An important aspect of a Property Tax Manager’s job is to forecast the expected property tax liability for next year’s budget. But forecasting and budgeting is a complex and time-intensive process for property tax teams. Collaborating with your colleagues in property accounting, working with the nuances of various property types and jurisdictions, and trying to project accurately without comprehensive jurisdictional data makes this a complex process.
But a more accurate property tax forecast makes property tax planning easier, which can help maximize value across your organization. We sat down with Kevin Grad, Senior Director of Technology at Rethink Solutions, to discuss the top challenges of property tax forecasting and budgeting.
During forecasting and budgeting season, you’re creating a forecast across your entire portfolio. However, you may have varying levels of completeness for the data in each jurisdiction. That’s primarily because different jurisdictions operate on different property tax years.
Consider this scenario: you’re beginning your initial forecast in October. Some of your properties are in California, which has a property tax calendar that runs from July to June. You’ll have a different data set – and different data gaps – for your California properties than you will for, say, Alabama, which runs on a November to October calendar.
This begs two important questions, which we explore below.
For those working with assessment-based forecasts, you may have last year’s values (but not this year’s) for some of your properties. Similarly, you may have this year’s value for some properties in some jurisdictions, but not this year’s tax rates. For those doing a tax-based forecast you may only have last year’s taxes, or half of the current year’s taxes (the first installment), while the 2nd half is not yet known. The data you have will influence the assumptions you use in your forecasts in varying jurisdictions and states.
Since you lack complete data from different jurisdictions, you need to have a way to mark whether values are projected or actual across distinct jurisdictions. And, if you’re working in spreadsheets, you'll need to track this information across individual sheets.
Not only do you need to track this data, but you also need a way of reforecasting once you have updated values. For companies that are managing 100s or 1000s of parcels and properties, keeping everything straight quickly becomes a challenge.
When creating a projection, you may be taking last year’s jurisdictional data (or a historical trend of data) to project next year’s data. Because assumptions are typically the same at the jurisdiction level, companies will often apply a blanket methodology jurisdiction-wide.
In different jurisdictions, the assumptions you’ll use for your forecasting and budgeting will be different. For example, the tax rate may change differently in New York vs. California year over year. Perhaps you expect the tax rate in New York to increase by 3% and 5% in California. In this example, you’ll use these values accordingly to trend the tax rate in each state. (It should be noted, however, that you may complete your assumptions at a more refined jurisdictional level, rather than the state level.)
But how do you anticipate the tax rate changes in each of these states? You would try to trend them to forecast the new rate for New York and California. As well, third parties may advise you in this process, though they won’t know the actual rates, either.
This is also true for values, which trend differently from jurisdiction to jurisdiction.
After completing your projection at the jurisdiction level, you’ll likely go back and get more granular by location (and/or jurisdiction). For instance, you can go back and adjust a forecast if you know you have an abatement or a pending appeal in a certain jurisdiction. Or, you can make adjustments to a forecast if you know you’re doing construction or improvements to a particular property, as the value will change from one year to the next.
However, these nuances are typically done as one-offs and retroactively. That’s because the “bottom-up approach” - starting with each property or parcel on its own and working up - would be a slow and tedious process. But these differences in tax rates and values, along with jurisdiction-level incentives and abatements, must be accounted for to ensure an accurate forecast. And for multi-property portfolios, this is an often-overwhelming amount of data to work with.
Clearly, forecasting and budgeting is a difficult, time-intensive and data-heavy process. So how can you optimize this process? That’s the topic of our next post.
Kevin Grad is the Senior Director of Technology at Rethink Solutions.
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