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Reporting, use & meta-evaluationKPIDashboardManagement by objectivesMonitoringGovernment evaluation

Performance Measurement

Performance Measurement
Also known as: Performance measurement、Performance management、Monitoring、Government evaluation

Continuously measures defined indicators against baselines and targets to inform operational decisions. Tracks changes in outcomes as well as counts, with consistent numerical definitions and collection responsibilities. [1]

Performance indicator design and KPI definition worksheet — openReferences and checked sections
Difficulty
Intermediate
Cost
Medium
Duration
Illustrative estimate (adjust for scale and team): indicator design: 1–4 weeks / ongoing monitoring: quarterly to annually
Content updated: 2026-10-07Source checked: 2026-10-07 (includes AI cross-checking)No documented human reviewIncludes fictional examples

How it works at a glance

Performance measurement is a system for selecting, continually collecting and using indicators that support decisions. Specifying each indicator's calculation, data source, frequency, responsible person, baseline and target clarifies conditions for comparison over time. [1]

Gaps against targets offer clues for improvement, but cannot alone explain a program's causal effect. Record participant composition, missing data and definition changes, and use these to inform evaluation and dialogue about the reasons. [1]

  1. Review the outcome framework, such as a logic model
  2. Select and define indicators
  3. Establish baseline values
  4. Set targets
  5. Build data collection and aggregation arrangements
  6. Develop a dashboard and run review cycles
Sequence of implementation steps. See “Implementation steps” for details of each stage.

When to use it and when it is unsuitable

When to use it

  • When establishing arrangements to regularly manage and report program or policy progress
  • When collecting ongoing monitoring information as basic data for annual evaluation reports
  • When developing dashboards or performance management systems to support data-informed decisions
  • When organizing KPIs to meet grant or subsidy outcome-reporting requirements

When it is unsuitable

  • When demonstrating causal effects is required. Separate evaluation is needed to establish whether changes in measurements are program outcomes.
  • Programs whose main outcomes are complex, emergent changes that are difficult to capture with indicators. Complement qualitative monitoring or developmental evaluation.

Participants, roles, and deliverables

Participants and roles

Program staff, managers and evaluation or planning departments. Appoint dedicated data management staff depending on scale.

Main deliverables

  • Performance indicator list (KPI list)
  • Indicator definition document
  • Performance monitoring dashboard
  • Regular monitoring reports

Implementation steps

  1. Review the outcome framework, such as a logic model
    Organize program goals, outcomes and outputs to establish an overall picture of what to measure. If a logic model or results-based management framework already exists, start with its potential indicators.
  2. Select and define indicators
    Select indicators needed for decisions and specify definitions, numerators, denominators, sources, frequency and responsibilities. Do not fix the number of indicators; narrow them down based on both importance and collection burden.
  3. Establish baseline values
    Measure and record initial values before the program begins or at the current point. Without a baseline, change since the start cannot be assessed. Where attainment of an absolute target can be assessed, specify its scope and limitations. State explicitly if the baseline is reconstructed retrospectively from historical data.
  4. Set targets
    Set quantitative midterm and end-of-period targets. Explain their basis, such as past performance, benchmarks or expert views, and agree realistic targets that are neither overly optimistic nor pessimistic.
  5. Build data collection and aggregation arrangements
    Establish regular collection workflows, aggregation tools such as spreadsheets or BI tools, and reporting cycles. Clarify who collects, enters and validates data, and document procedures.
  6. Develop a dashboard and run review cycles
    Create a dashboard displaying indicator progress and discuss results at quarterly, semiannual or annual review meetings. Consider corrective measures when targets are missed, revising targets or indicators if needed.

Strengths and limitations

Strengths

  • Continuous data accumulation enables early identification of progress and trends
  • Shared indicators make stakeholder decisions and communication more efficient
  • Can provide quantitative evidence for accountability at low cost
  • Can directly support program improvement through the “check” stage of the PDCA cycle

Limitations

  • Easily measured indicators may take priority, marginalizing important but difficult-to-measure outcomes such as quality and equity
  • Indicator attainment can become an end in itself, potentially encouraging gaming
  • Cannot explain why targets were or were not met; separate evaluation is needed to develop improvements

Common pitfalls

  • Too many indicators become a “forest” that nobody seriously monitors. Keep core KPIs to around 10 at most.
  • Starting the program without collecting a baseline leaves later achievement difficult to assess
  • Collecting monitoring data without reviewing it in meetings becomes reporting for its own sake

Conditions of use and evidence

  • The measurement framework links indicators to sources, collection frequency, responsibilities, baselines and targets. [1]
Fictional example; not actual results

Read consultation referral connection rates monthly

The following is a fictional example for illustration. Confirm whether people contacted the referral destination after consultation, within the scope of their consent to follow-up.

Indicator nameResults level measured (output/outcome)Formula and unitData sourceCollection frequencyPerson responsibleBaseline valueTarget (end of period)
Connection confirmation rate within 30 daysOutcomesNumber with confirmed connections ÷ people consenting to follow-up that month × 100 (%)Consent-based follow-up formMonthly, after 30 daysConsultation staff member AJune: 12 confirmed connections / 20 eligible participants = 60%. Three of the 20 remain unconfirmed.Pilot a December target of 70% and review its appropriateness in October
Unconfirmed follow-up rateMeasurement qualityNumber unconfirmed by the deadline ÷ people consenting to follow-up that month × 100 (%)Same follow-up formMonthlyRecorder BJune: 3/20 = 15%10% or less in December; also review follow-up burden

Common errors in judgment

Common mistake

Remove unreachable people from the denominator to increase the achievement rate

How to revise

Retain the predefined denominator and show unconfirmed counts too

ReasonThis keeps bias from following up only reachable people visible.

Common mistake

Claim a high achievement rate proves program effects

How to revise

Examine progress separately from other influencing factors

ReasonIndicator trends alone provide no counterfactual.

Organize your thinking by writing

Performance indicator design and KPI definition worksheet

A practical template is available to fill in and print on A4 paper.

Open worksheet

Related practical guides

How to develop evaluation indicatorsTraining effectiveness measurementEvaluation methods for EBPMOutputs and outcomes

Related methods

Logic ModelIndicator DesignResults-Based ManagementBalanced ScorecardEvaluation Report Writing

References and checked sections

  1. Glossary of results-based management terms
    Global Affairs Canada
    Section consulted
    Baseline (Data); Performance measurement; Performance measurement framework; Performance reporting
    How it relates to the text
    The measurement framework links indicators to sources, collection frequency, responsibilities, baselines and targets.
    Source checked: (includes AI cross-checking)

Editorial and checking information

Content updated: Source checked: (includes AI cross-checking)No documented human reviewIncludes fictional examplesEditorial policy and scope of checkingCite this pageReport a correction

How to cite this page

EvalCompass Editorial Team. “Performance Measurement”. EvalCompass, updated 2026-10-07. https://evalcompass.jun-nakatani.com/en/methods/performance-measurement/
Add the date you accessed the page. Text created by this site is available under CC BY 4.0. Quotations, external materials, and bundled fonts have their own terms of use. When reusing content, credit the source, link to the license, and indicate any changes.

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Change history
  • — Corrected descriptions and procedures identified through content checks (U02). Preserved input field order, counts, labels and section structure.
  • — Clarified the relationship between 12 confirmed connections, 20 eligible participants and three unconfirmed cases in two fictional KPI examples. Preserved definitions, formulas and worksheet field order.
  • — Updated explanations to correspond with sources, and added method-specific fictional worksheet examples, judgment examples and revision history.