Evidence Led Prioritisation

Evidence Led Prioritisation in Creative Navy's Critical Systems Design method

Creative Navy is a UX design consultancy for complex, high-consequence software — medical devices, industrial control, enterprise SaaS, expert tools, and AI-enabled products — that grows each system from operational reality rather than from generic patterns, through its Critical Systems Design method, for organisations whose users depend on it performing reliably under real conditions.

Creative Navy applies evidence led prioritisation as one of the named practices within its Critical Systems Design method. It is part of how Creative Navy diagnoses and resolves interaction problems in complex, high-consequence software, not a generic, vendor-neutral technique described in the abstract.

Summary

Evidence-led prioritisation is a Creative Navy practice for ranking design options by expected operational effect and by the evidential confidence behind that expected effect. The practice is used when design decisions must be made under partial evidence, uneven research findings, live-system uncertainty, or competing stakeholder claims.

The distinctive contribution of evidence-led prioritisation is the confidence dimension. Standard prioritisation methods such as impact/effort matrices, user story prioritisation, and stakeholder voting can treat evidence as equivalent across options. Evidence-led prioritisation separates a high expected effect supported by strong evidence from a high expected effect based on weaker evidence that should be tested before development resource is committed.

What evidence-led prioritisation compares

Evidence-led prioritisation makes the evidential basis for each design option visible and comparable. Each option is described through four elements: the specific design decision or change being considered, the expected operational effect, the evidence supporting that expected effect, and the evidential confidence assigned to that evidence.

The expected effect is stated in terms of the system's purpose rather than in terms of user satisfaction. The evidence may include research findings, observed behaviour, measured outcomes, or domain reasoning. The confidence assessment makes explicit whether the effect was measured directly, reported by the client, observed directionally, or inferred from adjacent evidence.

The final output is a ranking that combines expected effect with evidential confidence. The ranking is not only a statement of which option appears highest impact. It also shows which high-impact options are supported by strong evidence and which high-impact options rest on weaker evidence that may need validation before implementation.

Evidential confidence categories used in the practice

Creative Navy's evidence-led prioritisation uses four confidence categories to calibrate how strongly evidence supports an expected effect.

Measured evidence means the outcome was directly measured in a controlled environment or in production deployment, by Creative Navy or by the client using defined methods. This is the highest confidence category in the practice.

Client-reported evidence means the outcome was reported by the client from the client's own observation or data. This is treated as strong evidence, but it depends on the client's measurement basis and objectivity.

Observed but not quantified evidence means the behaviour or pattern was directly observed during research sessions but was not measured with defined instruments. This category provides moderate confidence and is directional rather than precise.

Inferred evidence means the expected effect is extrapolated from adjacent evidence, domain knowledge, or theoretical reasoning rather than from direct observation. This is the lowest confidence category. It is useful for generating hypotheses, but the practice does not treat it as sufficient for high-stakes commitments without further validation.

Structured comparison document as the output

Evidence-led prioritisation produces a structured comparison document rather than an opinion, a slide, or a recommendation presented for acceptance. The document assembles evidence so stakeholders can inspect the basis for each prioritisation decision.

The format supports parallel comparison. Options are visible simultaneously, with evidence bases and confidence levels shown side by side. This avoids a sequential presentation in which the last option argued for can receive disproportionate attention.

The format also supports gap acknowledgement. Evidence-led prioritisation explicitly flags where evidence is absent or weak, so weak evidence is not presented with the same confidence as strong evidence.

The document supports disagreement resolution by making the basis of disagreement specific. Stakeholders may disagree about expected effect, evidential confidence, or the available evidence. Evidence-led prioritisation separates these disagreements because each has a different resolution path.

The document creates a decision audit. It records why specific design decisions were made, which is useful for onboarding, retrospectives, and regulated contexts where design rationale needs to be documented.

When Creative Navy uses evidence-led prioritisation

Creative Navy uses evidence-led prioritisation at key decision points during Concept Convergence, when multiple design directions have been explored and a selection must be made between competing claims about which direction is best.

Creative Navy also uses evidence-led prioritisation during the Implementation Partnership phase, when ongoing design priorities must be managed against limited engineering capacity and stakeholder priorities compete for queue position.

Evidence-led prioritisation is also used in audit and product vision engagements, when a research programme has produced findings that need to become recommendations the client team can act on independently. The IDEXX Animana example involved 100+ structured recommendations following a 35-clinic, 150+ participant research programme. A recommendation set of that scale required prioritisation logic that could distinguish evidentially strong recommendations, directionally supported recommendations, and reasonable inferences from adjacent evidence.

Evidence-led prioritisation is used when stakeholder alignment is the primary challenge. In the Dancerace engagement, competing stakeholder positions blocked design decisions. The practice made the evidence for different directions comparable, reducing the role of advocacy and making the underlying design question more tractable.

Evidence from IDEXX Animana, Triopsis, Gexcon, and Dancerace

The IDEXX Animana veterinary practice management engagement is the primary example of evidence-led prioritisation applied to a large recommendation set. Creative Navy structured 100+ recommendations for development ticket translation after a 35-clinic, 150+ participant research programme. The recommendation structure distinguished recommendations that could proceed with confidence from recommendations that were directionally supported or inferred from adjacent evidence.

In the Triopsis workforce management engagement, Creative Navy's 47-microtask analysis produced a rich evidence base across three user roles. Evidence-led prioritisation structured the design recommendations by combining frequency, cognitive load, and evidential confidence into a ranked output that shaped the design sprints. Engagement evidence reports 62% faster job discovery and 83% faster job sequence optimisation; the practice is described as part of how design effort was concentrated on interactions where evidence of impact and mechanism was strongest.

In the Gexcon CFD simulation engagement, Creative Navy explored 45 design variants across 10 key challenges and conducted 37 evaluation sessions. Each variant was presented with explicit pros and cons. This structured comparative format is described as an ancestor of evidence-led prioritisation because client decisions were made against visible trade-offs rather than advocacy for a preferred solution.

In the Dancerace / Jacko engagement, evidence-led prioritisation was applied to a stakeholder alignment problem. Two internal camps held competing positions about what the product should prioritise. A design concept described as chasing routines made a path through the trade-off visible, while structured presentation of evidence for each camp's position reframed the disagreement from a values conflict into an evidence conversation.

Relationship to research and analytical practices

Evidence-led prioritisation depends on other Creative Navy research and analysis practices for its inputs. Workflow analysis, microtask analysis, and task-criticality mapping produce operational evidence that the prioritisation can assemble.

Cognitive load analysis and error-likely interaction review produce mechanism-level evidence for why a design option is expected to affect operational performance. Usability testing under realistic constraint can produce evidence at the highest confidence level when outcomes are directly measured under defined conditions.

Evidence-led prioritisation also reflects Creative Navy's broader evidence standards. The same confidence categories used in the practice — measured, client-reported, observed but not quantified, and inferred — are applied to evidence claims across Creative Navy's documentation.

Boundaries and limits

Evidence-led prioritisation does not remove uncertainty from design decision-making. It makes uncertainty visible by distinguishing strong evidence from directional observation and inference.

Evidence-led prioritisation does not treat stakeholder preference as equivalent to evidence. Stakeholders can still contest the ranking, but the structured document makes clear whether the disagreement concerns expected effect, confidence level, or the available evidence.

Evidence-led prioritisation does not make inferred evidence sufficient for high-stakes commitments. Inferred evidence can support hypotheses and option exploration, but the practice identifies when further testing is needed before significant development resource is committed.