Performance indicator
A performance indicator or key performance indicator is a type of performance measurement. KPIs evaluate the success of an organization or of a particular activity in which it engages. KPIs provide a focus for strategic and operational improvement, create an analytical basis for decision making and help focus attention on what matters most.
Often success is simply the repeated, periodic achievement of some levels of operational goal, and sometimes success is defined in terms of making progress toward strategic goals. Accordingly, choosing the right KPIs relies upon a good understanding of what is important to the organization. What is deemed important often depends on the department measuring the performance – e.g. the KPIs useful to finance will differ from the KPIs assigned to sales.
Since there is a need to understand well what is important, various techniques to assess the present state of the business, and its key activities, are associated with the selection of performance indicators. These assessments often lead to the identification of potential improvements, so performance indicators are routinely associated with 'performance improvement' initiatives. A very common way to choose KPIs is to apply a management framework such as the balanced scorecard.
The importance of such performance indicators is evident in the typical decision-making process. When a decision-maker considers several options, they must be equipped to properly analyse the status quo to predict the consequences of future actions. Should they make their analysis on the basis of faulty or incomplete information, the predictions will not be reliable and consequently the decision made might yield an unexpected result. Therefore, the proper usage of performance indicators is vital to avoid such mistakes and minimise the risk.
KPIs are used not only for business organizations but also for technical aspects such as machine performance. For example, a machine used for production in a factory would output various signals indicating how the current machine status is. Some signals or signals as a result of processing the existing signals may represent the high-level machine performance. These representative signals can be KPI for the machine.
Categorisation of performance indicators
The effective use of performance indicators requires a clear understanding of their different types and purposes. Indicators can be categorised along several key dimensions to ensure a balanced and comprehensive measurement system that supports strategic objectives. A well-designed set of indicators will draw from multiple categories to avoid unintended consequences and provide a holistic view of organisational performance.A primary method of categorisation is based on the dimension of performance being measured. The Balanced Scorecard framework, for instance, groups indicators into four perspectives: financial, customer, internal business processes, and learning and growth. This approach prevents over-reliance on financial metrics alone.
Indicators are also commonly distinguished by their time orientation and function. In this typology:
- Lagging indicators are outcome-oriented, measuring the final results of past activities. They are easy to measure but hard to directly influence.
- Leading indicators are performance drivers, predictive measures that influence future outcomes. They are more actionable but can be harder to correlate directly with results.
- Input indicators measure resources consumed, providing context for interpreting outputs and outcomes.
Furthermore, indicators can be designed for different levels of the organisation. Strategic indicators monitor progress toward top-level goals, operational indicators track departmental or process efficiency, and individual indicators align personal objectives with organisational priorities.
Selecting the right mix of categories is a strategic exercise. An overemphasis on lagging quantitative indicators can lead to short-termism and "gaming" of metrics, while focusing solely on leading or qualitative indicators may lack a connection to ultimate outcomes. A balanced portfolio of indicators across these categories is therefore essential for effective performance management.
Points of measurement
The first step in performance measurement is determining what to measure.Performance indictors may be applied at various stages within a programme, service, or organisational process. These points capture distinct dimensions of performance, ranging from the earliest stages of resource allocation to final outcomes achieved. It is common to distinguish between:
- Inputs – the resources dedicated to an activity.
- Processes – how efficiently or effectively these resources are transformed into outputs.
- Outputs – the quantity, quality and timeliness of goods or services delivered.
- Impacts – the short to medium term effects on service users or stakeholders.
- Outcomes – the broader, long term societal changes that result from an activity.
Selecting the appropriate point of measurement is not simply a technical choice but also a strategic one. For example, focusing narrowly on inputs or outputs can incentivise ‘box-ticking’ behaviours and obscure whether real value is being created. Conversely, outcome and impact indicators may be harder to attribute to organisational effort, especially in complex public sector environments.
A balanced approach can involve linking indicators across multiple points of measurement, to trace the relationships between resources, activities and ultimate value. However, this requires careful design to avoid measurement burdens and to ensure alignment with an organisation’s overall strategic objectives.
Quality assurance across the points of measurement helps ensure indicators not only track activity levels but also produce robust, consistent and credible performance data.
Identifying indicators
Once appropriate points of measurement have been determined, the next task is to identify specific indicators that meaningfully capture performance at that stage. An indicator is a measurable variable used to show whether progress is being made towards a goal, rather than the goal itself.Choice of indicators reflects managerial decisions about what counts as successful performance. Indicators may be financial, such as revenue growth, or non-financial, such as customer satisfaction rates. A good indicator should be simple to understand while aligning closely with business or organisational goals.
The process of identifying indicators is often guided by frameworks such as SMART. Alternatives like the FABRIC principles emphasise ideal performance information is focused, appropriate, balanced, robust, integrated, and cost-effective.
In the public sector, where outcomes may depend on many different organisations and external influences, careful selection is needed to avoid misleading or overly broad results.
Key stages of identifying a performance indicator include:
- Clarifying objectives: defining the goals, benchmarks, and standard to be measured.
- Choosing the point of measurement: deciding whether inputs, outputs, impacts or outcomes best capture performance.
- Generating potential indicators: identifying options from existing data or stakeholder input.
- Assessing validity and feasibility: testing whether indicators are conceptually sound, measurable, and proportionate.
- Piloting and refining: trialling indicators to detect unintended incentives or data issues.
- Final selection and integration: embedding chosen indicators into reporting and decision-making.
Attribution is another challenge. In the public sector, multiple organisations may influence outcomes indicators, and may sometimes develop a shared outcomes framework with reporting to show the particular role an individual organisation. Where a clear link exists between employee effort and performance, indicators may be connected to motivation, reward and appraisal systems.
Data quality is another important consideration. Indicators depend on reliable and consistent information. Weak systems can undermine credibility, shaping which indicators are ultimately preferred. Finally, given the risks of gaming, data fabrication, and selective reporting on indictors, organisations should consider verifiability of underlying data when selecting indicators and choose indicators that are not susceptible to manipulation.
Examples
Accounts
These are some of the examples:- Percentage of overdue invoices
- Percentage of purchase orders raised in advance
- Number of retrospectively raised purchase orders
- Finance report error rate
- Average cycle time of workflow
- Number of duplicate payments
Marketing and sales
- New customer acquisition
- Customer acquisition cost
- Average deal size
- Demographic analysis of individuals applying to become customers, and the levels of approval, rejections, and pending numbers
- Status of existing customers
- Customer density
- Customer attrition
- Turnover generated by segments of the customer population
- Outstanding balances held by segments of customers and terms of payment
- Collection of bad debts within customer relationships
- Profitability of customers by demographic segments and segmentation of customers by profitability
Faster availability of data is a competitive issue for most organizations. For example, businesses that have higher operational/credit risk may want weekly or even daily availability of KPI analysis, facilitated by appropriate IT systems and tools.