Lean Six Sigma Glossary Brought To You By: View Online Lean Six Sigma Glossary Including Visuals & Infographics At: https://goleansixsigma.com/glossary/ The web is overflowing with Lean Six Sigma resources. Our glossary provides clear, straight-forward language, organized for quick access so you can easily find and understand terms that you’re searching for. For a better understanding of these terms and an overview of Lean Six Sigma, check out our Green Belt Training & Certification. P300 COPYRIGHT 2015 GOLEANSIXSIGMA.COM. ALL RIGHTS RESERVED. 1 5 Whys: 5 Whys is a simple but effective method of analyzing and solving problems by asking “why” five times, or as many times as needed in order to move past symptoms and determine root cause. This approach is used in tandem with Cause-and-Effect or Fishbone diagrams. 5S: 5S is a workplace organization technique composed for five primary phases: Sort, Set In Order, Shine, Standardize, and Sustain. 8 Wastes (aka Muda): The 8 Wastes; Defects, Overproduction, Waiting, Non-Utilized Talent, Transportation, Inventory, Motion, and Extra- Processing are a list of the most common reasons for excess cycle time in a process. The idea of process improvement is to identify and remove all forms of waste from a process in order to increase efficiency, reduce cost, and provide customer value. A3: On a literal level, A3 refers to a ledger size piece of paper, but in the Lean world it is a one page project report. This one-pager contains the problem, the analysis of the process, the identified root causes, potential solutions and action plan all on a large sheet of paper. The practice of using A3s forces project teams to focus their efforts while at the same time makes it easy for others to review their work. Affinity Chart (aka Affinity Diagram): An Affinity Chart (or Affinity Diagram) organizes a large amount of data according to their natural relationships. Useful for bringing order out of chaos, Affinity Charts make complex processes & procedures easier to grasp by breaking them down into their constituent parts and reorganizing them into groups based on similarity. In practice, this involves writing ideas onto notecards or sticky notes, and then grouping these ideas into similar columns. This is generally a silent activity completed by 1 or 2 members of a group. P300 COPYRIGHT 2015 GOLEANSIXSIGMA.COM. ALL RIGHTS RESERVED. 2 Alternative Path: Used in process mapping, the Alternative Path method shows multiple ways of achieving the same result. Ideal for the mapping of very large and detailed processes, alternative paths are a process analysis tool. This is often done by assigning percentages to each path (e.g, time/incidents) for comparison purposes. Alternative Hypothesis: The Alternative Hypothesis, known as HA, is a form of hypothesis that assumes there is a statistically significant difference between two or more data samples. In any hypothesis test, if there is a less than 5% probability that the difference is due to chance, then the Null Hypothesis is rejected and the Alternative Hypothesis can be pursued. Analyze Phase: The Analyze Phase is the third phase of the DMAIC process, and focuses on identifying the root cause (or causes) of a process problem. The Analyze Phase requires data and knowledge gleaned from the previous Define and Measure phases of DMAIC. This phase focuses on analysis of the data and the process. In terms of the data focus, statistical analysis is a cornerstone of Analyze, ensuring that potential root causes are not only validated but significant enough to merit attention. Methods and tools used include Process Maps, Charts and Graphs, Hypothesis Testing, and Value-Added Analysis. Andon: Andon is an alert system that can be visual or audible, facilitating quick response to any problems in the process or system. This system includes a way for employees to stop the process, physically or electronically, so that the issue can be addressed before production continues. ANOVA: ANOVA (Analysis of Variance) is a form of hypothesis testing that determines if there is a significant difference in the means or averages of two populations of data. Assumption Busting: Assumption Busting is a brainstorming and questioning technique that does two things: it identifies and challenges conventional assumptions and eliminates them if they are obstacles to optimal solutions. Attribute Data (aka Discrete Data): Attribute data refers to categories or counts that can only be described in whole numbers; i.e. you can’t have half a defect or half a customer. This type of data is the opposite of continuous or variable data (temperature, weight, distance, etc.). Typical Attribute Data refers to the number of defects, number passed vs. number failed as well as the counts of different categories; i.e. number blue, number red, number yellow, etc. Attribute data can be represented in percentages and ratios such as 2.1 guests per hotel room or a 75% occupancy rate, but the source unit, the guest, can still not be truly divided. Baseline Measures: Baseline measures are data collected to establish the initial capability of a process to meet customer expectations. By collecting this data prior to making any changes to the process it is possible to determine if solutions implemented later on have the desired impact. P300 COPYRIGHT 2015 GOLEANSIXSIGMA.COM. ALL RIGHTS RESERVED. 3 Batching: Batching is the practice of making large lots of a particular item to gain economic efficiencies. Although the assumption is that it increases efficiency, batching increases total cycle time and increases the waste of waiting both internally and for the customer. Batching is considered the opposite of the concept of "Single-Piece-Flow" where the goal is to use the smallest batch possible with the optimal size being one unit. Black Belt: A Black Belt is the second highest level of training for a Six Sigma practitioner; Master Black Belt is the highest. A Black Belt devotes 100% of their time to Six Sigma and focuses the execution of specific Six Sigma process improvement projects. In addition to project work, they are often assigned as a mentor to one or more Green Belts. Bottleneck: A Bottleneck is a step in the process where the process is limited in the volume it can handle. This is often the result of specialization, task imbalance or other constraints on capacity. Bottlenecks constrain the process and limit the ability of the process to flow at the rate of customer demand. Box Plot (aka Box and Whisker Plot): A Box Plot is a graphical view of a data set which involves a center box containing 50% of the data and “whiskers” which each represent 25% of the data. It divides the distribution of a data set into four portions: the lower “whisker” contains the first quartile or 25% of the data, the lower segment of the box contains the second quartile, above the median line to the top of the box is the third quartile and the upper “whisker” represents the 4th quartile of data. The midpoint of the box represents the median of the data set, and its position indicates if there is any skew to the data.. The endpoints of the top and bottom whiskers represent the largest and smallest data points, respectively. Outliers, or data that does not fit the predominant distribution, are represented by asterisks at the top and bottom of the box plot. This graph is most useful when comparing two or more strata or data sets. Brainstorming: Brainstorming is a free-thinking group method for generating ideas to handle a challenging situation. An underlying maxim for Brainstorming is “from quantity comes quality.” The primary objective of Brainstorming is to encourage innovation and out-of-the-box thinking. To achieve this goal, the Brainstorming session is performed with no editing: analysis, discussion, and criticism are allowed only after the session. Business Case: A Business Case is a broad statement that helps sell or justify a specific improvement opportunity to the senior leadership or stakeholders in an organization. This is generally part of a Lean Six Sigma Project Charter. A Business Case defines how the customer is negatively impacted, how long they’ve been impacted, and the benefits of making of an improvement–or, conversely, the risks of not doing so. This is done by tying the improvement opportunity to the organization’s business objectives, which include their overall business strategy, customers, and values. P300 COPYRIGHT 2015 GOLEANSIXSIGMA.COM. ALL RIGHTS RESERVED. 4 Cause and Effect Diagram: A Cause and Effect Diagram is structured brainstorming tool designed to assist an improvement team in listing potential causes of a specific effect. It is also known as an Ishikawa Diagram, for its creator, or a Fishbone Diagram, for its resemblance to the bones of a fish. Causes are often grouped into major categories, which are classically defined as the 6 Ms: Man/Mind Power (people), Methods (processes), Machines (technology), Materials (raw materials, information, consumables), Measurements (inspection), and Milieu/Mother Nature (environment). An additional 2 Ms are also sometimes used: Management/Money Power and Maintenance. Central Tendency: Central Tendency is the “center point” of a process distribution. It can be measured in one of three ways: Median (middle most data point in a sorted data set), Mode (data value repeated most often), and Mean (average). Changeover Reduction: Changeover Reduction is the practice of dramatically reducing or eliminating the time to change from one method or unit to another. This concept is also known as Set-up Reduction or Single Minute Exchange of Die (SMED) where the goal is to reduce the changeover time to single digits or under 10 minutes. This was originally developed by Shigeo Shingo in order to reduce the time spent in setting up equipment or materials since setup does not add value.