Michigan selects Deloitte for $78 million unemployment system upgrade
Michigan’s unemployment agency on Tuesday announced it selected Deloitte to install a modern benefits system, though its existing platform is not yet a decade old.
Many states have replaced their unemployment platforms in the wake of the COVID-19 pandemic, but most such upgrades are to replace much older systems, sometimes dating back as far as the 1960s. Julia Dale, director of the Michigan Unemployment Insurance Agency, said in a press release that Michigan’s $78 million, 10-year contract with Deloitte is part of her agenda to maintain a “robust and secure system.”
“Already, the UIA is in better shape than at any time over the last decade – but that’s not good enough,” she said. “Michigan workers should be able to apply for benefits with confidence, so they can support their families without worrying about when or if they’ll receive benefits.”
Michigan’s new platform is to run on Deloitte’s Unemployment Framework for Automated Claim and Tax Services, or uFACTS, system, which is already used by 15 other states, including California, Florida and Massachusetts, according to the firm. Michigan officials said the upgrade will allow the unemployment department to “react to economic changes,” limit the need for custom coding and quickly communicate information across agencies.
The new platform, which is scheduled to launch in 2025, is set to replace the Michigan Integrated Data Automated System, or MiDAS, system. The state’s existing system has a track record of errors, including falsely marking 40,000 applications as fraudulent between 2013 and 2015.
Many other states overhauled their systems after their frailty was exposed during the health crisis, when record numbers of people filed claims after losing work during mass business closures. Among those states were Colorado, Wisconsin and Kansas, the latter announcing in April it’s replacing a 1970s mainframe with a cloud-based solution.
Many legacy unemployment insurance systems have confusing interfaces, poor interoperability and a lack of scaling capabilities, traits commonly blamed for generating application backlogs that in many states have tallied into the tens of thousands.
