The first time I compared two rental deals side by side, I nearly bought the wrong one. Property A was listed at 18,800,000 yen and looked like the obvious pick. But once I ran both listings through a simple spreadsheet with about a dozen line items, Property B, priced 2,300,000 yen higher, actually returned close to 3 percentage points more in annual cash flow. That gap is why I never compare deals from memory anymore.
Over 15 years of buying, renovating, and managing 9 rental properties myself, I have rebuilt this comparison sheet more times than I can count, and it has settled into something simple: one tab, one row per property, the same 14 fields every time. No macros, no paid software, just numbers I trust because I typed them in myself.
Why I Stopped Trusting My Gut on Deals
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Early on I judged properties the way most people do: location, photos, the agent’s pitch. That approach cost me on my third purchase, a small apartment building I bought in month two of house hunting because it felt right. It took almost 4 years to realize the rent roll had been optimistic by about 12 percent. A spreadsheet does not care how a listing feels. It only cares whether the numbers you enter add up to a return worth the risk, and that discipline has saved me from at least 3 deals I would otherwise have regretted.
The Numbers I Put in Every Row
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Every property I seriously consider gets the same set of inputs before I even schedule a viewing. I keep the list short on purpose, because a 40-field monster spreadsheet is one I will eventually stop updating.
- Purchase price and estimated closing costs (usually 6 to 8 percent of price here in Japan)
- Expected monthly rent, based on at least 3 comparable listings nearby
- Vacancy assumption, which I set at a flat 10 percent even in strong areas
- Annual property tax and fixed asset tax estimate
- Management fee, typically 5 percent of collected rent if I outsource it
- Renovation budget needed before the first tenant moves in
- Loan amount, interest rate, and loan term if I am financing part of the purchase
How I Calculate Cash-on-Cash Return
Once those inputs are in, the spreadsheet does the rest with three formulas. First, gross annual rent minus vacancy and minus operating expenses gives net operating income. Second, I subtract annual loan payments to get actual cash flow. Third, I divide that cash flow by the total cash I put in, down payment plus renovation plus closing costs, to get cash-on-cash return as a percentage. On one duplex I bought 6 years ago, that number came out to 9.4 percent, and it has held within half a point of that every year since, which tells me the spreadsheet was doing its job before I ever signed anything.
Red Flags the Spreadsheet Reveals
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The real value is not the winning number, it is what the sheet exposes about a bad deal before you fall for it. I add a break-even occupancy row that shows what percentage of units need to stay rented just to cover the mortgage and expenses. Anything above 85 percent makes me nervous, because a single vacancy in a small building can push you underwater fast. I also track price per square meter against the other rows in the sheet, and if a property is priced 15 percent or more above similar listings I have logged, I want a very good reason why before I move forward, whether that is a recent full renovation or a location advantage the comps do not capture.
My Simple Ranking System
When I am looking at 3 or 4 properties at once, which happens most months since I am always scanning listings, I add a final column that ranks each deal on cash-on-cash return, break-even occupancy, and total cash required, weighted 50/30/20. It is not scientific, it is just consistent, and consistency is what lets me compare a small kominka (old traditional house) renovation project against a modern rental unit without letting the shinier listing win by default. The property that ranks highest gets a site visit within the week; everything else waits.
Keeping the Sheet Updated as Deals Change
Numbers move fast once you are actually negotiating. Interest rates shift, sellers counter, contractors quote higher than expected. I update the same row rather than starting a new one, so I can see exactly how a deal’s projected return changed from the day I first found the listing to the day I signed. On one property last year, 3 rounds of renegotiation moved the projected return from 6.1 percent up to 8.7 percent, and having that history in one place made it easy to know when to walk away and when to push for one more concession.
That is the approach I use across all 9 of my properties, and it is the only reason I still buy calmly after 15 years in this business.
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15 years of landlord experience u00b7 3 apartment buildings u00b7 DIY renovations that saved millions of yen. Browse all articles at diytosan.com
