Lean Six Sigma Concepts

A-Z Index:
A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U |V | W | X |Y | Z

A

Affinity Diagram

The Affinity Diagram is a tool used to organize large volumes of ideas, opinions, or data into meaningful categories based on natural relationships. It is especially useful during the early stages of problem-solving or when a team is brainstorming and needs to make sense of scattered input.

This method allows team members to sort thoughts without judgment, leading to deeper insights. Once grouped, the categories can help form the basis for prioritization or root cause analysis. It’s often used in conjunction with other tools such as the 5 Whys, brainstorming sessions, or Voice of the Customer (VOC) exercises.

Agile

Agile is a project management philosophy that emphasizes flexibility, speed, and iterative development. While it originated in software, Agile methods are widely used in Lean Six Sigma projects where quick experimentation and stakeholder feedback are essential.

Agile aligns with Lean principles by reducing waste, shortening cycle times, and enabling rapid learning. Techniques like Scrum and Kanban can be embedded into DMAIC improvement phases to accelerate progress without sacrificing structure.

Analyze Phase (DMAIC)

The Analyze Phase is the third stage in the DMAIC (Define, Measure, Analyze, Improve, Control) cycle and focuses on identifying the root causes of the problem. This phase involves dissecting data collected during the Measure phase and interpreting it through statistical and visual tools.

Typical tools include hypothesis testing, regression analysis, Pareto analysis, Fishbone diagrams, and 5 Whys. The goal is not just to see what’s wrong, but to deeply understand why it is happening—ensuring improvements target the real cause, not the symptoms.

Andon

Andon is a visual signaling system used in Lean manufacturing to alert when a problem occurs in the production process. Traditionally, it involves lights or displays that indicate whether everything is operating smoothly (green), needs attention (yellow), or has stopped due to an issue (red).

The purpose of an Andon is to empower operators to signal issues immediately, ensuring swift action and preventing defective products from moving forward. It fosters a culture of transparency and proactive problem resolution.

ANOVA (Analysis of Variance)

ANOVA is a statistical method used to compare the means of three or more groups to determine if at least one differs significantly. It tests the hypothesis that all group means are equal against the alternative that at least one is different.

In Lean Six Sigma, ANOVA is particularly useful when analyzing the impact of different factors (such as machines, shifts, suppliers) on process performance. It helps validate whether process changes yield statistically significant improvements.

Approval

In process documentation or project workflows, an Approval is a formal checkpoint where designated stakeholders review and endorse the next step. While approvals are critical for governance, too many can introduce bottlenecks.

Lean encourages minimizing unnecessary approvals by shifting toward built-in quality and process ownership, thereby improving speed without compromising control.

Attribute Data

Attribute data is qualitative and typically binary or categorical in nature—for example, Pass/Fail, Yes/No, or the number of defects. It differs from continuous data, which includes measurable variables like length, weight, or time.

In quality improvement, attribute data is used in tools like p-charts and np-charts. While easier to collect, it often requires larger sample sizes for meaningful analysis and can limit the use of advanced statistical methods.

Autonomation (Jidoka)

Autonomation, or Jidoka, refers to intelligent automation that can detect and respond to issues in real-time. In manufacturing, this means machines are equipped to stop themselves when problems occur—prompting human intervention and ensuring defects don’t accumulate.

This concept enforces built-in quality, allowing immediate correction of anomalies. It also extends to service and transactional processes where systems are programmed to flag irregularities for investigation.

Average (Mean)

The average, or mean, is a measure of central tendency calculated by summing all values in a dataset and dividing by the number of observations. It provides a baseline for comparing individual data points or process results.

In Lean Six Sigma, the mean is frequently used in control charts, capability analysis, and process monitoring. However, it’s sensitive to outliers and may not always reflect typical performance if the data is skewed.

B

Bartlett’s Test

Bartlett’s Test is a statistical procedure used to assess whether the variances of several groups are equal. It’s particularly important when preparing to use ANOVA, as one of its assumptions is homogeneity of variance.

If Bartlett’s Test indicates unequal variances, analysts may need to apply alternative methods like Welch’s ANOVA or non-parametric tests. Ensuring equal variance helps maintain the validity of statistical conclusions.

Bias

Bias is a systematic deviation from the true value, leading to consistently incorrect measurements or interpretations. It can occur in data collection, analysis, sampling, or even decision-making.

In Measurement System Analysis (MSA), bias quantifies how far the average of a measurement system is from the actual value. Identifying and correcting bias is crucial for reliable process monitoring and improvement.

Black Belt (Six Sigma)

A Six Sigma Black Belt is a professional with advanced expertise in Lean Six Sigma methodologies. They lead improvement projects, mentor Green Belts, and apply statistical tools to analyze and solve complex problems.

Black Belts are responsible for project execution and often act as change agents within the organization. Their skillset includes tools like hypothesis testing, regression, DOE, and control plans within the DMAIC framework.

Bottleneck

A bottleneck is a constraint or step in a process that limits the overall flow or capacity. It causes delays, increases lead time, and often leads to inventory buildup before the constrained operation.

Identifying and relieving bottlenecks is central to Lean thinking and is also addressed in the Theory of Constraints. Solutions may include redistributing tasks, increasing capacity, or simplifying the constraint step.

Box Plot

A box plot is a statistical graph that displays the spread and skewness of a dataset through five-number summary: minimum, first quartile (Q1), median, third quartile (Q3), and maximum.

It’s particularly effective for identifying outliers, understanding variation, and comparing distributions across multiple groups. In Lean Six Sigma, box plots are commonly used in the Analyze phase for visualizing differences between categories.

Break-Even Analysis

Break-even analysis determines the point at which total costs equal total revenue—i.e., when a product or service starts to generate profit. It’s a useful tool in justifying improvement investments or project selection.

The analysis considers fixed and variable costs and calculates how many units need to be sold or how much output is needed to cover expenses. It’s often visualized through a break-even chart.

Business Case

The business case is a foundational document that justifies the launch of a project or initiative. It defines the problem, quantifies potential benefits, outlines costs and risks, and ensures alignment with organizational goals.

In Lean Six Sigma, a strong business case helps gain leadership buy-in, secure resources, and maintain focus throughout the project lifecycle. It should be revisited and validated at each project milestone.

C

D

Defect

A defect is any instance where a product, service, or output fails to meet a defined specification or customer requirement. It may be caused by process variation, human error, faulty materials, or system breakdowns.

In Six Sigma, the goal is to minimize defects to the point where processes operate at a level of 3.4 defects per million opportunities (DPMO)—a near-perfect quality level.

Defect Opportunity

A defect opportunity is a point within a process where a defect could potentially occur. It’s not the actual defect, but a chance for something to go wrong based on the number of requirements or steps involved.

Defining all possible defect opportunities is essential when calculating metrics like DPMO or yield. It ensures the process capability is assessed based on risk exposure, not just final output quality.

Define Phase (DMAIC)

The Define Phase is the first step of the DMAIC cycle, where the project is scoped, the problem is clearly defined, and the business impact is established. Key outputs include the project charter, SIPOC diagram, VOC analysis, and high-level process mapping.

The success of the entire project hinges on a well-executed Define phase. If the problem is not accurately framed or aligned with business needs, subsequent analysis and solutions may be misdirected.

Design for Six Sigma (DFSS)

DFSS is a methodology used to design new processes, products, or services that meet Six Sigma standards from the outset. Unlike DMAIC, which improves existing processes, DFSS builds quality into the design using proactive tools.

Typical DFSS approaches include DMADV (Define, Measure, Analyze, Design, Verify) or IDOV (Identify, Design, Optimize, Verify). It’s commonly applied when a process is too broken to fix or when launching entirely new offerings.

Discrete Data

Discrete data consists of countable, distinct values such as the number of defects, number of calls handled, or number of rejected items. It is often expressed in whole numbers and used in attribute-based charts and analysis.

Unlike continuous data, discrete data has limitations in terms of statistical sensitivity but is often easier to collect, especially in transactional or service environments.

DMADV (Define, Measure, Analyze, Design, Verify)

DMADV is a methodology under the Design for Six Sigma (DFSS) umbrella used to develop new products or processes that meet customer expectations and Six Sigma quality levels.

Each step of DMADV focuses on:

• Define: Customer requirements and goals.

• Measure: Critical inputs and performance standards.

• Analyze: Design alternatives and risk analysis.

• Design: Detailed design with simulations.

• Verify: Pilot testing and validation before full rollout.

It’s used when DMAIC cannot sufficiently improve an existing system or when starting from scratch.

DMAIC (Define, Measure, Analyze, Improve, Control)

DMAIC is the core structured problem-solving methodology in Six Sigma. It provides a disciplined, data-driven approach for improving existing processes.

Each phase includes distinct deliverables and tools:

• Define: Clarify the problem and customer needs.

• Measure: Quantify current performance and establish baselines.

• Analyze: Identify root causes using statistical analysis.

• Improve: Develop, test, and implement solutions.

• Control: Sustain gains using monitoring and standardization.

DMAIC ensures that improvement efforts are systematic, measurable, and scalable.

DOWNTIME (8 Wastes)

DOWNTIME is a Lean acronym summarizing the eight key types of waste found in processes:

• Defects

• Overproduction

• Waiting

• Non-utilized Talent

• Transportation

• Inventory

• Motion

• Extra-processing

Eliminating or reducing these wastes is a core focus of Lean Six Sigma. Identifying them visually or through process walks (Gemba) helps uncover improvement opportunities quickly.

DPMO (Defects Per Million Opportunities)

DPMO is a key metric in Six Sigma that measures how many defects occur in a process per one million opportunities for a defect. It accounts for complexity by including all the ways things could go wrong—not just how many units are defective.

This standardized metric enables comparison across processes and industries, making it easier to benchmark and set improvement targets.

DPU (Defects Per Unit)

DPU measures the average number of defects per unit produced. It is calculated by dividing the total number of observed defects by the number of units examined.

While simpler than DPMO, DPU doesn’t account for the number of defect opportunities within each unit. It’s still a useful indicator of quality for processes with consistent inspection criteria.

E

Effectiveness

Effectiveness measures how well a process or activity achieves its intended outcome. It focuses on doing the right things—ensuring that goals are met and customer needs are fulfilled.

In Lean Six Sigma, effectiveness is often contrasted with efficiency. A process can be efficient but still ineffective if it doesn’t deliver what the customer wants. Therefore, any improvement effort must prioritize both dimensions.

Efficiency

Efficiency refers to the ability of a process to produce desired results using the least amount of resources. It’s about doing things right—with minimal waste, time, or effort.

A highly efficient process reduces costs, cycle times, and resource consumption while maximizing output. Lean Six Sigma uses tools like value stream mapping, takt time analysis, and standardized work to improve efficiency.

Error Proofing (Poka-Yoke)

Error Proofing, or Poka-Yoke, is the practice of designing processes or systems that prevent mistakes before they happen or make errors immediately detectable. It’s a core Lean concept developed by Shigeo Shingo at Toyota.

Common examples include color-coded cables, digital input validation, or jigs that only fit the correct component. Error proofing ensures quality at the source and reduces reliance on inspection.

External Failure Cost

External failure costs arise when defects or quality issues are discovered after the product or service has been delivered to the customer. These include warranty claims, customer returns, complaints, rework, and reputational damage.

Of all the COPQ categories, external failures are often the most expensive—both financially and in terms of brand credibility. Lean Six Sigma aims to eliminate such failures through proactive design and process control.

F

Failure Mode and Effects Analysis (FMEA)

FMEA is a structured, proactive risk assessment tool used to identify potential failure points in a process, product, or service. It evaluates each failure mode based on:

• Severity: Impact of the failure,

• Occurrence: Likelihood of the failure happening,

• Detection: Likelihood of catching the failure before it affects the customer.

Each combination yields a Risk Priority Number (RPN), which is used to rank and prioritize mitigation efforts. FMEA is often used in both Analyze and Improve phases of DMAIC or in DFSS projects.

First Pass Yield (FPY)

First Pass Yield measures the percentage of products or outputs that are produced correctly the first time—without rework, repairs, or corrections. It is a direct measure of process efficiency and quality.

A low FPY indicates significant waste, variation, or procedural gaps. Tracking FPY over time helps teams identify improvement opportunities and monitor the impact of changes.

Fishbone Diagram (Cause and Effect or Ishikawa Diagram)

The Fishbone Diagram is a visual tool used to explore and display all possible causes of a specific problem. The diagram resembles the skeleton of a fish, with the problem at the “head” and categories of causes as “bones.”

Typical categories (the 6Ms) include:

• Man (People),

• Method,

• Machine,

• Material,

• Measurement,

• Mother Nature (Environment).

By brainstorming and organizing root causes under these categories, teams can systematically narrow down where to focus investigation and data collection.

Flow

Flow refers to the smooth, uninterrupted progression of materials, information, or services through a process. In Lean terms, flow is the opposite of batch processing or stop-start delays.

Achieving flow requires eliminating waste, reducing handoffs, and aligning resources with demand. Tools like value stream mapping, line balancing, and takt time analysis help improve flow in both manufacturing and service settings.

Force Field Analysis

Force Field Analysis is a decision-making tool developed by Kurt Lewin that helps assess the forces that drive or resist change. It visually maps out “driving forces” that push for change and “restraining forces” that hold it back.

This analysis helps teams plan for successful change by strengthening enablers and reducing resistance. It’s particularly useful during the Improve or Control phases when embedding changes into culture.

G

Gage R&R (Repeatability and Reproducibility)

Gage R&R is part of Measurement System Analysis (MSA) and evaluates how much of the measurement variation is due to the measurement system itself rather than the actual process.

It consists of:

• Repeatability: Variation when the same operator measures the same item repeatedly.

• Reproducibility: Variation between different operators measuring the same item.

If the Gage R&R percentage is too high (e.g., >10–30%), the data collected may be unreliable. Improvements may require better training, calibration, or measurement tools.

Gallery Walk

A gallery walk is a collaborative workshop technique used to showcase Lean Six Sigma project ideas, progress, or results. It involves displaying visual project summaries on posters or walls and allowing teams to walk through them in a structured manner.

It encourages knowledge sharing, cross-functional learning, and stakeholder engagement. Gallery walks are commonly used in Kaizen events, improvement showcases, and solution selection phases.

Gemba

Gemba is a Japanese term meaning “the real place,” referring to where work actually happens—whether it’s a factory floor, service desk, or virtual platform.

Gemba walks involve leaders or improvement teams going to the process site to observe operations, ask questions, and understand the challenges firsthand. The philosophy behind Gemba is that problems are best understood at the source—not from reports or meetings.

Goal Statement

A Goal Statement defines the specific, measurable objective a Lean Six Sigma project aims to achieve. It is typically SMART: Specific, Measurable, Achievable, Relevant, and Time-bound.

For example: “Reduce pizza delivery cycle time from 45 minutes to 30 minutes by July 2025 with 95% consistency.” This statement guides solution design, stakeholder alignment, and performance tracking throughout the DMAIC cycle.

Green Belt

A Green Belt is a Six Sigma-certified individual trained to lead smaller improvement projects within their functional area. Green Belts typically complete 2–3 weeks of formal training and often support Black Belts on larger cross-functional projects.

They apply tools from all DMAIC phases, such as process mapping, capability analysis, cause-and-effect tools, and basic hypothesis testing. Green Belts usually balance their project work alongside their regular job responsibilities.

H

Heijunka

Heijunka is a Lean technique for leveling production by volume and variety. Instead of producing in large, inconsistent batches, Heijunka spreads production evenly across time to match customer demand more smoothly.

The goal is to eliminate unevenness (mura), overburden (muri), and waste (muda). Heijunka is essential for creating a stable, predictable production schedule and minimizing inventory buildup. It often uses visual tools like a Heijunka box or board to sequence tasks.

Histogram

A histogram is a graphical tool used to display the distribution of continuous data. It consists of bars that show the frequency of data points within specified ranges or intervals.

Histograms help identify the shape, spread, central tendency, and potential outliers in a dataset. In Lean Six Sigma, it’s frequently used during the Analyze phase to assess variation, process capability, or check for normal distribution.

Hoshin Kanri

Hoshin Kanri, also known as Policy Deployment, is a strategic planning method that aligns an organization’s goals from top-level vision to front-line execution. It connects long-term objectives with daily improvement efforts.

Typically visualized using an X-matrix, Hoshin Kanri ensures that improvement projects are prioritized based on strategic value. It fosters alignment, cross-functional collaboration, and focus on what truly matters across the enterprise.

Hypothesis Testing

Hypothesis testing is a statistical method used to evaluate assumptions about a population based on sample data. It typically involves:

• A null hypothesis (H₀) that assumes no effect or difference,

• An alternative hypothesis (H₁) proposing a change or difference.

Common tests include t-tests, chi-square tests, and ANOVA. Hypothesis testing is fundamental in the Analyze phase of DMAIC, helping teams validate whether observed changes are statistically significant or just random noise.

I

I-MR Chart (Individuals and Moving Range)

An I-MR chart is a control chart used to monitor individual data points (I chart) and the variation between them (MR chart). It’s especially useful when only one measurement is available per time point or sample.

This chart is ideal for low-volume production or service processes where subgrouping isn’t possible. The I chart tracks the central tendency, while the MR chart shows short-term variability.

Input

In Lean Six Sigma, an input refers to any resource, information, material, or factor that enters a process and affects its outcome. Inputs are the “x” variables in the equation Y = f(x), where Y is the output.

Identifying, measuring, and controlling inputs—especially the critical ones—is key to improving process performance. Inputs can be physical (materials), procedural (methods), or human (skills and decisions).

Inspection

Inspection is the process of checking a product or output to ensure it meets requirements. While necessary in some contexts, Lean views inspection as a form of waste because it occurs after errors are made rather than preventing them.

The goal in Lean Six Sigma is to build quality into the process through error proofing, standardization, and root cause elimination—thereby reducing the need for inspection altogether.

Institutionalization

Institutionalization is the act of embedding an improvement into the daily operations and culture of an organization. It ensures that successful changes become the new norm, sustained by systems, habits, and leadership.

This is the core objective of the Control phase in DMAIC. Institutionalization often involves creating SOPs, training materials, visual controls, and assigning process ownership to prevent regression.

Internal Failure Cost

Internal failure costs are incurred when a defect or issue is caught before it reaches the customer. These may include scrap, rework, downtime, or additional inspections.

While less damaging than external failures, internal failures still represent waste and lost value. Lean Six Sigma projects often start by analyzing these costs to identify improvement opportunities and prioritize actions.

Inventory

Inventory represents materials, parts, or information that are not actively being processed. In Lean, it is considered one of the key forms of waste because it ties up capital, space, and effort without adding value.

Too much inventory can mask deeper problems like process instability or bottlenecks. Lean aims to reduce inventory through pull systems, one-piece flow, and takt time alignment.

J

Jidoka (Autonomation)

Jidoka is a Lean principle that means “automation with a human touch.” It refers to systems that automatically detect process abnormalities and halt production to prevent further defects.

Whether through sensors, alarms, or human intervention, Jidoka ensures that errors are addressed immediately rather than passed downstream. It promotes built-in quality and empowers frontline workers to take ownership of process integrity.

Job Element Sheet

A Job Element Sheet is a Lean documentation tool that details each task required to complete a process step. It includes elements like cycle time, key motions, and safety or quality checks.

This standardized work tool helps ensure consistency across shifts and operators. It’s especially useful during training, audits, and continuous improvement efforts, as it forms the foundation for understanding and optimizing tasks.

Just-In-Time (JIT)

Just-In-Time is a production and inventory strategy where materials and products are delivered or produced only when needed, in the exact amount required. It aims to eliminate waste associated with overproduction, excess inventory, and waiting.

JIT requires high process stability and supplier reliability. In Lean environments, it’s supported by tools like Kanban systems and takt time scheduling to balance supply with real-time demand.

K

Kaizen

Kaizen is the Japanese term for “continuous improvement,” focusing on small, incremental changes that collectively yield significant results. It involves all employees—from the CEO to line workers—constantly looking for ways to improve processes.

Kaizen events, or “blitzes,” are short-term, focused improvement initiatives designed to achieve rapid results. Kaizen fosters a culture of ownership, learning, and performance excellence.

Kanban

Kanban is a visual scheduling system that helps control production and inventory levels by signaling when new work should begin. Originating from Toyota, it uses cards, bins, or digital signals to indicate demand pull.

Kanban promotes flow, reduces overproduction, and prevents resource overload. It’s a cornerstone of Lean production systems and is also widely adopted in Agile project management.

Kano Model

The Kano Model is a tool used to categorize and prioritize customer requirements based on their impact on satisfaction. It divides features into:

• Basic Needs: Must-haves; their absence causes dissatisfaction.

• Performance Needs: More is better; directly tied to satisfaction.

• Delighters: Unexpected features that create excitement.

This model helps teams balance product features and investment based on what customers truly value. It’s often used in VOC analysis and new product development.

L

Lead Time

Lead time is the total elapsed time between the initiation and completion of a process—from order receipt to delivery. It includes processing, transportation, waiting, and queue times.

Reducing lead time increases responsiveness, reduces inventory, and enhances customer satisfaction. Lean projects often track lead time to identify waste and opportunities for flow improvement.

Lean

Lean is a process improvement methodology that focuses on maximizing value while minimizing waste. Originating from the Toyota Production System, Lean emphasizes customer value, flow, pull systems, and respect for people.

The core principle is identifying and eliminating non-value-adding activities (the 8 wastes), leading to faster, more efficient, and more responsive processes. Lean tools include 5S, value stream mapping, Heijunka, and standard work.

Lean Six Sigma

Lean Six Sigma is a hybrid methodology that combines Lean’s focus on speed and waste elimination with Six Sigma’s emphasis on quality and variation reduction. It uses the DMAIC framework to identify problems, analyze root causes, implement solutions, and sustain improvements.

Organizations adopt Lean Six Sigma to drive customer satisfaction, improve efficiency, and reduce costs—all through data-driven decision-making and structured teamwork.

M

Master Black Belt (MBB)

A Master Black Belt is the highest level of certification in the Six Sigma hierarchy. MBBs are responsible for enterprise-wide project oversight, mentoring Black Belts and Green Belts, and ensuring alignment between Lean Six Sigma projects and strategic goals.

Beyond technical mastery of tools and methodologies, Master Black Belts also lead organizational change, facilitate training programs, and act as trusted advisors to senior leadership. They focus on long-term capability building and cultural integration of continuous improvement.

Measurement System Analysis (MSA)

MSA is the process of evaluating the accuracy, precision, and reliability of the tools and methods used to collect data. It ensures that data-driven decisions are based on trustworthy inputs.

MSA includes analysis of bias, linearity, stability, repeatability, and reproducibility. If a measurement system has high variation or bias, it could obscure actual process performance and lead to incorrect conclusions.

Mean (Average)

The mean is a measure of central tendency calculated by adding all values in a dataset and dividing by the number of values. It gives a useful snapshot of overall process performance.

In Lean Six Sigma, the mean is commonly used in control charts, capability studies, and hypothesis testing. However, it should be interpreted alongside variation measures like standard deviation to provide context.

Median

The median is the middle value in an ordered dataset, dividing it into two equal halves. Unlike the mean, it is not affected by extreme outliers or skewed data, making it a reliable measure of central tendency in such cases.

In improvement projects, the median is often used for time-related metrics like cycle time or response time when distributions are not symmetrical.

Mistake Proofing (Poka-Yoke)

Mistake proofing, also known as Poka-Yoke, involves designing processes so that errors are impossible or immediately detectable. It is a preventive approach to quality that eliminates reliance on inspections and rework.

Examples include USB connectors that only insert one way, or software that won’t proceed without completing mandatory fields. Mistake proofing is a cornerstone of Lean quality principles, especially in the Improve and Control phases.

Muda

Muda is the Japanese word for waste—any activity that consumes resources without adding value to the customer. Lean identifies eight types of Muda, summarized by the DOWNTIME acronym.

Eliminating Muda is the primary focus of Lean efforts. It requires direct observation (Gemba), value stream mapping, and deep analysis to uncover hidden inefficiencies across processes.

Mura

Mura refers to unevenness or inconsistency in workloads, production volumes, or customer demands. It causes overburden on people and systems and leads to unpredictable outcomes.

Eliminating Mura involves level loading (Heijunka), standard work, and demand forecasting. It helps create smoother flow and improves process stability.

Muri

Muri refers to overburdening people, machines, or systems beyond their natural capacity. It often results from poor planning, inadequate training, or lack of standardized procedures.

Reducing Muri prevents burnout, breakdowns, and mistakes. Solutions include cross-training, job rotation, and workload balancing.

N

Non-Value-Added (NVA)

Non-value-added activities are tasks or steps in a process that do not contribute to delivering what the customer needs and is willing to pay for. These include excessive movement, waiting, overprocessing, or unnecessary approvals.

Identifying and eliminating NVA tasks is a core goal in Lean. However, not all NVA work can be removed—some may be necessary for regulatory compliance or internal controls.

Normal Distribution

Normal distribution is a symmetrical, bell-shaped curve that describes how data points tend to cluster around the mean. Many natural and process-related variables follow this pattern.

Understanding whether a process is normally distributed helps determine the appropriate statistical tools to use. Tests like ANOVA, t-tests, and control charts assume normality, and departures from it may require data transformation or alternate methods.

O

Operational Definition

An operational definition clearly specifies how a concept, measurement, or process will be defined, collected, and interpreted. It removes ambiguity and ensures consistency among all stakeholders.

For example, defining “on-time delivery” as “pizza delivered within 30 minutes from placing the order” is much clearer than just saying “fast delivery.” Operational definitions are vital for data collection, measurement plans, and audits.

Output

An output is the end result of a process—either a product, service, report, or decision. Outputs are what the customer ultimately receives and are evaluated for quality, timeliness, and satisfaction.

In Lean Six Sigma, outputs are often referred to as “Y” in the equation Y = f(x), where Y is the outcome and x represents all the contributing inputs. Improving Y involves identifying and controlling the most influential x’s.

Overproduction

Overproduction is producing more than needed or sooner than needed. It’s considered the worst type of waste in Lean because it leads to other wastes—such as excess inventory, extra handling, and more rework.

Common in both manufacturing and services, overproduction can be triggered by poor forecasting, disconnected planning systems, or incentives based on output volume rather than customer demand.

O

Operational Definition

An operational definition clearly specifies how a concept, measurement, or process will be defined, collected, and interpreted. It removes ambiguity and ensures consistency among all stakeholders.

For example, defining “on-time delivery” as “pizza delivered within 30 minutes from placing the order” is much clearer than just saying “fast delivery.” Operational definitions are vital for data collection, measurement plans, and audits.

Output

An output is the end result of a process—either a product, service, report, or decision. Outputs are what the customer ultimately receives and are evaluated for quality, timeliness, and satisfaction.

In Lean Six Sigma, outputs are often referred to as “Y” in the equation Y = f(x), where Y is the outcome and x represents all the contributing inputs. Improving Y involves identifying and controlling the most influential x’s.

Overproduction

Overproduction is producing more than needed or sooner than needed. It’s considered the worst type of waste in Lean because it leads to other wastes—such as excess inventory, extra handling, and more rework.

Common in both manufacturing and services, overproduction can be triggered by poor forecasting, disconnected planning systems, or incentives based on output volume rather than customer demand.

P

P Chart (Proportion Chart)

A P Chart is a type of control chart used to monitor the proportion of defective units in a process over time. It’s ideal for attribute data where each unit is classified as either defective or non-defective.

P Charts help determine whether changes in defect rates are due to natural variation or special causes. They’re useful in call centers, healthcare, and manufacturing settings where binary outcomes are tracked.

Pareto Chart

The Pareto Chart is a graphical tool that helps prioritize problems or causes based on their relative frequency or impact. It combines a bar graph (showing counts in descending order) and a line graph (cumulative percentage).

It is based on the Pareto Principle, or 80/20 rule, which states that roughly 80% of problems are caused by 20% of causes. This tool helps teams focus their improvement efforts where they will have the greatest effect.

Pareto Principle (80/20 Rule)

The Pareto Principle suggests that a small number of causes are responsible for a large proportion of results. In quality terms, a few defect types or root causes typically account for the majority of failures.

Recognizing this pattern helps prioritize improvement actions. It’s the foundation for tools like Pareto Charts and is widely applicable in everything from customer complaints to machine breakdowns.

PDCA (Plan-Do-Check-Act)

PDCA is a simple yet powerful cycle for continuous improvement. It was popularized by Dr. W. Edwards Deming and consists of:

• Plan: Identify a goal and a strategy to improve,

• Do: Implement the change on a small scale,

• Check: Measure and analyze results,

• Act: Standardize the change or revise based on learnings.

PDCA is ideal for rapid testing and learning and is often embedded in Kaizen events and pilot projects.

Perfection (Lean Ideal)

In Lean thinking, perfection is not about flawlessness—it’s the relentless pursuit of continuous improvement to deliver maximum value with zero waste. It is considered an ideal state where processes operate with absolute efficiency, flexibility, and quality.

While perfection is rarely achieved, striving toward it helps organizations challenge current practices and unlock transformational gains.

Pilot

A pilot is a small-scale implementation of a proposed solution used to test its effectiveness before full-scale rollout. It allows teams to validate assumptions, observe unintended consequences, and gather feedback.

In Lean Six Sigma, pilots are crucial in the Improve phase to reduce implementation risk. Pilots are typically accompanied by metrics to assess success and justify wider deployment.

Poka-Yoke

Poka-Yoke is a Japanese term meaning “mistake-proofing.” It involves designing systems or tools so that it becomes impossible—or very difficult—to make an error.

Examples include color-coded wiring, fixtures that only fit in one direction, or alerts that warn users of incorrect inputs. Poka-Yoke techniques are commonly used in manufacturing, healthcare, and software design.

Process Capability

Process capability is a statistical measure of how well a process can consistently produce output within specification limits. It reflects both the spread and centering of the process data relative to customer expectations.

Key indices include Cp and Cpk. A capable process not only fits within the limits but also centers the mean appropriately, reducing defects and variation.

Process Mapping

Process mapping is the visual representation of the sequence of activities that make up a process. It helps teams understand workflows, handoffs, decision points, and potential areas of waste.

Types of process maps include:

• SIPOC (high-level),

• Swimlane or Cross-Functional Maps,

• Value Stream Maps (detailed Lean analysis),

• Detailed step-by-step flowcharts.

Mapping is foundational in the Define and Analyze phases, providing clarity and alignment across stakeholders.

Project Charter

The project charter is a formal document that initiates a Lean Six Sigma project. It defines the problem, scope, goals, timeline, metrics, stakeholders, and team roles.

A strong charter keeps the project focused, prevents scope creep, and ensures alignment with business objectives. It is typically created in the Define phase and reviewed throughout the DMAIC cycle.

Q

Quality

Quality in Lean Six Sigma is defined as conformance to customer requirements. It goes beyond defect reduction to encompass overall customer satisfaction—delivering the right product or service, at the right time, in the right way.

True quality is measured from the customer’s perspective. It includes factors such as reliability, performance, serviceability, and emotional satisfaction. Continuous quality improvement is the goal of every Lean Six Sigma effort.

Quality Function Deployment (QFD)

QFD is a structured methodology that translates customer needs (Voice of the Customer) into specific product or process requirements. Often visualized through a “House of Quality,” QFD links what customers want to how the organization will deliver it.

QFD ensures alignment between marketing, design, manufacturing, and quality assurance. It’s especially powerful in DFSS projects and is frequently used in new product development or service design.

Quantitative Data

Quantitative data refers to numerical data that can be measured, analyzed statistically, and used to calculate averages, variances, and probabilities. Examples include cycle time, cost per unit, and defect count.

This type of data forms the basis for many Lean Six Sigma tools, including control charts, regression analysis, hypothesis testing, and capability studies. It offers more analytical flexibility than qualitative or categorical data.

Quartile

A quartile divides a dataset into four equal parts:

• Q1 (25%),

• Q2 (median),

• Q3 (75%).

Quartiles are used in box plots and descriptive statistics to understand the spread and skewness of data. They help detect outliers and compare performance across groups.

R

RACI Matrix

A RACI Matrix clarifies roles and responsibilities for process tasks or project deliverables. It stands for:

• Responsible: Does the work,

• Accountable: Owns the outcome,

• Consulted: Provides input or expertise,

• Informed: Needs updates.

RACI ensures accountability and reduces confusion, especially in cross-functional teams. It’s a valuable tool for stakeholder management during process improvement or implementation.

Range

Range is a measure of dispersion that shows the difference between the highest and lowest values in a dataset. While simple, it can be misleading in the presence of outliers.

In Lean Six Sigma, range is often used in control charts (e.g., X-bar and R charts) and descriptive statistics. It offers a quick view of data spread but is usually paired with standard deviation for more robustness.

Regression Analysis

Regression analysis is a statistical technique used to understand the relationship between one dependent variable (Y) and one or more independent variables (X). It identifies which inputs significantly affect the output and quantifies the strength and direction of that impact.

Used extensively in the Analyze phase, regression helps teams model process behavior and prioritize improvement actions. Types include linear, multiple, and logistic regression depending on the nature of the data.

Repeatability

Repeatability refers to the consistency of measurements when the same person uses the same instrument under the same conditions. It is a component of Gage R&R and reflects short-term variation due to the measurement system itself.

High repeatability ensures that observed process changes are real and not due to variation in data collection. It’s essential for valid conclusions in data-driven projects.

Reproducibility

Reproducibility refers to the consistency of measurements when different operators use the same measurement system under similar conditions. Like repeatability, it is part of Gage R&R analysis.

Poor reproducibility suggests issues with training, measurement interpretation, or environmental factors. Ensuring both repeatability and reproducibility improves data quality and builds confidence in decisions based on that data.

Risk Priority Number (RPN)

The RPN is a score used in Failure Modes and Effects Analysis (FMEA) to prioritize risks based on:

• Severity (of the effect),

• Occurrence (of the cause),

• Detection (likelihood of catching the issue).

RPN = Severity × Occurrence × Detection

A higher RPN indicates a greater risk and helps teams focus mitigation efforts on the most critical issues. Although RPN has limitations, it’s widely used for risk assessment in Lean Six Sigma projects.

Root Cause

A root cause is the underlying reason a problem occurs—not just a symptom or surface-level issue. Addressing root causes prevents recurrence and leads to sustainable improvement.

Root cause analysis involves techniques such as 5 Whys, Fishbone diagrams, Pareto analysis, and hypothesis testing. The Analyze phase of DMAIC is dedicated to uncovering and validating root causes with data.

Root Cause Analysis (RCA)

RCA is a structured approach for identifying the true source of a problem rather than merely treating symptoms. It ensures that corrective actions are effective and sustainable.

Common RCA tools include:

• 5 Whys (for quick cause chaining),

• Fishbone (to categorize causes),

• Fault tree analysis (for complex scenarios).

RCA is essential in Six Sigma projects and should always be followed by solution validation in the Improve phase.

Run Chart

A run chart is a basic line graph that displays process performance over time. It is used to identify trends, shifts, or cycles in a process before applying formal statistical control limits.

Run charts are ideal for early-stage process monitoring or when introducing new metrics. They help determine if further statistical analysis is warranted and are easy for all stakeholders to interpret.

S

SIPOC Diagram

SIPOC stands for:

• Suppliers,

• Inputs,

• Process,

• Outputs,

• Customers.

This high-level process mapping tool provides a bird’s-eye view of a system and its boundaries. It is commonly used in the Define phase of DMAIC to scope projects and align stakeholders.

SIPOC diagrams clarify who provides what, to whom, and through what process. They are particularly useful when dealing with unfamiliar or cross-functional processes.

Scatter Plot

A scatter plot is a graph that shows the relationship between two numerical variables. Each point represents one observation, and the overall shape indicates the type of relationship (positive, negative, or none).

Scatter plots are frequently used in the Analyze phase to explore potential input-output (X-Y) relationships. They are often precursors to correlation or regression analysis.

Sigma Level

The Sigma level represents the capability of a process to produce defect-free outcomes. It measures how many standard deviations fit between the process mean and the nearest specification limit.

A 6 Sigma level corresponds to only 3.4 defects per million opportunities (DPMO), reflecting near-perfect performance. Higher Sigma levels indicate fewer defects and more capable processes.

Six Sigma

Six Sigma is a data-driven methodology aimed at eliminating defects, reducing process variation, and improving customer satisfaction. It uses a structured approach—DMAIC—for existing process improvements, and DMADV for new designs.

Six Sigma combines statistical tools, process discipline, and leadership support. Its belt-based certification structure (White, Yellow, Green, Black, Master Black Belt) ensures scalable expertise across organizations.

Standard Deviation

Standard deviation is a statistical measure of dispersion that indicates how spread out values are around the mean. A smaller standard deviation suggests more consistent performance; a larger one indicates more variability.

In Lean Six Sigma, it is used in capability analysis, control charts, and hypothesis testing. It is foundational for understanding process behavior and diagnosing instability.

Standard Work

Standard work refers to the best known, most efficient, and safest method of performing a task. It documents the sequence, timing, and quality expectations of a process to ensure consistency and repeatability.

Standard work supports continuous improvement by providing a stable baseline for experimentation. It also reduces variation, improves training, and supports lean flow principles.

Stratification

Stratification is the practice of separating data into categories or groups to reveal patterns that may be hidden in aggregated data. It helps determine if a particular subgroup is driving performance issues.

Stratification can be applied by time, location, team, machine, product, or any relevant factor. It’s often used alongside Pareto analysis, box plots, and root cause exploration.

Swimlane Map (Cross-Functional Process Map)

A Swimlane Map visually represents a process and how tasks flow between different departments or roles. Each “lane” represents a function, and the process steps show how work moves across them.

This tool is ideal for identifying handoff delays, duplication, or responsibility gaps. It provides clarity in complex or cross-functional processes, supporting both analysis and redesign.

T

Takt Time

Takt time is the pace at which products or services must be completed to meet customer demand. It is calculated by dividing the available work time by the customer demand in that period.

Takt Time = Available Time / Customer Demand

Takt time creates a rhythm that guides production planning, resource allocation, and line balancing. It is a central concept in Lean, helping to synchronize processes and avoid overproduction or bottlenecks.

Theory of Constraints (TOC)

The Theory of Constraints is a methodology for identifying the most significant limiting factor (constraint) in a process and systematically improving it until it no longer constrains the system.

Constraints can be physical (e.g., a machine), policy-based (e.g., outdated procedures), or behavioral (e.g., skill gaps). TOC complements Lean Six Sigma by ensuring that improvements are focused where they have the greatest impact on throughput.

Throughput

Throughput refers to the number of units a process can produce or deliver over a given period of time. It is an indicator of process speed, flow, and efficiency.

Increasing throughput without increasing resource consumption is a common goal in Lean environments. Improvements to cycle time, bottleneck elimination, and process stability all contribute to higher throughput.

Time Observation Sheet

A time observation sheet is a Lean tool used to record the actual time taken for each step in a process. It helps identify value-added vs. non-value-added activities and spot opportunities for cycle time reduction.

This tool is frequently used during Gemba walks, Kaizen events, and standard work development to capture current performance with minimal assumptions.

V

Value

Value in Lean Six Sigma is defined from the customer’s perspective—what the customer is willing to pay for. It refers to any activity that transforms the product or service in a way that meets customer needs.

Lean focuses on maximizing value by eliminating activities that do not contribute to the final output. Understanding value is essential for mapping value streams and prioritizing improvement.

Value Stream

A value stream includes all the steps—both value-added and non-value-added—required to deliver a product or service from start to finish. It encompasses information and material flow across departments or systems.

Value streams are analyzed using Value Stream Mapping (VSM), a core Lean tool. Mapping helps visualize process inefficiencies, highlight delays, and prioritize improvements holistically.

Value Stream Mapping (VSM)

VSM is a visual tool used to analyze the flow of materials and information throughout a process. It includes timelines, cycle times, waiting times, and process connections, giving a clear end-to-end picture.

Value Stream Maps differentiate between current state (as-is) and future state (to-be), supporting strategic improvement planning. It’s essential for identifying waste, bottlenecks, and improvement leverage points.

Variation

Variation is the inevitable fluctuation in process output, even under stable conditions. It may be caused by machines, materials, people, or environment. Six Sigma’s primary focus is identifying and reducing harmful variation.

There are two types of variation:

• Common cause: inherent to the system,

• Special cause: due to specific, assignable sources.

Statistical tools help differentiate between these and guide appropriate corrective actions.

Voice of the Customer (VOC)

VOC is a structured method for capturing customer needs, expectations, and feedback. It can be gathered through surveys, interviews, complaints, focus groups, or direct observation.

VOC is translated into measurable Critical-to-Quality (CTQ) requirements that guide improvement initiatives. It ensures that improvements are aligned with what truly matters to the customer.

Voice of the Business (VOB)

VOB reflects the needs and priorities of the business, such as cost savings, profitability, compliance, or strategic objectives. It must be balanced with VOC to create win-win outcomes for both customers and the organization.

Lean Six Sigma projects succeed when they address both VOB and VOC, ensuring sustainability and stakeholder buy-in.

Voice of the Process (VOP)

VOP refers to what the process data tells us about how the system is performing. It is revealed through metrics, control charts, dashboards, and statistical analysis.

Comparing VOP to VOC helps determine whether a process is meeting customer expectations. If not, it signals the need for root cause analysis and process redesign.

W

Waiting

Waiting is one of the eight forms of Lean waste. It occurs when people, materials, or information sit idle due to delays, bottlenecks, or poor scheduling.

Common causes of waiting include approvals, batch processing, unbalanced workloads, or equipment downtime. Lean seeks to eliminate waiting through better flow, load leveling, and streamlined communication.

Waste (Muda)

Waste refers to any activity that does not add value from the customer’s perspective. Lean classifies waste into eight types (DOWNTIME):

• Defects,

• Overproduction,

• Waiting,

• Non-utilized talent,

• Transportation,

• Inventory,

• Motion,

• Extra-processing.

Identifying and eliminating waste is a core pursuit of Lean thinking.

White Belt

A White Belt is the entry-level certification in Lean Six Sigma. White Belts are introduced to basic principles, terminology, and the DMAIC framework, typically through a few hours of training.

They support improvement efforts by participating in projects, identifying waste, and promoting a culture of quality. They are not expected to lead projects independently.

Work in Process (WIP)

WIP includes items that are partially completed and still in the process of being worked on. Excess WIP creates waste in the form of waiting, storage, and overproduction.

Lean aims to reduce WIP by implementing pull systems, improving flow, and balancing capacity across process steps.

X

X-bar Chart

An X-bar chart is a type of control chart used to monitor the mean (average) of a process over time. It is typically used in conjunction with an R chart (range) to assess both central tendency and variation.

X-bar charts help detect shifts or trends in a process and are key tools in Statistical Process Control (SPC).

Y

Y = f(x)

This foundational Six Sigma equation means that the output (Y) is a function of one or more inputs (x). By identifying and controlling the critical Xs, teams can influence the process outcome.

This equation underpins the entire Six Sigma methodology—especially during root cause analysis, experimentation, and solution design.

Yellow Belt

A Yellow Belt is trained in Lean Six Sigma fundamentals and supports process improvement projects as a team member. They understand the DMAIC phases, basic tools, and the importance of data in decision-making.

Yellow Belts serve as valuable contributors to larger Green or Black Belt-led initiatives. In some organizations, they also lead small-scale projects within their area.

Yield

Yield measures the proportion of units produced without defects. It reflects the efficiency and effectiveness of a process and is expressed as a percentage.

Types of yield include:

• First Pass Yield (FPY): No rework or corrections needed,

• Rolled Throughput Yield (RTY): Considers yield across all process steps.

Yield is a key metric for tracking process performance and customer satisfaction.

Z

Z-Score

A Z-score indicates how many standard deviations a data point is from the process mean. It helps compare values across different distributions and assess statistical significance.

Z-scores are also used in Sigma level calculations. A higher Z-score indicates a process output that is further from the mean—in either a good or bad direction—depending on the specification limits.

Zero Defects

Zero Defects is a quality philosophy introduced by Philip Crosby that emphasizes doing things right the first time. It promotes the belief that defects are not inevitable and that processes can be designed to prevent them.

While not literal perfection, Zero Defects aims for a mindset shift—where quality becomes everyone’s responsibility, and the tolerance for errors is eliminated through prevention.