9.10 Ongoing Evaluation of the Improved Process

ASQ Certified Six Sigma Black Belt CSSBB

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1 Chapter 1: Introduction & CSSBB Exam Strategy

1.1 CSSBB Exam Format, Scoring, and Testing Windows 1.2 Eligibility, Project Affidavits, Application, and Recertification 1.3 Open-Book Strategy, Reference Materials, and a 16-Week Study Plan

2 Chapter 2: Organization-Wide Planning and Deployment

2.1 Fundamentals of Six Sigma and Lean Methodologies 2.2 Selecting the Right Methodology: DMAIC, DFSS, and Lean 2.3 Business Systems, Processes, and Stakeholder Relationships 2.4 Strategic Planning and Deployment of Six Sigma Initiatives 2.5 Six Sigma Roles and Responsibilities 2.6 Organizational Barriers and Common Causes of Six Sigma Failure 2.7 Change Management: Stakeholder Analysis, Readiness, and Communication

3 Chapter 3: Organizational Process Management and Measures

3.1 Impact of Six Sigma Projects on Customers, Suppliers, and Stakeholders 3.2 Benchmarking Types and Performance Goal Setting 3.3 Performance Measures: Balanced Scorecard, KPIs, KBIs, OKRs, and Line of Sight 3.4 Leading and Lagging Indicators and Performance Dashboards 3.5 Financial Measures: Revenue Growth, Margin, NPV, ROI, and Cost-Benefit Analysis 3.6 Cost of Poor Quality and Hard versus Soft Savings

4 Chapter 4: Team Management

4.1 Team Types and Constraints 4.2 Team Roles, Responsibilities, and Member Selection 4.3 Team Success Factors and Ground Rules 4.4 Motivational Techniques and Overcoming Demotivators 4.5 Stages of Team Development and Conflict Resolution 4.6 Team Communication Plans 4.7 Team Leadership Models: Direct, Coach, Support, and Delegate 4.8 Group Behaviors, Conflict Resolution, and Meeting Management 4.9 Facilitation Techniques and Team Decision-Making Methods 4.10 Team Training: Needs Assessment, Delivery, and Evaluation

5 Chapter 5: Define Phase

5.1 Customer Identification and Segmentation 5.2 Customer Data Collection: Methods, Validity, and Reliability 5.3 Customer Requirements: CTX, CTQ Trees, and Operational Definitions 5.4 The Kano Model and Quality Function Deployment 5.5 SIPOC and Process Mapping 5.6 Business Case Justification 5.7 The Project Charter and the Problem Statement 5.8 Project Scope and Boundaries 5.9 SMART Goals and Project Performance Measurements 5.10 Project Charter Reviews and Toll-Gate Governance 5.11 Project Management Tools: Gantt Charts, Toll-Gate Reviews, WBS, and RACI 5.12 Analytical Tools Used Throughout the DMAIC Cycle

6 Chapter 6: Measure Phase

6.1 Process Flow Metrics and the Hidden Factory 6.2 Process Analysis Tools and Value Stream Mapping 6.3 Types of Data and Measurement Scales 6.4 Sampling Concepts, Methods, and Sample Size for Estimation 6.5 Data Collection Plans and Common Pitfalls 6.6 Gage R&R for Variable Measurement Systems 6.7 Attribute Agreement Analysis and Audit MSA 6.8 Measurement Systems Across the Organization, and Metrology 6.9 Population Parameters, Sample Statistics, and Valid Statistical Conclusions 6.10 Descriptive Statistics: Central Tendency, Dispersion, and Shape 6.11 Graphical Methods for Exploratory Data Analysis 6.12 Probability Concepts, Common Distributions, and the Central Limit Theorem 6.13 Additional Distributions: Hypergeometric, Exponential, Lognormal, Weibull, and Bivariate 6.14 Process Capability and Performance Indices 6.15 Capability Studies, Attributes Capability, Yield Metrics, and Long-Term Capability

7 Chapter 7: Analyze Phase

7.1 The Correlation Coefficient, Its Confidence Interval, and Causation 7.2 Linear Regression and Residual Analysis 7.3 Multivariate Tools: Factor Analysis, Discriminant Analysis, and MANOVA 7.4 Hypothesis Testing Terminology, Errors, and Single-Sample Tests 7.5 Statistical Versus Practical Significance 7.6 Sample Size for Hypothesis Tests 7.7 Point Estimates, Confidence, Prediction, and Tolerance Intervals 7.8 Tests for Means, Variances, and Proportions 7.9 Analysis of Variance 7.10 Chi-Square Goodness-of-Fit and Tests of Independence 7.11 Types of Risk and Failure Mode and Effects Analysis 7.12 Gap Analysis and Root Cause Analysis 7.13 Waste Analysis: The Seven Classic Wastes and Resource Under-Utilization

8 Chapter 8: Improve Phase

8.1 Design of Experiments: Objectives, Terminology, and Effects 8.2 DOE Design Principles: Randomization, Blocking, Replication, and Resolution 8.3 Planning and Evaluating Designed Experiments 8.4 One-Factor Experiments: Completely Randomized, Randomized Block, and Latin Square Designs 8.5 Full Factorial Experiments and Design Selection 8.6 Two-Level Fractional Factorial Experiments and Confounding 8.7 Response Surface Methodology and Optimization 8.8 Waste Elimination: Pull Systems, Kanban, 5S, and Poka-Yoke 8.9 Cycle-Time Reduction: Continuous Flow, SMED, and Heijunka 8.10 Kaizen, Kaizen Blitz, Theory of Constraints, and OEE 8.11 Implementation Planning, Piloting, and Solution Selection

9 Chapter 9: Control Phase

9.1 SPC Objectives, Variable Selection, and Rational Subgrouping 9.2 Control Charts for Variables Data 9.3 Control Charts for Attributes Data 9.4 Short-Run SPC and Moving Average Charts 9.5 Control Chart Analysis: Common Cause, Special Cause, and Run Rules 9.6 Total Productive Maintenance and Visual Controls 9.7 Measurement System Reanalysis 9.8 Control Plan Development and Process Owner Handoff 9.9 Lessons Learned, Documentation, and Training for Sustainment 9.10 Ongoing Evaluation of the Improved Process

10 Chapter 10: Design for Six Sigma (DFSS)

10.1 DFSS Frameworks: DMADV, DMADOV, and Design Transfer 10.2 Design for X (DFX) 10.3 Robust Design, Parameter Design, and Verification 10.4 Tolerance Design and Statistical Tolerancing

9.10 Ongoing Evaluation of the Improved Process

Key Takeaways Explain This Topic AI

Ongoing evaluation combines control charts, control plan audits, leading and lagging indicators, and a scheduled review cadence.

Leading indicators are process inputs that predict the outcome; lagging indicators confirm it after the fact.

Control plan audits verify that the control is executed as written, which is different from verifying that the result is still good.

A defined review cadence with a named owner is what distinguishes sustained improvement from a gain that quietly decays.

Ongoing evaluation should feed the next improvement cycle, because a stable improved process reveals the next constraint.

Last updated: August 2026

What ongoing evaluation covers

Four questions, each with its own instrument and frequency.

Question Instrument Frequency Owner

Is the process still in statistical control? Control chart with an out-of-control action plan Per subgroup Operator

Are the controls being executed as written? Layered process audit, control plan audit Daily to weekly Supervisor

Is the outcome still at the improved level? Lagging KPI against the post-project baseline Weekly to monthly Process owner

Is the financial benefit still being realized? Finance validation 6 and 12 months Finance and sponsor

The second row is the one most often omitted, and it is the leading indicator of sustainment failure:

results usually decay after compliance decays, so an outcome-only monitoring plan detects the problem

a month or two late.

Leading and lagging indicators in sustainment

Leading Lagging
What it measures Process inputs and behaviours ( X X X s) Process outcomes ( Y Y Y s)
Timing Available now; predictive Available after the fact
Actionability High -- corrective action still possible Low -- the result is already produced

Examples Control chart signals per week, audit compliance rate, calibration on-time rate, training coverage, setup verification completion Defect rate, DPMO, first pass yield, customer complaints, warranty claims

A sustainment monitoring plan needs both. Leading indicators tell you the improvement is about to fail;
lagging indicators confirm whether it has. Monitoring only lagging indicators means learning about the

failure from the customer.

Two or three leading indicators is the right number. A monitoring plan with fifteen measures is not

monitored.

Control plan audits
A control plan audit answers "is the control being executed as written?" -- which is a different
question from "is the output still good?" A process can produce acceptable output for weeks after its

controls have lapsed, right up until the condition that the control was protecting against occurs.

Layered process audits (LPA) are the standard mechanism: short, frequent checks of the same small set

of high-risk process controls, performed at several levels of the organization.

Layer Who Frequency Typical scope
1 Team leader or supervisor Daily, each shift 5-10 questions on the critical controls
2 Department manager Weekly Same questions, a sample of stations
3 Plant manager or senior staff Monthly Same questions, spot check
The multi-layer structure is what makes it work: senior participation signals that the controls matter,
and it removes the possibility of a supervisor quietly stopping the audits. Findings must be corrected

immediately or logged with an owner and a date.

The review cadence

Interval Review Content Attendees
Daily Shift review Control chart signals, andon events, audit findings Operators, supervisor
Weekly Process review KPI trend, open corrective actions, audit compliance Process owner, quality

Monthly Sustainment review Performance versus the post-project baseline; leading indicator trends Process owner, sponsor

6 and 12 months Benefit validation Finance confirmation that the benefit persists Finance, sponsor, Black Belt
The 6 and 12-month checks are the ones that distinguish a real sustainment system from a paper one, and
they should be scheduled at project closure with a calendar invitation and a named owner , not left

to be remembered.

Detecting decay

Symptom Likely cause Response

Control chart drifts back toward the old mean The control is not being executed Audit compliance; re-train; check whether the control is impractical

Audit compliance falls while results hold Early sustainment failure Intervene now, before results follow

A new special-cause pattern appears New source of variation: material, personnel, equipment Investigate as a new problem, not as project failure

Benefit erodes without a process change Volume, mix, or cost-basis change Recompute the benefit basis with finance

The control plan has not been updated after a process change Documentation drift Change control; update FMEA and control plan together

The most common sustainment failure is not resistance but impracticality : a control that takes too
long, obstructs the work, or conflicts with an output target will be abandoned quietly. When compliance

falls, ask whether the control is workable before concluding that the people are the problem.

Feeding the next cycle
The Body of Knowledge asks specifically that ongoing evaluation identify additional opportunities for
improvement , and this is not an afterthought. A stabilized process makes the next opportunity visible

in a way that a chaotic one never could:

The new constraint. Removing one bottleneck exposes another; the theory of constraints says to go

back to step 1.

The residual variation. A control chart on a stable improved process shows the common-cause

variation that remains, which is the target for the next capability project.

Newly visible special causes. Once the dominant noise is gone, smaller assignable causes become

detectable.

Replication targets. The solved problem probably exists elsewhere.

The entitlement gap. The best week of the improved process is the new entitlement, and the gap

between it and the new average is the next project.

Closing a project should therefore produce two artifacts: a control plan with a named owner, and a short

list of the next opportunities the project revealed, handed to the project selection process.