Risk Taxonomy
A structured classification of risks into categories, helping organizations identify, assess, and manage different types of risks. Important for understanding and managing risks effectively within an organization.
61 topics found for:
“risk mitigation”
Operational Risk
The risk of loss resulting from inadequate or failed internal processes, people, and systems. Important for identifying and mitigating potential operational threats.
Swiss Cheese Model
A risk management model that illustrates how multiple layers of defense (like slices of Swiss cheese) can prevent failures, despite each layer having its own weaknesses. Crucial for understanding and mitigating risks in complex systems.
Risk Management
The process of identifying, assessing, and mitigating potential threats that could impact the success of a digital product, including usability issues, technical failures, and user data security. Essential for maintaining product reliability, user satisfaction, and data protection, while minimizing the impact of potential design and development challenges.
Feasibility Risk
The risk that the product cannot be built as envisioned due to technical limitations, resource constraints, or other practical challenges. Important for confirming that the product can be realistically developed and deployed with the available technology and resources.
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.
Peltzman Effect
The hypothesis that safety measures may lead to behavioral changes that offset the benefits of the measures, potentially leading to risk compensation. Crucial for understanding risk behavior and designing systems that account for compensatory behaviors.
Groupshift
A phenomenon where group members make decisions that are more extreme than the initial inclination of its members due to group discussions and interactions. Crucial for understanding and mitigating the risks of extreme decision-making in group settings.
Canary Testing
A deployment strategy where a new version is released to a small subset of users to detect any issues before a full rollout. Crucial for minimizing risk and ensuring the stability of digital products during updates and deployments.
Crisis-Response Design
Designing systems and processes to effectively respond to and manage crises, ensuring resilience and quick recovery. Crucial for preparing for unexpected events and minimizing their impact.
Usability Risk
The risk that users will find the product difficult or confusing to use, preventing them from effectively utilizing its features. Crucial for making sure the product is user-friendly and intuitive, enhancing the user experience and adoption.
Viability Risk
The risk that the product will not be financially or strategically sustainable for the business, potentially leading to a lack of support or profitability. Essential for ensuring that the product aligns with business goals and can be maintained and supported long-term.
Normalcy Bias
The tendency to believe that things will always function the way they normally have, often leading to underestimation of disaster risks. Important for understanding risk perception and designing systems that effectively communicate potential changes.
TRiSM
Trust, Risk, and Security Management (TRiSM) is a framework for managing the trust, risk, and security of AI systems to ensure they are safe, reliable, and ethical. Essential for ensuring the responsible deployment and management of AI technologies.
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.
Regret Aversion
A tendency to avoid making decisions that might lead to regret, influencing risk-taking and decision-making behaviors. Crucial for understanding decision-making processes and designing systems that minimize regret.
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.
Dependency Management
The process of identifying, assessing, and controlling dependencies between tasks or projects to minimize risks and ensure smooth project execution. Crucial for effective project management and delivery.
Planning Fallacy
A cognitive bias where individuals underestimate the time, costs, and risks of future actions while overestimating the benefits. Important for realistic project planning and setting achievable goals for designers.
Groupthink
A psychological phenomenon where the desire for harmony and conformity in a group results in irrational or dysfunctional decision-making. Crucial for recognizing and mitigating the risks of poor decision-making in teams.
Winner’s Curse
A phenomenon where the winner of an auction tends to overpay due to emotional competition, leading to a less favorable outcome than anticipated. Important for understanding decision-making biases and designing systems that mitigate overbidding risks.
Pilot
A preliminary version of a project or system used to test and validate its feasibility before full-scale implementation. Crucial for identifying potential issues and making necessary adjustments to improve the final product.
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.
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.
Negative Float
A scheduling term that indicates a delay in the project timeline that cannot be recovered. Important for identifying and addressing potential project delays, ensuring timely delivery of digital products.
Project Management
The abilities and knowledge required to effectively plan, execute, and close projects, including leadership, communication, time management, and risk management. Essential for ensuring successful project outcomes and achieving business objectives.
Red Teaming
A strategy where a team plays the role of an adversary to identify vulnerabilities and improve the security and robustness of a system. Crucial for testing the resilience of digital products and identifying areas for improvement.
Pseudocertainty Effect
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.
Certainty Effect
A cognitive bias where people give greater weight to outcomes that are certain compared to those that are merely probable. Important for designers to consider how users weigh certain outcomes more heavily in their decision-making.
Assumed Similarity Bias
A cognitive bias where people assume others share the same beliefs, values, or preferences as themselves. Important for helping designers avoid projecting their own biases and assumptions onto users during research and design.
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.
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.
Scaling Fallacy
A cognitive bias where people underestimate the complexity and challenges involved in scaling systems, processes, or businesses. Important for understanding the difficulties of scaling and designing systems that address these challenges.
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.
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.
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.
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.
Value Risk
The risk that the product being developed will not deliver sufficient value to the users, meaning it won't meet their needs or solve their problems. Critical for ensuring the product will be desirable and valuable to the users, which is essential for its success.
KYC
Know Your Customer (KYC) is a process used by businesses to verify the identity of their clients and assess potential risks of illegal intentions for the business relationship. Essential for preventing fraud, money laundering, and terrorist financing, particularly in financial services, while also ensuring compliance with regulatory requirements and building trust with customers.
Compliance
Adhering to laws, regulations, and guidelines relevant to business operations and product development. Crucial for ensuring products and practices meet legal and ethical standards.
Feature Flag
A technique used in software development to enable or disable features in a production environment without deploying new code, allowing for controlled feature rollouts. Essential for managing feature releases and testing in live environments.
Hofstadter’s Law
A principle that states tasks always take longer than expected, even when considering Hofstadter's Law itself. Important for setting realistic project timelines and managing expectations in digital product development.
Ethical AI Frameworks
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible. Crucial for building trust and ensuring the responsible use of AI technologies.
Market Validation
The process of determining whether there is a need or demand for a product in the target market, often through testing and feedback. Crucial for ensuring that a product will meet market needs and be successful.
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.
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.
Prompt Defense
A method used in AI and machine learning to ensure prompts and inputs are designed to produce the desired outcomes. Essential for improving the accuracy and relevance of AI responses.
Design Debt
The accumulated consequences of poor design decisions, which can hinder future development and usability. Crucial for understanding and addressing the long-term impact of design choices.
Project Manager
A professional responsible for planning, executing, and closing projects, ensuring they are completed on time, within scope, and on budget. Crucial for managing project activities and ensuring successful delivery of project goals.
Business Viability
The potential for a project or solution to be economically sustainable and profitable. Important for ensuring that design and development efforts align with business goals and market demands.
ASI
Artificial Superintelligence (ASI) is a hypothetical AI that surpasses human intelligence and capability in all areas. Important for understanding the potential future impacts and ethical considerations of AI development.
House of Brands
A brand architecture strategy where multiple distinct brands are managed under a single parent company. Crucial for managing diverse product lines and maximizing market reach.
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.
Stakeholder Management
The systematic identification, analysis, planning, and implementation of actions designed to engage and influence stakeholders in a project. Crucial for maintaining positive relationships and ensuring stakeholder support throughout the project lifecycle.
Scope Creep
Also known as feature creep, the continuous addition of new features to a product, often beyond the original scope, leading to project delays and resource strain. Important for managing project scope and ensuring timely delivery.
Projection Bias
The tendency to overestimate how much our future preferences and behaviors will align with our current preferences and behaviors. Important for understanding user behavior and designing experiences that account for changes over time.
Product Launch Management
The comprehensive process of planning, executing, and overseeing all activities related to the introduction of a new product to the market. Crucial for coordinating efforts to ensure a successful product launch and achieving market impact.
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.
ARA
Application Release Automation (ARA) is the process of automating the release of applications, ensuring consistency and reducing errors. Crucial for accelerating the delivery of software updates and maintaining high-quality digital products.
UCD
User-Centered Design (UCD) is an iterative design approach that focuses on understanding users' needs, preferences, and limitations throughout the design process. Crucial for creating products that are intuitive, efficient, and satisfying for the intended users.