01
Inventory the apartment systems that hold data
List every source: PMS, accounting, CRM, maintenance, utilities, screening, and the spreadsheets that fill the gaps between them. Silos you have not named cannot be connected.
Apartment data silos are what you get when every system an operator runs keeps its own version of the truth. The property management system, the accounting package, the marketing tools, and the maintenance platform each hold part of the picture, and none of them share it. On this episode of Proptech Espresso, Elizabeth Braman joins Justin Hughes to talk about that dilemma and how connectivity across an operator’s existing technology gives them a holistic view of properties, tenants, and portfolios.
Elizabeth Braman, Co-Founder and CEO, appears on Proptech Espresso to discuss solving apartment owners’ data silo dilemma. At the time of the episode, the company was JoyHub, which later became Revolution RE. The episode is available on Audible.
JoyHub is a business intelligence platform specifically for professional rental owners, managers, and operators. By providing access and connectivity across their existing technology infrastructure, JoyHub provides rental operators with a holistic view of their properties, tenants, and portfolios. Powered by a proprietary integration layer, JoyHub connects, collects, and aggregates data from various data sources to support secure data storage, custom reporting, and predictive analytics.
With access to data from across their various systems, operators view dashboards, create aggregated reports, and develop risk models to capitalize on trends, respond to unpredictability, and maximize NOI to deliver greater overall value to investors.
An apartment data silo is a store of property information that only one system, one team, or one vendor can read. The rent roll lives in the property management system. The general ledger lives in accounting. Leads and tours live in the CRM. Work orders live in the maintenance platform, and utility usage lives with a billing vendor. Each is complete on its own terms and incomplete for the questions an owner actually asks.
The dilemma in the episode’s title is that the systems are not broken. Each does its job well. The problem is that the job of the portfolio, seeing properties, tenants, and financials together, belongs to none of them. Apartment data silos are a side effect of buying good tools for separate tasks.
Silos are not a sign of poor management. They are the predictable result of how rental technology is bought and built. Four mechanisms account for most of it.
A property management system is designed to run leasing and rent collection. An accounting package is designed to close the books. Neither was designed to be the other’s data source. Each stores what it needs, in the structure it needs, and treats everything else as someone else’s concern.
Systems that do exchange data still disagree about what the data means. One calls a unit a “1BR,” another “One Bedroom.” One counts a renewal on signature, another on move-in anniversary. Without an agreed definition for each field, connecting systems just moves the disagreement into one place. That is the case for a multifamily-specific model, explained in what makes an apartment data model different.
Acquisitions bring properties that run on a different PMS. Third-party managers use their own stacks. A new marketing platform gets added because it is better, not because it integrates. Over years, the number of systems grows and the number of connections between them does not.
Exports are often limited, APIs are inconsistent, and the vendor that holds the data has a natural interest in keeping the analysis inside its own product. The owner ends up with rental data connectivity that depends on each vendor’s goodwill.
The messy reality of the results, mismatched numbers, delayed reports, and unanswered questions, is covered in more depth in why rental property data is such a mess.
The answer described in the episode is connectivity across existing technology infrastructure, rather than replacing that infrastructure. Operators keep the systems that run their business. An integration layer connects, collects, and aggregates the data those systems produce. The work breaks into stages.
List every source: PMS, accounting, CRM, maintenance, utilities, screening, and the spreadsheets that fill the gaps between them. Silos you have not named cannot be connected.
Extract data from each system through its API or export on a schedule, so the portfolio view no longer depends on someone remembering to pull a report.
Map every field to a single definition and structure. This is the step that turns connected data into comparable data. Our breakdown of the multifamily ETL process walks through how extraction, transformation, and loading fit together.
Standardized data lands in secure storage where it can be aggregated across properties, managers, and systems. Portfolio questions become queries instead of projects, and the answers stay consistent from one month to the next because the definitions never change.
Dashboards, aggregated reports, custom reporting, and predictive analytics sit on top. A business intelligence tool built for rental portfolios is only as useful as the connected, standardized data underneath it.
The episode description lists the outcomes plainly. With access to data from across their systems, operators view dashboards, create aggregated reports, and develop risk models. Those capabilities let them capitalize on trends, respond to unpredictability, and maximize NOI, delivering greater overall value to investors. Each of those depends on the silos being gone. A risk model built on one system’s data models one system’s risk.
The holistic view is the point. An owner who can see properties, tenants, and portfolios together can answer questions that span systems, which are the questions that move NOI. Which properties are trending toward vacancy before it shows in the financials? Which managers hit their numbers on identical definitions? Where is unpredictability turning into risk?
Investors feel it too. Reporting to them from apartment data silos means reconciling by hand every quarter and hoping the numbers agree. Reporting from connected, standardized data means the same figures every time, traceable to source. That is the difference between a portfolio that explains itself and one that requires an analyst to explain it.
The conversation dates from the JoyHub era, and the framing has held up. Property management system integration is still the bottleneck, and connecting existing infrastructure is still the practical route, because ripping and replacing the systems that run a business is rarely an option. What has changed is how much more the connected data can do once it exists.
A data silo in property management is property, tenant, or financial information that only one system or team can access, such as a rent roll in the PMS or a ledger in accounting that does not connect to anything else. Apartment data silos leave operators with several partial views and no holistic one. They form naturally as each system is bought to do its own job.
Owners connect data by adding an integration layer over their existing technology infrastructure rather than replacing it. That layer connects, collects, and aggregates data from each source, standardizes it into one model, and stores it securely. Dashboards, aggregated reports, custom reporting, and predictive analytics then run on the connected data.
Property management systems are built to run leasing and rent collection for their own users, not to serve as a data source for other systems. They store data in their own structures with their own definitions, offer inconsistent exports and APIs, and have little commercial incentive to share. Connecting them requires an integration and standardization layer that translates each system into a common model.
A holistic view brings properties, tenants, and portfolios into one place, drawing on every system an operator runs. It lets operators view dashboards, create aggregated reports, and develop risk models on the same data. The purpose is to capitalize on trends, respond to unpredictability, and maximize NOI to deliver greater value to investors.
Connecting and standardizing the data your existing systems already produce is how apartment owners replace silos with a portfolio they can actually see.
See plans and pricing