Augmented Intelligence
A design pattern that combines human and machine intelligence to enhance decision-making and problem-solving. Important for leveraging AI to support and amplify human capabilities.
299 topics found for:
“decision-making in design”
Moneyball
The practice of using data analytics and metrics to make informed decisions, focusing on measurable outcomes and efficiency rather than intuition or traditional methods. Important for optimizing design processes, improving product performance, and making data-driven decisions that enhance user experience and business success.
Placement Bias
A cognitive bias where people overemphasize information that is placed prominently or in a way that catches their attention first. Crucial for designing interfaces and information displays that manage user attention effectively.
Analytics
The systematic computational analysis of data or statistics to understand and improve business performance. Essential for data-driven decision making in design, product management, and marketing.
Illusory Truth Effect
A cognitive bias where repeated statements are more likely to be perceived as true, regardless of their actual accuracy. Crucial for understanding how repetition influences beliefs and designing communication strategies for users.
Law of the Instrument
Also known as "Maslow's Hammer," a cognitive bias where people rely too heavily on a familiar tool or method, often summarized as "if all you have is a hammer, everything looks like a nail.". Important for designers to recognize and avoid over-reliance on familiar methods in problem-solving and design.
Cost-Benefit
An analysis comparing the costs and benefits of a decision or project to determine its feasibility and value. Important for making informed business and design decisions.
JAD
Joint Application Development (JAD) is a collaborative approach to gathering requirements and designing solutions in software development projects. It facilitates rapid decision-making and consensus-building by bringing together key stakeholders, including users, developers, and project managers, in structured workshop sessions.
Occam’s Razor
A principle that suggests the simplest explanation is often the correct one, favoring solutions that make the fewest assumptions. Crucial for problem-solving and designing straightforward, efficient solutions.
Introspection Illusion
A cognitive bias where people wrongly believe they have direct insight into the origins of their mental states, while treating others' introspections as unreliable. Important for designing experiences that account for discrepancies between user self-perception and actual behavior.
Ostrich Effect
A cognitive bias where people avoid negative information or situations, preferring to remain uninformed or ignore problems. Important for understanding user behavior and designing systems that encourage proactive engagement.
Forecasting
The process of making predictions about future trends based on current and historical data. Useful for anticipating user needs and market trends to inform design decisions.
Data Visualization
The representation of data through graphical elements like charts, graphs, and maps to facilitate understanding and insights. Essential for making complex data accessible and actionable for users.
Negativity Bias
The tendency to give more weight to negative experiences or information than positive ones. Crucial for understanding user behavior and designing systems that balance positive and negative feedback.
Mental Accounting
A behavioral economics concept where people categorize and treat money differently depending on its source or intended use. Crucial for understanding financial behavior and designing systems that align with users' mental accounting practices.
Continued Influence Effect
The persistence of misinformation in memory and influence on reasoning, even after it has been corrected. Crucial for understanding and mitigating the impact of misinformation in design and communication.
Affinity Diagram
A tool used to organize ideas and data into groups based on their natural relationships. Essential for designers and product managers to synthesize information and generate insights.
Information Aversion
The tendency to avoid information that one perceives as potentially negative or anxiety-inducing. Important for designing experiences that encourage information-seeking behavior.
Knowledge Engineering
The process of integrating knowledge into computer systems to solve complex problems, often used in AI development. Important for developing intelligent systems that can perform complex tasks and support decision-making in digital products.
Confidence Interval
A range of values, derived from sample statistics, that is likely to contain the value of an unknown population parameter. Essential for making inferences about population parameters and understanding the precision of estimates in product design analysis.
Restraint Bias
A cognitive bias where individuals overestimate their ability to control impulsive behavior, leading to overexposure to temptations. Important for designing systems that help users manage self-control and avoid overexposure to temptations.
Empathy Gap
A cognitive bias where people underestimate the influence of emotional states on their own and others' behavior. Crucial for designers to account for varying user emotional states in experience design.
Quantitative Research
A research method that focuses on collecting and analyzing numerical data to identify patterns, relationships, and trends, often using surveys or experiments. Essential for making data-driven decisions and validating hypotheses with statistical evidence.
ROI
Return on Investment (ROI) is a performance measure used to evaluate the efficiency or profitability of an investment or compare the efficiency of different investments. Crucial for assessing the financial effectiveness of business decisions, projects, or initiatives.
Information Foraging
The theory that users search for information in a manner similar to animals foraging for food, aiming to maximize value while minimizing effort. Important for designing efficient and user-centered information retrieval systems.
Status Quo Bias
A cognitive bias that leads individuals to prefer things to remain the same rather than change, often resisting new options or changes. Crucial for understanding resistance to change and designing strategies to overcome it among users.
Herd Behavior
The tendency for individuals to mimic the actions of a larger group, often leading to conformity and groupthink. Crucial for understanding social influence and designing experiences that consider group dynamics.
Intention Action Gap
The discrepancy between what people intend to do and what they actually do. Crucial for designing interventions that bridge the gap between user intentions and actions.
Denomination Effect
A cognitive bias where people are less likely to spend large denominations of money compared to an equivalent amount in smaller denominations. Useful for designers to understand consumer behavior and design pricing strategies that consider spending biases.
Familiarity Bias
A cognitive bias where people prefer familiar things over unfamiliar ones, even if the unfamiliar options are objectively better. Useful for designing interfaces and products that leverage familiar elements to enhance user comfort.
STEEPLE Framework
Social, Technological, Economic, Environmental, Political, Legal, and Ethical (STEEPLE) is an analysis tool that examines the factors influencing an organization. Crucial for comprehensive strategic planning and risk management in product design.
Big Data Engineer
A professional who designs, builds, and maintains systems for processing large-scale data sets. Essential for enabling data-driven decision-making and supporting advanced analytics in organizations.
Semmelweis Reflex
A cognitive bias where new evidence or knowledge is automatically rejected because it contradicts established norms or beliefs. Important for recognizing resistance to change and designing strategies to encourage openness to new ideas among designers.
Product Metrics
Quantitative measures used to track and assess the performance and success of a product, such as usage rates, customer satisfaction, and revenue. Essential for making data-driven decisions to improve product performance and achieve business goals.
SCR
Situation-Complication-Resolution (SCR) is a communication and problem-solving framework used to structure information clearly and logically. Crucial for effectively conveying complex ideas and solutions in business and design contexts.
Ingroup Bias
A cognitive bias where people favor members of their own group over those in other groups. Important for designing inclusive and equitable experiences for users.
Outliers
Data points that differ significantly from other observations and may indicate variability in a measurement, experimental errors, or novelty. Crucial for identifying anomalies and ensuring the accuracy and reliability of data in digital product design.
Implementation Intentions
A self-regulation strategy in the form of "if-then" plans that can lead to better goal attainment and behavior change. Useful for designing interventions that promote positive user behaviors.
Value vs. Complexity
A prioritization framework used to assess and compare the value a feature will deliver to users against the complexity and cost of implementing it. Crucial for making informed decisions about feature prioritization and resource allocation.
Top-Down Product Strategy
A strategic approach where decisions and direction are set by top-level management and flow down through the organization, often aligned with overarching business goals. Crucial for ensuring strategic alignment and coherence across all levels of an organization.
Last Touch
The final interaction a customer has with a brand before making a purchase. Important for understanding which touchpoints drive conversions.
Impact Mapping
A strategic planning technique that uses visual maps to align activities with business goals and user needs. Essential for ensuring that development efforts are aligned with strategic objectives.
Liking Principle
A psychological principle where people are more likely to be influenced by those they like. Important for understanding social influences and improving user engagement and marketing strategies.
BPMN
Business Process Model and Notation (BPMN) is a graphical representation for specifying business processes in a workflow, using standardized symbols and notations. Essential for creating clear, standardized diagrams that facilitate understanding and communication of business processes in digital product design.
Human-AI Collaboration
The combined efforts of humans and AI systems to achieve better outcomes than either could alone. Important for leveraging the strengths of both humans and AI in various tasks.
Chaos Theory
The study of dynamic systems that are highly sensitive to initial conditions, leading to unpredictable behavior. Important for recognizing and managing unpredictable elements in design and development processes.
Group Attribution Error
A cognitive bias where people attribute group behavior to the characteristics of the group members rather than the situation. Crucial for understanding team dynamics and avoiding misattribution in collaborative settings.
Law of Diminishing Returns
A principle stating that as investment in a single area increases, the rate of return on that investment eventually decreases. Important for understanding and optimizing resource allocation in product design and development.
Thin Data
Quantitative data that provides broad, numerical insights but often lacks the contextual depth that thick data provides. Useful for capturing high-level trends and patterns, but should be complemented with thick data to gain a deeper understanding of user behavior and motivations.
GIGO
Garbage In-Garbage Out (GIGO) is a principle stating that the quality of output is determined by the quality of the input, especially in computing and data processing. Crucial for ensuring accurate and reliable data inputs in design and decision-making processes.
InfoVis
Information Visualization (InfoVis) is the study and practice of visual representations of abstract data to reinforce human cognition. Crucial for transforming complex data into intuitive visual formats, enabling faster insights and better decision-making.
Pattern Recognition
The ability to identify and interpret patterns in data, often used in machine learning and cognitive psychology. Crucial for designing systems that leverage pattern recognition for predictive analytics and user interactions.
LLM
Large Language Model (LLM) is an advanced artificial intelligence system trained on vast amounts of text data to understand and generate human-like text. Essential for natural language processing tasks, content generation, and enhancing human-computer interactions across various applications in product design and development.
Moral Suasion
The act of persuading individuals or organizations to act in a certain way based on moral arguments or appeals. Useful for designing persuasive communications and ethical influence strategies.
Predictive Analytics
The use of statistical techniques and algorithms to analyze historical data and make predictions about future outcomes. Important for optimizing marketing strategies and anticipating customer needs.
Association Fallacy
A logical fallacy in which it is assumed that qualities of one thing are inherently qualities of another, due to an irrelevant association. Important for avoiding incorrect associations in user research and data interpretation.
Technical Feasibility
The practicality of implementing a solution based on technical constraints and capabilities. Crucial for evaluating the viability of design and development projects.
Longitudinal Study
A research method that involves repeated observations of the same variables over a period of time. Crucial for understanding changes and developments over time.
Scarcity
A psychological principle where people place higher value on objects or opportunities that are perceived to be limited or rare. Important for understanding consumer behavior and designing marketing strategies that leverage perceived scarcity.
Anecdotal Fallacy
A logical fallacy where anecdotal evidence is used to make a broad generalization. Crucial for improving critical thinking and avoiding misleading conclusions.