Systems Theory
An interdisciplinary study of systems, examining the complex interactions and relationships between components within a whole. Crucial for understanding and designing complex, interconnected systems.
An interdisciplinary study of systems, examining the complex interactions and relationships between components within a whole. Crucial for understanding and designing complex, interconnected systems.
A holistic approach to analysis that focuses on the way that a system's constituent parts interrelate and how systems work over time and within the context of larger systems. Essential for solving complex problems and designing systems that account for interdependencies and dynamics.
The study of complex systems and how interactions within these systems give rise to collective behaviors. Useful for understanding and managing the complexity in design processes and systems.
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.
The study of the relationships between people, practices, values, and technologies within an information environment. Helps in understanding and designing systems that are sustainable and adaptive to human and environmental changes.
A mode of thinking, derived from Dual Process Theory, that is fast, automatic, and intuitive, often relying on heuristics and immediate impressions. Important for understanding how users make quick decisions and respond to design elements instinctively, aiding in the creation of intuitive and user-friendly interfaces.
A problem-solving process that includes logical reasoning, pattern recognition, abstraction, and algorithmic thinking. Important for developing efficient and effective solutions in digital product design and development.
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.
A methodology for creating design systems by breaking down interfaces into their basic components (atoms, molecules, organisms, templates, and pages). Essential for creating scalable and maintainable design systems.
Case-Based Reasoning (CBR) is an AI method that solves new problems based on the solutions of similar past problems. This approach is essential for developing intelligent systems that learn from past experiences to improve problem-solving capabilities.
A cognitive bias where individuals give stronger weight to payoffs that are closer to the present time compared to those in the future. Important for understanding user time-related decision-making and designing systems that encourage long-term thinking.
A model by Don Norman outlining the cognitive steps users take when interacting with a system: goal formation, planning, specifying, performing, perceiving, interpreting, and comparing. Important for designing user-friendly and effective products by understanding and supporting user behavior at each stage.
The structural design of a product, defining its components, their relationships, and how they interact to fulfill the product's purpose. Important for ensuring that a product is well-organized, scalable, and maintainable.
Elements of a service or product that are not visible to the user but are essential for delivering the front-stage experience. Crucial for understanding and designing the full user experience, including behind-the-scenes elements.
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.
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.
A test proposed by Alan Turing to determine if a machine's behavior is indistinguishable from that of a human. Important for evaluating the intelligence of AI systems.
A problem-solving method that explores all possible solutions by examining the structure and relationships of different variables. Useful for generating innovative design solutions and exploring a wide range of possibilities in digital product development.
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.
The process of anticipating future developments to ensure that a product or system remains relevant and functional over time. Essential for designing durable and adaptable products.
The practice of guiding and inspiring teams to create effective, user-centered design solutions that align with business goals. Crucial for fostering a culture of innovation, collaboration, and excellence in design practices within organizations.
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.
The level of sophistication and integration of design practices within an organization's processes and culture. Essential for assessing and improving the effectiveness of design in driving business value and innovation.
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.
A problem-solving method that involves asking "why" five times to identify the root cause of a problem. Useful for designers and product managers to uncover underlying issues and improve processes and solutions.
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.
A repository for team members to submit and collect innovative ideas, reflecting a commitment to fostering creativity and shared ownership of product development. Crucial for maintaining an open culture of innovation and capturing diverse perspectives that contribute to the product's evolution and success.
A mindset and approach that embodies the entrepreneurial spirit, passion for improvement, and deep sense of ownership typically associated with a company's founders. Essential for maintaining agility, innovation, and customer-centricity as organizations grow and mature.
A project or venture that starts from scratch, with no constraints imposed by prior work, enabling innovation and flexibility in development. Essential for recognizing opportunities for innovation and fresh development in business initiatives.
A strategic research process that involves evaluating competitors' products, services, and market positions to identify opportunities and threats. Essential for informing product strategy, differentiating offerings, and gaining a competitive advantage in the market.
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.
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.
New Product Development (NPD) is the complete process of bringing a new product to market, from idea generation to commercialization. Essential for companies to innovate, stay competitive, and meet evolving customer needs through a structured approach to creating and launching new offerings.
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.