital product development with the broader mission and objectives of the organization.
Inflection Point
A moment of significant change in a process or system, where the direction of growth, performance, or trend shifts markedly. Important for recognizing critical transitions in design or business strategies, enabling timely adjustments and informed decision-making.
Loss Aversion
A cognitive bias where the pain of losing is psychologically more powerful than the pleasure of gaining. Important for designing user experiences that account for and mitigate loss aversion.
CoD
Cost of Delay (CoD) is a metric that quantifies the economic impact of delaying a project, feature, or task. Important for making informed decisions about project prioritization and resource allocation.
Identity Priming
The process of triggering particular aspects of a person's identity to influence their behavior or decisions. Important for designing personalized and effective user experiences.
Goldilocks Effect
The psychological phenomenon where people prefer options that are not too extreme, but just right. Crucial for designing products and experiences that cater to the majority preference.
Probability Matching
A decision-making strategy where individuals allocate resources proportionally to the probability of an outcome occurring, rather than optimizing the most likely outcome. Important for understanding decision-making behaviors and designing systems that guide better resource allocation.
Representativeness
Representativeness is a heuristic in decision-making where individuals judge the probability of an event based on how much it resembles a typical case. Crucial for understanding biases in human judgment and improving decision-making processes.
Allais Paradox
A decision-making paradox that shows people's preferences can violate the expected utility theory, highlighting irrational behavior. Important for understanding inconsistencies in user decision-making and designing better user experiences.
Base Rate Fallacy
A cognitive bias where people ignore general statistical information in favor of specific information. Critical for designers to use general statistical information to improve decision-making accuracy and avoid bias.
Ambiguity Effect
A cognitive bias where decision-making is affected by the lack of information or uncertainty. Important for understanding and mitigating user decision-making biases due to uncertainty or lack of information.
Sunk Cost Fallacy
The tendency for individuals to continue a behavior or endeavor as a result of previously invested resources (time, money, or effort) rather than future potential benefits. Important for understanding decision-making biases and designing systems that help users avoid irrational persistence.
Irrational Escalation
The phenomenon where people continue a failing course of action due to the amount of resources already invested. Important for recognizing and mitigating biased decision-making.
Availability Bias
A cognitive bias where people overestimate the importance of information that is readily available. Essential for designers to understand and mitigate how easily accessible information can disproportionately influence decisions.
Dual Self Model
A behavioral economics model that explains decision-making as a conflict between a present-oriented "doer" and a future-oriented "planner". Useful for understanding user decision-making and designing interventions that balance short-term and long-term goals.
Behavioral Strategy
The use of behavioral science insights to inform and guide strategic decision-making in organizations. Crucial for developing strategies that effectively influence behavior and drive business success.
Myopic Loss Aversion
A cognitive bias where individuals tend to avoid risks when they perceive potential losses more acutely than potential gains. Important for understanding decision-making behavior in users and designing systems that mitigate risk aversion.
Category Size Bias
A cognitive bias where people judge the likelihood of an event based on the size of its category rather than its actual probability. Crucial for designers to understand how category size influences user perception and decision-making processes.
Egocentric Bias
A cognitive bias where people rely too heavily on their own perspective and experiences when making decisions. Important for designers to recognize and mitigate their own perspectives influencing design decisions.
Surrogation
The process by which a measure or metric comes to replace the underlying objective it is intended to represent, leading to distorted decision-making. Important for ensuring that metrics accurately reflect true objectives and designing systems that prevent metric manipulation.
Naive Allocation
A heuristic where individuals evenly distribute resources across all options, regardless of their specific needs or potential. Useful for understanding and designing around simplistic decision-making strategies.
Conjunction Fallacy
A logical fallacy where people assume that specific conditions are more probable than a single general one. Important for understanding and addressing cognitive biases in user behavior.
Ratio Bias
A cognitive bias where people judge the likelihood of an event based on its relative size rather than absolute probability. Important for understanding user decision-making biases and designing systems that present information accurately.
Subadditivity Effect
A cognitive bias where the total probability assigned to a set of events is less than the sum of the probabilities assigned to each event individually. Important for understanding how users estimate probabilities and make decisions under uncertainty.
Salience Bias
A cognitive bias where people focus on the most noticeable or prominent information while ignoring less conspicuous details. Important for understanding user decision-making and ensuring balanced presentation of information.
Behavioral Finance
The study of how psychological influences affect financial behaviors and decision-making. Essential for understanding and influencing financial decision-making and behavior.
Placing Bets
A strategic approach where multiple potential solutions are tested to identify the most promising one. Crucial for innovation and reducing risk in decision-making.
Extension Neglect
A cognitive bias where people ignore the relevance of sample size in making judgments, often leading to erroneous conclusions. Crucial for designers to account for appropriate sample sizes in research and analysis.
Survivorship Bias
A cognitive bias that occurs when conclusions are drawn from a non-representative sample, focusing only on successful cases and ignoring failures. Crucial for making accurate assessments and designing systems that consider both successes and failures.
RICE Scoring Model
A prioritization framework used in product management to evaluate features based on Reach, Impact, Confidence, and Effort. Crucial for making informed decisions about which product features to prioritize and develop.
SWOT Analysis
Strengths, Weaknesses, Opportunities, and Threats (SWOT) is a strategic planning tool that is applied to a business or project. Essential for strategic planning and decision-making.
Bikeshedding
Also known as Parkinson's Law of Triviality, is the tendency to spend excessive time on trivial details while neglecting more important issues. Crucial for improving project management and team efficiency.
XAI
Explainable AI (XAI) are AI systems that provide clear and understandable explanations for their decisions and actions. This transparency is crucial for building trust and confidence in AI applications across various domains.
Competitive Intelligence
The process of gathering and analyzing information about competitors to inform business strategy and decision-making. Essential for understanding market positioning and developing effective competitive strategies.
ICE Scoring Model
Impact, Confidence, and Ease of implementation (ICE) is a prioritization framework used in product management to evaluate features. Essential for making informed and strategic decisions about feature development and prioritization.
Machine Learning
A type of artificial intelligence that enables systems to learn from data and improve over time without being explicitly programmed. Crucial for developing intelligent systems that can make data-driven decisions.
BI
Business Intelligence (BI) encompasses technologies, applications, and practices for the collection, integration, analysis, and presentation of business information. Crucial for making data-driven decisions and improving business performance.
Homo Economicus
A theoretical concept in economics that portrays humans as rational and self-interested agents who aim to maximize their utility. Important for understanding economic decision-making and designing systems that align with rational behavior.
Affective Forecasting
The process of predicting how one will feel in the future, which often involves biases and inaccuracies. Important for understanding user behavior and decision-making, aiding in the design of better user experiences.
ZMOT
Zero Moment of Truth (ZMOT) is a concept in marketing that refers to the point in the buying cycle when the consumer researches a product before the seller even knows they exist. Crucial for understanding consumer behavior and optimizing marketing strategies to influence decision-making at this early stage.
Confirmation Bias
The tendency to search for, interpret, and remember information in a way that confirms one's preexisting beliefs or hypotheses. Crucial for understanding cognitive biases that affect user decision-making and designing interventions to mitigate them.
Belief Perseverance
The tendency to cling to one's beliefs even in the face of contradictory evidence. Important for understanding resistance to change and designing interventions that address this bias.
Game Theory
A mathematical framework used to analyze strategic interactions where the outcomes depend on the actions of multiple decision-makers. Useful for designing systems and processes that involve competitive or cooperative interactions.
Optimization Theory
The study of finding the best solution from a set of feasible solutions. Crucial for improving efficiency and performance in design and development processes.
Attribution Theory
A theory that explains how individuals determine the causes of behavior and events, including the distinction between internal and external attributions. Crucial for understanding user behavior and designing experiences that address both internal and external factors.