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Measure software quality in an Agile team by defining what quality means for users and the product, then tracking both product outcomes and delivery performance. Use ISO/IEC 25010:2023 to identify relevant product-quality characteristics, and DORA’s five delivery performance measures to understand how changes move to users and how often delivery needs recovery or rework. Review the measures in context; neither framework produces a universal quality score.
Start by defining quality for this product
“Quality” is not one property that can be inferred from a single number. A team building a payment service may prioritize security, reliability, and correct transaction handling; a content tool may place greater emphasis on usability and accessibility. The appropriate measures depend on the product, its users, and the risks that matter.
ISO/IEC 25010:2023, Edition 2, published in November 2023, defines a product-quality model with nine characteristics. ISO describes the model as a reference for specifying, measuring, and evaluating software product quality. Use it as a structured checklist for requirements—not as a ready-made scorecard. Select the characteristics that matter to your product, then make them concrete in user- and system-level requirements.
For each quality objective, record the stakeholder need, the affected part of the product, the risk being managed, and what evidence would show whether the objective is being met. This prevents a team from measuring what is easy to count while overlooking what users actually need.
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Choose measures that answer a decision
A useful measure has a defined purpose and an operational definition. Before collecting it, agree on:
- Question: What decision or improvement discussion should this measure support?
- Indicator and calculation: What exactly is counted, and what is the numerator and denominator where applicable?
- Data source: Which system, test, user feedback channel, or incident record supplies the evidence?
- Scope and review period: Which application, service, user group, and time window are included?
- Owner: Who checks the data quality and brings changes or anomalies to the team?
ISO/IEC 25020:2019 is a separate ISO framework for quality measurement. It is relevant when designing and evaluating a measurement model. The key practical point is to define what a measure means before interpreting its value: an indicator cannot support conclusions beyond what its underlying data captures.
Measure product quality and delivery performance separately
Product measures describe qualities of the software and its outcomes for users. Delivery measures describe how changes reach users and the instability or intervention associated with that process. They complement each other, but they are not interchangeable: a team can deliver frequently without proving that its product is usable, secure, or dependable, and a product-quality measure alone does not explain how safely changes are delivered.
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| Measurement view | Question it helps answer | Examples of evidence | What it does not establish by itself |
|---|---|---|---|
| Product quality | Does the product meet the relevant needs and quality requirements? | Measures selected for relevant ISO/IEC 25010:2023 characteristics, such as observed product behavior or test results tied to a requirement. | How efficiently changes move through delivery. |
| Delivery performance | How quickly do changes reach users, and how often does delivery require recovery or rework? | DORA’s five software delivery performance measures. | Whether the product as a whole meets every user or quality need. |
| Team or organisational goal | What broader development or organisational outcome should be understood? | A framework selected to fit the goal, potentially including SPACE, DevEx, or H.E.A.R.T. | A universal substitute for product or delivery evidence. |
DORA’s framework-selection guidance emphasizes matching the approach to organisational goals and describes combining delivery measures with a product-excellence framework as one possible approach. Choose frameworks by the decision they need to inform, rather than treating them as rival versions of a single score.
Use DORA’s current five delivery measures
DORA currently describes five software delivery performance measures, grouped as throughput and instability. Use DORA’s definitions when instrumenting them, and keep the scope to an application or service: DORA says the measures are best suited to one application or service at a time.
| Measure | What it helps the team examine | Interpretation caution |
|---|---|---|
| Change lead time | How long changes take to move through delivery. | Agree on the start and end events in the team’s implementation; different event choices produce different measurements. |
| Deployment frequency | How often the service is deployed. | A higher frequency alone does not show that deployments are valuable or safe. |
| Failed deployment recovery time | How long recovery takes after a failed deployment. | Define what qualifies as a failed deployment and when recovery is considered complete. |
| Change fail rate | How often a deployment results in a failure requiring intervention. | Use a consistent definition of qualifying failure and deployment; do not silently change the counting rules. |
| Deployment rework rate | How much deployment activity is rework rather than planned delivery. | Make the classification of rework explicit so teams can compare like with like over time. |
The table summarizes the questions these measures address; for implementation, consult DORA’s own definitions rather than inferring a formula from a short label. The measures show aspects of delivery throughput and instability, not a complete evaluation of the software product.
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Build a small, product-specific measurement set
- Name one quality objective. State whose need it serves and what risk or outcome matters.
- Choose evidence for that objective. Select one or more indicators grounded in the relevant product-quality characteristic or delivery question. Avoid adding measures solely because a tool makes them easy to collect.
- Write an operational definition. Specify the events, calculation, exclusions, source, scope, review window, and owner. For subjective evidence, document how it is gathered and whose experience it represents.
- Establish a baseline. Observe the measure using stable definitions before deciding what change would be meaningful. The available standards and DORA guidance do not provide a universal target threshold for every team.
- Review trends and investigate changes. Examine measures for the same application or service over time, alongside relevant incidents, releases, user feedback, and changes in scope.
- Choose an improvement action and review its effects. Record the hypothesis, the change made, and what evidence would support or challenge the expected result. Revisit the measure if it no longer informs a decision.
Use measures without creating distorted incentives
A metric becomes dangerous when a proxy is treated as the goal without checking what behavior it encourages. For example, maximizing deployment frequency in isolation could focus attention on count rather than whether changes are useful or safe. Treat that as a reason to interpret measures together and in context, not as a claim that any one metric inevitably causes a specific behavior.
- Do not rank teams using figures whose service scope, event definitions, or operating conditions differ.
- Do not interpret an improvement in one delivery measure as proof that product quality improved.
- Pair a measure with evidence that can reveal its blind spots—for example, review a delivery change alongside relevant product outcomes or incidents.
- When the data changes, check whether the product, definitions, collection process, or user population changed before attributing the shift to team performance.
Use screenshots as supporting evidence for interface changes
For a web interface, screenshots can help a team inspect what a particular page or state looked like during a review or acceptance check. They are supporting evidence, not a substitute for measures of accessibility, behavior, reliability, or user outcomes. Record the target URL, viewport or device, capture time, and relevant test state so reviewers understand what the image represents. Keep credentials and sensitive user data out of public captures.
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Common measurement problems and fixes
| Problem | Likely cause | Practical fix |
|---|---|---|
| A metric moves, but the team cannot say what it means. | The event definition, scope, or data source was never agreed. | Document the calculation and source, validate sample records, and establish a fresh baseline if the definition changes. |
| Delivery looks faster while users still encounter quality problems. | Delivery measures are being treated as a proxy for product quality. | Add evidence tied to the affected product requirement or user outcome, and investigate both views together. |
| Comparisons between services seem unfair. | The services differ in scope or the metrics are aggregated across applications. | Review each application or service on its own terms, consistent with DORA’s guidance. |
| A target improves while maintainability or user experience appears to suffer. | The target may be optimizing a proxy rather than the intended outcome. | Revisit the objective, inspect counter-evidence, and adjust the measure or incentive before treating the target as success. |
| Trend changes coincide with a change in instrumentation. | Collection rules or definitions may have changed. | Mark the change, check whether historical values remain comparable, and avoid presenting a discontinuous series as one consistent trend. |
Frequently asked questions
Does ISO/IEC 25010:2023 give a team a quality score?
No. It provides a model of nine product-quality characteristics to support specifying, measuring, and evaluating quality. A team must select relevant requirements and measures for its product and stakeholders.
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Are DORA measures the same as the older four-key model?
DORA’s current guidance describes five measures, including deployment rework rate. Use the current five-measure set and DORA’s definitions rather than substituting older terminology.
Should every Agile team use SPACE, DevEx, or H.E.A.R.T.?
No universal framework is prescribed here. DORA’s guidance is to choose measurement frameworks in line with organisational goals; the right mix depends on the question the team needs to answer.
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