Case Study · Portfolio Strategy · Residential
Watershed: which of 244 homes should become short-term rentals?
A full real estate analytics workflow, from database extraction and rent normalization to nightly-rate
optimization, property-level financial modeling, and capital allocation under a $500,000 cash limit.
The result is a staged plan to convert 15 properties, backed by an interactive Tableau sensitivity dashboard.
Case studyBuilt on a project dataset. Watershed Properties and its portfolio come from a real estate analytics project dataset. The analysis, models, and conclusions are real work.
Recommended strategy
Proceed in stages
Enter selectively, then scale
15 of 244 properties · $25,000 annual-profit hurdle
Upfront capital
$450K
15 × $30,000
Reserve retained
$50K
10% of cash limit
Priority assets
15
6.1% of portfolio
Year 1 cash flow
$483K
After conversion spend
Annual profit
$753K
Years 2–4, incremental
244 propertiesEach evaluated individually
62 location groupsCity, state, and ZIP across the U.S.
$500K cash · no debtThe binding portfolio constraint
Tableau dashboardNine adjustable assumptions
02 · The Brief
A proven long-term model, asked to try something new.
The decision: Should Watershed enter the short-term rental market, which properties should be converted first, and how much capital could be committed without weakening liquidity?
Watershed Properties manages several thousand residential rentals across more than 60 U.S. neighborhoods and markets. Its established model relied on year-long leases and had historically achieved 97.3% occupancy. A major client asked the company to investigate whether part of its 244-property portfolio could earn more as short-term rentals marketed through online booking platforms.
The opportunity was not simply higher nightly rent. Short-term operation can produce more revenue, but it also brings variable occupancy, furnishing and conversion spending, platform and regulatory fees, utilities, cleaning, guest-service costs, and ongoing replacement expense. Watershed needed a property-by-property answer that accounted for both the upside and the added operating burden.
- Estimate the cost to convert and operate each property as a short-term rental.
- Use comparable rents and occupancy to estimate a revenue-maximizing nightly rate.
- Measure the incremental cash flow and profit versus continued long-term operation.
- Rank the assets, quantify total cash required, and recommend an entry sequence.
A late-stage constraint changed the answer. Management confirmed the initiative could use no more than current cash reserves and could not rely on debt. That turned the work from a profitability screen into a capital-allocation decision.
244client properties
$500Kcash available
$0debt permitted
03 · The Decision
Deploy the cash where the economics are strongest.
Recommendation · Proceed in stages
Begin with 15 properties that each exceed $25,000 in modeled annual incremental profit.
This subset fits inside Watershed’s $500,000 cash limit without borrowing, stays cash-flow positive in aggregate during the conversion year, and keeps a 10% liquidity buffer. Sequence the rollout by modeled profitability, then cluster execution within the selected markets to simplify vendors, cleaning routes, and operating oversight.
$450K deployed · 90%$50K retained
Priority conversions
15
6.1% of the 244-property portfolio
Initial capital
$450K
15 properties × $30,000
Conversion-year cash flow
$483K
Incremental, after conversion spending
Conversion-year profit
$843K
Incremental vs. long-term operation
Annual profit thereafter
$753K
Years 2–4; upkeep of $6,000 per property begins after the conversion year
Positive year 1 cash flow
15/15
At the property level under the model
04 · Approach
More than comparing monthly and nightly rent.
Short-term rentals can command higher nightly rates, but they also bring lower occupancy, platform and regulatory fees, utilities, cleaning and guest-service costs, recurring replacement expense, and a large upfront furnishing requirement. The analysis had to find the revenue-maximizing rent for every asset, translate it into cash flow and accounting profit, and then identify the portfolio that fit Watershed’s risk and capital limits.
Properties
244
Evaluated individually
Location groups
62
City, state, and ZIP
Property types
4
By bedrooms and asset type
Cash limit
$500K
No borrowing permitted
01
Retrieve & structure
Queried the property and comparable-rental data, producing one analysis-ready row for each Watershed property.
02
Profile the markets
Reviewed rent, occupancy, location, and property-type variation; kept all observations and used market-relative comparisons.
03
Normalize rent
Placed each nightly rent on a market-relative scale between the 10th and 90th percentile comparable rents.
04
Optimize revenue
Estimated how occupancy changes with rent and solved for the nightly rate that maximizes annual short-term revenue within supported bounds.
05
Allocate & stress-test
Modeled profit and cash flow, ranked each asset, applied the cash constraint, and exposed the assumptions in Tableau.
05 · Pricing Model
Pricing was normalized before occupancy was forecast.
Raw nightly prices are not comparable across cities and property types. A $250 rate can be premium in one market and ordinary in another.
06 · Capital Allocation
The best answer was not “convert every profitable property.”
The profit hurdle works as a portfolio-selection tool. It controls both how many assets are admitted and how much conversion capital is committed.
Default screen
Convert all qualifying assets
Minimum annual profit: $6,000
- Properties selected
- 40
- Conversion capital
- $1.20M
- Conversion-year cash flow
- $375,814
- Conversion-year profit
- $1,335,814
- Annual profit thereafter
- $1,095,814
- Fits the $500K limit
- No · 2.4× cash
versus
Recommended screen
Concentrate capital in priority assets
Minimum annual profit: $25,000
- Properties selected
- 15
- Conversion capital
- $450,000
- Conversion-year cash flow
- $483,441
- Conversion-year profit
- $843,441
- Annual profit thereafter
- $753,441
- Fits the $500K limit
- Yes · $50K buffer
+$107,627 more conversion-year cash flow from the 15-property strategy than the broader 40-property screen, while converting 25 fewer assets. The excluded lower-ranked properties are profitable in steady state, but they absorb a large share of conversion-year cash. Concentrating the first deployment improves liquidity and keeps options open.
07 · Interactive Dashboard
Sensitivity analysis and asset selection in Tableau.
Decision-makers can compare current inputs with the fixed base case, change operating assumptions, inspect the profit distribution, and see where the selected assets are located.
TB
Watershed STR Portfolio DashboardTableau Public · nine parameter controls
01
Start with the parameters
Nine controls cover conversion capital, depreciation period, fees, upkeep, average stay, utilities, hospitality cost, and the profit hurdle. The saved scenario uses a $25,000 hurdle; the fixed default uses $6,000.
02
Compare the outcomes
Bar-in-bar views show aggregate cash flow and net profit for the conversion year and years 2–4. Light teal is the fixed default; dark navy is the current inputs.
03
Inspect the portfolio
The histogram groups qualifying properties by annual profit and colors them by type. The box plot summarizes the distribution and highlights unusually strong assets.
04
Locate the opportunity
The map shows only properties that pass the current screen, colored by type, with slight jitter to separate shared locations. Hover for details.
05
Test one change at a time
Change one assumption and watch the dark bars, property count, distribution, and map respond. Use Tableau’s reset control before the next test.
Try this: raise the marketplace fee from 20% to 25% while keeping the $25,000 hurdle. The qualifying portfolio falls from 15 to 9 properties, and later-year annual profit among qualifying assets falls from $753,441 to $515,143. Reset the fee to 20% when finished.
08 · Rollout
Three profitability tiers, with operating stage gates.
Every conversion carries the same $30,000 upfront cost, so ranking by incremental annual profit also ranks capital efficiency.
Tier 1 · First deployment
Highest-conviction 5 properties
W156 · W155 · W164 · W163 · W107
- Capital
- $150K
- Annual profit
- $423K
- Conversion-year cash flow
- $333K
- Average profit / asset
- $84.6K
Tier 2 · Scale after validation
Next 5 properties by annual profit
W120 · W108 · W67 · W190 · W152
- Capital
- $150K
- Annual profit
- $197K
- Conversion-year cash flow
- $107K
- Average profit / asset
- $39.4K
Tier 3 · Complete initial portfolio
Remaining 5 priority properties
W66 · W110 · W160 · W192 · W46
- Capital
- $150K
- Annual profit
- $134K
- Conversion-year cash flow
- $44K
- Average profit / asset
- $26.8K
Selected portfolio pattern: the 15 assets span 10 location groups and lean toward houses: 8 two-bedroom houses, 5 one-bedroom houses, and 2 two-bedroom apartments. Keep the profitability ranking, but sequence properties within nearby markets where that lowers vendor mobilization and operating complexity.
Gate 1Validate demand
Compare realized nightly rate and occupancy with the model before releasing the next capital tranche.
Gate 2Validate operations
Track average stay, turnover cost, utilities, review quality, and time-to-ready by property and market.
Gate 3Reforecast and scale
Refresh the dashboard with actual performance, re-rank the remaining portfolio, then reinvest selectively.
09 · Risk & Controls
What to validate before a live rollout.
Key operating risks
- Seasonal demand and event-driven pricing are outside the annualized model.
- Local short-term rental rules, taxes, permitting, and caps can change by jurisdiction.
- Cleaning, key exchange, maintenance, and guest support may differ by location and asset type.
- The comparable dataset is cross-sectional; ongoing market data should be added before dynamic pricing.
Recommended production controls
- Reconcile contract rent, collected rent, and the 97.3% long-term occupancy baseline.
- Use actual booking curves and contribution margin by property, not gross revenue alone.
- Monitor variance to model monthly and set stop-loss or reversion rules for underperforming assets.
- Keep the $50,000 reserve until working-capital timing and conversion schedules are confirmed.
Model scope. Reported cash flow and profit figures are incremental changes from long-term to short-term operation, before any sharing between Watershed and the property owner. The published Tableau workbook annualizes the current monthly rent field as the long-term baseline; a production refresh should reconcile that baseline to actual collected rent and occupancy. Applying the 97.3% occupancy factor would modestly strengthen the short-term conversion case, not weaken it.
10 · Skills Applied
What this project demonstrates.
SQL
Data retrieval and structuring
Joined property, comparable-rent, and occupancy information into a portfolio-ready dataset.
FX
Predictive modeling and optimization
Normalized different markets, estimated price-demand response, and solved for optimal rents.
CF
Property-level financial analysis
Separated cash flow from accounting profit and modeled fixed, variable, and capital costs.
BI
Decision visualization
Turned the model into a dynamic Tableau tool that lets stakeholders test assumptions directly.
Bottom line · $753K modeled annual incremental profit
A broad opportunity, turned into a controlled and measurable operating plan.
Start with the assets that offer the highest modeled profit per conversion dollar, preserve liquidity, validate the most uncertain operating assumptions, and let real performance decide how far and how fast to scale.
Portfolio case study. Watershed Properties, its client, and the 244-property portfolio come from a Coursera real estate analytics capstone dataset. This was not a client engagement. The data preparation, pricing model, financial model, capital allocation, and Tableau dashboard are the author’s own work.
