Lab Intelligence Planning
Guide lab managers and data science teams through designing, building, and governing a portfolio of BI products for clinical laboratories.
Workflows
This skill supports three primary workflows. Determine which applies based on user intent:
| User Intent | Workflow | Key References |
|---|---|---|
| "What should we build?" / "Where are our gaps?" | Discovery | personas.md, portfolio-types.md |
| "Design a dashboard for X" / "What should this report contain?" | Design | personas.md, quality-indicators.md |
| "How do we manage our reports?" / "Should we retire this?" | Governance | governance.md |
Discovery Workflow
Use when assessing current state or identifying what to build.
Step 1: Inventory Current State
Gather information about existing BI products:
- •What reports/dashboards exist today?
- •Who uses each one? How frequently?
- •What systems source the data (LIS, LIMS, EHR, instruments)?
- •What pain points exist (manual processes, data gaps, stale reports)?
Step 2: Map Stakeholder Needs
Load references/personas.md and work through each relevant persona:
- •Which personas are served by current products?
- •Which personas have unmet needs?
- •What decisions does each persona need to make?
Step 3: Identify Portfolio Gaps
Load references/portfolio-types.md and assess coverage:
- •Which archetype categories are well-covered?
- •Which are missing or weak?
- •Are there redundant products serving the same need?
Step 4: Prioritize Opportunities
For each gap identified, assess:
- •Impact: How many personas benefit? How critical are their decisions?
- •Feasibility: Is data available? What integration effort?
- •Urgency: Regulatory deadline? Safety concern? Strategic initiative?
Output a prioritized backlog of BI products to build or improve.
Design Workflow
Use when specifying a new dashboard, report, or data product.
Step 1: Define the Product
Establish scope:
- •Name: Clear, descriptive title
- •Primary persona(s): Who is this for? (Load
references/personas.mdif needed) - •Archetype: Which category? (Load
references/portfolio-types.mdif needed) - •Key questions answered: What decisions will this enable?
Step 2: Specify Content
For each visualization or data element:
- •Metric/measure: What is being shown?
- •Dimensions: How can it be sliced (time, section, instrument, staff)?
- •Comparisons: Targets, benchmarks, prior periods?
- •Drill-down paths: What details should be accessible?
Load references/quality-indicators.md for standard KPIs by lab phase and specialty.
Step 3: Define Interactions
Specify user experience:
- •Filters: What parameters can users control?
- •Refresh frequency: Real-time, hourly, daily, on-demand?
- •Alerts/thresholds: What conditions trigger notifications?
- •Export needs: PDF, Excel, API access?
Step 4: Validate with Stakeholders
Before building:
- •Review specification with primary persona representatives
- •Confirm metrics align with how they actually make decisions
- •Identify any missing context or comparisons
- •Agree on acceptable data latency and accuracy requirements
Governance Workflow
Use when establishing or improving portfolio management practices.
Step 1: Establish Ownership Model
Load references/governance.md for detailed guidance. Key decisions:
- •Product owner: Who approves changes and prioritizes enhancements?
- •Data steward: Who ensures data quality and definitions?
- •Technical owner: Who maintains the implementation?
Step 2: Define Review Cadence
Establish recurring review cycles:
- •Usage review (quarterly): Which products are used? By whom?
- •Quality review (quarterly): Are metrics accurate? Definitions current?
- •Strategic review (annual): Does portfolio align with lab priorities?
Step 3: Set Lifecycle Policies
Define criteria for each lifecycle stage:
- •Promotion: From pilot to production
- •Enhancement: When to invest in improvements
- •Deprecation: When to retire (low usage, superseded, inaccurate)
- •Archival: How long to retain historical access
Step 4: Manage Portfolio Health
Ongoing activities:
- •Track usage metrics for all products
- •Maintain a portfolio registry with ownership and status
- •Conduct rationalization exercises to reduce redundancy
- •Balance self-service enablement with governed core products
Output Formats
Portfolio Assessment Summary
When completing discovery, output:
# Lab Intelligence Portfolio Assessment ## Current State - Total products: [N] - Active/used: [N] - Orphaned/unused: [N] ## Coverage by Archetype | Category | Products | Gaps | |----------|----------|------| | Operational | ... | ... | | Quality/Compliance | ... | ... | | Financial | ... | ... | | Clinical Decision Support | ... | ... | | Strategic | ... | ... | ## Coverage by Persona [Table showing which personas are well-served vs. underserved] ## Recommended Priorities 1. [Priority 1 with rationale] 2. [Priority 2 with rationale] 3. [Priority 3 with rationale]
Product Specification
When completing design, output:
# [Product Name] Specification ## Overview - **Archetype**: [Category] - **Primary personas**: [List] - **Key questions answered**: [List] - **Refresh frequency**: [Frequency] ## Content Specification | Element | Metric | Dimensions | Target/Benchmark | |---------|--------|------------|------------------| | ... | ... | ... | ... | ## Interactions - **Filters**: [List] - **Drill-downs**: [List] - **Alerts**: [Conditions and recipients] ## Data Requirements - **Sources**: [Systems] - **Latency**: [Acceptable delay] - **Quality requirements**: [Accuracy, completeness] ## Governance - **Product owner**: [Role] - **Review cycle**: [Frequency]
Reference Files
Load these as needed based on the workflow:
- •
references/personas.md- Detailed stakeholder needs by role - •
references/portfolio-types.md- Dashboard/report archetypes with examples - •
references/governance.md- Lifecycle management, ownership, review practices - •
references/quality-indicators.md- Standard KPIs by lab phase and specialty