ITIL 4 HVIT cheat sheet

High-velocity IT is the application of digital technology and lean-agile ways of working to enable fast, resilient, and co-created value delivery; it is a lens on ITIL 4, not a separate framework.

Three defining characteristics of high-velocity IT: fast delivery of value, resilience under volatility, and co-creation of value with customers and partners.

Four dimensions of the ITIL 4 model still apply: organizations and people, information and technology, partners and suppliers, value streams and processes.

VUCA describes the operating context: volatility, uncertainty, complexity, ambiguity. High-velocity IT responds with speed, experimentation, and adaptability rather than fixed plans.

Digital products are products whose value depends on digital technology; the digital product lifecycle spans concept, design, build, run, and retire, and is managed as a whole rather than as a project.

Digital transformation is the use of digital technology to change business models and customer experience, not merely the digitization of existing manual processes.

Cynefin-informed decision rule: use best practice for clear/simple contexts, expert analysis for complicated, safe-to-fail experiments for complex, and immediate action for chaotic.

ITIL 4 guiding principles (focus on value, start where you are, progress iteratively with feedback, collaborate and promote visibility, think and work holistically, keep it simple and practical, optimize and automate) apply unchanged in high-velocity IT.

Lean, agile, resilient, and continuous (LARC) is a shorthand for the four orientations that high-velocity IT combines; resilience is not optional even when speed is prioritized.

Safety culture: psychological safety means people can report failure and dissent without punishment; it is a precondition for fast feedback and learning.

Blameless post-mortem rule: analyze systemic causes and contributing factors, not individual fault; outputs are actions and learning, not sanctions.

Learning culture vs blame culture: a learning culture treats errors as information; a blame culture drives concealment and increases risk.

Ethics and values in high-velocity IT: decisions are tested against stated organizational values and societal impact, especially where automation and data use are involved.

Collaboration and visibility: information radiators, shared backlogs, and open metrics reduce handoff delay and misalignment between business and IT.

T-shaped and E-shaped people: breadth across disciplines plus depth in at least one; cross-functional teams reduce dependencies and queue time.

Intrinsic motivation (autonomy, mastery, purpose) outperforms extrinsic reward for creative knowledge work; incentive schemes that reward individual output undermine team flow.

Customer-centricity behaviour: value is defined by the customer's outcome, so feedback loops with real users are designed into work, not added after release.

Leadership behaviour in high-velocity IT: servant/leader-as-coach, removing impediments, protecting the team, and making constraints and priorities explicit.

The ITIL 4 practices most associated with high-velocity IT include: architecture management, deployment management, infrastructure and platform management, software development and management, availability management, capacity and performance management, service continuity management, service design, service desk, and relationship management.

Continuous integration requires automated build plus automated tests on every change; continuous delivery adds automated release readiness; continuous deployment removes the manual release gate.

Test-driven development cycle: write a failing test, make it pass with the simplest code, refactor; the test suite becomes the regression safety net for fast change.

Infrastructure as code: infrastructure is defined in version-controlled files and applied by automation, making environments reproducible and disposable.

Canary release and blue/green deployment limit blast radius: shift a small or parallel traffic slice, verify, then promote or roll back.

Feature toggles decouple deployment from release, allowing dark launches and instant rollback without redeploying code.

Chaos engineering: deliberately inject controlled failure in production-like environments to validate resilience hypotheses before real incidents occur.

Value stream mapping identifies lead time, process time, and the ratio of value-adding to non-value-adding steps; the goal is to shorten lead time and reduce batch size.

Minimum viable product is the smallest thing that produces validated learning from real users; it is a learning instrument, not a low-quality release.

Value stream definition: the series of steps an organization uses to create and deliver products and services to consumers; value streams are mapped end to end, not by department.

Value stream mapping outputs: lead time, process time, flow efficiency (process time divided by lead time), queues, handoffs, and rework loops.

Little's law: average items in progress equals arrival rate multiplied by average time in system; reducing work in progress reduces cycle time when throughput is stable.

Batch size rule: smaller batches reduce queue time and feedback delay and lower risk per release; transaction cost per batch falls with automation.

DevOps three ways: flow (left to right), feedback (right to left), and continual learning and experimentation.

Continuous improvement and the Deming cycle (plan-do-check-act) underpin the continual improvement practice in high-velocity value streams.

Product vs project: a digital product is funded and managed for its whole lifecycle with an empowered, persistent team; a project is temporary and dissolves at handover.

Value stream and value chain distinction: the value chain is the organization-wide set of activities; value streams are the specific flows that create value for a consumer.

Feedback loop design: shorten the loop (fast telemetry), widen it (real user and business signals), and close it (decisions and actions from the data).