3. Process Thinking and Value-Stream Analysis

Introduction and Context

Lean and Six Sigma improvement begins with a change in the unit of analysis. Traditional management often examines departments, job descriptions, budgets, and functional targets. Customers, however, experience neither departments nor organizational charts. They experience a sequence: a request is made, information is collected, decisions are taken, work is performed, and an outcome is delivered. Quality problems frequently arise not within a single activity but between activities, functions, systems, suppliers, and customers.

Process thinking provides a way to understand this sequence as an interconnected flow of work, information, decisions, materials, and responsibility. It asks how an output is created, where delays occur, how defects are introduced, and whether each activity contributes to customer or organizational value. Value-stream analysis extends this perspective across the complete end-to-end system, including activities that may cross departmental or organizational boundaries.

In Lean Six Sigma, process analysis is not merely a drawing exercise. A process map is a representation of reality used to support measurement, diagnosis, prioritization, and redesign. The quality of the analysis depends on the boundaries selected, the level of detail, the people involved, and the evidence used. A visually attractive map can still be misleading if it omits queues, rework, informal approvals, or customer effort.

This chapter develops four complementary approaches: SIPOC diagrams, process maps, value-stream maps, and service blueprints. It also examines bottlenecks, handoffs, queues, constraints, waste, and value leakage. The central argument is that improvement should be directed toward the flow of value rather than isolated local efficiencies.

Learning Objectives

After studying this chapter, students should be able to:

1. Explain process thinking and distinguish it from a purely functional view of work.

2. Construct and interpret SIPOC diagrams, cross-functional process maps, value-stream maps, and service blueprints.

3. Identify process boundaries, customers, suppliers, handoffs, queues, bottlenecks, constraints, rework, and value leakage.

4. Select appropriate process-analysis tools for different managerial and operational questions.

5. Use data such as cycle time, lead time, work-in-process, first-pass yield, and process time to diagnose flow problems.

6. Evaluate processes across organizational boundaries and propose Lean Six Sigma improvements.

7. Recognize common mapping errors, ethical concerns, and the role of digital technologies in process analysis.

From Functional Management to End-to-End Process Thinking

A process is a linked set of activities that transforms specified inputs into outputs for a customer or stakeholder. The customer may be external, such as a purchaser receiving a product, or internal, such as a claims examiner receiving a complete case file. A process has a beginning, an end, inputs, outputs, resources, controls, and recipients of its results.

A functional view asks, “What does the finance department do?” Process thinking asks, “How does a customer request become an approved and completed service, and where does finance contribute?” The second question reveals interactions that functional analysis can conceal. For example, a sales department may achieve its target for order volume while creating incomplete orders that generate downstream clarification, rework, and customer dissatisfaction.

End-to-end thinking does not make functional expertise irrelevant. Rather, it places expertise within the flow of value. Functional departments remain responsible for capability, standards, people, and technical decisions, but improvement decisions are assessed against total process performance. Local optimization is therefore treated cautiously. Reducing the workload of one department by transferring work to another is not genuine improvement.

A useful distinction is between activity and value-adding activity. An activity is value-adding when it changes the product or service in a way the customer requires, is performed correctly the first time, and does not violate applicable requirements. Some necessary activities, such as regulatory checks, may not be directly valued by the customer but are essential to responsible delivery. Other activities—waiting, duplicate entry, avoidable movement, correction, excessive approval, and searching—consume resources without increasing the value of the output. Lean analysis seeks to remove or reduce such waste while preserving necessary control.

Establishing the Process View: SIPOC

SIPOC is a high-level framework representing Suppliers, Inputs, Process, Outputs, and Customers. It is commonly used at the beginning of a Define or Measure activity because it establishes scope without prematurely becoming lost in operational detail.

A SIPOC is developed by first stating the process name and its intended start and end points. The team then identifies major process steps, usually at a high level, followed by outputs, customers, inputs, and suppliers. The sequence can be adjusted, but the resulting model should show the logic of transformation: suppliers provide inputs; the process converts those inputs; outputs are delivered to customers.

For example, a university admissions process might be represented as follows:

• Suppliers: applicants, examination bodies, payment providers, academic departments.
• Inputs: application data, transcripts, examination results, payment confirmation, admission criteria.
• Process: receive application, validate information, assess eligibility, make decision, communicate outcome, complete enrolment.
• Outputs: admission decision, notification, enrolment record, outstanding-information request.
• Customers: applicants, academic departments, registry, and regulators.

The SIPOC is not intended to show every approval, screen, or movement. Its value lies in clarifying scope, major participants, and output expectations. It also encourages the team to define customers broadly. A process can have several customers with different requirements; speed may matter to an applicant, accuracy to the registry, and compliance evidence to a regulator.

SIPOC is particularly useful when participants hold different assumptions about where the process begins and ends. It also exposes upstream input quality problems. If staff repeatedly correct incomplete applications, the problem may not be located in the assessment step but in the design of the input and submission process.

Mapping the Actual Work

Once scope is agreed, a more detailed process map can represent activities, decisions, loops, roles, systems, and flows. A conventional flowchart is suitable for showing sequence and decision logic. A cross-functional or swimlane map adds responsibility by placing activities in lanes for departments, roles, systems, suppliers, or customers.

The most reliable map describes the process as it is actually performed, often called the “current state,” rather than the documented or intended process. This requires observation, interviews, transaction records, and examination of exceptions. Employees may perform informal workarounds that are absent from standard operating procedures. Such workarounds are not simply deviations to be blamed; they may indicate that the formal design is impractical or that essential information is missing.

A process map should show:

• the trigger and completion condition;
• activities and decisions;
• inputs and outputs at significant points;
• responsible roles or systems;
• rework loops and exception paths;
• waiting points, queues, and batching;
• handoffs between people, departments, or technologies; and
• controls, approvals, and information requirements.

The level of detail must match the purpose. A map used to explain an entire order-to-cash process may contain ten to twenty macro-steps. A map used to diagnose invoice errors may need to show individual data fields, system validations, and correction loops. Excessive detail can obscure the main flow, whereas insufficient detail can conceal the cause of delay.

A practical mapping discipline is to distinguish activity time from elapsed time. An employee may spend five minutes reviewing a request, while the request remains in a queue for two days. If the map shows only the five-minute task, it presents a distorted picture of the customer's experience. Likewise, a handoff should be treated as a process event, not merely an arrow. At a handoff, information can be lost, responsibility can become ambiguous, and work may wait for acceptance.

Value-Stream Mapping: Seeing Flow and Time

Value-stream mapping (VSM) examines the flow of materials and information required to deliver a product or service. It is broader than a task sequence because it combines process structure with performance data. A typical map displays process steps, information flows, inventory or work-in-process, external suppliers and customers, production or service-control signals, and a timeline distinguishing processing time from waiting time.

Although VSM originated in manufacturing, its logic applies to transactional and service environments. In a loan application, for example, work-in-process consists of incomplete applications awaiting review, clarification, verification, or approval. Information flows may include emails, workflow notifications, spreadsheets, and system queues. The customer may experience a long lead time even though the total professional review time is short.

Important measures include:

• Lead time: elapsed time from the beginning to the end of the process.
• Process or touch time: time during which work is actively performed.
• Queue time: time work waits before the next activity.
• Work-in-process (WIP): items started but not yet completed.
• First-pass yield: proportion completed correctly without rework.
• Throughput: completed units per period.
• Takt time: the available production or service time divided by customer demand, used as a demand-based pacing reference.
• Process cycle efficiency: touch time divided by lead time, often used as an indicative measure of flow efficiency.

Little’s Law, expressed as WIP = Throughput × Flow Time, provides a useful relationship for stable systems. If an operation completes 40 cases per day and cases remain in the process for an average of 5 days, average WIP is approximately 200 cases. The relationship does not itself identify the cause of delay, but it shows why increasing WIP without increasing capacity generally increases flow time.

A current-state VSM should be based on observed data rather than estimates alone. Teams commonly collect demand volume, available time, staffing, processing times, queue sizes, changeover or setup time, defect and rework rates, and information-release frequency. The future-state map then depicts a deliberately redesigned flow. It may include pull signals, reduced batch sizes, clearer standards, workload balancing, mistake-proofing, and simplified information routes.

VSM should not be reduced to a hunt for the shortest processing time. A process may have low touch time but poor reliability, excessive variation, or weak controls. The future state must balance flow, quality, capacity, compliance, and customer requirements.

Service Blueprints and the Customer Experience

A service blueprint is especially valuable when the product is intangible and the customer participates in delivery. It separates customer actions, frontstage employee interactions, backstage activities, and support processes. It commonly includes a line of interaction between customer and provider, a line of visibility separating visible from invisible work, and a line of internal interaction separating frontline work from support processes.

Consider a hospital outpatient appointment. The customer's actions may include searching for a clinic, booking, completing forms, arriving, waiting, consulting, and receiving follow-up information. Frontstage activities include reception and clinical interaction. Backstage activities include record retrieval, appointment preparation, coding, and diagnostic coordination. Support processes include scheduling software, billing, laboratory services, and facilities management.

The blueprint reveals experience failures that an internal process map may miss. A patient may be asked to provide the same information at several points, wait without explanation, or encounter a mismatch between the promised and actual service. It also highlights “moments of truth,” where the customer's perception is strongly affected by communication, empathy, reliability, or recovery from failure.

Service blueprints complement VSM. VSM emphasizes flow, time, and waste across the value stream; blueprinting emphasizes customer participation, visibility, interaction quality, and backstage dependencies. In complex services, both perspectives may be needed.

Finding Bottlenecks, Constraints, and Handoffs

A bottleneck is a resource or stage whose effective capacity limits the output of the process. A constraint is broader: it is any factor that restricts the system from achieving its purpose. The constraint may be physical capacity, a policy, an approval rule, limited expertise, poor-quality inputs, an information system, or demand variability. A bottleneck can move when interventions change the system, so diagnosis must be repeated after improvement.

A busy resource is not automatically the system constraint. A resource may appear highly utilized because work is released to it in large batches, while another constraint is hidden by starvation or rework. Teams should compare demand with effective capacity, observe queues before and after each step, examine variation, and test whether improving a resource would increase total throughput.

The Theory of Constraints offers a practical logic: identify the constraint, exploit it using existing capability, subordinate other activities to it, elevate its capacity if necessary, and then reassess because the constraint may have shifted. This logic discourages indiscriminate improvement projects and focuses attention on the factor that governs system performance.

Handoffs deserve special attention. Every transfer of work creates potential for delay, information loss, unclear ownership, and divergent interpretation. A handoff is more reliable when the receiving party, acceptance criteria, required information, timing, and escalation route are explicit. Digital transfer does not eliminate handoff risk; automated systems can reproduce poor data, ambiguous statuses, or hidden queues at greater scale.

Queues are created when arrival rate temporarily or persistently exceeds service capacity, when work is deliberately batched, or when a downstream activity is unavailable. Queue reduction may require capacity, demand smoothing, prioritization, standard work, smaller batches, or prevention of incomplete inputs. Simply urging employees to work faster can increase defects and rework.

Waste and Value Leakage Across Boundaries

Lean commonly classifies waste as transportation, inventory, motion, waiting, overproduction, overprocessing, defects, and underused human capability. In services, these forms may appear as repeated data entry, excess reports, unused approvals, email searching, unresolved cases, duplicated verification, and customer effort.

Value leakage describes the loss of potential value between customer need and delivered outcome. It may result from defects, delays, poor communication, preventable customer effort, inconsistent decisions, or failure to use information generated earlier in the process. A process can meet internal output targets while leaking value externally. For example, a call centre may measure calls handled per hour but transfer customers repeatedly, creating dissatisfaction and repeat demand.

Boundary problems are particularly important. One organization may receive incomplete data from a supplier; a department may reject work that another considers complete; a platform may not share status information with a partner; or a customer may perform administrative work that the provider could have designed out. Analysis should therefore follow the product, case, patient, order, or request across the boundary rather than stopping at the local department.

An Integrated Method for Value-Stream Analysis

A disciplined analysis can proceed through the following sequence, adapted to the process and organizational context.

First, establish the improvement purpose and customer requirement. Define the unit of flow, such as an order, claim, application, patient episode, or service request. Specify the start and end points and identify the principal customer outcomes.

Second, form a cross-functional team. Include process owners, frontline employees, downstream recipients, data specialists, and—where appropriate—customers or representatives. A map created only by managers often reflects policy rather than practice.

Third, create a SIPOC to agree on scope and major relationships. Then walk the process and construct a current-state map or blueprint. Record exceptions, rework, queues, workarounds, and informal communication.

Fourth, add data. Measure demand, lead time, touch time, WIP, defects, rework, queue age, handoff frequency, and capacity. Use sampling where complete data are unavailable, but state assumptions clearly.

Fifth, interpret the flow. Identify the constraint, the longest queues, unstable inputs, repeated decisions, quality-at-source failures, and points where customer value is lost. Separate symptoms from causes. A queue may be a symptom of batch release, poor input quality, or an approval constraint.

Sixth, design a future state. Consider pull rather than uncontrolled push, smaller batches, standard work, visual controls, error-proofing, cross-training, automation, decision rights, and improved customer communication. Compliance and risk controls must be redesigned rather than casually removed.

Seventh, test and control the changes. Pilot where feasible, measure outcomes, obtain stakeholder feedback, and establish process ownership. Control plans, dashboards, standard work, and periodic review help prevent the process from returning to its former state.

Illustrative Case: Reducing Delays in a Commercial Insurance Claims Process

Background

The following is an illustrative case designed to demonstrate value-stream analysis. A commercial insurer receives property-damage claims from business customers through brokers, an online portal, and a call centre. The claims department reports that customers are dissatisfied with slow decisions, although staff believe that individual claims are reviewed promptly.

Situation and Problem

The stated target is a decision within ten working days. A preliminary investigation shows an average elapsed time of 18 working days. The process crosses brokers, customer service, claims intake, field assessors, legal reviewers, finance, and an external repair network. No single department owns the end-to-end experience.

Analysis

A SIPOC identifies brokers and policyholders as major suppliers of information, and claimants, brokers, finance, and regulators as customers of different outputs. A swimlane map reveals that customer service enters information into one system, while claims staff re-enter parts of it into another. Claims are placed in a daily batch for assignment. An assessor may wait several days for site access, and legal review is requested inconsistently.

The value-stream map records average touch time of 6.5 hours but lead time of 18 working days. The largest queues occur before assessor assignment and before final approval. Approximately one-third of claims are returned to intake because photographs, policy details, or loss descriptions are incomplete. The apparent speed of individual review therefore disguises waiting and rework.

The analysis identifies the assignment team as a practical constraint during peak demand, but also shows that poor input quality consumes its limited capacity. The process has multiple handoffs, and customers often contact the call centre because they cannot see claim status. This creates additional demand without advancing claims.

Approach and Solution

The improvement team introduces a minimum-information checklist at submission, with immediate prompts for missing data. A single digital intake record is made available to the relevant teams, reducing duplicate entry. Claims are segmented by complexity: straightforward claims follow a standard route, while high-risk cases receive early specialist review. Assignment is moved from a large daily batch to smaller, more frequent releases. Clear criteria define when legal review is required, and customers receive status updates at agreed milestones.

The redesigned future-state map preserves regulatory and fraud controls but places them earlier and closer to the point where relevant information becomes available. A visual queue shows claim age, priority, and next action. The process owner reviews lead time, first-pass completeness, rework, customer contacts per claim, and decision quality.

Outcome

In the pilot, the principal improvement is not faster assessment alone. It is the reduction of avoidable waiting and rework. The organization observes shorter queues, fewer incomplete referrals, and improved visibility for customers. The case demonstrates that the original problem was a system-flow problem, not simply an effort problem within the claims department.

Learning Points

The case illustrates five lessons. First, a department can perform its local task well while the end-to-end process performs poorly. Second, input quality is a capacity issue because incomplete work consumes constrained resources. Third, batch release creates hidden waiting. Fourth, service transparency can reduce avoidable customer contacts. Finally, control requirements should be integrated into the flow rather than treated as a reason to accept unnecessary delay.

Common Errors, Risks, and Limitations

Process maps can create false confidence. One common error is mapping the ideal procedure rather than the actual process. Another is beginning with solutions, such as automation, before understanding demand, variation, and failure modes. Teams may also confuse utilization with productivity, omit customer actions, or ignore exceptions because they are inconvenient to represent.

A further risk is over-simplification. A map that removes regulatory checks or rare but severe failure paths may recommend unsafe changes. Conversely, an excessively detailed map can become unmanageable and discourage action. The appropriate response is layered mapping: begin at a high level and drill down where evidence indicates a problem.

Data can also mislead. Average lead time may conceal a long tail of very old cases; average cycle time may hide variation by product type; and throughput may rise while defects increase. Segmenting data by customer type, complexity, channel, shift, location, and failure category is often necessary.

There are human and ethical risks. Mapping should not become a covert exercise in ranking individual employees or assigning blame. Privacy must be protected when customer or patient journeys are examined. Employee participation should be honest about the purpose of data collection. Automation decisions must consider accessibility, fairness, explainability, and the consequences of excluding people who cannot use a digital channel.

Digital Tools, Automation, and Emerging Practice

Process-mining technologies can reconstruct process sequences from event logs, showing actual paths, rework loops, waiting times, and variation. They are useful where transactions are recorded digitally, but they cannot see unrecorded conversations, informal work, emotional experience, or the quality of decisions. Event-log analysis should therefore be combined with observation and interviews.

Workflow platforms, electronic kanban boards, queue dashboards, and robotic process automation can support future-state designs. Automation is most effective when the process is sufficiently understood and stable. Automating a defective handoff can make waste faster without making the customer experience better. Artificial intelligence may assist with classification, forecasting, anomaly detection, document extraction, and workload prioritization, but governance is essential. Organizations must validate accuracy, monitor drift, protect confidential information, and retain appropriate human accountability.

Emerging practice increasingly combines process mining with customer-journey analytics, real-time operational data, digital twins, and sustainability measures. Environmental impact can be added to value-stream analysis through energy use, material loss, travel, packaging, and carbon-intensive rework. The future of process improvement is therefore not limited to speed and cost; it includes resilience, inclusion, sustainability, and responsible use of data.

Best Practices for Professional Application

Effective process analysis generally follows several principles:

• Define the customer outcome before optimizing internal activity.
• Map the real process with the people who perform and receive the work.
• Make boundaries, assumptions, and exclusions explicit.
• Show waiting, rework, queues, and information flows—not only productive tasks.
• Use data to validate the map and segment variation where necessary.
• Distinguish a local bottleneck from the system constraint.
• Treat handoffs as risk points requiring clear ownership and acceptance criteria.
• Improve quality at the source rather than relying on downstream inspection.
• Design controls into the future state instead of removing them without analysis.
• Pilot changes, monitor unintended consequences, and assign process ownership.

Chapter Summary

Process thinking examines how inputs are transformed into outputs across the complete flow of work, rather than treating departments as isolated units. SIPOC establishes high-level scope and relationships. Detailed process maps reveal activities, decisions, roles, loops, and handoffs. Value-stream maps add time, flow, capacity, information, and performance data. Service blueprints extend analysis to customer actions, visible interactions, backstage work, and support processes.

Bottlenecks and constraints determine system performance, while queues, batching, rework, and poor handoffs often create most of the customer's elapsed time. Measures such as lead time, touch time, WIP, throughput, first-pass yield, and process cycle efficiency help distinguish activity from flow. Little's Law links WIP, throughput, and flow time, while the Theory of Constraints directs attention to the factor limiting system output.

Effective value-stream analysis is cross-functional, evidence-based, and customer-centred. It should identify value leakage across boundaries, preserve necessary controls, and use technology responsibly. The goal is not simply to produce a map but to create a shared basis for redesign, measurement, and sustained improvement.

Key Terms

Process: A linked set of activities that transforms inputs into outputs for a customer or stakeholder.

Process thinking: An end-to-end perspective that focuses on flow and outcomes rather than isolated functions.

SIPOC: A high-level representation of Suppliers, Inputs, Process, Outputs, and Customers.

Process map: A visual representation of activities, decisions, sequence, responsibility, and flow.

Swimlane map: A process map that assigns activities to roles, departments, systems, or organizations.

Value stream: The complete set of activities required to deliver a product or service to a customer.

Value-stream mapping: A method for visualizing material and information flow together with performance data.

Service blueprint: A service-analysis diagram showing customer actions, frontstage interactions, backstage work, and support processes.

Lead time: Total elapsed time from process initiation to completion.

Touch time: Time during which work is actively performed on an item or case.

Queue time: Time work waits before the next activity.

Work-in-process: Items that have entered a process but are not yet complete.

Bottleneck: A stage whose effective capacity limits process output.

Constraint: Any factor restricting a system from achieving its intended performance.

Handoff: The transfer of work, information, or responsibility between parties.

First-pass yield: The proportion of outputs completed correctly without rework.

Takt time: Available operating time divided by customer demand.

Value leakage: Loss of potential customer or organizational value through delay, defects, rework, or poor coordination.

Process cycle efficiency: Touch time divided by total lead time, used as an indicator of flow efficiency.

Review Questions

Short Answer Questions

1. What is the purpose of a SIPOC diagram?

2. Distinguish lead time from touch time.

3. Why are handoffs important in process analysis?

4. What does Little's Law relate?

5. Define value leakage and give one example.

Long Answer Questions

1. Explain how process thinking differs from a functional management perspective.

2. Compare process maps, value-stream maps, and service blueprints.

3. Describe a systematic method for conducting a current-state and future-state value-stream analysis.

4. Explain how bottlenecks, constraints, queues, and batching influence process performance.

5. Discuss the ethical, managerial, and governance issues associated with digital process analysis and automation.

Analytical / Application Questions

1. A service process has 300 cases in progress, completes 60 cases per day, and is operating in a relatively stable condition. Estimate average flow time using Little's Law and explain what additional evidence you would collect before recommending improvement.

2. A hospital department reports that clinicians spend only 20 minutes per patient, yet patients remain in the system for three hours. Design a mapping approach to identify the sources of delay and customer dissatisfaction.

3. A company proposes automating a claims-validation step because employees spend substantial time entering data twice. Using the concepts in this chapter, evaluate the proposal and identify safeguards required before implementation.

22. Multiple Choice Questions with Answers

Question 1

Which question is most appropriate for process thinking?

A. Which department has the largest budget?

B. How does a customer request become a completed outcome across functions?

C. Which employee completes the most individual tasks?

D. Which function has the highest utilization?

Correct Answer: B. How does a customer request become a completed outcome across functions?

Question 2

What is the primary purpose of a SIPOC diagram?

A. To show every detailed task and screen in a process

B. To calculate statistical process capability

C. To establish high-level process scope and relationships

D. To replace all forms of customer research

Correct Answer: C. To establish high-level process scope and relationships

Question 3

A process has five minutes of touch time and a two-day lead time. What does this most strongly suggest?

A. The process has no waiting time

B. Most elapsed time is probably spent waiting or in queues

C. The process has excessive takt time

D. The process must have high first-pass yield

Correct Answer: B. Most elapsed time is probably spent waiting or in queues

Question 4

Which feature most clearly distinguishes a value-stream map from a basic flowchart?

A. It excludes information flows

B. It focuses only on customer emotions

C. It combines process flow with time, WIP, and performance data

D. It can be used only in manufacturing

Correct Answer: C. It combines process flow with time, WIP, and performance data

Question 5

In a service blueprint, backstage activities are best described as activities that:

A. Are performed by the customer before service begins

B. Are visible, face-to-face interactions with the customer

C. Support service delivery but are generally not visible to the customer

D. Occur only after a service failure

Correct Answer: C. Support service delivery but are generally not visible to the customer

Question 6

A department receives incomplete applications and returns many of them for correction. Which interpretation is most consistent with the chapter?

A. The problem is necessarily low employee effort in the receiving department

B. Input quality may be consuming capacity and creating rework

C. The process should immediately add another approval

D. The queue is evidence that demand has disappeared

Correct Answer: B. Input quality may be consuming capacity and creating rework

Question 7

Which action reflects the Theory of Constraints?

A. Improve every process step equally, regardless of system impact

B. Identify and exploit the factor limiting total system performance

C. Maximize inventory before every activity

D. Measure only individual employee utilization

Correct Answer: B. Identify and exploit the factor limiting total system performance

Question 8

A company reduces work in one department by transferring data-entry tasks to another department. From an end-to-end perspective, this is:

A. Automatically a successful Lean improvement

B. A possible local optimization rather than total process improvement

C. Proof that the bottleneck has been removed

D. An example of eliminating all non-value-adding work

Correct Answer: B. A possible local optimization rather than total process improvement

Question 9

Which measure is most directly concerned with completion without rework?

A. First-pass yield

B. Queue time

C. Takt time

D. Work-in-process

Correct Answer: A. First-pass yield

Question 10

Before automating an unreliable digital handoff, the most appropriate first step is to:

A. Automate it immediately to increase speed

B. Remove all controls associated with the handoff

C. Understand the current process, failure modes, data quality, and accountability

D. Measure only the software's processing time

Correct Answer: C. Understand the current process, failure modes, data quality, and accountability