Input Management
Identify inputs required for IT capacity forecasting. Gather and validate input data for forecast scenarios.
Improvement Planning
Practices-Outcomes-Metrics (POM)
Representative POMs are described for Input Management at each level of maturity.
- 1Initial
- Practice
- Collect data as needed.
- Outcome
- Increased likelihood of accurate model predictions for models fed with empirical data.
- Metrics
- # of IT capacity empirical data input sources.
- % of resources covered by IT capacity empirical data.
- Frequency of IT capacity data collection.
- Practice
- Monitor the actual IT capacity headroom for selected resources.
- Outcome
- The actual IT capacity headroom of individual resources is understood and can be acted upon.
- Metric
- # of IT resources monitored for IT capacity headroom.
- 2Basic
- Practice
- Collect IT resource data on a regular basis.
- Outcome
- IT capacity modelling for some IT resources is based on up-to-date empirical data.
- Metrics
- # of empirical data input sources.
- % of resources covered by empirical data.
- Frequency of data collection.
- Practice
- Use basic model change scenarios, for selected resources to drive forecasts.
- Outcome
- Capacity forecasting is informed by basic change scenarios for some resources.
- Metrics
- # of IT capacity scenarios agreed with the rest of the business.
- Frequency of IT capacity scenario review and refresh.
- Practice
- Use IT assumptions as the main input into the ongoing capacity modelling and planning.
- Outcome
- The IT capacity plans produced are largely based on IT driven assumptions and inputs.
- Metrics
- # of IT capacity input assumptions.
- Frequency of IT capacity input from IT.
- 3Intermediate
- Practice
- Implement a process to capture IT capacity empirical data for all modelled resources.
- Outcome
- the IT Capacity model accuracy is improved as it is based on a good level of empirical data.
- Metrics
- # of IT capacity empirical data input sources.
- % of resources covered by the IT capacity empirical data.
- Frequency of IT capacity data collection.
- Practice
- Communicate the IT capacity data quality issues to data owner immediately.
- Outcome
- Increased the likelihood of accurate model predictions due to an increased quality of data inputs.
- Metrics
- # of IT capacity empirical data input sources.
- % of resources covered by the IT capacity empirical data.
- Frequency of IT capacity data collection.
- % of IT capacity inputs checked for quality.
- Practice
- Agree with the rest of the business on a set of scenarios to use to drive IT capacity forecasts.
- Outcome
- IT capacity forecasting is driven by defined and agreed scenarios.
- Metrics
- # of IT capacity scenarios agreed with the business.
- Frequency of IT capacity scenario review and refresh.
- Practice
- Operate a process for the collection of strategic direction, vision, business forecasts and operational objectives from the business for IT capacity planning.
- Outcome
- The IT capacity plans produced are informed by an ongoing flow of input from the business and are aligned to future business requirements.
- Metrics
- # of IT capacity business input assumptions.
- Frequency of IT capacity input from the business.
- 4Advanced
- Practice
- Establish a process to verify the quality of all the data used as input for the IT capacity model.
- Outcome
- There is an Increased likelihood of accurate IT capacity model predictions, due to increased quality of the data inputs.
- Metrics
- # of IT capacity empirical data input sources.
- % of resources covered by IT capacity empirical data.
- Frequency of IT capacity data collection.
- % of IT capacity inputs checked for quality.
- Practice
- Establish an escalation process for IT capacity data availability and data quality.
- Outcome
- There is an increased likelihood of accurate model predictions due to increased quality of IT capacity data inputs.
- Metrics
- # of IT capacity empirical data input source.
- % of resources covered by IT capacity empirical data.
- Frequency of IT capacity data collection.
- % of IT capacity inputs checked for quality.
- Practice
- Implement a process to establish and agree consistent scenarios for all IT capacity planning activities across different resources and business areas.
- Outcome
- IT capacity forecasting is driven by a consistent set of scenarios agreed with the business.
- Metrics
- # of IT capacity scenarios agreed with the business.
- Frequency of IT capacity scenario review and refresh.
- Practice
- Include macro trends and actual business usage patterns into IT capacity collection and input process.
- Outcome
- The IT capacity plans produced are calibrated to take account of any macro trends identified and actual usage patterns.
- Metrics
- # of business macro trends included in IT capacity planning.
- Frequency of IT capacity input from the business.
- 5Optimized
- Practice
- Refine and optimize the IT capacity data collection process continually with key stakeholders.
- Outcome
- The IT capacity models maintain accuracy with a continual feed of refined, optimized empirical data.
- Metrics
- # of IT capacity empirical data input sources.
- % of IT capacity resources covered by empirical data.
- Frequency of IT capacity data collection.
- % of IT capacity inputs checked for quality.
- Practice
- Optimize the IT capacity process for the collection and harmonisation of scenarios continually with key stakeholders.
- Outcome
- IT capacity forecasting is informed by a consistent set of scenarios that are continually reviewed and updated.
- Metrics
- # of IT capacity scenarios agreed with the business.
- Frequency of IT capacity scenario review and refresh.
- Practice
- Continuously refine and optimize the IT capacity collection process with key stakeholders and discuss the impact on model predictions with all key stakeholders.
- Outcome
- Capacity plans are accurately aligned to meet current and future business demands and requirements.
- Metrics
- # of business input assumptions for IT capacity planning.
- Frequency of input from the business for the IT capacity plan.