🏥 Executive Health Dashboard
Business Health
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Overall
Liquidity
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Cash months
Hiring Risk
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Exposure
Debt Exposure
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Debt/payroll
AI Opportunity
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Savings/yr
Pricing Leakage
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Left on table
HOLD
Enter your numbers across all modules to see your executive health score.
View mode:
Basic shows only what you need to act on. Advanced shows full tables and calculations.
📊 CEO Summary — Your company · Your sector
Log in and enter your numbers to see your CEO summary.
⚡ Scenario Simulator
Select a macro scenario. RateShield instantly recalculates every module and shows how your business performs in each environment.
Base Case — Current environment
CPI 3.2% · Unemployment 4.2% · GDP 2.1% · 10Y Treasury 4.3%. Transition environment with modest cuts ahead.
Predicted Rate
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Safe Hires
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AI Profit Gain
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Monthly Interest
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Optimal Price
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Predicted rate — all 5 scenarios
12-month Fed rate forecast under each macro environment
Business impact — profit and optimal price
Equilibrium profit and recommended price in each scenario
Financing Strategy
Enter 5 macro numbers. Get the probability of a rate hike, hold, or cut — and the exact action your sector should take right now.
Predicted rate — 12 months
3.25%
Gradual easing — transition environment
FOMC probabilities
Rate hike
8%
Hold
34%
Rate cut
58%
Rate path
Current rate3.75%
In 6 months3.50%
In 12 months3.25%
In 18 months3.00%
Model confidence74%
What this means for your sector
Loading sector context...
Analyst Notes — Rate Prediction Model
Predicted rate = 2.5% base + Σ(signal × weight) | Taylor Rule variant with 55yr FRED calibration
| Signal | Your input | Neutral | Pressure | Weight |
|---|
CPI and Core PCE carry 35% combined weight (Fed dual mandate inflation target 2.0%). Unemployment deviation from 4.0% full employment carries 25%. GDP growth relative to 2.5% trend carries 20%. 10Y Treasury as market expectation signal carries 20%. Historical analog matching uses Euclidean distance across all 5 signals against 1970–2025 FRED data.
Macro signal contribution to rate forecast
Recommended decision
Do this now
Lock floating rate debt to fixed if in HIGH environment
Watch this metric
Core PCE — must fall below 2.5% before rate cuts begin
Revisit when
After next Fed meeting or when CPI moves above 4% or below 2%
18-month rate path — 3 scenarios
Base case + bull (more cuts) + bear (fewer cuts) · Source: CME FedWatch + FRED 55yr data
| Period | Base case | Bull | Bear | vs. Today |
|---|
Verified FRED historical data
Peak rate 1981 — Volcker shock (CPI 14.8%)20.0%
Low rate 2003 — post dot-com crash1.0%
Zero rate era 2008–2015 — financial crisis0.25%
Post-COVID peak 2023 — fastest hike in 40 years5.25%
Current rate — April 20263.75%
Yield curve recession accuracy (DataSetIQ)87.5% — 7 of 8
Closest historical analog to today1995 — 74% match
Workforce Capacity
Enter your numbers. Get one answer: how many people you can safely hire right now — and what happens to your cash if you hire more.
Analyst Notes — Hiring Safety Calculation
Safe hires = min(planned_hires, affordable_hires) × environment_factor
Cash runway (months) = (cash_reserves × 1000) ÷ monthly_payroll_burn
Monthly burn = (headcount × avg_salary_$K × 1000) ÷ 12
Debt/payroll ratio = (total_debt × 1M) ÷ (headcount × salary_$K × 1000)
| Variable | Value | Threshold | Status |
|---|
Environment factor: HIGH rate environment = 0.25× (max 25% of planned hires). TRANSITION = 0.55×. LOW = 1.0× (full planned hires safe). Affordable hires = max hires before cash runway drops below 3 months. Debt/payroll above 1.5× = high risk; above 2.5× = critical.
Cash runway vs planned hires
Recommended decision
Do this now
Hire only the safe number shown above — hold the rest until cash runway exceeds 6 months
Watch this metric
Cash runway in months — minimum 3 months payroll required before hiring
Revisit when
When cash runway exceeds 6 months or rate environment shifts to LOW
Hiring scenario comparison
Current vs. after all hires vs. after safe hires only
AI Advantage
AI can reduce your operating costs, improve productivity, and protect margins if demand softens. See exactly how much you can save and what to do first.
How AI creates a competitive cost advantage
AI reduces operating costs
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Protect margins
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Lower prices safely
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Gain more volume
→
Win market share
AI can reduce operating costs, improve productivity, and protect margins if demand softens. Companies that automate first gain a structural cost advantage. WEF 2025: businesses using AI see 15–40% cost reductions across key functions.
Before vs. after AI compression — revenue, costs, profit
4 stages: current → AI cuts costs → lower prices → volume gain
Sector-specific AI action plan — your sector
Analyst Notes — AI Savings Model
AI labour saving = revenue × (labour_% ÷ 100) × automation_proxy × sector_multiplier
Automation proxy = min(1, (labour_share ÷ 0.65)) — higher labour share = more automatable
Net profit gain = AI_saving − implementation_cost_amortised + volume_gain_from_price_cut
| Cost component | % of costs | AI impact | Annual saving |
|---|
Sector AI implementation benchmarks: Manufacturing (robotic process automation, predictive maintenance) saves 8–15% of labour costs. Technology (code generation, QA automation) saves 12–25%. Restaurant (AI scheduling, ordering) saves 10–18% of labour. Retail (demand forecasting, inventory) saves 6–12% of raw material costs. Source: McKinsey Global Institute 2024, WEF 2025.
Recommended decision
Do this now
Implement the AI action with fastest payback shown in the action plan below
Watch this metric
Labour cost as % of revenue — should fall after AI is implemented
Revisit when
Every 6 months, or when a relevant AI tool drops below $5,000/month
Debt Exposure
Drag the slider to see exactly what each loan type costs at every possible Fed rate — and compare to what you would have paid at the 2023 peak of 5.25%.
Federal funds rate — drag to see live impact
| Federal funds rate | % · April 2026 = 3.75% | |
| Change to model scenarios · COVID low=0.25% · 2023 peak=5.25% | ||
Most important loans for your sector
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Prime rate loans
Moves same day as Fed
6.75%
Fed + 3.00%
Credit cards, overdraft, working capital
$500K → $3,375/mo
SBA 7(a) loans
Adjusts quarterly
9.50%
Prime + 2.75%
Most common small business loan
$500K → $3,958/mo
SOFR loans
Updates daily — most volatile
7.05%
SOFR + spread (replaced LIBOR)
CRE, large equipment $1M+
$2M → $11,750/mo
Commercial real estate
Tied to 10Y Treasury
7.45%
10Y Treasury + ~3.00%
Warehouses, offices, factories
$3M → $18,625/mo
Equipment financing
Floating or fixed — your choice
7.25%
Prime + 0.50% if floating
Machinery, vehicles, AI systems
$800K → $4,833/mo
Fixed rate loans
Fed rate = zero impact ✓
LOCKED
Set at origination — never changes
<
AI savings by cost category
SBA 504, fixed mortgages. Always the goal.
Your rate — forever
Total monthly interest — typical debt mix
$38,541/mo
$462,492/year — $500K credit + $500K SBA + $2M SOFR + $800K equipment
Annual interest cost vs. Fed rate
Same loans — every Fed rate level · Source: Prime=Fed+3%, SBA=Prime+2.75%, SOFR≈Fed+3.15%
Analyst Notes — Loan Rate Mechanics
Prime rate = Fed Funds rate + 3.00% (historical bank spread)
SBA loan rate = Prime + 2.75% (SBA variable rate ceiling)
SOFR floating = Fed Funds + 3.15% (30-day SOFR + credit spread)
Equipment loan = Prime + 0.50% (secured, lower risk premium)
Monthly payment = (balance × annual_rate ÷ 100) ÷ 12
| Loan type | Rate formula | At current Fed rate | At 2023 peak (5.25%) | Risk |
|---|
Rate sensitivity by sector: Real estate carries 2.5% profit impact per 1% Fed move (highest). Construction 1.8%. Restaurant 1.5%. Retail 1.2%. Manufacturing 0.8%. Professional services 0.4%. Technology/SaaS 0.3% (lowest — minimal physical capital). Fixed-rate debt eliminates this exposure entirely; refinancing window depends on yield curve slope.
Monthly interest cost by Fed rate
Recommended decision
Do this now
Refinance any SOFR or floating loans to fixed if Fed rate is above 3.5%
Watch this metric
Monthly interest as % of revenue — warning if above 2%
Revisit when
When Fed signals direction change, or before your floating loan next resets
Growth & Pricing Optimizer
Finds your profit-maximising price and output using real economics tailored to your sector. Shows how rising rates shift your cost curve and exactly where your equilibrium moves.
Loading sector model...
Log in and select your sector to load the correct economic model
Analyst Notes — Equilibrium Pricing Model
Optimal price = (a + VC_adjusted) ÷ 2, where a = P + b×Q (demand intercept), b = P ÷ (Q × elasticity)
Profit-maximising output = (a − VC_adjusted) ÷ (2 × b)
VC_adjusted = VC × (1 + (Fed_rate − 2.5%) × rate_sensitivity)
| Variable | Current | Optimal / Adjusted | Impact |
|---|
Rate sensitivity per sector: Real estate 2.5% · Construction 1.8% · Restaurant 1.5% · Retail 1.2% · Manufacturing 0.8% · Professional 0.4% · Technology 0.3%. Elasticity above 1.0 = price-sensitive customers; below 1.0 = captive/loyal buyers. MR=MC condition is the necessary condition for profit maximisation under imperfect competition.
Recommended decision
Do this now
Adjust price to the recommended level shown in Table 1 row 2
Watch this metric
Pricing power score — if falling, competitors are undercutting you
Revisit when
Every quarter, or immediately after any Fed rate change above 0.25%
Current profit/yr
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At your current price
Recommended price
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Profit-maximizing level
Recommended volume
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Units/yr at that price
Expected profit gain
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vs. today
Profit at different price points
Green = recommended price · Blue = current price
Scenario comparison
Revenue, costs and profit across rate scenarios
Table 1 — Scenario comparison: current vs. optimal vs. rate scenarios
profit-maximizing price and volume · Rate shifts cost curve · Green = profit-maximising · All values from your inputs
| Scenario | Price | Output | Revenue | Variable costs | Profit | Margin | vs. Today | Status |
|---|
Table 2 — Unit-by-unit profit analysis: step-by-step profit optimisation (31 levels)
Make more when revenue gained > cost to produce · Stop here — peak profit · Never make more whe
Price vs profit curve
When cost>MR · Green = equilibrium
| Output | Price | Total revenue | Revenue from next unit | Cost of next unit | Profit/unit | Total cost | Profit/Loss | Decision |
|---|
Table 3 — Operating leverage, break-even, Pricing power score — benchmarked vs. sector
profit sensitivity = profit amplification with volume · Pricing power score (0=commodity, 1=monopoly)
| Metric | Your business | Industry benchmark | What it means |
|---|
Table 4 — How your ideal price changes at every Fed rate
Higher rates push cost curve up → optimal output falls, price rises · Highlighted = current rate
| Fed rate | VC impact | Optimal price | Optimal output | Profit | vs. Today | Pricing power | Action |
|---|
Executive Advisor
Your sector-aware financial advisor. Knows your industry benchmarks, the current rate environment, and gives specific numbers-based answers — not generic advice.
Conversations private to your account · Not used for training · Encrypted in transit
Analyst Notes — What the Executive Advisor Knows
| Data source | Current value | How it shapes advice |
|---|---|---|
| Sector benchmarks | — | Margin, labour %, elasticity, rate sensitivity vs. industry average |
| Rate environment | — | Determines hiring safety factor, debt urgency, and pricing window |
| Pricing gap | — | Distance between current price and profit-maximising equilibrium |
| AI opportunity | — | Estimated annual saving from AI automation vs. sector peers |
| Hiring risk | — | Cash runway and debt/payroll ratio against safe-hire threshold |
| Debt exposure | — | Monthly interest burden and % of revenue at current Fed rate |
The Executive Advisor receives all of the above as system context on every query. It does not have access to your conversation history between sessions. The model used is Claude Sonnet — calibrated for financial specificity, not general conversation.
Advisor input stack
Welcome. I know your sector benchmarks and the current rate environment. Ask me anything — I give specific numbers, not generic advice.