Building Portfolio Energy and EPD Analysis
Analyzes building and product portfolio data to report EPD usage across organizations and subsidiaries and to screen affordable housing projects for healthy, efficient, affordable, and certification-ready design outcomes.
The Problem
“Portfolio-scale analysis of EPD usage and affordable housing design performance”
Organizations face these key challenges:
EPD usage data is fragmented across subsidiaries and reporting systems
Organization, product, and project naming is inconsistent
Manual reporting is slow and error-prone
Affordable housing screening requires balancing multiple competing criteria
Impact When Solved
The Shift
Human Does
- •Export EPD, product, project, and subsidiary data from separate sources
- •Normalize organization, product, and project names across records
- •Aggregate EPD usage and prepare portfolio reports manually
- •Review affordable housing projects against scorecards and certification checklists
Automation
- •No significant AI-driven tasks in the legacy workflow
Human Does
- •Set portfolio reporting priorities and screening criteria
- •Review flagged data mismatches and scoring exceptions
- •Approve recommendations for project actions or product strategy
AI Handles
- •Extract and normalize EPD, product, organization, and project attributes from mixed inputs
- •Monitor portfolio usage across organizations and subsidiaries and refresh KPI reporting
- •Score affordable housing projects for health, efficiency, affordability, and certification readiness
- •Generate recommendations, trend summaries, and narrative portfolio reports
Operating Intelligence
How it works
AI runs the first three steps autonomously.
Humans own every decision.
The system gets smarter each cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Assemble Context
Step 2
Analyze
Step 3
Recommend
Step 4
Human Decision
Step 5
Execute
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI handles assembly, analysis, and execution. The human gate sits at the decision point. Every cycle refines future recommendations.
The Loop
6 steps
Assemble Context
Combine the relevant records, signals, and constraints.
Analyze
Evaluate options, risk, and likely outcomes.
Recommend
Present a ranked recommendation with supporting rationale.
Human Decision
A human accepts, edits, or rejects the recommendation.
Authority gates · 1
The system must not finalize certification-readiness decisions without review and sign-off from a responsible human reviewer [S1].
Why this step is human
The decision carries real-world consequences that require professional judgment and accountability.
Execute
Carry out the approved action in the operating workflow.
Feedback
Outcome data improves future recommendations.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Building Portfolio Energy and EPD Analysis implementations:
Key Players
Companies actively working on Building Portfolio Energy and EPD Analysis solutions:
Real-World Use Cases
Automated digital EPD usage statistics reporting by organization and subsidiary
EC3 can email a company a summary of how many valid digital EPDs it has, how many product categories those EPDs appear in, and how often people opened them recently.
Affordable housing portfolio screening for healthy and efficient design outcomes
An AI tool could help affordable housing teams compare projects, flag likely health/efficiency issues, and prioritize which designs are most likely to meet program goals.