IVI Framework Viewer

Event, Incident, and Request Management

D2

Manage service events, incidents, and requests from creation/detection to completion/closure.

Improvement Planning

Practices-Outcomes-Metrics (POM)

Representative POMs are described for Event, Incident, and Request Management at each level of maturity.

2Basic
  • Practice
    Establish basic monitoring of key events.
    Outcome
    Key events can be tracked.
    Metric
    % of services that are monitored for events.
  • Practice
    Ensure that incidents are tracked, recorded, and reported in a satisfactory manner.
    Outcome
    Current and historical incident data is available.
    Metrics
    • # of incidents recorded.
    • % of support time that is covered by trouble-tickets.
  • Practice
    Ensure that requests are dealt with, even if there is no advanced prioritization in place.
    Outcome
    Requests are typically handled in chronological order.
    Metrics
    • Mean time to close request.
    • Mean time to respond to request.
3Intermediate
  • Practices
    • Put in place automated event monitoring.
    • Ensure that events are prioritized and filtered according to importance.
    Outcome
    Data on relevant events can be passed to key processes.
    Metrics
    • % of services that are monitored for events.
    • % of key processes that automatically receive data on relevant events.
  • Practices
    • Put in place an effective, tool-supported, end-to-end, trouble ticketing system.
    • Track, record, and report incidents effectively, and prioritize and manage incidents based on the urgency to restore services as defined by SLAs.
    Outcome
    SLA violations decrease.
    Metrics
    • # of incidents recorded.
    • % of support time that is covered by trouble-tickets.
    • % of incidents causing a breach of an SLA.
  • Practice
    Prioritize requests effectively according to predefined request classes or metrics (e.g. time for fulfilment, etc.).
    Outcomes
    • Requests are handled more efficiently.
    • Ticket progress can be tracked and traceability of requests is possible.
    Metrics
    • Mean time to close request.
    • Mean time to respond to request.
    • % of requests recorded from end-to-end.
4Advanced
  • Practice
    Use event-monitoring data to help address all incidents, both proactively and reactively.
    Outcome
    Service availability and reliability is increased.
    Metrics
    • % of services that are monitored for events.
    • % of key processes that automatically receive data on relevant events.
  • Practices
    • Incorporate system-generated trouble messages into the trouble ticket system.
    • Address recurring incidents through problem management based on Root Cause Analysis (RCA).
    Outcomes
    • There is improved identification of trouble messages.
    • The root causes of recurring incidents are identified and can be addressed.
    Metrics
    • % of trouble messages that are generated automatically by systems.
    • % of recurring incidents solved with RCA.
  • Practice
    Put in place tool-supported request management to prioritize requests according to the business relevance of affected services, as defined by Service Level Agreements (SLAs).
    Outcomes
    • SLA violations are minimized.
    • The efficiency and quality of IT services are improved.
    Metrics
    • Mean time to close request.
    • Mean time to respond to request.
    • % of requests recorded from end-to-end.
    • % of requests completed within agreed SLAs.
5Optimized
  • Practice
    Complement existing proactive and reactive event management with effective self-healing processes.
    Outcome
    Event management is optimized with effective self-healing processes.
    Metrics
    • % of services that are monitored for events.
    • % of key processes that automatically receive data on relevant events.
    • Evidence of self-healing processes.
  • Practices
    • Set up effective, defined processes for updating the knowledge database, the known error database, and Root Cause Analysis (RCA) results.
    • Put automated incident prediction systems in place.
    Outcomes
    • The majority of potential incidents are averted.
    • Those incidents that do occur are handled automatically.
    • The time taken to resolve incidents is minimized.
    Metrics
    • Mean time to resolve incident.
    • % of requests resolved using the knowledge database.
  • Practices
    • Put in place an automated, role-based, request submission capability (e.g. via an online catalogue).
    • Dynamically prioritize requests based on SLAs, business relevance, and the business cycle.
    Outcomes
    • There is efficient and high quality administration of service requests.
    • Management of service requests is recognized as a key strength by stakeholders across the business ecosystem.
    Metric
    Existence of automated, role-based request submission capabilities.