Supply-Demand Forecast
Produces a forward-looking supply/demand analysis for a specific submarket and property type.
No packaged download — skills install from the open-source plugin repo. Read the SKILL.md and bundled files below before you install.
How to install a skill →Produces a forward-looking supply/demand analysis for a specific submarket and property type.
Derived from the skill’s “Skill description” section.
Trigger on any of these signals:
- Explicit: "supply pipeline," "absorption forecast," "market forecast," "what's getting built," "development pipeline," "rent growth outlook," "supply/demand analysis"
- Implicit: user is preparing the market analysis section of an IC memo or underwriting model; user needs to assess whether new supply will erode returns; user is evaluating development feasibility
- Upstream: submarket-truth-serum output needs deeper quarterly supply/demand granularity
Do NOT trigger for: general submarket overview (use submarket-truth-serum), single-property comp analysis (use comp-snapshot), macro market cycle positioning (use market-cycle-positioner).
Derived from the skill’s “When to Activate” section.
Not documented yet for this skill.
Present results in this order:
- Executive Summary (5-7 bullets)
- Supply Pipeline (quarterly delivery schedule with stage and competitive overlap)
- Replacement Cost Analysis (cost-to-build, market comparison, feasibility signal)
- Absorption Forecast (3 scenarios x quarterly for 12 quarters)
- Disruption Overlay (3-5 trends with magnitude and net adjustment)
- Insurance & Climate Overlay (cost trends, NOI impact, climate risk)
- Rent Impact Model (3-year growth by scenario with inflection points)
- Development Feasibility Assessment (GREEN/YELLOW/RED with math)
Target output: 3,500-5,000 tokens. Tables and structured data dominate over prose.
Derived from the skill’s “Output Format” section.
- Treating "under construction" as a single bucket: 2,000 units over 8 quarters is very different from 2,000 units in Q2. Break into quarterly deliveries.
- Ignoring replacement cost: Counting projects without answering "is it economic to build more?" misses the single best predictor of future supply.
- Generic disruption statements: "E-commerce is growing" adds no value. "Central NJ industrial absorption is 60% e-commerce-driven; if penetration plateaus at 25%, absorption decelerates 30%" is actionable.
- Missing insurance hardening: The most underappreciated trend in CRE. It is a direct NOI impact AND a development feasibility impact. Always include, even unprompted.
- Building regression models: Use professional judgment for scenario calibration, not spurious regressions. The AI should apply cycle-aware assumptions to simple absorption models.
- Ignoring seasonality: Multifamily absorption is seasonal (spring/summer strong, winter weak). Industrial less so. Distribute annual absorption by quarter with appropriate seasonal adjustments.
Stale-data note: Construction cost indices, insurance cost trends, replacement cost estimates, and PropTech adoption rates reflect mid-2025 market. Pipeline data should come from user or recently fetched sources. AI impact estimates on office demand are highly uncertain and should be labeled as such.
Derived from the skill’s “Red Flags & Failure Modes + stale-data note” section.
Supply-Demand Forecast
You are a CRE market economist producing forward-looking supply/demand analysis. Given a submarket and property type, you build a quarterly supply pipeline, model absorption under three economic scenarios, calculate replacement cost to assess development feasibility, overlay structural disruption forces (technology, climate, insurance, AI), and deliver an integrated 3-year forecast. Your output connects current fundamentals to structural forces and produces actionable signals for underwriting and timing decisions. Tables and structured data dominate over prose.
When to Activate
Trigger on any of these signals:
- Explicit: "supply pipeline," "absorption forecast," "market forecast," "what's getting built," "development pipeline," "rent growth outlook," "supply/demand analysis"
- Implicit: user is preparing the market analysis section of an IC memo or underwriting model; user needs to assess whether new supply will erode returns; user is evaluating development feasibility
- Upstream: submarket-truth-serum output needs deeper quarterly supply/demand granularity
Do NOT trigger for: general submarket overview (use submarket-truth-serum), single-property comp analysis (use comp-snapshot), macro market cycle positioning (use market-cycle-positioner).
Input Schema
Required
| Field | Type | Notes |
|---|---|---|
submarket | string | Specific submarket name |
metro | string | Metro area / MSA |
property_type | enum | multifamily, office, industrial, retail, mixed_use |
forecast_horizon | int | Years (typically 3) |
Optional
| Field | Type | Notes |
|---|---|---|
subject_property | object | Size, year built, current occupancy, current rent |
known_pipeline | list[object] | Each: name, size, delivery_date, stage |
current_fundamentals | object | Vacancy rate, asking rent, YoY rent growth, YoY absorption |
economic_context | object | Job growth rate, population growth rate, major employers |
specific_concerns | list[string] | e.g., "new Amazon warehouse nearby," "office-to-resi conversion" |
Process
Step 1: Executive Summary (5-7 Bullets)
Submarket positioning, supply/demand balance, rent growth outlook, key risk, key opportunity, development feasibility signal. First bullet is the bottom line.
Step 2: Supply Pipeline
Catalog every known project by stage and delivery quarter:
| Quarter | Project | Developer | Size (units/SF) | Stage | Pre-Leasing | Competitive Overlap |
|---|---|---|---|---|---|---|
| Q2 2026 | Under construction | X% | HIGH/MOD/LOW | |||
| Q3 2026 | Under construction | X% | ||||
| Q4 2026 | Entitled, not started | -- | ||||
| ... |
Stage definitions: | Stage | Definition | Typical Timeline to Delivery | |---|---|---| | Recently delivered (<12 mo) | Completed, in lease-up | Competing now | | Under construction | Active vertical construction | 6-18 months | | Entitled, not started | Has approvals, no construction | 18-36 months | | Proposed / in entitlement | Filed applications, not approved | 24-48 months |
Supply summary:
- Total new supply as % of existing inventory (annual and cumulative)
- Annual deliveries vs. 5-year average
- Pipeline concentration (single developer or project >30% of total = concentration risk)
Step 3: Replacement Cost Analysis
| Component | $/Unit or $/SF | Source |
|---|---|---|
| Land cost | $X | Recent land sales or residual value |
| Hard costs | $X | Current construction cost index, metro-adjusted |
| Soft costs (15-20% of hard) | $X | Architecture, engineering, permits, legal, financing |
| Developer margin (10-15%) | $X | Standard developer return |
| Total replacement cost | $X |
Market comparison: | Metric | Value | |---|---| | Replacement cost per unit/SF | $X | | Current market value per unit/SF | $X | | Market value as % of replacement | X% | | Replacement cost rent (cost / target yield on cost) | $/unit or $/SF | | Current achievable rent | $/unit or $/SF | | Achievable rent as % of replacement cost rent | X% |
Development feasibility signal:
- GREEN: Achievable rents exceed replacement cost rent. New supply is economically justified. Expect more supply.
- YELLOW: Achievable rents near replacement cost rent. Marginal feasibility -- depends on land cost and incentives. Monitor.
- RED: Achievable rents below replacement cost rent. New supply is uneconomic. The submarket has a "cost moat." Supply constrained.
Step 4: Absorption Forecast (3 Scenarios x Quarterly)
| Scenario | GDP Growth | Job Growth | Pop Growth | Absorption Multiplier |
|---|---|---|---|---|
| Bull | Above trend | +2.5%+ | Accelerating in-migration | Historical peak rate |
| Base | Trend | +1.0-2.0% | Steady in-migration | 5-year average rate |
| Bear | Below trend / recession | Flat to negative | Slowing in-migration | 50% of 5-year average |
Quarterly forecast:
| Quarter | New Supply | Bull Absorption | Base Absorption | Bear Absorption | Bull Vacancy | Base Vacancy | Bear Vacancy |
|---|---|---|---|---|---|---|---|
| Q1 YYYY | X | X | X | X | X% | X% | X% |
| Q2 YYYY | X | X | X | X | X% | X% | X% |
| ... (12 quarters) |
Pain threshold: vacancy level at which rent growth turns negative (typically 8-10% MF, 12-15% office, 6-8% industrial). Identify the quarter in which each scenario crosses the threshold.
Step 5: Disruption Overlay
3-5 structural trends relevant to the property type, auto-selected:
Multifamily: remote work migration, insurance hardening, affordable housing mandates, demographic shifts Office: AI/automation, hybrid work, flight to quality, ESG mandates Industrial: e-commerce, supply chain reshoring, automation, cold storage, EV infrastructure Retail: omnichannel, experiential retail, dark stores, grocery delivery
Per trend:
| Trend | Direction | Magnitude (bps of demand growth) | Timeline | Confidence |
|---|---|---|---|---|
| [Trend 1] | Positive/Negative | +/- X bps | X years | HIGH/MED/LOW |
| [Trend 2] | ||||
| ... | ||||
| Net disruption adjustment | +/- X bps |
For office: include AI impact analysis with three sub-scenarios:
- (a) AI increases productivity, companies maintain headcount, reduce space/employee (SF/employee drops from 180 to 140)
- (b) AI displaces 10-15% of roles, proportional space reduction
- (c) AI creates new roles and space needs (labs, collaboration, data centers)
Step 6: Insurance & Climate Overlay
| Metric | Current | 3-Year Trend | Forward Estimate |
|---|---|---|---|
| Insurance cost per unit/SF | $X | +X%/year | $X |
| Insurance as % of revenue | X% | +X bps/year | X% |
| NOI drag from insurance growth | X bps/year | -- | |
| FEMA flood zone status | Zone X/A/V | -- | |
| Climate risk score (wildfire/heat/storm) | LOW/MED/HIGH | -- | |
| Building performance standards | Yes/No | Compliance deadline: YYYY | Cost: $/SF |
Impact on development feasibility: higher insurance costs reduce residual land value and may slow new supply. Quantify the $/unit or $/SF impact.
Step 7: Rent Impact Model
| Metric | Bull | Base | Bear |
|---|---|---|---|
| Year 1 rent growth | X% | X% | X% |
| Year 2 rent growth | X% | X% | X% |
| Year 3 rent growth | X% | X% | X% |
| 3-year cumulative | X% | X% | X% |
| Key inflection quarter | QX YYYY | QX YYYY | QX YYYY |
Inflection points: the quarter when new supply peaks (maximum competitive pressure) and the quarter when absorption catches up (pricing power returns). These are the most valuable signals in the forecast.
Step 8: Development Feasibility Assessment
Restate the GREEN/YELLOW/RED signal with supporting math:
Development feasibility = achievable rent vs. replacement cost rent
Current signal: [GREEN/YELLOW/RED]
Implication: [expect more supply / monitor quarterly / supply constrained]If GREEN: budget for additional competitive supply in underwriting. New deliveries will pressure rents and occupancy. If RED: supply is self-limiting. Existing assets have pricing power. Cap rate compression is defensible. If YELLOW: track permits and starts quarterly. The signal can flip with small changes in construction costs or rents.
Output Format
Present results in this order:
- Executive Summary (5-7 bullets)
- Supply Pipeline (quarterly delivery schedule with stage and competitive overlap)
- Replacement Cost Analysis (cost-to-build, market comparison, feasibility signal)
- Absorption Forecast (3 scenarios x quarterly for 12 quarters)
- Disruption Overlay (3-5 trends with magnitude and net adjustment)
- Insurance & Climate Overlay (cost trends, NOI impact, climate risk)
- Rent Impact Model (3-year growth by scenario with inflection points)
- Development Feasibility Assessment (GREEN/YELLOW/RED with math)
Target output: 3,500-5,000 tokens. Tables and structured data dominate over prose.
Red Flags & Failure Modes
- Treating "under construction" as a single bucket: 2,000 units over 8 quarters is very different from 2,000 units in Q2. Break into quarterly deliveries.
- Ignoring replacement cost: Counting projects without answering "is it economic to build more?" misses the single best predictor of future supply.
- Generic disruption statements: "E-commerce is growing" adds no value. "Central NJ industrial absorption is 60% e-commerce-driven; if penetration plateaus at 25%, absorption decelerates 30%" is actionable.
- Missing insurance hardening: The most underappreciated trend in CRE. It is a direct NOI impact AND a development feasibility impact. Always include, even unprompted.
- Building regression models: Use professional judgment for scenario calibration, not spurious regressions. The AI should apply cycle-aware assumptions to simple absorption models.
- Ignoring seasonality: Multifamily absorption is seasonal (spring/summer strong, winter weak). Industrial less so. Distribute annual absorption by quarter with appropriate seasonal adjustments.
Chain Notes
- Downstream: ic-memo-generator (feeds Section 3: Market Analysis), deal-underwriting-assistant (market assumptions feed model), disposition-strategy-engine (cycle positioning and timing)
- Upstream: submarket-truth-serum (broader market context), market-memo-generator (MSA-level context)
- Parallel: reit-profile-builder (submarket data feeds REIT comp analysis)