Lean Operations, Six Sigma and Continuous Improvement

Introduction

Lean operations and Six Sigma are complementary approaches to improving operational performance. Lean focuses primarily on the efficient flow of value and the removal of activities that do not create value for the customer. Six Sigma focuses primarily on reducing variation, defects and process instability through disciplined statistical and managerial methods. Continuous improvement connects both approaches to the development of repeatable learning, employee involvement and sustained organizational capability.

For operations managers, these methods are not merely collections of tools. They represent different ways of understanding work. Lean asks: What prevents value from flowing? Six Sigma asks: Why does the process fail to meet requirements consistently? A robust improvement system asks both questions while also considering cost, safety, employee well-being, environmental impact, resilience and customer experience.

Lean originated in the Toyota Production System, whose major ideas include just-in-time production, jidoka, standardized work, respect for people and systematic problem solving. Six Sigma was developed and popularized in industrial organizations such as Motorola and General Electric. Contemporary improvement programmes frequently integrate Lean and Six Sigma into Lean Six Sigma.

Learning Objectives

By the end of this chapter, the reader should be able to:

1. Explain the principles and objectives of Lean operations and Six Sigma.
2. Identify the eight forms of operational waste and distinguish value-adding from non-value-adding work.
3. Apply 5S, takt time, pull systems, Kanban, just-in-time production and cellular operations.
4. Use Kaizen, standard work and visual management to support continuous improvement.
5. Apply the DMAIC framework and root-cause analysis to process problems.
6. Interpret basic flow, capacity and quality measures relevant to improvement projects.
7. Evaluate the organizational, ethical and practical limitations of Lean and Six Sigma.
8. Design an improvement approach that produces sustainable operational and strategic benefits.

1. Foundations of Lean Operations

1.1 Value and the value stream

Lean begins with value as defined by the customer. An activity is value-adding when it changes the product or service in a way the customer requires, performs the transformation correctly, and does so right the first time. Activities that consume resources but do not create customer value are non-value-adding. Some non-value-adding activities may nevertheless be necessary because of regulation, technology or current process constraints; these should be minimized or redesigned.

A value stream includes all actions required to deliver a product or service, from customer demand through fulfilment. Value-stream mapping makes material, information and decision flows visible. It helps distinguish processing time from waiting, movement, inspection, rework and other forms of delay.

1.2 The eight wastes

The traditional Lean categories are often remembered by the acronym TIMWOODS:

The wastes are interconnected. Overproduction can create inventory; inventory can conceal defects; large batches can produce long waiting times; and poor workplace organization can increase motion and errors. Therefore, isolated waste removal may produce limited benefit unless the underlying system is redesigned.

1.3 Lean principles

Five commonly cited Lean principles are:

1. Specify value from the customer’s perspective.
2. Identify the value stream and expose waste.
3. Create flow by reducing interruptions, queues, changeover time and unevenness.
4. Establish pull so that downstream demand governs replenishment.
5. Pursue perfection through continuous improvement.

These principles should not be interpreted mechanically. A system designed for uninterrupted flow may be unsuitable where demand is highly uncertain, products are highly customized or capacity is constrained by long supplier lead times. Lean design must be contingent on product, process and demand characteristics.

2. Flow, Capacity and Takt Time

2.1 Takt time

Takt time is the pace of production required to meet customer demand. It is not the same as cycle time. Cycle time is the actual time required to complete one unit at a process step; takt time is the customer-required interval between completed units.

Available production time must exclude planned breaks, meetings and other non-production intervals. Both numerator and denominator must use consistent time units.

Worked example. A service centre operates 7.5 hours per shift, has one 30-minute planned break, and must complete 84 cases per shift. Available time is 7 hours, or 420 minutes.

The average process pace must therefore be no slower than one completed case every five minutes. This does not mean every case will take exactly five minutes; variation may require buffers or flexible capacity.

2.2 Cycle time, throughput and capacity

If a workstation has an effective cycle time of 4 minutes per unit, its theoretical rate is:

For a seven-hour shift:

This assumes the workstation is available throughout the scheduled time and that quality losses, changeovers and interruptions have already been reflected in the effective cycle time. If not, the result is only theoretical capacity.

For a process with sequential workstations, the bottleneck is the step with the lowest effective capacity. Improving a non-bottleneck step may increase local efficiency without increasing total throughput. Constraint-based analysis therefore complements Lean tools.

2.3 Line balancing

Line balancing assigns tasks to workstations so that work content is distributed as evenly as practical. If total task work content is W and the desired cycle time is C, the theoretical minimum number of stations is:

where ⌈x⌉ means rounding upward to the next whole station. The formula assumes tasks can be assigned without violating precedence constraints. Actual stations may exceed this minimum because tasks cannot always be divided, workers may require recovery time, or equipment and skill constraints may apply.

3. Pull Systems, Kanban and Just-in-Time

3.1 Push and pull

In a push system, production is authorized by a forecast, schedule or upstream plan, often regardless of downstream consumption. In a pull system, replenishment is triggered by actual use or a defined downstream signal. Pull does not eliminate planning; it changes the control logic from “produce because the schedule says so” to “replenish because the next process consumed it.”

Just-in-time (JIT) seeks to provide the right item, in the right quantity, at the right time and place. It requires dependable processes, short lead times, capable suppliers, rapid changeovers and reliable information. JIT is not simply low inventory. Low inventory without process capability can create frequent shortages and instability.

3.2 Kanban

Kanban is a visual or electronic authorization mechanism that controls replenishment. A kanban may be a card, container, barcode signal or digital message. A basic two-bin system uses one bin at the point of use and one replenishment bin. When the first bin is emptied, it becomes the signal for replenishment while the second bin supports continued use.

A commonly used starting-point formula for the number of kanban containers is:

where:

• n = number of containers or kanban cards;
• D = demand rate per time period;
• L = replenishment lead time in the same time unit;
• S = safety factor expressed as a decimal;
• C = quantity per container.

The formula assumes relatively stable demand, a reasonably known lead time and a fixed container quantity. It is a design approximation, not a guarantee against disruption.

Worked example. Demand is 240 components per day, replenishment lead time is 0.5 day, the safety factor is 10%, and each container holds 30 components.

Reducing the number of containers reduces authorized inventory, but it also reduces protection against variability. The appropriate number should be reviewed using service-level, lead-time and disruption data.

3.3 Conditions for successful pull systems

Successful pull systems normally require:

• stable definitions of demand and replenishment responsibility;
• reliable equipment and material availability;
• quality at the source;
• controlled batch sizes;
• clear signals and limits on work-in-process;
• rapid response to abnormal conditions; and
• disciplined adherence to standard work.

A Kanban card cannot solve an unstable process. If signals are ignored, quantities are altered informally or defects are passed downstream, the system becomes a form of disguised expediting.

4. 5S, Standard Work and Cellular Operations

4.1 5S

5S is a workplace organization and visual-management method:

1. Sort – remove unnecessary items.
2. Set in order – locate necessary items for efficient access.
3. Shine – clean and inspect the workplace.
4. Standardize – establish consistent methods and visual controls.
5. Sustain – audit, learn and maintain the discipline.

5S is not fundamentally a housekeeping campaign. Cleaning can reveal leaks, wear, contamination and abnormal conditions. Labels, shadow boards, floor markings and point-of-use storage reduce search time and expose deviations. However, 5S should not become an audit-based compliance exercise that burdens employees without improving work.

4.2 Standard work

Standard work specifies the best currently known method for performing a task safely, with the required quality, in the required time. It commonly identifies:

• takt or target cycle time;
• work sequence;
• standard in-process inventory; and
• quality and safety checkpoints.

Standard work is a baseline for improvement, not a claim that the method can never change. Without a stable baseline, managers cannot determine whether a change actually improved performance.

4.3 Cellular operations

A cellular layout groups machines, people and activities according to product or service families rather than functional similarity alone. A well-designed cell reduces transport, waiting and handoffs and makes flow visible. Cells may support one-piece flow or small batches.

Cellular design can create challenges. Equipment duplication may increase capital cost, workers may need broader skills, and demand changes may make a family-based layout less suitable. Managers should assess product variety, volume, routing similarity, ergonomic risk and workforce capability before implementing cells.

5. Kaizen and Problem-Solving Culture

Kaizen means continuous, incremental improvement. It can involve small daily changes by frontline employees or focused improvement events addressing a specific process. Effective Kaizen is based on direct observation, clear problem definition, experimentation and follow-up.

A useful improvement cycle is Plan–Do–Study–Act (PDSA):

• Plan: define the problem, understand the current condition and propose a test;
• Do: conduct the test on a controlled scale;
• Study: compare results with the prediction and investigate unexpected effects;
• Act: standardize the successful change or revise the hypothesis.

Kaizen differs from random idea generation. An idea becomes improvement only when the process performs better on a relevant measure without creating unacceptable harm elsewhere. Measures should include quality, safety, delivery, cost, employee experience and environmental consequences where relevant.

6. Six Sigma and Process Capability

6.1 Variation and defects

Six Sigma treats variation as a major source of defects, delay and cost. A defect occurs when an output fails to meet a defined requirement. A critical distinction is between common-cause variation, which is inherent in the current system, and special-cause variation, which arises from an unusual, identifiable event.

Control charts help distinguish these forms. A process should not be adjusted after every ordinary fluctuation; excessive adjustment can increase instability. Conversely, an unusual pattern should prompt investigation rather than be dismissed as noise.

6.2 Defects per million opportunities

A commonly used quality measure is defects per million opportunities (DPMO):

A unit may contain more than one opportunity for failure. The measure requires a clearly defined defect opportunity and consistent counting rules. DPMO is not the same as defective units per million because one unit may contain several defects.

Example. An organization examines 2,000 forms, each with 5 possible defect opportunities, and identifies 30 defects.

6.3 Process capability

For a stable, approximately normally distributed process with specification limits, potential capability is often represented by:

where USL is the upper specification limit, LSL is the lower specification limit and σ is the within-process standard deviation. Cₚ measures the width of the specification range relative to process spread but does not consider centering.

Centered capability is represented by:

where μ is the process mean. These indices are meaningful only when the process is reasonably stable and the assumptions about distribution and measurement are appropriate. A high capability index calculated from an unreliable measurement system or an unstable process can be misleading.

7. DMAIC and Root-Cause Analysis

DMAIC is the principal Six Sigma improvement framework:

Define

Specify the customer, problem, business impact, boundaries, objectives and project governance. A useful problem statement describes the gap without prematurely asserting its cause.

Measure

Define operational measures, validate the measurement system and establish the current baseline. Measurement-system analysis is essential: apparent process variation may originate from inconsistent inspectors, instruments or data definitions.

Analyze

Explore patterns and relationships using process maps, stratification, Pareto analysis, scatter plots, capability analysis and appropriate statistical methods. Correlation alone does not prove causation.

Improve

Develop, test and implement solutions. Experiments should consider technical feasibility, human factors, risk, cost and unintended consequences. Mistake-proofing, simplification, point-of-use information and improved process design are usually stronger than relying solely on inspection.

Control

Document the new standard, assign process ownership, establish monitoring, train affected employees and define a response plan for abnormal performance. Control is the mechanism that prevents temporary project gains from disappearing.

Root-cause tools

The five-whys method repeatedly asks why a condition occurred until a systemic, actionable cause is identified. It is useful for simple causal chains but can oversimplify complex interactions. Fishbone diagrams organize possible causes under categories such as people, methods, machines, materials, measurement and environment. Pareto analysis prioritizes categories by frequency, cost or impact; it does not imply that only the largest category deserves attention when safety or legal risk is involved.

A strong root-cause analysis tests hypotheses with evidence. “Operator error” is usually an incomplete conclusion. The analysis should ask why the error was possible, whether instructions were clear, whether the interface encouraged the mistake, whether workload or training was adequate and why controls failed to detect it.

8. A Lean Six Sigma Improvement Architecture

Lean and Six Sigma should be integrated according to the nature of the problem. Lean tools are particularly useful when the main issue is delay, excess work-in-process, poor flow or unnecessary activity. Six Sigma methods are especially valuable when the main issue is variation, defects or uncertain causal relationships.

A practical architecture is:

1. Establish strategic purpose and customer requirements.
2. Select a process and define its boundaries.
3. Observe the actual work and map the value stream.
4. Stabilize the workplace through safety, 5S, standard work and basic reliability.
5. Measure flow, quality, cost and variation.
6. Identify constraints and verified root causes.
7. Test improvements using Kaizen, DMAIC or PDSA.
8. Redesign pull, capacity, layout and information flows.
9. Control the new process and review benefits.
10. Replicate learning without assuming that every context is identical.

Improvement portfolios should distinguish local optimization from system performance. For example, increasing machine utilization may increase inventory and lead time if the machine is not the constraint. Similarly, reducing headcount without improving process design may transfer work, increase risk or damage capability.

9. Metrics and Governance

Useful operational measures include lead time, throughput, first-pass yield, on-time delivery, work-in-process, changeover time, availability, employee suggestions implemented and customer complaints. A balanced performance system should avoid rewarding one measure at the expense of others.

Little’s Law provides a useful relationship for a stable process:

where L is average work-in-process, λ is average throughput rate and W is average flow time. Units must be consistent, such as cases, cases per day and days. The relationship applies to long-run averages in a stable system; it does not by itself explain causes or guarantee that reducing inventory will reduce lead time.

For example, if a process completes 40 orders per day and average flow time is 3 days, average work-in-process is:

If flow time is reduced while throughput remains constant, work-in-process should decline. Managers should verify that the reduction is real and not caused by delayed transactions or work being moved outside the measured boundary.

Governance requires clear ownership, transparent definitions and regular review. Improvement data should not be manipulated to satisfy targets. Employees should be able to report hazards, quality concerns and process weaknesses without retaliation.

10. Applied Case: Improving Order Fulfilment in a Distribution Centre

The following is an illustrative case based on common distribution-centre conditions.

Background

A regional distributor processes 1,200 customer orders per day. Customers expect shipment on the same day for orders received before 14:00. The centre has five functional zones: receiving, storage, picking, packing and dispatch.

Problem

Only 88% of eligible orders ship on time. Observations show long walking distances, batches waiting for complete picking, frequent location searches and rework caused by incorrect quantities. Average work-in-process between picking and packing is 2,400 order lines.

Analysis

A value-stream map shows that actual picking and packing work totals approximately 18 minutes per order, but average elapsed time is 6.2 hours. A Pareto analysis identifies three major contributors to late shipment: waiting for batch completion, location-search time and picking errors. Interviews reveal that replenishment signals are informal and that high-volume items are not located according to demand patterns.

The team checks measurement definitions and samples orders across shifts. It finds that the late-shipment measure excludes orders held for correction, masking the customer impact. This illustrates why measurement-system validation is necessary before improvement.

Approach

The centre introduces the following changes:

• 5S and visual location standards in picking zones;
• a demand-based slotting review for high-frequency items;
• two-bin replenishment Kanban for selected fast movers;
• smaller picking waves and a controlled pull signal from packing;
• standard work for scanning, quantity confirmation and exception handling;
• a daily Kaizen review of defects and delays;
• a DMAIC project for recurring picking errors.

The team does not immediately purchase automation. It first stabilizes data, locations and work methods. A pilot is conducted in one zone for four weeks, with measures for on-time shipment, picking accuracy, walking distance, work-in-process and employee-reported ergonomic strain.

Outcome

After the pilot, on-time shipment rises from 88% to 96%, average work-in-process falls from 2,400 to 1,500 order lines and picking accuracy improves. The team also identifies an unintended effect: replenishment work becomes concentrated at a particular time, creating ergonomic strain. The schedule is therefore redesigned and job rotation is introduced. The results are not accepted as permanent until the new standard is audited over several demand cycles.

Learning points

The case demonstrates that Lean improvement is a system intervention, not a single tool. 5S supports visibility, Kanban supports replenishment, standard work supports consistency, and DMAIC supports evidence-based analysis. It also demonstrates the importance of measuring employee impact and testing unintended consequences. A project that improves delivery while increasing injury risk would not represent operational excellence.

11. Implementation Challenges and Limitations

Change resistance and culture

Employees may resist Lean when previous programmes used “efficiency” to justify arbitrary workload increases or job reductions. Leaders must explain the purpose, involve employees in design and distinguish waste removal from indiscriminate labour reduction. Psychological safety is essential for reporting problems.

Over-standardization

Standards can support quality, but excessive rigidity can prevent professional judgment and adaptation. Standard work should identify the normal method and escalation rules while allowing controlled response to unusual conditions.

Local optimization

Improving one department may worsen total flow. Functional targets such as utilization, output per hour or local cost must be balanced with end-to-end measures such as lead time, first-pass yield and customer service.

Data and statistical limitations

Poor definitions, small samples, autocorrelation, non-independent observations and unstable processes can invalidate conclusions. Statistical significance is not identical to managerial importance. A small effect may be statistically detectable but operationally irrelevant; a safety-critical effect may require action even with limited data.

Supply-chain vulnerability

Very low inventory and single sourcing can increase exposure to disruption. Resilience may require strategic buffers, multiple suppliers, postponement, flexible capacity or scenario planning. Lean should eliminate unnecessary inventory, not all protective capacity.

Ethical and regulatory considerations

Improvement must comply with labour, safety, privacy, environmental and product-quality requirements. Digital work measurement and AI-enabled monitoring can create surveillance risks, biased performance assessments and loss of autonomy. Data governance should specify purpose, access, retention, validation and employee rights. Automation decisions should consider redeployment, retraining and distributive effects rather than treating labour solely as a cost.

12. Technology, AI and Contemporary Development

Digital technologies can strengthen Lean and Six Sigma when they improve visibility and decision quality. Internet-of-Things sensors can provide real-time equipment data; process mining can reconstruct actual administrative workflows; digital Kanban can coordinate replenishment; and machine learning can support anomaly detection or predictive maintenance.

However, technology does not remove the need for process understanding. An algorithm trained on incomplete or biased data may amplify errors. Automated alerts can create alert fatigue, while dashboards can encourage managers to optimize what is easy to measure. Before implementing AI, organizations should define the decision, validate data quality, test model performance across operating conditions and retain human accountability.

Contemporary improvement programmes increasingly combine operational excellence with sustainability and resilience. Energy use, emissions, material loss, worker well-being and supply continuity should be treated as process outcomes. A process that is fast but unsafe, wasteful or fragile is not excellent in a broad managerial sense.

Best-Practice Principles

1. Begin with customer and stakeholder value, not with a favourite tool.
2. Observe the actual process before proposing solutions.
3. Stabilize safety, quality and basic process conditions first.
4. Use takt time, capacity and bottleneck analysis to understand flow.
5. Reduce batch size and work-in-process only when process capability supports it.
6. Validate data and measurement systems before drawing conclusions.
7. Treat frontline employees as sources of knowledge, not merely recipients of instructions.
8. Prefer prevention and mistake-proofing to end-of-process inspection.
9. Pilot changes, measure unintended consequences and revise standards.
10. Make improvement part of normal management rather than a temporary campaign.

Chapter Summary

Lean operations improve the flow of customer value by removing waste, reducing delay and establishing disciplined pull systems. Takt time translates demand into a required production pace, while cycle time and bottleneck analysis reveal capacity limitations. Kanban and JIT coordinate replenishment, but they depend on stable processes, reliable quality and responsive suppliers. 5S, standard work and cellular operations create visibility and repeatability.

Kaizen develops continuous, employee-involved improvement through observation, experimentation and learning. Six Sigma addresses variation and defects through measurement, statistical reasoning and the DMAIC framework. Root-cause analysis must move beyond blaming individuals to examine system conditions and failed controls. Metrics such as DPMO, process capability and Little’s Law support analysis when their assumptions and definitions are respected.

Lean Six Sigma is most effective when aligned with strategy and governed through balanced measures. Its success depends on leadership behaviour, employee participation, ethical data use and sustained control. Low inventory, high utilization or rapid throughput should not be pursued in isolation. Operational excellence requires safe, reliable, customer-oriented, resilient and socially responsible processes.

Key Terms

Lean operations: An approach focused on customer value, flow and waste elimination.

Value stream: All activities and information flows required to deliver a product or service.

Waste: Resource consumption that does not create required customer value.

Takt time: Customer-required production pace, calculated as available time divided by demand.

Cycle time: Time required to complete one unit at a process step.

Pull system: A system in which downstream consumption authorizes replenishment.

Kanban: A visual or electronic signal controlling production or replenishment.

Just-in-time: Provision of the right item, quantity and timing with minimal unnecessary inventory.

5S: Sort, Set in order, Shine, Standardize and Sustain.

Standard work: The best currently known safe and effective method for performing a task.

Cellular operations: Grouping resources around product or service families to support flow.

Kaizen: Continuous, incremental improvement involving systematic learning.

Six Sigma: A disciplined approach to reducing defects and process variation.

DPMO: Defects per million opportunities.

Process capability: The ability of a stable process to meet specification requirements.

DMAIC: Define, Measure, Analyze, Improve and Control.

Root cause: A verified systemic condition whose removal prevents recurrence.

Common-cause variation: Variation inherent in the current process system.

Special-cause variation: Variation arising from an identifiable unusual event.

Poka-yoke: Mistake-proofing that prevents or immediately detects error.

Review Questions

Short Answer Questions

1. What is the difference between takt time and cycle time?
2. Identify the eight categories of Lean waste.
3. What is the purpose of a Kanban signal?
4. Why is standard work important for continuous improvement?
5. Distinguish common-cause variation from special-cause variation.

Long Answer Questions

1. Explain the five principles of Lean operations and discuss their interdependence.
2. Describe the DMAIC framework and explain the importance of measurement-system validation.
3. Compare push and pull systems, including the conditions required for effective JIT operations.
4. Explain how 5S, cellular operations and standard work can jointly improve operational flow.
5. Critically evaluate the benefits and limitations of integrating Lean and Six Sigma.

Analytical / Application Questions

1. A process operates for 450 available minutes per shift and must produce 90 units. Calculate takt time and explain how it should be used in line balancing.
2. Daily demand is 300 components, replenishment lead time is 0.4 day, safety factor is 15%, and container size is 25 components. Calculate the required number of Kanban containers using the formula in this chapter. State one limitation of the calculation.
3. A department reports improved machine utilization but longer customer lead times and rising work-in-process. Use bottleneck logic and Little’s Law to diagnose how this result may have occurred and recommend two actions.

Multiple Choice Questions with Answers

Question 1

Which statement best distinguishes takt time from cycle time?

A. Takt time is the actual processing time, while cycle time is customer demand.

B. Takt time is the customer-required pace, while cycle time is the time needed to complete a unit.

C. Takt time applies only to services, while cycle time applies only to manufacturing.

D. Takt time measures defects, while cycle time measures inventory.

Correct Answer: B. Takt time is the customer-required pace, while cycle time is the time needed to complete a unit.

Question 2

A process has 360 available minutes and demand for 72 units. What is the takt time?

A. 3 minutes per unit

B. 5 minutes per unit

C. 72 minutes per unit

D. 432 minutes per unit

Correct Answer: B. 5 minutes per unit

Question 3

Which of the following is an example of overproduction?

A. Moving material between adjacent workstations

B. Correcting an incorrect customer order

C. Producing reports before they are requested or needed

D. Waiting for equipment maintenance

Correct Answer: C. Producing reports before they are requested or needed

Question 4

What is the primary function of a Kanban signal?

A. Authorize replenishment based on downstream consumption

B. Measure employee satisfaction

C. Calculate process capability

D. Replace all production planning

Correct Answer: A. Authorize replenishment based on downstream consumption

Question 5

In DMAIC, which phase establishes the baseline and validates the measurement system?

A. Define

B. Measure

C. Improve

D. Control

Correct Answer: B. Measure

Question 6

A process produces 20 defects in 1,000 units, with 4 opportunities per unit. What is the DPMO?

A. 500

B. 2,000

C. 5,000

D. 20,000

Correct Answer: C. 5,000

Question 7

Which Lean practice is most directly associated with organizing, cleaning and visually controlling the workplace?

A. 5S

B. DMADV

C. Benchmarking

D. Regression analysis

Correct Answer: A. 5S

Question 8

If average throughput is 50 orders per day and average flow time is 2 days, what is average work-in-process according to Little’s Law?

A. 25 orders

B. 48 orders

C. 100 orders

D. 250 orders

Correct Answer: C. 100 orders

Question 9

Why can improving a non-bottleneck workstation fail to increase total throughput?

A. Non-bottleneck workstations never create value.

B. The system’s throughput remains constrained by the bottleneck.

C. Lean prohibits improvements outside the bottleneck.

D. Non-bottleneck workstations cannot be measured.

Correct Answer: B. The system’s throughput remains constrained by the bottleneck.

Question 10

Which statement about process capability indices is correct?

A. They are meaningful even when the process is unstable and the measurement system is invalid.

B. Cₚ considers centering, whereas Cₚₖ ignores centering.

C. Cₚ compares specification width with process spread, while Cₚₖ also reflects process centering.

D. Both indices measure customer satisfaction directly.

Correct Answer: C. Cₚ compares specification width with process spread, while Cₚₖ also reflects process centering.