OGTIC: RedLab Innovation Network
Structured capability, shared methods, and cohort learning across public institutions.
We helped design and facilitate RedLab, aligning labs under a common method, installing governance and cadence, and moving priority challenges from ideas to evidence backed delivery.
Built on MicroCanvas® v2.1 and IMM‑P® gates.

At a glance
- Sector: Public sector, multi-institution
- Scope: Innovation network design, cohorts, and operating model
- Approach: Evidence-led, gates and cadence, shared playbooks
- Result: Labs aligned to a common method and faster, clearer decisions
Context
The Red de Laboratorios de Innovación, RedLab, was created under OGTIC to strengthen innovation capacity in the Dominican Republic public sector. The goal was to move from isolated efforts to a structured, scalable ecosystem where teams can design, test, and implement solutions to complex challenges.
Early hurdles included uneven methods, fragmented governance, and uncertainty about how to sustain participation across diverse institutions. RedLab needed a common framework, a clear program structure, and practical tools that build capability while delivering visible results.
Doulab partnered with OGTIC to design and facilitate Cohorts 01 and 02, anchored in the MicroCanvas Framework, MCF 2.1 and the Innovation Maturity Model Program, IMM-P®. The aim was to give public servants effective tools and a repeatable process that position RedLab as a pillar for public innovation.
RedLab in one line: clearer gates, shared language, better delivery.
Who benefits first: policy, service delivery, and digital teams that need clearer gates and faster decisions.
Social proof: cohort format and shared playbooks help teams see quick wins and reuse what works.
Key risks and mitigations
- Adoption risk: Mitigated with peer reviews, light templates, and visible quick wins.
- Continuity risk: Mitigated with named owners, a simple operating rhythm, and playbooks.
- Evidence quality risk: Mitigated with standard evidence packs and gate criteria.
What RedLab implemented: operating model, cohorts, shared method, governance, and playbooks.
What we did
- Network and operating model: Co-designed the network structure, lab charter template, intake, and decision gates with accountable owners.
- Cohort program: Ran cohort cycles, discovery to validation to delivery, with peer reviews, demo days, and evidence packs at each gate.
- Shared method: Adopted MCF 2.1 for problem framing, value definition, and experiment design across institutions.
- Governance and cadence: Installed rhythms, stand-ups, reviews, decision forums, and stage appropriate KPIs tied to policy and service outcomes.
Governance model: RACI per initiative; weekly cadence; gate checklist per stage; decision log and risk register for traceability.
KPI tree by stage: Discovery, signal quality and interview coverage; Validation, conversion to key action and time to decision; Delivery, cycle time and escaped defects; Scale, adoption, satisfaction, and unit economics where relevant.
Examples: Discovery, interview coverage; Validation, conversion to key action; Delivery, cycle time; Scale, adoption and satisfaction.
Capability baseline at kickoff, tracked quarterly against the KPI tree to show maturity gains over time.
Operational rhythm: weekly reviews, monthly gate checks, and quarterly capability snapshots.
SLA: gate review response within five working days, with decision memo or next-evidence request.
- Playbooks and handover: Produced guides for lab charters, evidence packs, gate criteria, and role definitions to preserve institutional memory and scale.
Evidence pack: problem and assumptions, stakeholders and JTBD, experiment plan and results, artifact links, decision memo, next step.
Insights are coded into a signal library to inform next experiments and program roadmaps.
After-action reviews at the end of each cohort feed into the signal library and the next-cohort roadmap.
Timeline
- Cohort 01: 2024, network design, charters, and first evidence packs.
- Cohort 02: 2025, scale out of shared methods and deeper governance and cadence.
What changed, how decisions improved, and capability growth.
Outcomes
- Labs stood up: Seven innovation labs co-created and aligned to a common method and cadence, as of September 2025.
- Faster decisions: Gate reviews and accountable owners reduced decision latency across participating entities.
- Quicker cycles: Priority projects moved from ideas to pilots with auditable evidence.
- Reusable playbooks: Charters, gate criteria, and evidence templates standardize how work moves.
- Capability uplift: Teams practiced evidence-led delivery, increasing confidence and alignment.
Tracked families, as of September 2025: decision latency, cycle time, adoption and satisfaction, and capability growth.
Why it mattered
- Shifted innovation from one-off projects to a system with clear roles, rules, and rhythms.
- Enabled cross-institution learning and reuse, which lowers risk and duplication.
- Created traceability from policy goals to experiments and delivery decisions.
- Built a base to scale future cohorts and to embed innovation in public management.
Start small: Discovery call → ClarityScan → Gate 1 pilot.
To speed things up: share your goals, timelines, constraints, and how you measure success today.
Prefer a briefing for your team or partners? Request a briefing.
Planning a cohort or event? Co host a session.
Exploring co-branded cohorts or MOUs? Let’s outline options.
Related services: Programs, IMM-P® and Diagnostics, ClarityScan®. See more examples in Case studies.
Process (diagram)

Diagram: high‑level flow of context → work → outcomes.
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