6.1 Process Flow Metrics and the Hidden Factory

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

6.1 Process Flow Metrics and the Hidden Factory

Key Takeaways Explain This Topic AI

Takt time is customer demand rate, computed as available production time divided by customer demand; it is set by the customer, never by the process.

Cycle time is the actual time between successive completions at a step; the bottleneck is the step whose cycle time is longest.

Little's Law states that work in process equals throughput multiplied by lead time, so lead time can be reduced by cutting WIP without changing the process.

Touch time is value-added work time only; process cycle efficiency is touch time divided by total lead time and is typically under 10% in office processes.

A hidden factory is undocumented rework that inflates touch time and consumes capacity while never appearing in the recorded yield or scrap figures.

Last updated: August 2026

The core flow metrics

• Metric Definition Set by
• Takt time Available production time divided by customer demand over the same period The customer
• Cycle time Actual elapsed time between two successive completions at a step The process
• Lead time Total elapsed time from entry to exit of the process, including all waiting The system
• Touch time Time actually spent adding value to the unit The work content
• Throughput Units completed per unit of time The bottleneck
• Work in process (WIP) Units inside the process boundary, started but not finished Release policy
• Work in queue (WIQ) Units waiting to be worked on, a subset of WIP Imbalance and batching

Takt versus cycle time Takt time = Available production time Customer demand \text{Takt time} = \frac{\text{Available production time}}{\text{Customer demand}} Takt time = Customer demand Available production time ​

If a line runs two 8-hour shifts with 45 minutes of breaks per shift and demand is 870 units per day: Takt = 2 × ( 480 − 45 ) min 870 = 870 870 = 1.0 min/unit \text{Takt} = \frac{2 \times (480 - 45) \text{ min}}{870} = \frac{870}{870} = 1.0 \text{ min/unit} Takt = 870 2 × ( 480 − 45 ) min ​ = 870 870 ​ = 1.0 min/unit

Takt is a requirement , not a measurement. Cycle time is a measurement of what the process

actually does. Comparing the two at each step is the standard line-balancing analysis:

Step cycle time greater than takt: the step cannot keep up; it constrains the line.

Step cycle time much less than takt: the step is under-utilized; consider combining stations.

All steps close to but under takt: balanced line.

The bottleneck is the step with the longest cycle time. Throughput of the whole process equals the

throughput of the bottleneck, which is why improving a non-bottleneck step changes nothing.

Little's Law W I P = Throughput × Lead time ⟺ Lead time = W I P Throughput WIP = \text{Throughput} \times \text{Lead time} \quad \Longleftrightarrow \quad \text{Lead time} = \frac{WIP}{\text{Throughput}} W I P = Throughput × Lead time ⟺ Lead time = Throughput W I P ​

Little's Law is the most useful relationship in the Measure phase because it holds for any stable

process regardless of its internal structure. Two consequences:

Lead time can be reduced by reducing WIP alone , with no change to the process itself. Halving

the number of orders released into a stable process halves the lead time.

WIP is a controllable input. Releasing more work into a system already at capacity increases WIP

and therefore lead time, without increasing throughput at all.

Worked example. A claims process holds 480 open claims and completes 60 per day. Lead time = 480 60 = 8 days \text{Lead time} = \frac{480}{60} = 8 \text{ days} Lead time = 60 480 ​ = 8 days

If a WIP cap reduces open claims to 240 while throughput stays at 60 per day, lead time falls to 4

days. Nothing about the work changed; only the queue did.

Touch time and process cycle efficiency Process cycle efficiency = Touch time (value-added time) Total lead time × 100 \text{Process cycle efficiency} = \frac{\text{Touch time (value-added time)}}{\text{Total lead time}} \times 100 Process cycle efficiency = Total lead time Touch time (value-added time) ​ × 100

• A loan application with 42 minutes of touch time and a 6-day (2,880 working-minute) lead time has an
• efficiency of 1.5%. Transactional processes commonly fall between 1% and 10%; a well-run lean
• manufacturing cell may reach 25% or more. The number is worth computing early because it tells the
• team where the opportunity is: at 1.5%, working on the 42 minutes of touch time is pointless, and all

the value is in the 2,838 minutes of waiting.

• Identifying the constraint
• The Body of Knowledge specifically asks that these metrics be used to determine constraints . A

practical sequence:

Compute takt time from actual customer demand.

Measure cycle time at every step, with enough observations to see the variation, not just the mean.

Plot cycle time by step against the takt line.

Look for where WIP and WIQ accumulate -- inventory piles up in front of the constraint.

Confirm with utilization: the constraint runs near 100% while others idle.

The physical evidence usually settles it before the arithmetic does. Queues form immediately upstream

of the bottleneck and starvation appears immediately downstream.

• The hidden factory
• A hidden factory is the set of undocumented activities -- rework, retest, workarounds, informal
• inspection, chasing missing information -- that a process performs routinely but that appears in no

routing, no standard time, and no yield report.

Why it matters to each metric:

• Metric Distortion caused by the hidden factory
• Touch time Understated, because rework loops are not in the standard routing
• Cycle time Actual step cycle time exceeds the standard, apparently without cause
• Throughput Effective capacity is lower than nameplate; overtime is chronic
• WIP Higher than the routing predicts, because units cycle back
• First-pass yield Overstated, because units repaired in-station are counted as good
• Capability Overstated, because the measured output has already been corrected
• The classic symptom is a process that reports 99% yield but requires 15% overtime to meet a schedule

it was sized for. That gap is the hidden factory.

• Finding it
• Walk the process and count every unit that moves backwards. Rework almost always travels

against the primary flow.

Compare standard routing time with actual labour hours per unit. The difference is unrecorded

work.

Ask operators what they do when something is wrong , not whether defects occur. The answer is

usually a well-established informal procedure.

Measure first-pass yield at each step , defined as units passing with no rework of any kind,

rather than final yield after correction.

Look for uncounted inventory : the reject bin that gets reworked at shift end, the "pending

clarification" folder, the parts on the maintenance bench.

• The measurement fix is to define first-pass yield as right first time with no touch-up , and to
• make rework visible by requiring it to be recorded with a reason code before the unit re-enters the
• flow. Making rework visible almost always reduces reported yield in the first month, which must be

explained to the sponsor in advance or it will be read as the project making things worse.