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.
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.
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.
Total Quality Management (TQM) is a comprehensive management approach focused on continuous improvement in all aspects of an organization. Essential for ensuring high-quality products and services and achieving customer satisfaction.
A statistical rule stating that nearly all values in a normal distribution (99.7%) lie within three standard deviations (sigma) of the mean. Important for identifying outliers and understanding variability in data, aiding in quality control and performance assessment in digital product design.
A data-driven methodology aimed at improving processes by identifying and removing defects, and reducing variability. Crucial for enhancing the quality and efficiency of digital product development processes.
The process of identifying unusual patterns or outliers in data that do not conform to expected behavior. Crucial for detecting fraud, errors, or other significant deviations in various contexts.
Define, Measure, Analyze, Improve, and Control (DMAIC) is a data-driven improvement cycle used in Six Sigma. Crucial for systematically improving processes and ensuring quality in digital product development.
A statistical phenomenon where a large number of hypotheses are tested, increasing the chance of a rare event being observed. Crucial for understanding and avoiding false positives in data analysis.
The use of algorithms to generate new data samples that resemble a training dataset, often used in AI for creating realistic outputs. Important for developing creative and innovative solutions in digital product design, such as content generation and simulation.
Also known as the 68-95-99.7 Rule, it states that for a normal distribution, nearly all data will fall within three standard deviations of the mean. Important for understanding the distribution of data and making predictions about data behavior in digital product design.
The error of making decisions based solely on quantitative observations and ignoring all other factors. Important for ensuring a holistic approach to decision-making.
A tendency for respondents to answer questions in a manner that is not truthful or accurate, often influenced by social desirability or survey design. Important for understanding and mitigating biases in survey and research data.
Plan-Do-Check-Act (PDCA) is an iterative four-step management method used for continuous improvement of processes and products. Essential for quality control and operational efficiency.
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.
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.
A set of fundamental principles and guidelines that inform and shape user research practices. Crucial for maintaining consistency and ensuring high-quality user insights.
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.
Quality Function Deployment (QFD) is a method used to transform customer needs into engineering characteristics for a product or service. Essential for ensuring that customer requirements are systematically incorporated into the design and development process.
The ability to deliver products or services in the most cost-effective manner without sacrificing quality. Key to reducing costs and improving profitability.
A type of artificial intelligence capable of generating new content, such as text, images, and music, by learning from existing data. Important for automating creative processes and generating novel outputs.
An algorithm used by Google Search to rank web pages in their search engine results, based on the number and quality of links to a page. Essential for understanding search engine optimization and improving website visibility.
A statistical theory that states that the distribution of sample means approximates a normal distribution as the sample size becomes larger, regardless of the population's distribution. Important for making inferences about population parameters and ensuring the validity of statistical tests in digital product design.
The characteristics and qualities that define a brand and distinguish it from competitors. Essential for creating a unique brand identity and guiding brand communications.
Crit (Design Critique) is a structured feedback session where designers present their work and receive constructive feedback from peers. Essential for refining design quality through collaborative input.
The extent to which a measure represents all facets of a given construct, ensuring the content covers all relevant aspects. Important for ensuring that assessments and content accurately reflect the intended subject matter.
The process of comparing design metrics to historical performance, competitive standards, or industry best practices to identify areas for improvement. Crucial for measuring progress, improving practice maturity, and evaluating competitive differentiation.
A Japanese word meaning inconsistency or variability in processes. Helps in recognizing and addressing workflow imbalances to improve efficiency.
The principle that the more a metric is used to make decisions, the more it will be subject to corruption and distort the processes it is intended to monitor. Important for understanding the limitations and potential distortions of metrics in design and evaluation.
Marketing Qualified Lead (MQL) is a prospective customer who has shown interest in a company's product or service and meets specific criteria indicating a higher likelihood of becoming a customer. Essential for prioritizing leads and optimizing the efficiency of sales and marketing efforts by focusing resources on prospects most likely to convert.
Capability Maturity Model (CMM) is a framework for improving and optimizing processes within an organization. Essential for assessing and enhancing the maturity and efficiency of processes in product design and development.
The process of generating a broad set of ideas on a given topic, with no attempt to judge or evaluate them initially. Crucial for creative problem-solving and developing innovative solutions in product design and development.
Voice of the Customer (VOC) is a process for capturing customers' expectations, preferences, and aversions. Crucial for guiding product development and improving customer satisfaction.
The process of self-examination and adaptation in AI systems, where models evaluate and improve their own outputs or behaviors based on feedback. Crucial for enhancing the performance and reliability of AI-driven design solutions by fostering continuous learning and improvement.
Retrieval-Augmented Generation (RAG) is an AI approach that combines retrieval of relevant documents with generative models to produce accurate and contextually relevant responses. Essential for improving the accuracy and reliability of AI-generated content.
A system where outputs are fed back into the process as inputs, allowing for continuous improvement based on user responses. Crucial for iterative development and continuous improvement in design and product management.
The sequence of phases through which a product or project passes from conception to completion. Essential for managing and tracking the progress of development projects.
Model-Based Systems Engineering (MBSE) is a methodology that uses visual modeling to support system requirements, design, analysis, and validation activities throughout the development lifecycle. Essential for managing complex systems, improving communication among stakeholders, and enhancing the overall quality and efficiency of systems engineering processes.
A cognitive bias where individuals overestimate their own abilities, qualities, or performance relative to others. Important for understanding user self-perception and designing systems that account for inflated self-assessments.
The tendency of consumers to continuously purchase the same brand's products over time. Essential for driving repeat business and ensuring long-term brand success.
A squeeze page is a type of landing page designed to capture a visitor's email address or other contact information. Highly effective for building an email list by offering a valuable incentive in exchange for the user's details.
A strategy used to determine the proportion of various SMEs needed to support a pipeline of work. Important for optimizing resource allocation, enhancing efficiency, and ensuring teams have the appropriate support based on design demand and complexity.
A comprehensive analysis of a website to assess its performance in search engine rankings and identify areas for improvement. Essential for diagnosing and enhancing a website's SEO performance.
Rich Internet Application (RIA) is a web application that offers interactive and engaging user experiences similar to desktop applications. Essential for providing enhanced functionality and better user interfaces on the web.
The process of systematically collecting, analyzing, and acting on feedback from users to improve products and services. Essential for ensuring that user insights are effectively integrated into the development process.
A logical fallacy that occurs when one assumes that what is true for a part is also true for the whole. Important for avoiding incorrect assumptions in design and 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.
A pricing strategy that offers a middle option with substantial value at a moderate price, often perceived as the best deal by users. Useful for driving sales by presenting a balanced choice that appears more attractive relative to higher and lower-priced options.
The process of attracting and converting strangers and prospects into someone who has indicated interest in your company's product or service. Essential for building a sales pipeline and driving business growth.