30/60/90 Cadence Playbook for Learning Ops

Welcome — why a 30/60/90 cadence matters

Experiments without rhythm tend to be one-offs. A disciplined 30/60/90 cadence turns discovery into durable improvement by linking diagnosis, focused experiments, and adoption into a predictable cycle teams can run repeatedly. This playbook gives teams the roles, artifacts, meeting rhythm, and templates you need to run the cadence starting today.

Core idea

Run repeating 30-day sprints with linked purposes: diagnose in the first sprint, run prioritized experiments in the second, and adopt/scale what works in the third. Each sprint has clear outputs, owners, measurement anchors, and communication expectations so learning becomes institutional knowledge rather than tribal memory.

High-level cadence

• Days 1–30 (Diagnose): Understand the problem, collect baseline measures, create an experiment backlog, and select the highest-impact tests.
• Days 31–60 (Experiment): Run rapid, instrumented experiments, capture results, and form practical recommendations.
• Days 61–90 (Adopt): Operationalize successful experiments with checklists, training, updated procedures, and owner assignment for scale.

Roles & responsibilities

• Sprint Lead — owns the cadence for the sprint, runs kickoff and reviews, keeps the backlog groomed.
• Experiment Owner — designs and runs the experiment, collects data, writes the brief and results.
• Data Steward / Analyst — defines measures, ensures data quality, and produces measurement anchors.
• Operator / Frontline Lead — provides practical constraints, tests procedures, and validates adoption feasibility.
• Stakeholder / Sponsor — authorization for resource changes and commitment for adoption if successful.
• Librarian / Knowledge Curator — captures learning records, templates, and updates the team knowledge base.

Artifacts (what to produce)

• Diagnostic Report — concise summary of the problem, baseline metrics, root causes, and prioritized experiment backlog.
• Experiment Brief — hypothesis, metrics, design, sample size or scope, risks, and acceptance criteria.
• Experiment Tracker — a living log of status, interim results, and deviations.
• Adoption Checklist — concrete steps, owners, training needs, and rollback plans for operationalizing successful experiments.
• Learning Record — template entry capturing context, what was learned, supporting evidence, and recommended next steps.

Meeting cadence (recommended)

• Sprint Kickoff (90 minutes, day 1) — align problem statement, roles, success criteria, and backlog priorities.
• Weekly Huddle (30 minutes) — progress updates, blockers, quick decisions. Keep it focused on removing impediments and deciding whether to continue, pivot, or stop experiments.
• Mid-sprint Review (60 minutes, day 15) — review early signals, data quality issues, and adjust scope.
• Demo & Retrospective (90 minutes, day 30) — share results, surface learnings, update the knowledge base, and select experiments to scale.
• Adoption Review (end of adoption sprint) — confirm operational readiness, training completion, ownership, and update SOPs.

Measurement anchors (make success measurable)

Each experiment and adoption plan should include:

1. Primary metric: the single measure that matters (e.g., defect rate, lead time, customer satisfaction).
2. Baseline and target: numeric baseline, short-term target, and long-term goal.
3. Leading indicators: upstream measures you can check frequently to detect trends early.
4. Confidence and sample size: how much data is needed before making a decision.
5. Data frequency & owner: who reports, how often, and where it's stored.

Templates you can copy

Sprint Kickoff agenda (copy-paste)

1. Opening & purpose (5m)
2. Problem statement & baseline metrics (10m)
3. Review prioritized experiment backlog (20m)
4. Assign experiment owners & data stewards (10m)
5. Agree measurement anchors and success criteria (15m)
6. Communication plan & documentation location (10m)
7. Risks & mitigation (10m)
8. Next steps & weekly schedule (10m)

Experiment Brief (one-page template)

Experiment Tracker (table head you can use)

Adoption Checklist (use to operationalize)

• [ ] Confirm experiment meets acceptance criteria and stakeholder sign-off
• [ ] Update SOPs, checklists, and job aids
• [ ] Assign operational owner and backup
• [ ] Complete training for affected staff and confirm competency
• [ ] Publish learning record with evidence and tags (process, metric, site)
• [ ] Schedule follow-up KPIs at 30/90/180 days
• [ ] Rollback plan documented and tested

Communication plan (short & practical)

Use a single channel for sprint artifacts (e.g., a folder or space in your team knowledge base). Share weekly huddle notes and experiment tracker updates to a stakeholder distribution list. Encourage short demo recordings for asynchronous stakeholders. The Librarian curates learning records and ensures search tags make lessons discoverable.

Common pitfalls & how to avoid them

• No clear success criteria: Define numeric acceptance criteria before running an experiment.
• Poor measurement: Assign a data steward at kickoff and validate data pipelines immediately.
• No owner for adoption: Require an operational owner before approving scale decisions.
• Over-centralization: Keep experiments local where appropriate and let local teams own adoption, while centralizing templates and learning capture.
• Lack of documentation: Capture short learning records immediately — small notes beat lost memories.

Quick-start 30/60/90 checklist

1. Day 1–3: Kickoff, confirm baseline, and prioritize top 3 experiments.
2. Day 4–10: Prepare experiment briefs, data collection, and training as needed.
3. Day 11–30: Run and monitor experiments; hold weekly huddles and a day-15 check.
4. Day 31–60: Continue experiments, collect full results, and prepare recommendations.
5. Day 61–90: Execute adoption checklist for approved experiments and schedule KPI follow-ups.

How to tailor this playbook

Smaller teams can compress checkpoints (e.g., two-week internal syncs) while keeping the 30/60/90 rhythm for visibility. Regulated environments should add compliance review gates to the adoption checklist. Use the experiment brief as the single source of truth for decisions.

Next practical steps

1. Copy the Sprint Kickoff agenda and run a 90-minute kickoff this week.
2. Create your first diagnostic report and populate the experiment tracker with 3 candidate tests.
3. Assign a Librarian to capture a learning record template and make the artifacts discoverable.

Tip: Start small. The cadence scales as teams gain confidence. The goal is predictable, evidence-driven learning — not process for its own sake.