March 28, 2005 By Julie Ritzer Ross
That has changed, however, thanks to the DOR's Local Government Sales Tax Information System. The homegrown, Web-based system lets each jurisdiction generate customized local tax reports by mining local sales data compiled by the department. It also lets them obtain a variety of standard monthly tax reports and vendor profiles.
The DOR knew improvements in its reporting methodology were warranted.
"Quite a few years ago, the state auditor was here on an annual visit and pointed out that we needed to do something to identify retailers whose revenues varied from month to month," said Neil Tillquist, director of the DOR's Taxpayer Service Division.
In 2000, the DOR decided to upgrade the reporting process that served the state's local tax jurisdictions.
"The comments from the state auditor validated the automation idea, and because we wanted the solution to be dynamic, we opted for a Web-based platform," Tillquist said.
The DOR asked several jurisdictions, all of which actively review sales tax accounts on a regular basis, to test the sales tax information system for several months beginning in January 2001, he said. When it became clear later that year that no substantive changes to the technology were needed, the DOR rolled the system out to all 241 jurisdictions.
"With this version of 'online banking' in place, we have a better handle on local sales tax procedures," he said. "Even more importantly, we're doing a more effective job of giving our jurisdictions the information they need than was ever possible with paper-based reporting."
Mining the Data
Tillquist said one of the system's more popular components is its data-mining function. The DOR surveyed local tax jurisdictions about reports they would be interested in obtaining by mining DOR's database. The department designed a series of reports and a password-protected Web site that serves as a portal to the online tax collection data warehouse.
Based on the survey's feedback, the system's data-mining component --its most comprehensive feature -- was configured to produce "comparison," "retailers with highest revenues" and "highest variance of revenues" reports.
Tillquist said the data-mining aspect of the system has proven particularly advantageous to the jurisdictions employing it. Administrators report the ability to look at "what-if" scenarios allows them to make informed business decisions regarding potential tax collection changes, as well as to formulate more realistic budgets.
"Suppose a local government is considering making grocery stores exempt from paying food sales tax, which is a very realistic scenario," Tillquist said. "The administrator could easily create a comparative report of taxes paid by grocery stores for the last year and current year, giving him or her a better idea of how much revenue would be lost based on the exemption and whether it would be a good idea."
Similarly, in cases where local governments want to set a lodging tax or local improvement district sales tax within a specific part of town, administrators can view a report of sales by hotels or sales within certain ZIP codes to see what the impact would be.
Administrators also use the system to produce trend analyses that permit them to make educated guesses about future revenues, based on rates of change between the current and prior year, as well as to estimate the effect on revenues should a particular business in their jurisdiction close its doors.
Other aspects of the solution are yielding benefits as
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