Benchmarks and Big Data: How to Build Better Budgets

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3 minute read

Anyone who’s ever created a budget knows that you need good benchmarks for revenue and operating expenses. Market data from a large sample size can be invaluable, which is precisely what the National Apartment Association’s 2016 Survey of Operating Income & Expenses (IES) provides.

The IES contains data from 3,892 properties containing 987,342 units. The findings are broken down by garden and midrise/high-rise properties, then further segmented by individually metered and master-metered utilities. The survey also contains detailed data for 10 geographic regions.

Audrey McEntee, director of operations and compliance at Celtic Property Management in Scottsdale, Arizona, is in her second year of using the survey data for budgeting. “If you don’t know what other people are doing, you are kind of going in blind” when creating a budget, she says. “You don’t know if you are doing it the right way and where you can save costs. It’s helpful to see the averages of other communities.”

And while history-based budgeting is useful, it can mask long-term discrepancies. Larry Goodman, chief operating officer at multifamily management company Pinnacle in Addison, Texas, has used the IES data for the past five years to create both budgets and pro formas. He has discovered operational problems by comparing individual community data with the survey averages.

“This survey is so valuable because it calls for more investigative research as to why a category is either over or under so much,” Goodman says. “Even if we may say that that category historically is not the best, it actually makes us look at everything and question if we need to review things in more depth.”

Valuable Data All Year Long

Goodman finds the IES data on payroll and controllable expenses to be particularly invaluable. “Before we started using this survey to look at payroll, you only had internal data and knowledge of history, but you didn’t have the sampling size to say, ‘Does this feel right?’” McEntee agrees, since per-unit cost of payroll can be standard in a region.

McEntee also pays particular attention to the utilities data in the survey, which provide a heads-up when something at a community is off. Recently, the data proved useful when an apartment community had a major water leak. Maintenance staff eventually figured out that faulty water-saving, dual-flush toilet valves were causing the leak, and the IES data are the benchmark the company is using to recoup at least some of the $200,000 in losses from the valve manufacturer.

Tracking operational expenses is a year-round job, so McEntee doesn’t confine her use of IES data just to budget season. “We look at the data a lot throughout the year to see how we are doing and how we can do better,” she says. “You have to keep analyzing in management to make sure you are spending correctly.”

Goodman agrees. “It’s not just a one-time, once-a-year, one-and-done tool. Nothing compares to the amount of detail that this report has, especially when you have the breakdown by regions.”