CASE STUDY
How a 30-year-old housing foundation turns location data into a key part of their operations
For thirty years, Yrjö ja Hanna Kodit has built homes with purpose: Communal, accessible, sustainable housing across some 20 localities in Finland, from Helsinki to Rovaniemi.
Today the foundation operates with two mandates at once. Much of its existing portfolio, including ASO (right-of-occupancy housing) and senior housing, is governed by cost recovery rather than profit: rents need to cover financing, maintenance, operations and future repairs. But its newer, fund-based developments compete in the open market, where yield, demand and commercial viability decide whether a project happens at all.
Running both models well requires a level of market understanding that spreadsheets and developer-supplied assumptions can't always delive reliably. A srtong foundation in location intelligence becomes crucial as a part of their development and strategy.
Customer:
Yrjö ja Hanna Kodit
Use Case:
Data-Driven Rent Pricing, Area Analysis & Data-driven design
Industry:
Real estate development, Property asset management
By grounding development decisions in market data, Yrjö ja Hanna Kodit evaluates opportunities fasterand and with far more accuracy.
Faster go/no-go decisions on new developments
Apartment mix tested against real local demand
Whole-building comparisons, not just unit-by-unit guesswork
Like-for-like benchmarking across ASO assets
Yield assumptions grounded in current market rents
Visibility into competing supply, present and future
VERDICT
A strong data-driven workflow becomes an essential part of the operations
THE CHALLENGE
The most expensive question in housing development
A proposal arrives. A location, a proposed building, an apartment mix, a construction cost. The question is deceptively simple: should we build this?
Answering it well means holding a dozen moving parts in view at once: What rents the location can genuinely support, what services and infrastructure surround the site, what's already competing nearby, what's coming next, what the mix should be, and whether the whole thing clears the target yield.
Historically that meant assembling the picture by hand: developer-supplied information, internal cost calculations, manually built rental assumptions, and a spreadsheet holding it all together. It worked, but it rested on assumptions that were difficult to verify, and by the time the analysis was complete, the market view behind it was probably already ageing.
The challenge is that Yrjö ja Hanna Kodit's portfolio doesn't behave like a uniform investment vehicle. Senior housing isn't comparable to ordinary rental stock. ASO properties follow their own logic and should be measured against other ASO properties, not against market rentals. Buildings vary in age, condition and regulatory framework. A market comparison that ignores those differences isn't just imprecise, but misleading.
"The market is moving in a more competitive direction, and that means we have utilize all data there is. CHAOS gives us the visibility we need to make efficient, forward-looking decisions, and just as importantly, they work alongside us. Our co-operation with them is tight.
this is a proposed testimonial on our end.
Name Here
Occupation here
CHAOS gives Yrjö ja Hanna Kodit a holistic view of the markets they're evaluating: Rent levels by neighbourhood and apartment type, comparable properties, demographics, services and reachability, competing supply, plots and building rights.
Applied to a development proposal, that changes the nature of the analysis in three ways:
Feasibility becomes evidence-based: Instead of starting from estimated rents, the team can see what the local market currently supports for each apartment type, and build the case from there. CHAOS' AI Report turns that market picture into something shareable, ready for internal discussion and decision-making.
The whole building can be assessed as one asset: A development isn't a single apartment. It's a mix of typologies, each facing its own local market. Comparing the proposed building's rent and income assumptions against current market levels, broken down by type, gives a far more honest read than evaluating units in isolation.
Scenarios can be tested rather than debated: More studios or more three-bedrooms? Smaller average size, or fewer units at higher quality? Each configuration produces a different combination of market fit, occupancy potential, rental income and yield, and being able to compare them against real demand data turns a judgement call into a comparison.
For the existing portfolio, the same principle applies in reverse: the comparison group has to be defined correctly before an asset is flagged as above or below market. ASO compared with ASO. Senior housing compared with senior housing. That precision is what makes portfolio monitoring meaningful for an organisation with this mix of assets.
THE SOLUTION
Studios or three-bedrooms? Now the data answers
THE RESULT
Asking the right questions, and answering them faster
Using CHAOS, the team can now:
Assess whether a proposed development is worth investigating, before committing analysis time to it
Ground rent assumptions in current, location-specific market data
Test alternative apartment mixes against real local demand
Compare a whole proposed asset with existing supply, type by type
Understand competing supply, both what exists today and what's coming
Benchmark ASO and specialist assets against genuinely comparable properties
And the way the work happens matters as much as the platform itself. Rather than a vendor relationship at arm's length, Yrjö ja Hanna Kodit and CHAOS develop side by side, close enough that the product keeps evolving around the decisions the team actually faces.
Judgement still decides these projects. Thirty years of housing expertise isn't replaced by a dashboard. But that judgement now starts from what the market is actually doing, which is exactly the point.
