Metrics are a system of parameters or ways of quantitative and periodic assessment of a process that is to be measured, along with the procedures to carry out such measurement and the procedures for the interpretation of the assessment in the light of previous or comparable assessments. Metrics are usually specialized by the subject area, in which case they are valid only within a certain domain and cannot be directly benchmarked or interpreted outside it.
Metrics are used in business model, CMMI, ISM3, Balanced scorecard and knowledge management. These measurements or metrics can be used to track trends, productivity, resources and much more. Typically, the metrics tracked are key performance indicators, also known as KPIs. For example, you would use metrics to better understand how a company is performing compared to other companies within its industry.
The intention is to identify future-state objectives, relate them to specific goals that can be achieved through critical success factors or performance drivers which are then monitored and measured by key performance indicators. Through this hierarchy, organizations can define and communicate relationships between metrics and how they contribute to the achievement of organizational goals and objectives.
Metrics are important in IT Service Management including ITIL; the intention is to measure the effectiveness of the various processes at delivering services to customers. Some suggest that data from different organizations can be gathered together, against an agreed set of metrics, to form a benchmark, which would allow organizations to evaluate their performance against industry sectors to establish, objectively, how well they are performing.
There is strong disagreement with these views from other quarters. No agreed standard set of best practice metrics exists; Kaner has raised serious objections about the purported validity of metrics used in software engineering. Douglas Hubbard published his findings that unless the value of information is quantified, managers are unlikely to choose the highest payoff metrics. Subsequent US Government studies further demonstrated this .