Using Policy Labs as a process to bring evidence closer to public policymaking: a guide to one approach

The article addresses the persistent challenge that policymaking requires more than the presentation of robust evidence. It explores how collaborative engagement models can bridge gaps between evidence producers (academics) and users (policymakers, practitioners, the public). Focusing on ‘Policy Labs’ as an activity/process rather than an institution or space, the authors aim to: (a) provide a guide to how they have run 15 Policy Labs (January 2015–September 2019) and share what works; and (b) demonstrate how such labs can bring evidence closer to policymaking by aligning their characteristics with enablers identified in the literature. The study is situated within the broader context of policy engagement initiatives and acknowledges the complexity, values, and constraints inherent in policymaking processes.

The authors highlight key enablers for bringing evidence closer to policymaking, drawing primarily on two systematic reviews (Oliver et al., 2014; Oliver & Cairney, 2019). They group enablers into three guiding principles: Trust, Translation, and Timing. Trust: Establish collaborations and relationships between academics and policymakers; co-design/co-creation approaches; policy brokerage roles in universities; integrity and high-quality research; transparency about methods and limitations. Translation: Improve availability and access to research; make research relevant, readable, and clearly communicated; provide concise, graded-entry formats (e.g., one-page messages, executive summaries, full reports); ensure contextual relevance and applicability; use syntheses like systematic reviews. Timing: Recognize policy windows (Kingdon, 1984); be routinely accessible and engaged so evidence can reach decision-makers at the right moment; balance rapid provision of the best available evidence with longer-term evidence building. Table 1 (summarized) links specific enablers—collaboration, relationships with policymakers and researchers, academics understanding policy processes, engaging routinely and humbly, availability and dissemination, clarity/relevance/reliability, high-quality research, and readability—to the Trust, Translation, and Timing themes.

Reporting on experience from 15 Policy Labs (2015–2019), the authors present an eight-step guide to running Policy Labs as an iterative process rather than a standalone event: 1) Set aside time for planning: Allocate substantial preparation (approx. 20–40 staff-days across a team; 5–10 hours of consultations) to frame the problem appropriately, understand existing evidence, gaps, and potential areas of contention. 2) Establish the need and purpose: Position the lab within any stage of the policy cycle (issue identification, formulation, implementation, evaluation). Early-stage labs may clarify research and future policy agendas; mid-stage labs can design options and plan evaluation; implementation labs identify barriers/facilitators; evaluation labs consider assessment strategies. Labs can be initiated by ‘push’ (researcher-driven) or ‘pull’ (policymaker-driven) dynamics. 3) Select and invite participants: Tailor to the lab’s policy stage and questions; include policymakers, implementers, academics, practitioners, industry, and end users/beneficiaries. Intentionally include diverse and opposing viewpoints; create a forum for open discussion to surface barriers, constraints, and values. 4) Synthesise and communicate the evidence: Develop an advance ‘briefing pack’ summarizing high-quality evidence (prioritizing systematic reviews and peer-reviewed syntheses where available), current practice, international examples, and ongoing research. Aim for accessibility while preserving nuance, and clearly delineate areas of ambiguity, insufficiency, and disagreement to form the basis for discussion. 5) Plan agenda and facilitation: Determine length (from focused 4-hour sessions to 1–1.5-day formats) based on group dynamics and objectives. Use experienced facilitators skilled in participatory decision-making, culturally sensitive where relevant, and involved in co-designing the session. 6) Conduct the Policy Lab: Establish a safe space; begin with shared understanding from the briefing pack and invite feedback. Use plenary and breakouts to explore key questions (evidence strength, implementation barriers, solutions, scaling, design ingredients). Employ creative techniques (e.g., competitive idea games, simple props) and methods such as the ‘diamond’ approach (diverge then converge) or Situation–Complication–Question framing. 7) Report the results: Systematically capture ideas and distill key messages into accessible outputs (policy briefings, pamphlets, reports, journal articles). Use graded-entry formats (e.g., one-page infographics for rapid advocacy plus detailed reports timed to policy moments such as conferences). 8) Create and support the new coalition: Focus on long-term outcomes beyond the event. Facilitate advocacy, follow-up meetings, identification of champions, participant pledges (6–12 months), and commitments to action (e.g., regulatory/document changes). Recognize resource constraints; empower participant ownership to sustain momentum and targeted engagement strategies. Boxed examples illustrate applications across domains (diabetes, dentistry/caries prevention, UK research landscape, Mental Health Act review), participants (~20–26), durations (4 hours to 1.5 days), and outputs (briefs, infographics, op-eds, reports, follow-on evidence sessions).

- The Policy Lab process, when designed around Trust, Translation, and Timing, offers a practical mechanism to bring evidence closer to policymaking. - Across 15 Policy Labs (Jan 2015–Sep 2019), the approach consistently: (i) builds networks, collaborations, and partnerships between academics and policymakers; (ii) synthesizes available evidence into robust, accessible formats (briefing packs, graded-entry outputs, concise policy briefs, infographics); and (iii) provides timely access to evidence aligned with policy windows and stakeholder concerns. - Resource and design details: Labs typically require 20–40 staff-days for preparation; 5–10 hours of scoping consultations; participant groups around 20–26; durations from 4 hours to 1.5 days; and professional facilitation. - Notable outcome examples: • Diabetes Policy Lab (2015) clarified barriers to appropriate use of metabolic/bariatric surgery for Type 2 diabetes; subsequent NICE guideline updates (2018) referenced bariatric surgery as an option for higher BMI patients (authors do not claim causation). • Dentistry/‘Towards a Cavity-free Future’ labs (2017–2018) yielded immediate advocacy tools (infographic; summary report) and tangible follow-ons: a sub-group with the Wales Chief Dental Officer to plan a new local payment system pilot, a CariesCare Practice Guide with the British Dental Journal, and trial implementation of new payment models in France. • ‘Positioning the UK within the global research landscape’ lab produced a policy brief used in advocacy by sector bodies and informed internal KCL policy; strengthened stakeholder relationships. • ‘Future of the Mental Health Act’ lab supported the independent review (policy brief cited), and contributed to ongoing work on advance choice documents, including a follow-on evidence session in the House of Lords. - Measurable policy influence: The authors could directly track two of the 15 labs influencing policy decisions via citations of lab outputs. - The labs function as safe, structured spaces to surface constraints (political, budgetary, operational) and co-design feasible, context-aware solutions, enhancing the relevance and usability of evidence.

The Policy Lab model operationalizes literature-identified enablers for evidence use in policy by: (i) creating trusted networks and co-design partnerships that connect diverse stakeholders around shared goals; (ii) translating evidence through curated briefing packs and message-driven reports that clarify strengths, limitations, and relevance; and (iii) aligning with policy timing by tailoring content, participants, and discussions to imminent or future decision points. The process exposes academics to real-world constraints and policy logics, while giving policymakers structured engagement with the most relevant evidence. Safe-space facilitation fosters openness, critical examination, and coalition-building, enabling participants to become advocates for agreed outcomes. Despite challenges in attributing long-term policy change to single events, the labs contribute to ongoing policy development pathways, particularly when embedded in existing processes and timed to policy windows. Overall, Policy Labs are best viewed as part of a sustained engagement process that can incrementally improve policymaking effectiveness and culture by integrating evidence with stakeholder values, experiences, and practical constraints.

Policy Labs, conceived as an engagement process rather than isolated events, provide structured, collaborative spaces that bring evidence closer to policymaking by building trust among stakeholders, translating research into accessible and relevant formats, and aligning engagement with policy timing. The approach includes careful preparation (evidence synthesis and problem framing), inclusive participation and skilled facilitation, accessible reporting for advocacy, and coalition-building for follow-through. While not the only model, it embodies characteristics shown to influence policymaking: network creation, robust evidence synthesis, and timely access to evidence. Recognizing attribution and measurement challenges, the authors recommend embedding Policy Labs within longer-term policy development processes. Future work could strengthen evaluation of long-term impacts, resource sustained follow-up, and continue refining design features that maximize policy relevance and uptake across different policy stages.

- Attribution and measurement: It is difficult to evaluate long-term policy impacts and attribute decisions to a single lab within complex, multi-actor policy environments; only two of 15 labs could be directly tracked as influencing policy decisions via citations. - Resource constraints: Limited staff time and resources can restrict post-lab follow-up beyond initial briefings, potentially reducing sustained impact. - Evidence and timing constraints: Variability in available evidence and unpredictable policy windows can limit immediate uptake; aligning academic timelines with policy needs remains challenging. - Generalizability: Outcomes are context-dependent; lab effectiveness may vary by policy domain, stakeholder mix, and existing policy processes. - Dependence on process integration: Labs are more likely to have impact when embedded in ongoing policy development; as standalone events, their ability to effect change is limited.