Decision Staging
The process of breaking down decisions into smaller, manageable stages to simplify the decision-making process. Useful for guiding users through complex decisions in a structured manner.
156 topics found for:
“decision-making support”
System Two
A mode of thinking, derived from Dual Process Theory, that is slow, deliberate, and analytical, requiring more cognitive effort and conscious reasoning. Crucial for designing complex tasks and interfaces that require thoughtful decision-making and problem-solving, ensuring they are clear and logical for users.
Take the Best Heuristic
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.
Critical Thinking
The objective analysis and evaluation of an issue in order to form a judgment. Essential for making informed and rational design decisions.
OODA Loop
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.
Weighted Scoring
A prioritization method that assigns different weights to criteria based on their importance, helping to make informed decisions and prioritize tasks effectively. Crucial for making objective and balanced decisions in project management and product development.
McNamara Fallacy
The error of making decisions based solely on quantitative observations and ignoring all other factors. Important for ensuring a holistic approach to decision-making.
Bounded Rationality
A concept that humans make decisions within the limits of their knowledge, cognitive capacity, and available time, leading to satisficing rather than optimal solutions. Crucial for designing systems and processes that account for human cognitive limitations and decision-making processes.
Delphi Method
A structured communication technique originally developed as a systematic, interactive forecasting method which relies on a panel of experts. Important for gathering expert opinions and making informed decisions.
Fast and Frugal Heuristics
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.
Availability Heuristic
A mental shortcut that relies on immediate examples that come to mind when evaluating a specific topic, concept, method, or decision. Crucial for understanding how people make decisions and the biases that influence their choices.
DACI Framework
Drivers, Approvers, Contributors, and Informed (DACI) is a responsibility assignment framework that clarifies roles and responsibilities. Essential for making clear and effective decisions in collaborative environments.
Executive Function
A set of cognitive processes that include working memory, flexible thinking, and self-control, crucial for planning, decision-making, and behavior regulation. Crucial for designing interfaces and experiences that support users' cognitive abilities.
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.
Friction
Elements in a process that cause resistance or slow down user actions, which can lead to frustration or be used intentionally to prevent errors and encourage deliberate actions. Important for recognizing both the negative impact of unnecessary delays and the positive use of intentional friction to enhance user decision-making and reduce errors.
Standard Deviation
A statistical measure that quantifies the amount of variation or dispersion of a set of data values. Essential for understanding data spread and variability, which helps in making informed decisions in product design and analysis.
Decision Theory
The study of how individuals make choices among alternatives and the principles that guide these choices. Important for designing decision-making processes and interfaces that help users make informed choices.
Illusion of Validity
A cognitive bias where individuals overestimate the accuracy of their judgments, especially when they have a lot of information. Important for understanding and mitigating overconfidence in user decision-making.
Opportunity Cost Neglect
A cognitive bias where individuals overlook or underestimate the cost of opportunities they forego when making decisions. Crucial for understanding user decision-making behavior and designing systems that highlight opportunity costs.
Decision Paralysis
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.
Decision Fatigue
The deteriorating quality of decisions made by an individual after a long session of decision making, due to mental exhaustion. Important for designing interfaces that minimize cognitive load and simplify decision processes.
Fist To Five
A consensus-building technique where participants show their level of agreement or support by raising zero to five fingers. Useful for quickly gauging team agreement and making collaborative decisions in product design and development meetings.
Information Bias
A cognitive bias where people seek out more information than is needed to make a decision, often leading to analysis paralysis. Crucial for designing decision-making processes that avoid information overload for users.
Intertemporal Choice
The study of how people make choices about what and how much to do at various points in time, often involving trade-offs between costs and benefits occurring at different times. Crucial for designing systems that account for delayed gratification and long-term planning.
Escalation of Commitment
A cognitive bias where individuals or organizations continue to invest in a failing project or decision due to the amount of resources already committed. Important for designers to recognize and mitigate their own risks of continuing unsuccessful initiatives.
Dual Process Theory
A framework suggesting there are two systems of thinking: System 1 (fast, automatic) and System 2 (slow, deliberate), influencing decision-making and behavior. Crucial for understanding how users process information and make decisions.
Risk-as-Feelings Theory
A theory that emphasizes the role of emotions in risk perception and decision-making, where feelings about risk often diverge from cognitive assessments. Important for designing systems that account for emotional responses to risk and improve decision-making.
Overconfidence Effect
A cognitive bias where a person's subjective confidence in their judgments is greater than their objective accuracy. Crucial for understanding user decision-making and designing systems that account for overconfidence.
Scenario Mapping
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.
Priming
A psychological effect where exposure to one stimulus influences the response to a subsequent stimulus, without conscious guidance or intention. Crucial for designing experiences that subtly guide user behavior and decision-making.
Monte Carlo Simulation
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.
Crystallized Intelligence
The ability to use learned knowledge and experience, often increasing with age and accumulated learning. Important for understanding how expertise and knowledge accumulation impact design and decision-making.
Convergent Thinking
A cognitive process where ideas are brought together to find a single, best solution to a problem. Important for problem-solving and decision-making in design processes.
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.
Prioritization Matrix
A decision-making tool that helps prioritize tasks or projects based on specific criteria, such as impact and effort. Essential for effective project management and resource allocation.
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.
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.
Framing Bias
A cognitive bias where people's decisions are influenced by how information is presented rather than just the information itself. Crucial for designers to minimize bias in how information is presented to users.
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.
Preference Reversal
A phenomenon where individuals' preferences between options change when the options are presented in different ways or contexts. Important for understanding and designing around inconsistencies in user choices.
BRE
Business Rules Engine (BRE) is a software system that executes one or more business rules in a runtime production environment. Crucial for automating decision-making processes and ensuring consistency and compliance in digital products.
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.
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.
Less Is Better Effect
A cognitive bias where people prefer a smaller set of higher-quality options over a larger set with lower overall quality. Useful for designing product offerings and experiences that emphasize quality over quantity for users.
Principle of Choices
The Principle of Choices is an information architecture guideline that emphasizes providing users with meaningful options to navigate and interact with a system. Crucial for enhancing user experience by ensuring users can easily find what they need without being overwhelmed.
User Autonomy
The degree to which users feel they have control over their actions and decisions when interacting with a product or system. Crucial for designing systems that empower users and enhance their sense of control and satisfaction.
Information Processing
The series of actions or operations involved in the acquisition, interpretation, storage, and retrieval of information. Crucial for understanding how users handle information and designing systems that align with cognitive processes.
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.
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.
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.
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.
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.
Active Choice
A decision-making strategy where individuals are prompted to make a choice rather than defaulting to a pre-set option. Useful for increasing user engagement and ensuring intentional decision-making.
Gambler’s Fallacy
A cognitive bias where individuals believe that past random events affect the probabilities of future random events. Important for designers to understand user decision-making biases related to randomness.
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.
Choice-Supportive Bias
The tendency to attribute positive qualities to one's own choices and downplay the negatives, enhancing post-decision satisfaction. Useful for understanding user satisfaction and designing experiences that reinforce positive decision outcomes.
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.
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.