# Analyzing Digital Infrastructure Assets > Evaluates data centers, fiber networks, and tower assets with capacity analysis, tenant credit, and technology obsolescence risk. Use when analyzing digital infrastructure, evaluating tower portfolios, or assessing data center investments. - Skill: `lev-os/analyzing-digital-infrastructure-assets` (Agent Skill) - Install (CLI): `npx skillmds@latest add lev-os/analyzing-digital-infrastructure-assets` - Raw SKILL.md: https://api.skillmd.com/api/skills/lev-os/analyzing-digital-infrastructure-assets/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: lev-os (https://skillmd.com/u/lev-os) - Updated: 2026-09-10 - Page: https://skillmd.com/skills/lev-os/analyzing-digital-infrastructure-assets --- # Analyzing Digital Infrastructure Assets ## When To Use - Evaluating a data center acquisition or development financing (single-site or portfolio) - Analyzing a wireless tower portfolio for purchase, sale, or lease-up valuation - Assessing fiber network assets (lit or dark fiber) for infrastructure fund deployment - Conducting due diligence on colocation, hyperscale, or edge data center investments - Reviewing digital infrastructure assets within a broader PPP or project finance structure ## Inputs To Gather - **Asset inventory**: Site addresses, facility types (tower/data center/fiber route), owned vs. leased land, build year, and remaining useful life estimates - **Capacity and utilization data**: Total MW/rack capacity vs. current load (data centers), available tenancy slots vs. occupied (towers), lit vs. dark fiber strand counts - **Tenant and revenue detail**: Tenant roster with contract terms, escalation schedules, renewal options, and credit ratings; revenue concentration by tenant - **Capital expenditure history and projections**: Maintenance capex, expansion capex, technology refresh cycles, and deferred maintenance backlog - **Operating metrics**: Power Usage Effectiveness (PUE) for data centers, average revenue per tower (ARPT), fiber route miles and density metrics - **Regulatory and permitting status**: Zoning, FCC/FAA compliance (towers), local power and water entitlements (data centers), right-of-way agreements (fiber) [VERIFY jurisdiction-specific requirements] - **Debt and financing terms**: Existing securitization structures (e.g., tower ABS), project-level debt covenants, DSCR requirements ## Workflow 1. **Classify asset type and scope** — Determine whether the analysis covers towers, data centers, fiber, or a mixed portfolio. Identify the investment thesis (yield play, growth/lease-up, development) as this drives which metrics matter most. 2. **Analyze physical capacity and utilization** - Data centers: Calculate current vs. total MW capacity, rack density, cooling headroom, and PUE trends. Flag facilities above 85% utilization as capacity-constrained. - Towers: Count tenancy ratio (tenants per tower), identify co-location capacity remaining, and assess ground space for additional equipment. - Fiber: Map lit vs. dark strand utilization, route redundancy, and proximity to demand anchors (enterprise campuses, wireless towers, data centers). 3. **Evaluate tenant credit and revenue quality** - Build a tenant concentration table: top 5 tenants by revenue share, weighted-average remaining lease term (WALT), and credit ratings. - Flag single-tenant concentration above 25% of revenue or any tenant below investment-grade credit. - Assess contractual escalators (CPI-linked vs. fixed) and mark-to-market opportunity on below-market leases. 4. **Assess technology obsolescence risk** - Towers: Evaluate 5G densification impact — will small-cell deployments reduce macro tower demand, or drive amendment revenue? Assess carrier consolidation risk. [VERIFY current carrier M&A landscape] - Data centers: Review power and cooling architecture against current hyperscaler requirements. Facilities built pre-2015 with air-cooled designs may require significant retrofit for AI/ML workload density. - Fiber: Assess whether existing fiber plant supports current wavelength standards; evaluate competitive overbuild risk in the service area. 5. **Model cash flows and valuation** - Build a 10-year discounted cash flow with explicit assumptions for: tenant churn, new lease-up pace, escalators, capex, and terminal value. - Apply sector-appropriate cap rates: towers (low-to-mid single digits), data centers (mid-single digits, varies by tier), fiber (varies by lit vs. dark economics). [VERIFY current market cap rates] - Stress-test for: 20% tenant churn scenario, power cost escalation (data centers), interest rate sensitivity on leveraged returns. 6. **Identify structural and regulatory risks** - Review ground lease terms for towers (remaining term, renewal risk, rent escalation). - Assess power and water availability and long-term pricing for data centers, especially in constrained markets. - Evaluate right-of-way renewal risk and municipal franchise requirements for fiber. [VERIFY local franchise/ROW renewal terms] ## Output Structure the analysis report with the following sections: - **Executive Summary**: Asset type, investment thesis, headline valuation range, and top 3 risks - **Asset Overview**: Inventory table with key physical attributes and geographic distribution - **Capacity and Utilization Analysis**: Current utilization, expansion runway, and capacity constraints - **Tenant and Revenue Analysis**: Concentration table, WALT, credit quality summary, and escalator profile - **Technology Obsolescence Assessment**: Risk rating (low/medium/high) per asset class with supporting rationale - **Financial Model Summary**: Base case IRR/MOIC, key assumptions table, and sensitivity analysis output - **Risk Matrix**: Ranked risks with likelihood, impact, and proposed mitigants - **Appendix**: Detailed assumptions, data sources, and items marked [VERIFY] ## Quality Checks - Confirm that utilization metrics are sourced from operator-provided data, not estimates; flag any interpolated figures - Verify that tenant credit ratings are current (within 12 months) and sourced from recognized agencies - Ensure cap rates and discount rates reflect the specific asset sub-type, not generic "digital infrastructure" benchmarks - Check that technology obsolescence assessment references specific technical standards (e.g., power density per rack in kW, fiber wavelength capacity) rather than vague trend commentary - Validate that the DCF model ties to the tenant-by-tenant revenue build-up, not a top-down growth assumption - Confirm all jurisdiction-dependent items (zoning, FCC/FAA, ROW, franchise) are marked [VERIFY] with the relevant authority identified