Real estate companies face a range of financial planning and analysis (FP&A) challenges.
The biggest challenge is forecasting accurately. If real estate management would have a better idea of when repairs will be needed, when the weather will affect utilities, and when occupancy rates fluctuate, they would be able to maximize their profits far better.
In addition to forecasting accurately, FP&A teams at real estate companies run into other challenges:
Capital budgeting- Real estate companies must make informed capital budgeting decisions, such as when to acquire, develop, or dispose of properties. These decisions require accurate analysis of the expected cash flows, risks, and returns associated with each property.
Portfolio management- Real estate companies must manage their portfolio of properties to optimize returns and minimize risks. This requires ongoing analysis of the performance of each property, the portfolio as a whole, and the market conditions that affect the value of the properties.
Data management- Real estate companies have large amounts of data, including property valuations, lease agreements, and financial reports. Managing this data and integrating it into FP&A processes can be a significant challenge.
Regulatory compliance- Real estate companies must comply with a range of regulations, including tax laws, building codes, and environmental regulations. Compliance with these regulations can impact financial performance and must be factored into FP&A processes.
Property management software such as Yardi and Buildium help to streamline and automate much of these problems by tracking real estate expenses, budgets, and income statements, allowing the finance teams to forecast and budget much more accurately.
One such real estate company, Broadstreet Properties, uses Yardi to track and consolidate all of their expenses and budgets. With over 13,000 apartments across Canada, keeping track of all of the data is a tough mission.
But many real estate management software are quite rigid and don’t allow for customized reports. This can be a problem in an industry such as real estate where there are so many factors involved in each real estate unit (location, weather, economic time period, real estate trends, etc.). The more units a company has, the more data and accuracy is needed.
Broadstreet found it difficult to create custom reports and drill down into the details with Yardi. This required a lot of manual work in order to format the Excel files and break down the data into what they needed.
So they went on a hunt for an FP&A software that can help them accelerate this process and reduce the manual work and found Datarails. Thanks to Datarails’ native Excel platform and integrations (including Yardi), Broadstreet was able to automate most of their FP&A processes and save 15 hours a month in the finance team on the month end close alone.
The time saved and advanced drill down capabilities allowed them to implement significant cost saving measures which increased their profit margins.
Custom Reporting
Real estate is not a cookie-cutter type industry. Rents fluctuate along with housing values and the costs of repairs can vary greatly depending on timing and the region. In Canada, another thing plays a big factor: the weather. Snow removal is costly and each region gets different amounts of snowfall.
Through Datarails, Broadstreet’s custom reports allowed them to report clearly by region and expense category. While previously, conducting variance analysis on every General Ledger would require a lot of manual manipulation to get it into the format they need, it is now done automatically.
Breaking down all of the GLs (plumbing, snow removal, etc.) by categories or region is now a breeze, and after running the actuals and variances, they are able to make more strategic and quick decisions.
Time Saving
Datarails now saves Broadstreet 15 hours a month on reports. Instead of doing them manually, Datarails now publishes them automatically and in real time with the click of a “refresh” button.
Drilling down is also much easier as instead of having to export the Yardi data to Excel and then drilling down (and having to export again if the numbers change) Datarails allows for them to transfer the data directly into the format they need without losing any drill down capabilities.
The combination of custom reporting and time saving has allowed Broadstreet to identify problems that they wouldn’t have been able to before.
One example is they realized that one of the regions uses hard water (excess calcium and magnesium) instead of soft water. After a drill down and analysis they put it together that this was causing the water tanks to last a lot shorter than they should. By identifying this problem and conducting the relatively easy and cheap switch to soft water, they were able to save the company costly emergency water tank replacements ($20- $25,000 each).
Another example that greatly improved their analysis is that with the extra time available they now started going over ALL of the GLs - not just the ones with high variances. While at first glance, actuals that match the budget can be written off, there are many instances where there is a better way to allocate the budget after an analysis, and by doing this it allowed Broadstreet to budget and forecast even more accurately.