2018 Best Practices Awards

“ We realistically wanted to capture data in a way that made us useful and better at parts of our job . If you give people a reason – the why – it helps .”

BEST ENFORCEMENT PROGRAM Vermont Department of Liquor Control

BY HILLARY RICHARD

“ On any given day , we can have as many as 7,000 active outlets engaging in the sale of alcohol or tobacco – and I have 11 investigators ,” says Chief Skyler Genest , of the Vermont Department of Liquor and Lottery Office of Compliance and Enforcement .

In his first year on the job as chief , Genest realized quickly that the department needed to evolve alongside the state ’ s burgeoning beer industry . Genest , who came from a computer science and law enforcement background , sought an efficient way to figure out how to allocate investigators across the state to the places they ’ re most needed .

When he met a state programmer working with predictive analytics in an engineering context who used math to predict where deficiencies would occur in infrastructure , Genest realized they were doing the same thing with that data he wanted to do in the law enforcement and social science landscapes . Genest felt there was a missed opportunity somewhere to compile everyone ’ s data and get a better idea of alcohol issues statewide .

The Vermont Department of Liquor Control found an affordable , modern solution to its data collection woes : they built an app for that . Project RABIT ( Resource Allocation Based on an Intelligence Toolkit ) started looking at ways the state collected data .

Previous compliance and inspection programs lived and died on paper forms that ended up collecting dust in filing cabinets – so the first step was to do away with inefficient paper forms . Then , they had two specialty iOS-based apps built . The first app was configured for all of their compliance- and inspection-based law enforcement programs ’ reporting , like statewide DUI arrests , population information , geospatial data , refined internal datasets ( such as licensing info ), public compliance and investigative data . A second app analyzed the data points , found relationships and created rankings of licensees on a weekly basis to determine which establishments

– CHIEF SKYLER GENEST

were most likely to have issues .

Project RABIT created a public-facing interactive dashboard that translated the data visually and created predictive models . Mining all of this and finding relationships and trends inside the data was a monumental task made very simple by technology .

“ We call it our strategic inspection model ,” Genest says . “ Everything before we transitioned to it on May 1 , 2017 , was randomized or based on gut instinct . We have statistics now to show how much more effective we are . We were observing violations about 2 % of the time during inspections . Since May 1 , we ’ re just under 14 % because of the app . It shows how much more effective we can be with just a little bit of help .”

Adjusting to the app system was a minor culture change , but what helped was that everyone knew they weren ’ t just introducing technology for the sake of technology .

“ We realistically wanted to capture data in a way that made us useful and better at parts of our job . If you give people a reason – the why – it helps ,” Genest says . “ This was a really low cost innovation . We ’ re talking about a couple thousand dollars for this strategy , so not all technology solutions have to be multi-million-dollar contracts .” •

12 StateWays | www . stateways . com | September / October 2018