Product Portfolio Framework
Draft v0.2
Purpose
The Product Portfolio Framework defines how research products are conceived, evaluated, developed, governed, maintained, expanded, and retired.
Its purpose is to ensure that product development remains aligned with the institution’s mission, research philosophy, operating model, and available resources.
Products are viewed as tools for observing specific aspects of economic reality. Products may evolve over time, but the institution’s domains, methodologies, governance standards, and historical record remain the foundation upon which all products are built.
Foundational Principle
Domains Are Permanent. Products Are Temporary.
The institution organizes research around enduring behavioral domains:
- Household Activity
- Business Activity
- Government Activity
- Financial Activity
- Labor Activity
These domains represent long-term areas of inquiry.
Research products exist to observe and measure specific phenomena within those domains.
Products may be:
- Created
- Expanded
- Modified
- Merged
- Retired
without altering the institution’s broader research framework.
The institution should never become dependent upon any single product.
Portfolio Architecture
Layer 1 — Institution
Defines:
- Organizational Philosophy
- Research Principles
- Governance Standards
- Methodology Standards
Layer 2 — Research Domains
Permanent areas of inquiry:
- Household Activity
- Business Activity
- Government Activity
- Financial Activity
- Labor Activity
Domains define what is studied.
Layer 3 — Research Programs
Programs represent broad investigative themes within a domain.
Examples:
Household Activity
- Luxury Consumption
- Housing Activity
- Durable Goods Activity
Business Activity
- Fleet Activity
- Freight Activity
- Capital Expenditure Activity
Programs define areas of ongoing inquiry.
Layer 4 — Research Products
Products operationalize research programs.
Examples:
Luxury Consumption Program
- LISI (Luxury Lot Inventory Index)
Fleet Activity Program
- Commercial Mobility Monitor
Fiscal Flow Program
- Fiscal Flow Monitor
Products generate observable measurements.
Product Classification
Products are classified according to maturity and institutional importance.
Category A — Core Indicators
Primary institutional measurements.
Characteristics:
- High maintenance priority
- Fully documented
- Publicly referenced
- Long-term commitment
- Continuously validated
Examples:
- LISI
Category B — Supporting Indicators
Indicators that support interpretation of Core Indicators.
Characteristics:
- Moderate maintenance priority
- Domain-specific
- Supporting analytical role
- Methodology documented
These indicators may not be publicly promoted; however, their methodologies and their role in supporting Core Indicators should be documented.
Category C — Experimental Products
Products undergoing active research, testing, and validation.
Characteristics:
- Subject to significant revision
- Not institutional benchmarks
- Validation in progress
- Limited audience distribution
Publication may be restricted to authenticated research environments where products can be reviewed, challenged, stress-tested, and improved before broader release.
Category D — Archived Products
Retired products preserved for historical reference.
Characteristics:
- Frozen methodology
- No active maintenance
- Archived permanently
- Historical record preserved
Product Admission Criteria
A new product should satisfy the following criteria before entering active development.
Research Relevance
The product addresses a meaningful question within an established research domain.
Observable Data
The underlying phenomenon can be measured using reasonably reliable and observable data.
Methodological Defensibility
A transparent methodology can be documented and explained.
Testability
The product’s outputs should be evaluable against external evidence.
Conditions under which the product’s signals would be considered uninformative, invalidated, or in need of revision should be identifiable and documented.
Sustainability
The underlying data acquisition, cleaning, validation, and publication processes should be highly automatable.
Products requiring continuous manual intervention should generally not be admitted unless their research value clearly justifies the operational burden.
Distinct Contribution
The product contributes information not already captured by existing products.
Product Lifecycle Governance
Products follow the lifecycle defined in the Research Platform Operating Model.
Data Acquisition ↓ Observation ↓ Exploration ↓ Prototype ↓ Validation ↓ Publication ↓ Maintenance ↓ Retirement
No product should bypass validation.
Product Evaluation Framework
Products should be evaluated periodically against the following criteria.
Data Integrity
Are source datasets stable, reliable, and observable?
Methodological Integrity
Does the methodology remain transparent, defensible, and reproducible?
Validation Record
Has the product demonstrated usefulness through documented relationships with external indicators, historical events, or validation case studies?
Validation outcomes should be preserved within the institutional archive.
Signal Purity
Have policy interventions, tax incentives, regulatory changes, market structure changes, or other external distortions materially altered the behavior being measured?
Products should be periodically reviewed for distortions that compromise comparability across time.
Research Utility
Does the product continue to provide meaningful analytical value?
Operational Sustainability
Can the product be maintained responsibly using available resources?
Audience Utility
Do users find the product useful, understandable, and relevant?
Cross-Domain Analysis
The institution views the portfolio as an interconnected research system rather than a collection of independent indicators.
Relationships among products may provide information that is not observable within any individual product.
Particular attention should be paid to:
- Convergences
- Divergences
- Lead-lag relationships
- Reinforcing signals
- Contradictory signals
Contradictions are not considered failures.
They are considered research opportunities.
Periodic cross-domain reviews should evaluate interactions among active products and identify emerging areas for investigation.
Cross-domain analysis constitutes a distinct research activity separate from individual product evaluation.
Product Expansion Rules
Expansion should occur only after existing products are stable.
Preferred sequence:
Maintain Existing Products ↓ Improve Existing Products ↓ Expand Existing Domains ↓ Create New Products
Expansion should not compromise maintenance.
Portfolio Capacity Limits
The institution should maintain a portfolio size consistent with available resources.
Before admitting a new Core Indicator, the institution should evaluate whether existing products can continue to meet maintenance, validation, documentation, and governance standards.
Expansion should not create maintenance debt.
Product Retirement Governance
Retirement is a normal part of portfolio management.
A product may be retired due to:
- Structural degradation of underlying data sources
- Irreconcilable changes in the observed environment
- Methodological invalidation
- Failure to satisfy ongoing validation standards
- Resource constraints preventing responsible maintenance
- Emergence of superior methodologies
Retired products are frozen, documented, and preserved within the institutional archive.
Products are retired; they are not erased.
Portfolio Balance
A healthy portfolio maintains balance among:
Stability
Established products with demonstrated value.
Improvement
Existing products undergoing refinement.
Exploration
New concepts undergoing investigation.
Over-concentration in any category introduces institutional risk.
Resource Allocation
Given finite resources:
Core Products ↓ Supporting Products ↓ Experimental Products
Maintenance takes precedence over expansion.
Quality takes precedence over quantity.
Measures of Portfolio Success
A healthy portfolio demonstrates:
- Alignment with research domains
- High data integrity
- Transparent methodologies
- Strong validation records
- Sustainable maintenance
- Useful outputs
- Historical accountability
- Product interoperability
- Continuous learning
The objective is not to maximize the number of products.
The objective is to build a coherent portfolio of durable research assets that improve understanding across multiple domains of economic behavior.