## PART XV - SECTOR PLAYBOOKS | MODULE 074 # Cloud and Data Centers Analyst Playbook > Mission. Build a sector-specific research system for Cloud and Data Centers that converts operating data into financial outcomes, highlights the accounting areas most likely to distort comparability, and selects valuation methods that reflect the sector's economics. ## Economic engine and binding constraints Model commissioned MW, booked MW, utilization, power availability, PUE, lease pricing, construction cost, time to energization, and financing. Power interconnection and equipment lead times are often the binding growth constraints. ## Primary KPI stack | KPI | Construction / analyst control | | --- | --- | | MW commissioned | Data-center critical IT megawatts placed in service and available for customer load during the period. Validation: Tie physical/operating units to company disclosures or source-system data; reconcile beginning/ending populations where applicable and test scope, ownership, and period consistency. | | MW under construction | Critical IT megawatts in active construction with committed capital and defined expected delivery dates; separate owned and partner capacity. Validation: Tie physical/operating units to company disclosures or source-system data; reconcile beginning/ending populations where applicable and test scope, ownership, and period consistency. | | booked MW | Critical IT megawatts covered by signed customer commitments or leases, whether operating or under construction; disclose commencement timing. Validation: Tie physical/operating units to company disclosures or source-system data; reconcile beginning/ending populations where applicable and test scope, ownership, and period consistency. | | utilization | Actual productive output or occupied capacity divided by practical available capacity after planned downtime, yield loss, and maintenance constraints. Validation: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. | | power cost | Electricity expense divided by kWh consumed, or contracted all-in $/MWh including delivery/hedge effects where relevant. Validation: Recalculate price/cost from underlying dollars and physical units; test mix, rebates, FX, timing, and unit-definition effects; reconcile to reported revenue or expense. | | revenue per MW | Annualized data-center revenue divided by average commissioned or occupied critical IT MW, using a consistent occupancy basis. Validation: Recalculate price/cost from underlying dollars and physical units; test mix, rebates, FX, timing, and unit-definition effects; reconcile to reported revenue or expense. | | PUE | Total facility energy consumed divided by IT equipment energy consumed; lower values indicate less non-IT overhead. Validation: Recalculate from same-scope numerator and denominator; confirm period, units, cohort/geography, and issuer definition; reconcile material differences to filings or operating data. | | backlog | Contracted or awarded revenue not yet recognized, using the issuer's disclosed backlog definition and separating cancellable/undedicated amounts when possible. Validation: Reconcile beginning balance + additions - revenue/shipments - cancellations/adjustments to ending balance where data allow; verify cancellation rights, timing, and definition changes. | ## Sector-specific accounting and comparability traps - Lease accounting: reconcile issuer treatment with peer treatment and quantify the effect on reported growth, margin, cash flow, capital, or valuation before comparing outputs. - Capitalized interest: reconcile issuer treatment with peer treatment and quantify the effect on reported growth, margin, cash flow, capital, or valuation before comparing outputs. - Construction-in-progress: reconcile issuer treatment with peer treatment and quantify the effect on reported growth, margin, cash flow, capital, or valuation before comparing outputs. - Joint ventures: reconcile issuer treatment with peer treatment and quantify the effect on reported growth, margin, cash flow, capital, or valuation before comparing outputs. - Power commitments: reconcile issuer treatment with peer treatment and quantify the effect on reported growth, margin, cash flow, capital, or valuation before comparing outputs. ## Valuation frameworks - EV/EBITDA: enterprise value divided by normalized EBITDA; adjust leases, pensions, minorities, recurring restructuring and capital intensity before peer comparison. - EV/MW: enterprise value divided by owned/contracted operating MW, adjusted for development stage, technology, duration, capacity factor, PPAs, debt, and project economics. - AFFO: start with FFO and deduct recurring capital expenditures and economically recurring adjustments; use a clearly defined issuer-independent AFFO before applying a multiple. - DCF: forecast FCFF from operating drivers, discount at a capital-structure-consistent WACC, model terminal growth/ROIC coherently, and bridge enterprise value to common equity. ## Sector diligence questions - What is the most important leading indicator for Cloud and Data Centers, and how many months does it lead reported revenue or cash flow? ## Sector stress and falsification - Stress MW commissioned and MW under construction together in the direction most likely to break the equity story; flow the result through working capital, capex, liquidity, financing, dilution, and valuation. - Explicitly test lease accounting. Determine whether it can make the reported sector comparison look better or worse without equivalent economic change. ## 99-point standalone execution extension ### Model architecture and forecast chain Model commissioned MW, booked MW, utilization, revenue per MW or rack, power cost, PUE, land, interconnection, construction cost, and lease duration. Separate powered shell, wholesale, colocation, and cloud service economics. ### Leading-indicator dashboard Track utility interconnection queues, transformer/switchgear lead times, land and power contracts, preleasing, customer capex, construction starts, financing spreads, and regional power prices. ### Primary-source map SEC filings and REIT/developer supplements; EIA and utility tariffs; ISO/RTO interconnection queues; local permitting/land records; hyperscaler capex and lease disclosures. ### Accounting normalization test Backlog can include long-dated options; construction in progress, capitalized interest, leases, and development JV accounting can flatter near-term operating metrics. ### Valuation implementation Use project-level DCF/NAV plus corporate valuation. Cap rates and EV/EBITDA need normalization for development pipeline and capital intensity. ### Worked numerical mini-case > Illustrative MW economics. A 100 MW campus is 80% leased at $185/kW-month. Annualized gross revenue = 100,000 kW x 80% x $185 x 12 = $177.6m. If delivered project cost is $10m/MW, test unlevered yield against financing cost and required return. Do not value booked MW as operating MW. Model energization, lease commencement, tenant improvements and power availability. ### Monitoring and falsification cadence Thesis breaks include power unavailable on schedule, customer concentration, overbuilding in a region, financing cost exceeding project returns, or technology reducing space/power demand per workload. At every quarterly update, rebuild the driver bridge from operating units to revenue, margin, cash flow and valuation; compare leading indicators with the prior forecast; record definition changes; and precommit the threshold that would trigger a thesis reset rather than a cosmetic estimate change. ## Sector exit standard The Cloud and Data Centers work is complete only when the analyst can explain the business in its native operating units, reproduce the KPI history, identify the binding growth constraint and marginal price setter, normalize sector-specific accounting, quantify a coherent adverse case, and translate the current market price into the operating expectations that must be met or exceeded.