A decision-making rule where individuals choose the option with the highest perceived value based on the first good reason that comes to mind, ignoring other information. Crucial for understanding and designing for quick decision-making processes.
Observe, Orient, Decide, and Act (OODA) is a decision-making framework often used in strategic planning and rapid response situations. Crucial for agile decision-making and strategic planning in dynamic environments.
A cognitive bias where individuals overestimate the likelihood of extreme events regressing to the mean. Crucial for understanding decision-making and judgment under uncertainty.
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.
Decision-making strategies that use simple heuristics to make quick, efficient, and satisfactory choices with limited information. Important for designing user experiences that support quick and efficient decision-making.
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.
A state of overthinking and indecision that prevents making a choice, often due to too many options or uncertainty. Important for designing interfaces that simplify decision-making processes for users.
A theory in economics that models how rational individuals make decisions under risk by maximizing the expected utility of their choices. Essential for understanding decision-making under risk.
A method used to create detailed narratives of potential future events to explore and understand possible outcomes and inform decision-making. Essential for strategic planning and anticipating the impact of different decisions or changes.
A cognitive bias where people perceive an outcome as certain while it is actually uncertain, based on how information is presented. Crucial for understanding and mitigating biased user decision-making.
A statistical technique that uses random sampling and statistical modeling to estimate mathematical functions and simulate systems. Useful for risk assessment, decision-making, and performance optimization in digital product design.
A cognitive bias where people perceive past events as having been more predictable than they actually were. Important for understanding and mitigating biases in user feedback and decision-making.
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.
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.
A motivational theory suggesting that individuals are motivated to act based on the expected outcomes of their actions and the attractiveness of those outcomes. Important for understanding motivation and behavior, distinct from decision-making under uncertainty.
A theory that describes how individuals pursue goals using either a promotion focus (seeking gains) or a prevention focus (avoiding losses). Crucial for designing motivation strategies and understanding user behavior in goal pursuit.
Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) is an acronym for describing the challenging conditions of the modern world. Important for understanding and navigating dynamic and unpredictable environments.
A short, time-boxed period used in Agile development to research a concept or explore a new technology. Important for reducing uncertainty and risk in development.