2.3 Business Systems, Processes, and Stakeholder Relationships

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

2.3 Business Systems, Processes, and Stakeholder Relationships

Key Takeaways Explain This Topic AI

A business system is a set of interdependent processes; system output is limited by the interactions between processes, not by the best-performing process.

Optimizing a sub-process against local metrics while degrading system performance is sub-optimization, and it is the single most common failure of departmental improvement.

Stakeholders divide into internal (employees, functions, executives), connected (customers, suppliers, distributors, shareholders), and external (regulators, communities, industry bodies).

SIPOC is the standard tool for making system interdependencies visible at project scope, because it names suppliers and customers explicitly.

ASQ tests this topic at the Understand level, focusing on recognizing interdependence and predicting the impact of a change on other parts of the system.

Last updated: August 2026

Processes, systems, and why the distinction matters
A process is a set of activities that transforms inputs into outputs for a customer. A business
system is a network of processes whose outputs feed one another, governed by shared resources,
shared information, and shared constraints. The distinction is not academic: a Black Belt who treats a

process as an island will produce a locally impressive project with no measurable enterprise benefit.

Deming's formulation is the one worth memorizing: a system must have an aim , and the components
must be managed to optimize the aim of the system rather than the aims of the components. It follows
that the requirements of a sub-process may not align with organizational objectives -- and when they

conflict, the sub-process requirement is the one that must give way.

The enterprise process architecture

Most organizations describe their processes in a three-tier hierarchy:

Tier Name Example Typical owner
1 Core / value-creating Order to cash, concept to launch, procure to pay Value-stream owner
2 Support / enabling Recruiting, IT service management, facilities, training Functional manager
3 Governance / management Strategic planning, risk management, internal audit Executive team

Core processes touch the external customer directly and are where DMAIC projects normally live.

Support processes have internal customers and are chronically under-measured, which makes them
fertile project ground once the core is stable. Governance processes are where project selection and

resourcing decisions are actually made -- which is why a Black Belt who cannot influence them stalls.

Interactive relationships and sub-optimization
Processes interact through four channels, and every one of them is a route by which a local

improvement can damage the system:

Material and work flow. Speeding an upstream step without matching downstream capacity simply

moves the queue and inflates work in process.

Shared resources. Two processes drawing on the same equipment, inspectors, or specialists are

coupled even when their flows never touch. Loading one starves the other.

Information. Forecast accuracy, specification changes, and engineering change orders propagate

across process boundaries with lags that create the classic bullwhip amplification.

Policy and incentive. A purchasing department measured on unit price buys cheaper material

that raises scrap in production. This is the textbook case of a metric creating a defect.

Sub-optimization is the general name for all four failures: improving a component measure while
degrading the system measure. The diagnostic question is always the same -- what does this
improvement do to the next process downstream, to the processes sharing my resources, and to the

measures my counterparts are judged on?

Stakeholders

The exam uses "stakeholder" broadly. A workable classification:

Class Who What they care about How a project reaches them

Internal Operators, engineers, functional managers, executives Workload, job security, targets, capital Process changes, new standard work, retraining

Connected Customers, suppliers, distributors, shareholders Quality, delivery, price, return Specification changes, delivery performance, cost

External Regulators, accreditation bodies, local community, industry associations Compliance, safety, environmental impact Validated changes, notifications, reporting

Two implications matter for a Black Belt. First, suppliers are inside the system , not outside it:

tightening an internal tolerance without telling the supplier who feeds that characteristic converts
your improvement into their defect. Second, regulated processes cannot be improved unilaterally ;
in medical devices, pharmaceuticals, aerospace, and food safety, a validated process change requires
change control, revalidation, and sometimes regulatory notification, and that timeline belongs in the

project plan from Define.

Making interdependence visible

Three tools do most of the work:

SIPOC (Suppliers, Inputs, Process, Outputs, Customers) forces you to name who feeds the process
and who consumes its output before you scope anything. It is the standard Define-phase answer to
"who else does this touch?"
Value stream maps extend the view across process boundaries, showing information flow as well

as material flow and exposing where queues form between departments.

Interrelationship digraphs map cause-and-effect links among issues and identify which node is

the strongest driver -- useful when the interactions are organizational rather than physical.

Worked example
A distribution center reduces outbound picking time 30% by batching orders into larger waves. Local
metrics improve: picks per labour hour rise, and the picking manager's dashboard turns green. System
effects: order cycle time rises because early orders in a wave wait for the wave to fill; carrier
trailers now load in a compressed window, so dock congestion and detention charges rise; and customer
service handles more "where is my order" calls. Net effect on the enterprise measure -- perfect order

fulfilment -- is negative.

The failure was not the technique. Wave picking is a legitimate lean tactic. The failure was

evaluating it against a component metric without checking the three adjacent processes it touched.

Exam framing
ASQ tags I.A.3 at the Understand level. Expect scenario questions where a described improvement
helps one department and harms another, and you must identify the interaction, name the affected

stakeholder, or select the systems-level measure that should have governed the decision.