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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Measuring to Improve | 15% | - Avoiding measurement pitfalls - Value stream mapping - Meaningful metrics and indicators |
| Topic 2: Articulating and Realising Value | 10% | - Communicating value to stakeholders - Investment cases and business justification - Value outcomes and benefits realization |
| Topic 3: Measuring to Learn | 15% | - Evaluating DevOps performance - Tools and techniques for measurement - Purpose of measurement |
| Topic 4: Unlearning Behaviors | 15% | - Mindset and mental models - Governance, risk and compliance in DevOps - Cognitive bias and psychological safety |
| Topic 5: Becoming a DevOps Organisation | 15% | - Building safety and continuous improvement - DevOps principles and adoption - Differences between DevOps and traditional IT |
| Topic 6: Leading Cultural Change | 5% | - Empowerment and participation - Driving behavioural and cultural transformation |
| Topic 7: DevOps and Transformational Leadership | 15% | - Leadership frameworks for change - Definitions and benefits of DevOps - Transformational leadership principles |
| Topic 8: Target Operating Models and Organizational Design | 10% | - Conway's Law and organizational structure - Designing DevOps-aligned operating models - Team structures and collaboration |
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NEW QUESTION # 34
When you are putting the customer upfront and center, what shouldn't you do?
Answer: C
Explanation:
The correct answer is A because customer-centric DevOps decision-making should be based on evidence, feedback, and validated learning rather than hierarchy. The "highest paid person's opinion" problem, often called HiPPO-driven decision-making, occurs when seniority overrides customer evidence, operational data, team insight, or experiment results. This is especially harmful in DevOps evolution because it reinforces command-and-control behavior and prevents organizations from learning from the actual users of the system.
Putting the customer upfront and center means using customer feedback, telemetry, usage data, support patterns, market signals, and outcome measures to guide prioritization and improvement. Pulling improvement ideas from customers is appropriate because it connects delivery to real needs. Using live- streaming reaction and prediction services can help organizations understand behavior and sentiment quickly.
Being data-driven supports faster feedback and better product decisions.
A DevOps leader should create conditions where decisions are informed by the people closest to the customer, the work, and the evidence. Relevant study guide references: Measuring to Learn; Becoming a DevOps Organization; DevOps and Transformational Leadership; Articulating and Socializing Vision.
NEW QUESTION # 35
In Kolb's Learning Styles, when a person is thinking and watching, what are they doing?
Answer: B
Explanation:
The correct answer is B. In Kolb's Learning Styles model, "thinking and watching" corresponds to Assimilating. Kolb's model combines two dimensions: how people perceive information and how they process it. "Thinking" aligns with abstract conceptualization, while "watching" aligns with reflective observation. Together, these form the Assimilating learning style.
Assimilating learners tend to prefer logical analysis, structured models, concepts, theories, and reflective understanding. They often want to understand the "why" behind a practice before applying it. In DevOps leadership, recognizing different learning styles is useful because transformation requires people to learn new behaviors, unlearn old assumptions, and adopt new ways of working. A leader who only communicates through one style may fail to engage the whole organization.
The other styles map differently. Diverging is feeling and watching. Converging is thinking and doing.
Accommodating is feeling and doing. DevOps leaders should support learning through explanation, experimentation, reflection, practice, and feedback so that different learning preferences are addressed.
Relevant study guide references: Unlearning Behaviors; Maintaining Energy and Momentum; DevOps and Transformational Leadership.
NEW QUESTION # 36
Where should you start with your DevOps evolution?
Answer: D
Explanation:
The correct answer is D because DevOps evolution should begin with a value stream. DevOps is concerned with the end-to-end flow of work from idea to customer value, not merely with reorganizing departments, selecting a single application, or avoiding legacy systems. A value stream view allows leaders and teams to understand how work actually moves through the organization, where delays occur, where handoffs create friction, and where feedback is lost.
Starting with a reorganization is risky because structural change without understanding the system of work may simply recreate the same constraints in a new chart. Starting with an application can be too narrow unless it is examined within the broader value stream that delivers and operates it. Avoiding legacy systems is also not a reliable principle; legacy services may be central to business value and therefore important to include.
A value stream approach helps identify constraints, reduce waste, improve flow, and connect technical improvements to business outcomes. It also gives leaders a practical basis for measurement and improvement.
Relevant study guide references: Becoming a DevOps Organization; Measuring to Improve; Measuring to Learn; Target Operating Models and Organizational Designs.
NEW QUESTION # 37
When thinking of the dimensions of transformational leadership, which of the following is how we would expect a transformational leader to behave?
Answer: B
Explanation:
A transformational leader is expected to orient people around a compelling shared vision and inspire them to move beyond narrow local interests, habits, or individual preferences. In a DevOps context, this is essential because transformation requires people to change long-established behaviors, cross functional boundaries, challenge legacy processes, and focus on outcomes that matter to the whole organization. Option D is the strongest answer because transformational leadership is associated with vision, purpose, inspiration, role modelling, and mobilizing people toward a future state.
Option A may appear positive, but it is closer to a transactional or contingent-reward behavior: recognition is given in response to specific performance. That can be useful, but it is not the defining behavior of transformational leadership. Option B is incorrect because accepting the status quo conflicts with transformation, continuous learning, and improvement. Option C is also incorrect because blame and humiliation damage psychological safety, reduce learning, and discourage transparency.
The DOL leadership theme emphasizes that DevOps change requires leaders who can articulate vision, challenge existing assumptions, build trust, and energize people through change. Relevant study guide references: DevOps and Transformational Leadership, Articulating and Socializing Vision, Unlearning Behaviors, and Maintaining Energy and Momentum.
NEW QUESTION # 38
What is the key metric for DevOps teams over traditional IT teams?
Answer: C
Explanation:
The key metric for DevOps teams is flow. Traditional IT management often emphasizes cost control, resource utilization, capacity, and individual productivity. While those measures can be useful, they frequently optimize local activity rather than end-to-end value delivery. DevOps instead focuses on how work flows from idea to customer outcome: how quickly, safely, and predictably value moves through the system.
Flow-oriented measurement helps leaders identify constraints, queues, handoffs, rework, excessive work in progress, long lead times, failed changes, and feedback delays. This is critical because a team may appear fully utilized and productive while customers still experience slow delivery and unstable services. DevOps teams therefore measure outcomes and system performance rather than only internal effort. Common flow- related measures include lead time, deployment frequency, change failure rate, mean time to restore service, throughput, work in progress, and wait time.
Cost and capacity are not irrelevant, but when they become the dominant measures, they can encourage silo optimization and high utilization at the expense of speed and resilience. Productivity is also difficult to interpret unless connected to value. Relevant study guide references: Measuring to Improve, Measuring to Learn, Becoming a DevOps Organization, and Target Operating Models and Organizational Designs.
NEW QUESTION # 39
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