Revenue Operations Manager
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- Build the revenue operating model, lifecycle definitions and trustworthy CRM foundation
- Turn pipeline and planning data into accurate forecasts, coverage decisions and operating cadence
- Redesign the GTM system for seller productivity, AI-enabled execution and durable adoption
Benchmark: OpenAI Sales Strategy & Operations + Anthropic Revenue Strategy & Operations + Anthropic TPM, Revenue Operations (current Sep 2026) Market refresh: GTM lifecycle design, CRM/data quality, pipeline and forecast cadence, territory/quota/capacity planning, quote-to-cash, seller productivity, AI/automation, change adoption and executive decision systems.
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Build the revenue operating model, lifecycle definitions and trustworthy CRM foundation
Revenue model, GTM motion + customer lifecycle
Coverage: Revenue Operations / GTM Strategy / CRM Lifecycle Management
CRM data model, hygiene + workflow automation
Coverage: CRM / Data Quality / Workflow Automation
Turn pipeline and planning data into accurate forecasts, coverage decisions and operating cadence
Pipeline, forecasting + business-review cadence
Coverage: Forecasting & Decision Science / Revenue Analytics / Executive Reviews
Territory, quota + capacity planning
Coverage: Sales Planning / Resource Allocation / Scenario Analysis
Redesign the GTM system for seller productivity, AI-enabled execution and durable adoption
Quote-to-cash, GTM systems + agentic sales workflows
Coverage: Revenue Systems / CPQ / Workflow Automation / AI Agents
Change adoption, seller productivity + executive influence
Coverage: Change Management / Program Management / Executive Communication
Role-Readiness Proof / Capstone
Build and operate a Revenue Operations system for a simulated B2B SaaS or AI business. Define the GTM model, lifecycle stages, CRM objects/required fields, routing rules and SLAs; create data-quality controls and a source-of-truth KPI dictionary; design territories, quotas and capacity assumptions; audit pipeline in SQL or CRM reporting and run a weekly forecast plus MBR/QBR cadence; map lead-to-cash and quote-to-cash handoffs; automate one high-friction seller workflow with approvals and human fallback; measure selling time, stage conversion, pipeline coverage, forecast accuracy, cycle time and revenue impact; then deliver a field-adoption plan and executive reallocation recommendation.
Proof Rubric
- Show one coherent revenue operating model from lifecycle definitions through systems and leadership cadence
- prove CRM/data-quality discipline and auditable metric definitions
- defend territory, quota and capacity logic with scenarios
- quantify forecast accuracy, pipeline risk and conversion
- demonstrate working automation with permissions, controls and fallback
- connect quote-to-cash and seller-productivity changes to measurable outcomes
- manage rollout and adoption rather than assuming compliance
- communicate decision-ready insights, dependencies and tradeoffs across Sales, Finance, Marketing, Legal, Systems and executives