ASQ CSSBB Certification Exam Syllabus

I. Organization-Wide Planning and Deployment (12 Questions)

1. Fundamentals of Six Sigma and lean methodologies
- Define and describe the value and goals of these approaches, and describe the integration and complementary relationship between them. Identify and understand an organization’s lean six sigma maturity model. (Understand)

1. Roles and responsibilities
- Describe the roles and responsibilities of executive leadership, champions, sponsors, process owners, Master Black Belts, Black Belts, and Green Belts in driving Six Sigma and lean initiatives. Understand the importance of coaching multiple levels of leadership and belts on appropriate six sigma tools and techniques. Understand the importance of finance and its role supporting a project and confirming its outcome. Describe how each group influences project deployment in terms of providing or managing resources, enabling changes in organizational structure, and supporting communications about the purpose and deployment of the initiatives. (Understand)

2. Organizational barriers
- Describe how an organization’s structure and culture can impact Six Sigma projects. Identify common causes of Six Sigma failures, including lack of management support and lack of resources. (Apply)

3. Change Management
- Apply and facilitate change management techniques, including stakeholder analysis, readiness assessments, proactive change management, and communication plans to overcome barriers and drive organization-wide change. (Apply)

II. Organizational Process Management and Measures (12 Questions)

1. Performance measures
- Define and describe balanced scorecard, key performance indicators (KPIs), key behavior indicators (KBIs), objectives and key results (OKRs), customer loyalty metrics, and leading and lagging indicators. Explain how to create a line of sight from performance measures to organizational strategies. (Analyze)

2. Financial measures
- Define and use revenue growth, market share, margin, net present value (NPV), return on investment (ROI), and cost benefit analysis (CBA). Explain the difference between hard cost measures (from profit and loss statements) and soft cost benefits of cost avoidance and reduction. (Apply)

III. Team Management (15 Questions)

1. Team types and constraints
- Define and describe various teams, including virtual, cross-functional, and self-directed. Determine what team type will work best for a given a set of constraints, e.g., geography, technology availability, staff schedules, time zones. (Apply)

2. Team roles and responsibilities
- Define and describe various team roles and responsibilities for the leader, facilitator, coach, and individual member. (Understand)

3. Team member selection criteria
- Describe various factors that influence the selection of team members, including the ability to influence, openness to change, required skill sets, subject matter expertise, and availability. (Apply)

4. Team success factors
- Identify and describe the elements necessary for successful teams, e.g., management support, clear goals, ground rules, and timelines. (Apply)

1. Motivational techniques
- Describe and apply techniques to motivate team members. Identify factors that can demotivate team members and describe techniques to overcome them. (Apply)

2. Team stages of development
- Identify and describe the classic stages of team development: forming, storming, norming, performing, and adjourning. (Apply)

3. Team communication
- Describe and explain the elements of an effective communication plan, e.g., audience identification, message type, medium, and frequency. (Apply)

4. Team leadership models
- Describe and select appropriate leadership approaches (e.g., direct, coach, support, and delegate) to ensure team success. (Apply)

1. Group behaviors
- Identify and use various conflict resolution techniques (e.g., coaching, mentoring, and intervention) to overcome negative group dynamics, including dominant and reluctant participants, groupthink, rushing to finish, and digressions. (Evaluate)

2. Meeting management
- Select and use various meeting management techniques, including using agendas, starting on time, requiring pre-work by attendees, and ensuring that the right people and resources are available. (Apply)

3. Team decision-making methods
- Define, select, and use various tools (e.g., consensus, nominal group technique, and multi-voting) for decision making. (Apply)

1. Needs assessment
- Identify the steps involved to implement an effective training curriculum: identify skills gaps, develop learning objectives, prepare a training plan, and develop training materials. (Understand)

2. Delivery
- Describe various techniques used to deliver effective training, including adult learning theory, soft skills, and modes of learning. (Understand)

3. Evaluation
- Describe various techniques to evaluate training, including evaluation planning, feedback surveys, pre-training and post-training testing. (Understand)

IV. Define (20 Questions)

1. Customer Identification
- Identify and segment customers and show how a project will impact both internal and external customers. (Apply)

2. Customer data collection
- Identify and select appropriate data collection methods (e.g., surveys, focus groups, interviews, and observations) to gather voice of the customer data. Ensure the data collection methods used are reviewed for validity and reliability. (Analyze)

3. Customer requirements
- Define, select, and apply appropriate tools to determine customer needs and requirements, including critical-to-X (CTX when “X” can be quality, cost, safety, etc.), CTQ tree, quality function deployment (QFD), supplier, input, process, output, customer (SIPOC), and Kano model. (Analyze)

1. Business case
- Describe business case justification used to support projects. (Understand)

2. Problem statement
- Develop a project problem statement and evaluate it in relation to baseline performance and improvement goals. (Evaluate)

3. Project scope
- Develop and review project boundaries to ensure that the project has value to the customer. (Analyze)

4. Goals and objectives
- Identify SMART (specific, measurable, actionable, relevant, and timebound) goals and objectives on the basis of the project’s problem statement and scope. (Analyze)

5. Project performance measurements
- Identify and evaluate performance measurements (e.g., cost, revenue, delivery, schedule, and customer satisfaction) that connect critical elements of the process to key outputs. (Analyze)

6. Project charter review
- Explain the importance of having periodic project charter reviews with stakeholders. (Understand)

V. Measure (25 Questions)

1. Process flow metrics
- Identify and use process flow metrics (e.g., work in progress (WIP), work in queue (WIQ), touch time, takt time, cycle time, and throughput) to determine constraints. Describe the impact that “hidden factories” can have on process flow metrics. (Analyze)

2. Process analysis tools
- Select, use, and evaluate various tools, e.g., value stream maps, process maps, work instructions, flowcharts, spaghetti diagrams, and gemba walk. (Evaluate)

1. Types of data
- Define, classify, and distinguish between qualitative and quantitative data, and continuous and discrete data. (Evaluate)

2. Measurement scales
- Define and use nominal, ordinal, interval, and ratio measurement scales. (Apply)

3. Sampling
- Define and describe sampling concepts, including representative selection, homogeneity, bias, accuracy, and precision. Determine the appropriate sampling method (e.g., random, stratified, systematic, subgroup, and block) to obtain valid representation in various situations. (Evaluate)

4. Data collection plans and methods
- Develop and implement data collection plans that include data integrity, accuracy, and processing tools, e.g., check sheets, and data normalization. Avoid data collection pitfalls by defining the metrics to be used or collected, ensuring that collectors are trained in the tools and understand how the data will be used, and checking for seasonality effects. (Analyze)

1. Measurement system analysis (MSA)
- Use gauge repeatability and reproducibility (R&R) studies and other MSA tools (e.g., bias, correlation, linearity, precision to tolerance, and percent agreement) to analyze variable measurement system capability. Use audit MSA for attribute measurement system. (Evaluate)

2. Measurement systems across the organization
- Identify how measurement systems can be applied across all functional areas of the organization (e.g., marketing, sales, engineering, research and development (R&D), supply chain management, operations, and customer experience). (Understand)

3. Metrology
- Define and describe elements of metrology, including calibration systems, traceability to reference standards, and the control and integrity of measurement devices and standards. (Understand)

1. Basic statistical terms
- Define and distinguish between population parameters and sample statistics, e.g., proportion, mean, and standard deviation. (Apply)

2. Central limit theorem
- Explain the central limit theorem and its significance in the application of inferential statistics for confidence intervals, hypothesis tests, and control charts. (Understand)

3. Descriptive statistics
- Calculate and interpret measures of dispersion and central tendency. (Evaluate)

4. Graphical methods
- Construct and interpret diagrams and charts, e.g., box-and-whisker plots, scatter diagrams, histograms, normal probability plots, frequency distributions, and cumulative frequency distributions. (Evaluate)

5. Valid statistical conclusions
- Distinguish between descriptive and inferential statistical studies. Evaluate how the results of statistical studies are used to draw valid conclusions. (Evaluate)

1. Basic concepts
- Describe and interpret probability concepts, e.g., independence, mutually exclusive events, addition and multiplication rules, conditional probability, complementary probability, and joint occurrence of events. (Understand)

2. Common distributions
- Describe, interpret, and use normal, Poisson, binomial, chi square, Student’s t, and F distributions. (Evaluate)

3. Additional distributions
- Identify hypergeometric, bivariate, exponential, lognormal, and Weibull distributions. (Understand)

1. Process capability indices
- Define, select, and calculate Cp and Cpk. (Evaluate)

2. Process performance indices
- Define, select, and calculate Pp, Ppk, Cpm, and process sigma. (Evaluate)

3. General process capability studies
- Describe and apply elements of designing and conducting process capability studies relative to characteristics, specifications, sampling plans, stability, and normality. (Evaluate)

4. Process capability for attributes data
- Calculate the process capability and process sigma level for attributes data. (Apply)

5. Process capability for non-normal data
- Identify non-normal data and determine when it is appropriate to use Box-Cox or other transformation techniques. (Apply)

6. Process performance vs. specification
- Distinguish between natural process limits and specification limits. Calculate process performance metrics, e.g., percent defective, parts per million (PPM), defects per million opportunities (DPMO), defects per unit (DPU), first pass yield, and rolled throughput yield (RTY). (Evaluate)

7. Short-term and long-term capability
- Describe and use appropriate assumptions and conventions when only short-term data or only long-term data are available. Interpret the relationship between short-term and long-term capability. (Evaluate)

VI. Analyze (22 Questions)

1. Correlation coefficient
- Calculate and interpret the correlation coefficient and its confidence interval and describe the difference between correlation and causation. (Evaluate)

2. Linear regression
- Calculate and interpret regression analysis and apply and interpret hypothesis tests for regression statistics. Use the regression model for estimation and prediction, analyze the uncertainty in the estimate, and perform a residuals analysis to validate the model. (Evaluate)

3. Multivariate tools
- Understand sources of variation through multivariate tools (e.g., factor analysis, discriminant analysis, and multiple analysis of variance (MANOVA). (Understand)

1. Terminology
- Define and interpret the significance level, power, type I, and type II errors of statistical tests. (Evaluate)

2. Statistical vs. practical significance
- Define, compare, and interpret statistical and practical significance. (Evaluate)

3. Sample size
- Calculate sample size for common hypothesis tests: equality of means and equality of proportions. (Apply)

4. Point and interval estimates
- Define and distinguish between confidence and prediction intervals. Define and interpret the efficiency and bias of estimators. Calculate tolerance and confidence intervals. (Evaluate)

5. Tests for means, variances, and proportions
- Use and interpret the results of hypothesis tests for means, variances, and proportions. (Evaluate)

6. Analysis of variance (ANOVA)
- Select, calculate, and interpret the results of ANOVAs. (Evaluate)

7. Goodness-of-fit (chi square) tests
- Define, select, and interpret the results of these tests. (Evaluate)

1. Types of risk
- Identify, assess, and prioritize various types of risk such as, enterprise, operational, supplier, security, product, and cyber-security. (Analyze)

2. Failure mode and effects analysis
- Describe, the purpose and elements of FMEA, including risk priority number (RPN), and evaluate FMEA results for processes, products, and services. Distinguish between design FMEA (DFMEA) and process FMEA (PFMEA), and interpret their results. (Evaluate)

1. Gap analysis
- Analyze scenarios to identify performance gaps, and compare current and future states using predefined metrics. (Analyze)

2. Root cause analysis
- Define and describe the purpose of root cause analysis, recognize the issues involved in identifying a root cause, and use various tools (e.g., 5 whys, Pareto charts, fault tree analysis, cause and effect diagrams, and A3) to resolve chronic problems. (Analyze)

3. Waste analysis
- Identify and interpret the seven classic wastes (overproduction, inventory, defects, over-processing, waiting, motion, and transportation) and resource under-utilization. (Analyze)

VII. Improve (21 Questions)

1. Terminology
- Define basic DOE terms, e.g., independent and dependent variables, factors and levels, response, treatment, error, and nested. (Understand)

2. Design principles
- Define and apply DOE principles, e.g., power, sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, and resolution. (Apply)

3. Planning experiments
- Plan and evaluate DOEs by determining the objective, selecting appropriate factors, responses, and measurement methods, and choosing the appropriate design. (Evaluate)

4. One-factor experiments
- Understand when to use completely randomized, randomized block, and Latin square designs. (Understand)

5. Two-level fractional factorial experiments
- Understand these types of experiments, and describe how confounding can affect their use. (Understand)

6. Full factorial experiments
- Understand these types of experiments. (Understand)

1. Waste elimination
- Select and apply tools and techniques for eliminating or preventing waste, e.g., pull systems, kanban, 5S, standard work, and poka-yoke. (Analyze)

2. Cycle-time reduction
- Use various tools and techniques for reducing cycle time, e.g., continuous flow, single-minute exchange of die (SMED), and heijunka (production leveling). (Analyze)

3. Kaizen
- Define and distinguish between kaizen and kaizen blitz and describe when to use each method. (Apply)

4. Other improvement tools and techniques
- Identify and describe how other process improvement methodologies are used, e.g., theory of constraints (TOC), and overall equipment effectiveness (OEE). (Understand)

VIII. Control (17 Questions)

1. Objectives
- Explain the objectives of SPC, including monitoring and controlling process performance, tracking trends, runs, and reducing variation within a process. (Understand)

2. Selection of variables
- Identify and select critical process characteristics for control chart monitoring. (Apply)

3. Rational subgrouping
- Define and apply the principle of rational subgrouping. (Apply)

4. Control chart selection
- Select and use control charts in various situations: X-R, X-s, individual and moving range (ImR), p, np, c, u, short-run SPC, and moving average. (Apply)

5. Control chart analysis
- Interpret control charts and distinguish between common and special causes using rules for determining statistical control. (Analyze)

1. Total productive maintenance (TPM)
- Define the elements of TPM and describe how it can be used to consistently control the improved process. (Understand)

2. Visual controls
- Define the elements of visual controls (e.g., pictures of correct procedures, color-coded components, and indicator lights), and describe how they can help control the improved process. (Understand)

1. Measurement system reanalysis
- Review and evaluate measurement system capability as process capability improves, and ensure that measurement capability is sufficient for its intended use. (Evaluate)

2. Control plan
- Develop a control plan to maintain the improved process performance, enable continuous improvement, and transfer responsibility from the project team to the process owner. (Apply)

1. Lessons learned
- Document the lessons learned and benefits realized from all phases of a project and identify strategies for reinforcing and replicating improvements. (Apply)

2. Documentation
- Develop or modify documents including standard operating procedures (SOPs), work instructions, and control plans to ensure that the improvements are sustained over time. (Apply)

3. Training for process owners and staff
- Develop and implement training plans that are handed off to process owners to ensure consistent execution of revised process methods, KPIs to confirm sustained benefits, and standards to maintain process improvements. (Apply)

4. Ongoing evaluation
- Identify and apply tools (e.g., control charts, and control plans) for ongoing evaluation of the improved process, including monitoring leading indicators, lagging indicators, and additional opportunities for improvement. (Apply)

IX. Design for Six Sigma (DFSS) Framework and Methodologies (6 Questions)