Study guide
6.2 Process Analysis Tools and Value Stream Mapping
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
6.2 Process Analysis Tools and Value Stream Mapping
Key Takeaways Explain This Topic AI
Takt time establishes the mandatory pace of production required to match customer demand and is computed as Takt = Net Available Operating Time / Customer Demand Quantity.
Value-Stream Mapping (VSM) visualizes both information and material flows across an end-to-end process, distinguishing between Value-Added (VA), Non-Value-Added (NVA / Waste), and Necessary Non-Value-Added (NNVA) activities.
Process Lead Time represents the total elapsed clock time from process initiation to final delivery, whereas Cycle Time is the elapsed time required to complete one unit at an individual operational step.
Process Cycle Efficiency (PCE) measures lean process health as PCE = (Total Value-Added Time / Total Process Lead Time) * 100%, where lean world-class operations target PCE > 25% compared to traditional processes operating below 5%.
Last updated: August 2026
In the Measure phase of Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control), process flow analysis and Value Stream Mapping (VSM) serve as foundational techniques for establishing operational baselines. Before a Black Belt can quantify variation or process capability, the team must thoroughly map how work, materials, and information physically flow through the system. Value Stream Mapping expands traditional process flowcharting by capturing systemic relationships, inventory build-ups, information signals, and detailed time metrics across the end-to-end value chain.
Value Stream Mapping Architecture & Icons
A Value Stream encompasses all actions—both value-added and non-value-added—required to transform raw materials or initial customer requests into finished goods or completed services. Unlike standard high-level SIPOC (Suppliers, Inputs, Process, Outputs, Customers) diagrams or deployment (swimlane) flowcharts, a Value Stream Map explicitly couples material flow (moving from left to right across the lower half) with information flow (moving from right to left across the upper half).
Standard VSM Symbol Categories
Process Boxes : Represent individual operational work centers where transformation or handling occurs. Each box contains a dedicated Data Box recording empirical process parameters.
Data Boxes : Contain quantitative metrics collected during Gemba walks: Cycle Time ( C / T C/T C / T ), Changeover Time ( C / O C/O C / O ), Uptime (Machine Availability %), Work-in-Process (WIP) inventory, batch sizes, number of operators, and available shift time.
Inventory Triangles : Represent material queues, storage buffers, or staging areas between process steps, labeled with the exact quantity of inventory ( I I I ).
Information Flow Lines : Depict manual information flows (straight thin arrows) or electronic data transfers (zigzag lightning arrows) such as ERP/MRP scheduling, production control orders, and Kanban signals.
Timeline Ladder : Positioned at the bottom of the map, contrasting Value-Added Processing Time (on the lower step) against Non-Value-Added Inventory Lead Time (on the upper step).
Process Time Definitions & Mathematical Formulations
Precise statistical definition of time metrics is critical for Lean Six Sigma Practitioners to quantify waste and establish production cadence:
1. Takt Time
Derived from the German word Taktzeit (meter or beat), Takt Time is the maximum allowable time per unit of product or service required to meet customer demand. It is not the time it takes to build a product, but rather the required pace of production. Takt Time = Net Available Operating Time per Period Customer Demand Quantity per Period \text{Takt Time} = \frac{\text{Net Available Operating Time per Period}}{\text{Customer Demand Quantity per Period}} Takt Time = Customer Demand Quantity per Period Net Available Operating Time per Period
Where:
Net Available Operating Time = Total gross shift time minus planned downtime (rest breaks, meal times, shift handover, planned maintenance, and scheduled team meetings).
Customer Demand Quantity = Total units required by the customer over the identical operating period.
Example Calculation: A manufacturing cell operates on a single 8-hour (480-minute) shift per day. Planned downtime includes two 15-minute rest breaks and a 30-minute lunch break. Daily customer demand is 420 units.
Net Available Time = 480 min − ( 15 + 15 + 30 ) min = 420 minutes = 25 , 200 seconds 480\text{ min} - (15 + 15 + 30)\text{ min} = 420\text{ minutes} = 25,200\text{ seconds} 480 min − ( 15 + 15 + 30 ) min = 420 minutes = 25 , 200 seconds .
Takt Time = 25 , 200 seconds 420 units = 60.0 seconds/unit \frac{25,200\text{ seconds}}{420\text{ units}} = 60.0\text{ seconds/unit} 420 units 25 , 200 seconds = 60.0 seconds/unit .
The production cell must produce exactly one conforming unit every 60 seconds to satisfy customer demand without creating overproduction waste.
2. Cycle Time ( C / T C/T C / T )
Cycle Time is the actual measured time elapsed between the completion of consecutive units at a specific process step. It measures the operational speed of a process step.
Value-Added Cycle Time ( V A C / T VA C/T V A C / T ) : The portion of cycle time dedicated to physically transforming the part.
Machine Cycle Time : The time required for automated equipment to complete its processing cycle.
Operator Cycle Time : The hands-on work time required by an operator to load, unload, inspect, and run a process step.
3. Lead Time ( L / T L/T L / T ) & Little's Law
Process Lead Time (or Throughput Time) is the total calendar or clock time elapsed from the moment an order or part enters the process stream until it is fully completed and delivered. Inventory stored between process steps directly inflates Lead Time. Utilizing Little's Law , inventory quantities are converted into equivalent lead time: Inventory Lead Time = Work-in-Process (WIP) Inventory Quantity Daily Customer Demand (or Daily Output Rate) \text{Inventory Lead Time} = \frac{\text{Work-in-Process (WIP) Inventory Quantity}}{\text{Daily Customer Demand (or Daily Output Rate)}} Inventory Lead Time = Daily Customer Demand (or Daily Output Rate) Work-in-Process (WIP) Inventory Quantity Total Process Lead Time = ∑ Inventory Lead Times + ∑ Process Cycle Times \text{Total Process Lead Time} = \sum \text{Inventory Lead Times} + \sum \text{Process Cycle Times} Total Process Lead Time = ∑ Inventory Lead Times + ∑ Process Cycle Times
4. Process Cycle Efficiency (PCE)
Process Cycle Efficiency measures the proportion of total lead time that is genuinely spent adding value for the customer: PCE = ( Total Value-Added Time Total Process Lead Time ) × 100 % \text{PCE} = \left( \frac{\text{Total Value-Added Time}}{\text{Total Process Lead Time}} \right) \times 100\% PCE = ( Total Process Lead Time Total Value-Added Time ) × 100%
In traditional non-lean processes, PCE is frequently below 5 % 5\% 5% , meaning that over 95 % 95\% 95% of process lead time consists of waiting, storage, and queue delays. Lean world-class benchmark operations achieve a PCE greater than 25 % 25\% 25% .
Categorization of Process Activities
Six Sigma practice categorizes every process task into one of three distinct operational buckets to eliminate waste and optimize flow:
Activity Category Operational Definition Three Screening Criteria Strategic Action
Value-Added (VA) Tasks that directly transform the product or service into a state the customer desires. 1. The customer is willing to pay for the activity.; 2. The activity physically transforms the item.; 3. The activity is performed correctly the first time. Optimize & Standardize (Minimize variation)
Necessary Non-Value-Added (NNVA) Tasks that add no direct customer value but are required by current regulations, laws, safety standards, or technological limitations. 1. Customer will not pay for it.; 2. No physical transformation occurs.; 3. Required by external compliance or current technology. Minimize & Streamline (Reduce duration and labor overhead)
Non-Value-Added (NVA / Waste) Tasks that consume time, space, or resources without adding customer value or satisfying regulatory requirements. 1. Customer is unwilling to pay.; 2. No transformation occurs.; 3. Can be eliminated without impacting product compliance. Eliminate Completely (Identify root cause and remove)
The 8 Wastes of Lean (TIMWOODS)
Transportation : Excessive movement of materials, parts, or documents between locations.
Inventory : Excess raw materials, WIP, or finished goods exceeding immediate operational requirements.
Motion : Unnecessary physical movement of personnel (searching, bending, stretching, walking).
Waiting : Idle time spent waiting for materials, approvals, machine cycles, or upstream work.
Overproduction : Producing items faster, earlier, or in greater quantities than required by customer Takt time (the worst form of waste).
Overprocessing : Performing redundant, overly precise, or unnecessary process steps beyond customer specification.
Defects : Rework, scrap, inspection overhead, and corrective efforts caused by non-conforming work.
Skills / Talent Underutilization : Failing to engage employees' problem-solving capabilities, intelligence, and creative ideas.
- Selecting Among the Process Analysis Tools
- Body of Knowledge topic V.A.2 asks Black Belts to select, use, and evaluate process analysis tools at
- the Evaluate level, naming value stream maps, process maps, work instructions, flowcharts, spaghetti
- diagrams, and the gemba walk. Value stream mapping is treated above; the point of this topic is choosing
the right instrument for the question being asked.
Tool What it shows Best question to answer Blind spot
Value stream map Material and information flow, with process time, wait time, and inventory between steps Where does the lead time actually go? Too coarse to expose within-step method variation
Process map / flowchart Sequence of activities, decisions, and rework loops What are the steps, and where does work loop back? No time or distance information
Swimlane (deployment) map The same flow with responsibility by function or role Where are the handoffs, and who owns each step? Can hide physical movement
Spaghetti diagram The physical path a person, part, or document travels, drawn on a layout How much motion and transportation does the layout force? Says nothing about decision logic or quality
Work instruction Exactly how one task is performed Is the documented method the method actually used? Describes the intended process, not the real one
Gemba walk Direct observation of the process as it runs What actually happens, including the undocumented workarounds? Observer effect; one walk is one sample
- Spaghetti diagrams
- A spaghetti diagram is drawn on a scale layout of the work area. Follow one operator, one part, or one
- document through a full cycle and draw a continuous line along the actual path taken. The result makes
- motion and transportation waste immediately visible, and it quantifies them: measure the total path
length, multiply by the number of cycles per shift, and the walking becomes minutes of paid time.
- A worked figure of the kind these produce: an operator whose path measures 132 metres per cycle, running
- 34 cycles per shift, walks 4.5 km per shift. At a normal walking pace that is roughly 55 minutes of paid
- time per shift spent moving rather than working -- a business case that a process map alone would never
surface.
Spaghetti diagrams are the natural precursor to a cell redesign, a 5S event, or a point-of-use material
relocation, and re-drawing the diagram after the change is the simplest possible before-and-after proof.
Comparing the documented process with the real one
The most valuable analysis in this topic is the comparison between the work instruction and the gemba observation . Three outcomes, each with a different action:
- Finding Interpretation Action
- Documented and observed methods match The standard is real Improve the standard itself
Observed method is better than documented Operators have improved it informally Capture and standardize the better method
Observed method is worse, or varies by operator The standard is impractical, unclear, or untrained Fix the standard and the training, then re-observe
Skipping this comparison is how teams end up modelling and improving a process that exists only on
paper. Walk the process before mapping it, and map what you saw rather than what you were told.
- Conducting a gemba walk
- Go to the actual place, look at the actual process, and talk to the people doing the work. Practical
- discipline: observe a full cycle without interrupting, then ask questions; ask what happens when
- something goes wrong rather than whether problems occur; follow one unit end to end rather than watching
- one station; and observe on more than one shift, because shift-to-shift differences are frequently the
largest source of variation in the whole study.