Learning Ops Roles, RACI & Cadence Template

Purpose

This template helps teams assign clear ownership, accountabilities, and operational rhythm so learning experiments become repeatable, discoverable, and scalable. Use it as a starting point: copy, tailor role names, adapt cadences, and add local policies.

Core roles & short descriptions

Keep role scope pragmatic. Not every organization needs all roles as full-time hires; some are shared responsibilities or rotated.

• Knowledge Manager (KM): Owns the learning system, taxonomy, content lifecycle, access, and handoffs. Ensures discoveries become reusable knowledge and that the knowledge base stays current.
• Learning Engineer (LE): Designs experiments, learning experiences, and the formats for capture (tests, templates, microlearning, runbooks). Works with teams to operationalize experiments.
• Analyst (AN): Measures impact, builds dashboards and KPI reports, and validates experiment results against agreed metrics.
• Experiment Owner (EO): Day-to-day owner of a specific experiment or pilot; responsible for execution and local observations.
• Product/Process Owner (PO): The domain owner who sponsors experiments in their area and is accountable for decisions that follow from learning.
• Sponsor (SP): Senior stakeholder who secures resources and removes organizational blockers for learning ops initiatives.
• Community of Practice Lead (CoP): Facilitates cross-team sharing, curates high-value learning, and helps the organization adopt proven practices.

Sample RACI matrix

Below is a sample RACI for common learning ops activities. Use this as a baseline and adapt columns/roles to match your org.

Suggested meeting cadences (examples)

Match cadence to velocity and complexity. These are starting recommendations.

• Weekly KPI Huddle
  • Frequency: weekly
  • Duration: 30–45 minutes
  • Attendees: Analyst (lead), KM, LE, experiment owners from active pilots
  • Purpose: quick review of leading indicators, blocked experiments, and urgent learnings
  • Outputs: prioritized action items, measurement clarifications, escalation list
• Experiment Sync
  • Frequency: weekly or biweekly (per program)
  • Duration: 30–60 minutes
  • Attendees: EO, LE, KM, AN as needed
  • Purpose: coordinate execution, troubleshoot methods, ensure consistent measurement
  • Outputs: updated experiment logs, revised timelines
• Community of Practice (CoP) Share
  • Frequency: monthly
  • Duration: 60–90 minutes
  • Attendees: practitioners, KM, CoP Lead, invited PO/SP
  • Purpose: surface cross-team learnings, curate highlights for the knowledge base
  • Outputs: curated learning briefs, adoption proposals
• Quarterly Learning Review
  • Frequency: quarterly
  • Duration: 2 hours
  • Attendees: KM, LE, AN, PO, SP, selected EOs
  • Purpose: review portfolio-level impact, decide on scale/adopt/retire actions
  • Outputs: roadmap changes, resource allocation decisions

Handoff protocols & templates

Standardize handoffs to avoid lost context. Recommended artifacts:

• Experiment Brief (template): hypothesis, success metrics, owner, duration, key risks, data sources.
• Learning Capture Template: summary, evidence, recommended action, confidence level, next steps, relevant tags.
• Content Taxonomy & Tags: defined fields for product area, process, experiment type, outcome, and maturity (pilot, validated, adopted).
• Storage & Access: canonical location(s) and access rules, with version control and retention policy.

Hiring checklist for a Knowledge Manager

Use this to evaluate candidates and to design an onboarding experience.

• Clear job description: ownership of knowledge lifecycle, taxonomy, publishing standards, and learning ops tooling.
• Must-have skills: information architecture, stakeholder facilitation, content curation, basic analytics literacy, and tooling experience (wiki/LMS/knowledge base).
• Nice-to-have: experience with experiments, learning science, or operations in the domain.
• Interview stages: screening, role-specific case or take-home exercise (e.g., curate a 1-page learning brief), stakeholder interviews, reference checks.
• Evaluation tasks: assess a sample artifact for discoverability & suggest improvements; design a brief taxonomy change and outline migration steps.
• Offer & admin checklist: access provisioning, workspace, tool licenses, onboarding meetings scheduled with LE, AN, key POs, and CoP lead.

90-day ramp for a Knowledge Manager (practical plan)

Focus on learning the domain, stabilizing essential workflows, and delivering early value.

First 30 days — Learn & observe

• Meet core stakeholders (LEs, ANs, POs, active EOs, and the Sponsor) and attend current huddles.
• Audit existing knowledge artifacts and the current taxonomy/storage locations.
• Deliverable: short diagnostic (1–2 pages) listing top 5 quick fixes and top 3 structural risks (e.g., missing tags, unclear ownership).
• Success indicators: access to systems, stakeholder alignment on immediate priorities.

Days 31–60 — Stabilize & standardize

• Create or refine the Experiment Brief and Learning Capture templates.
• Run an intake test: capture learning from one recently completed experiment and publish it to the canonical location.
• Start taxonomy clean-up (tags, maturity states).
• Deliverable: published example learning brief and updated taxonomy doc.
• Success indicators: one published brief used in CoP; reduced time to find learning artifacts in spot checks.

Days 61–90 — Operate & scale

• Introduce lightweight governance: review cadence, owner responsibilities, and a 30/60/90 checklist for experiment owners.
• Design handoffs for scaling validated experiments into operations or product workstreams.
• Deliverable: run the first knowledge curation cycle, present at the CoP, and produce a 90-day roadmap.
• Success indicators: consistent use of templates across 2+ experiments, stakeholder approval of roadmap, and at least one adoption action enabled by a captured learning.

Quick adoption tips

• Start small: enforce templates for a handful of active experiments before applying org-wide.
• Measure adoption: track artifacts published, tags applied, and time-to-find recent learnings.
• Celebrate reuse: highlight where captured learning prevented rework or improved outcomes.
• Keep the system low-friction: prefer shorter templates and a clear, searchable canonical store.

Where to tailor this template

Consider customizing role names, the RACI, cadence frequencies, taxonomies, and compliance/audit steps to reflect regulatory or safety constraints in your industry. Keep the core principle: clear ownership, repeatable handoffs, and measured outcomes.

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