> ## Documentation Index > Fetch the complete documentation index at: https://docs.dacard.ai/llms.txt > Use this file to discover all available pages before exploring further. # Team Operations framework > Deep dive into the 27-dimension, 5-stage Team Operations assessment. > [!NOTE] > > Team Operations is the primary framework. We score your team across 27 dimensions in 6 functions, each 1-5, for a composite of 27-135. The composite places you on the 5-stage Team Operations ladder: Foundation, Building, Scaling, Leading, Compounding. # Team Operations framework Team Operations is the primary scoring framework. It reads a team's operational capability across **27 dimensions** in **6 functions**, each scored 1-5, for a composite of **27-135**. It answers the question: how capable is your team at building and shipping? ## Five maturity stages ![Maturity ladder from Foundation (27-48) through Compounding (114-135)](https://mintcdn.com/dacard/Lj-FH3-8rSmqL1t4/images/maturity-stages.svg?fit=max\&auto=format\&n=Lj-FH3-8rSmqL1t4\&q=85\&s=d1927dc11eaad91c56182e9a45927d6e) **1. Foundation (27-48)** Basics missing across most dimensions. Team hasn't yet established consistent practice. Most work is manual, ad hoc, or driven by individual contributors rather than shared systems. **2. Building (49-70)** Practice exists but lands unevenly. Some functions are stronger than others. Team is experimenting with new workflows but lacks repeatability and measurement. **3. Scaling (71-91)** Systematic process with measurable outcomes. Team ships features repeatedly and reliably. Data loops are starting to compound. **4. Leading (92-113)** Deeply integrated practice across all functions. Capability is embedded in the team's ways of working, not just the product. Distance from Building-stage peers is meaningful and widening. **5. Compounding (114-135)** Self-improving systems. Every function reinforces every other. Team gets better with every cycle, creating advantage that's hard to copy. ## Six functions, 27 dimensions ![27 dimensions organized across 6 functions: Strategy, Design, Development, Intelligence, Operations, GTM](https://mintcdn.com/dacard/Lj-FH3-8rSmqL1t4/images/dimensions-by-function.svg?fit=max\&auto=format\&n=Lj-FH3-8rSmqL1t4\&q=85\&s=12f2c782a831af0520bf15262e9c35c5) Dimensions live in six functions that map to the full product lifecycle. ### Strategy How well the team reads its market and makes evidence-based calls. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Market intelligence** | Quality of market signal collection and synthesis | No systematic market read | Continuous competitive intelligence with real-time synthesis | | **Decision quality** | Evidence behind product and strategic decisions | Gut-feel decisions, undocumented | Structured decision frameworks with measured outcome tracking | | **Roadmap discipline** | How well the roadmap reflects strategic priorities | Roadmap driven by stakeholder requests | Outcome-based roadmap with clear OKR linkage and regular pruning | | **Competitive positioning** | Clarity and defensibility of position | No differentiated position | Compounding position that deepens with scale and is hard to replicate | ### Design How effectively the team turns user insight into shipped experience. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Research and discovery** | Depth and consistency of user research | No research practice | Continuous discovery with rigorous synthesis and opportunity trees | | **Prototyping speed** | How fast the team goes from idea to testable artifact | Weeks to a prototype | Same-day prototypes with real user feedback loops | | **Experience design** | Quality of interaction patterns and UX craft | No coherent interaction model | Interactions feel native, adaptive, and refined | | **Design-dev handoff** | Efficiency and fidelity of the design-to-build handoff | Manual specs with high loss-in-translation | Automated handoff with design system coverage and zero spec debt | ### Development How efficiently and consistently the team builds and ships. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Architecture and systems** | Depth of capability integration in the technical stack | No capability in the stack | Models, pipelines, and inference are core to the architecture | | **Spec and context quality** | Quality of PRDs, tickets, and context handed to builders | Vague specs, high ambiguity | Rich context, acceptance criteria, examples | | **Build vs buy** | Decision rigor on model and infrastructure choices | No framework for build vs buy | Principled model with clear criteria, regular review, measured outcomes | | **Delivery velocity** | Speed and consistency of shipping improvements | Quarterly releases | Continuous deployment with assisted review, testing, and rollout | ### Intelligence How well the team captures, organizes, and uses customer and product signal. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Customer signal synthesis** | Quality of feedback collection and synthesis | No systematic feedback collection | Synthesis of all customer signal into actionable intelligence | | **Product analytics** | Depth and use of usage data | No analytics instrumentation | Real-time anomaly detection with surfaced insight | | **Data flywheel** | Whether data creates a defensible compounding advantage | No data strategy | Proprietary flywheel: usage generates data that improves the product | | **Feedback loop quality** | Whether usage data flows back to improve the product | No feedback mechanism | Real-time signal loop from user to model to product improvement | | **Knowledge management** | How well institutional knowledge is captured, organized, surfaced | No systematic capture | Knowledge captured, organized, and distributed automatically | ### GTM How effectively the team takes products to market and drives adoption. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Positioning and messaging** | Clarity and resonance of market messaging | Generic or feature-based positioning | Outcome-focused positioning with clear differentiation | | **Launch execution** | Consistency and quality of launches | Ad hoc launches with no playbook | Repeatable launch system with pre/post analytics and clear success metrics | | **Adoption and expansion** | How effectively the product drives growth and expansion | No adoption strategy | Onboarding, expansion loops, and retention flywheel | | **Pricing and packaging** | Whether pricing reflects value and supports growth | Traditional seat-based pricing | Usage or outcome-based pricing that scales with value delivered | ### Operations How well the team learns, adapts, and optimizes its own ways of working. | Dimension | What we measure | Score 1 | Score 5 | | - | - | - | - | | **Quality and experimentation** | Rigor of testing, evaluation, and quality processes | Manual QA with no eval pipeline | Automated eval pipelines with continuous quality monitoring | | **Team orchestration** | How the team coordinates work across people and systems | Manual planning with poor visibility | Real-time capacity and dependency tracking | | **Process iteration** | How fast the team improves its own ways of working | Processes are fixed until broken | Continuous process improvement with data-driven retrospectives | | **Cost and token economics** | How the team manages inference and infrastructure costs | No awareness of cost | Active token budget management with cost-per-feature analysis | | **Security and compliance** | How the team manages security and compliance risk | No security practice | Threats detected, vulnerabilities patched, compliance maintained continuously | | **Reliability and resilience** | How features handle failure and maintain availability | No specific monitoring | Failures predicted before they occur and infrastructure adjusted preemptively | ## How dimensions interact Dimensions compound within and across functions. * **Data flywheel + feedback loop quality** = the compounding engine. Strong data feeds strong models, which generate more useful data. * **Architecture and systems + delivery velocity** = the delivery engine. Deep integration enables fast iteration. * **Market intelligence + competitive positioning** = the positioning engine. Clear market read produces defensible differentiation. * **Customer signal synthesis + product analytics** = the intelligence layer. Strong collection plus strong analysis produces actionable read. ## Scoring criteria We score each dimension 1-5 based on observable signal: 1. **Public evidence** - what the product shows, says, and does externally 2. **Technical signals** - architecture patterns, API design, infrastructure choices 3. **Business model signals** - pricing structure, packaging, monetization 4. **Team signals** - job postings, engineering blog, conference talks 5. **Adapter signals** - operational ground truth from connected tools (GitHub, Linear, PostHog) ## Using your scores > **For individual contributors** > > Pick the function most relevant to your role and focus on its 4 dimensions. A PM leans on Strategy and Operations. An engineer leans on Development and Intelligence. Your function score is your primary growth lever. > **For product leaders** > > Use the dimension heatmap across your portfolio to surface systemic weakness. A dimension that scores low across multiple products is an org-level capability gap, not a team problem. Invest in org-wide training and tooling, not individual coaching. > **For founders and executives** > > Compare your Team Operations score against your Lifecycle and Product Assessment scores to surface the biggest tension. A high product score with a low team score means your product has more capability than your team can sustain. That's a scaling risk, not a strength. ## Related > **[Three frameworks](https://docs.dacard.ai/knowledge-base/three-frameworks.md)** > > How the three frameworks fit together. > **[Score your product](https://docs.dacard.ai/knowledge-base/scoring.md)** > > Run an assessment and read your 27-dimension breakdown. > **[Read your report](https://docs.dacard.ai/knowledge-base/ic-understand-report.md)** > > Walk through the maturity report. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.