casemark/analyzing-industrial-properties

Analyzing Industrial Properties

Structures industrial real estate analysis combining physical property evaluation, logistics market assessment, tenant credit analysis, and investment return modeling for warehouse, distribution, manufacturing, and flex-industrial assets.

When To Use

• Underwriting an acquisition or disposition of an industrial property
• Evaluating a warehouse or distribution center for REIT portfolio inclusion
• Assessing tenant creditworthiness and lease structure on industrial assets
• Comparing competing industrial investments across submarkets
• Reviewing logistics demand drivers for a target market or corridor

Inputs To Gather

• Property details: Address, building SF, clear height, dock doors (count and type), column spacing, truck court depth, trailer parking count, office finish ratio, year built/renovated
• Site data: Lot size, land-to-building ratio, expansion potential, rail access, proximity to interstate/port/airport (miles), zoning classification [VERIFY]
• Lease schedule: Tenant names, lease start/expiration, base rent per SF, annual escalations, renewal options, termination rights, TI allowances, free rent concessions
• Tenant credit: Credit ratings (Moody's/S&P), annual revenue, D&B scores, parent guaranty status, industry sector and concentration risk
• Financials: Trailing 12-month NOI, operating expense breakdown (CAM, insurance, taxes, management), capex reserves, historical occupancy (3–5 years)
• Market data: Submarket vacancy rate, net absorption (trailing 4 quarters), construction pipeline (SF under construction and planned), market rent per SF by product type, cap rate comps

Workflow

1. Classify the asset

   • Determine product type: bulk distribution, last-mile delivery, light manufacturing, cold storage, flex-industrial, data center shell
   • Note functional obsolescence indicators: clear height below 28', insufficient dock ratio (< 1 per 10,000 SF for bulk), narrow truck courts (< 130'), inadequate power [VERIFY against current submarket standards]

2. Evaluate physical and locational attributes

   • Score access to transportation infrastructure (interstate interchange distance, intermodal rail, port proximity)
   • Assess labor pool depth using MSA employment data and wage levels for warehouse/logistics roles
   • Identify last-mile relevance by mapping population density within 1-hour drive radius
   • Flag environmental concerns: Phase I/II ESA findings, flood zone designation, brownfield history [VERIFY]

3. Analyze the lease structure and tenant credit

   • Calculate weighted-average lease term (WALT) by rent and by SF
   • Map lease rollover schedule and quantify near-term rollover risk (leases expiring within 24 months)
   • Evaluate rent-to-market spread: in-place rent vs. submarket asking rent per SF
   • Assess tenant credit: investment-grade vs. non-rated, single-tenant concentration risk, industry cyclicality
   • Review expense structure: NNN vs. modified gross, landlord exposure to operating cost increases

4. Model investment returns

   • Build a stabilized NOI pro forma with market-supported assumptions for vacancy, credit loss, opex, and capex reserves
   • Calculate going-in cap rate and compare against trailing 4-quarter submarket comps
   • Run a discounted cash flow (DCF) over a 5–10 year hold period with explicit assumptions for rent growth, renewal probability, downtime, re-leasing costs, and exit cap rate
   • Compute levered and unlevered IRR, equity multiple, cash-on-cash yield, and net present value
   • Sensitivity-test key variables: exit cap rate (+/- 50 bps), vacancy (+/- 500 bps), rent growth (+/- 100 bps)

5. Assess logistics market fundamentals

   • Quantify net absorption trend relative to new supply pipeline
   • Identify demand drivers: e-commerce penetration, 3PL expansion, nearshoring/reshoring activity, cold chain growth
   • Evaluate supply constraints: land availability, entitlement timelines, construction costs per SF [VERIFY local jurisdiction]
   • Compare submarket metrics to broader MSA and national industrial benchmarks

6. Synthesize risk factors and investment thesis

   • Rank risks: tenant credit, lease rollover, functional obsolescence, market oversupply, environmental liability, interest rate sensitivity
   • Identify value-add opportunities: mark-to-market rent upside, expansion potential, operational improvements
   • State a clear investment recommendation with supporting rationale and key assumptions

Output

• Executive summary: One-page investment overview with property description, key metrics (NOI, cap rate, WALT, occupancy), and recommendation
• Property profile: Physical attributes, site plan summary, and locational scoring
• Tenant and lease analysis: Rent roll summary, rollover schedule, WALT, credit assessment table
• Financial pro forma: Stabilized NOI, DCF model outputs (IRR, equity multiple, cash-on-cash), sensitivity tables
• Market overview: Submarket vacancy, absorption, supply pipeline, rent trend, and demand driver commentary
• Risk matrix: Ranked risk factors with probability/impact assessment and mitigants

Quality Checks

• Confirm all rent, vacancy, and cap rate assumptions are sourced and dated — flag stale data (> 6 months) with [VERIFY]
• Validate that NOI reconciles from the rent roll through to the DCF; check that opex and capex assumptions align with historical actuals
• Ensure WALT and rollover calculations match the lease schedule exactly
• Cross-check tenant credit ratings against the most recent available reports
• Verify that submarket boundaries used in comps are consistent across all sections
• Confirm clear height, dock count, and column spacing against building plans or inspection reports — do not rely solely on marketing materials
• Flag any single-tenant or single-industry concentration exceeding 40% of gross revenue as elevated risk