Healthcare revenue cycle
A healthcare billing firm checks insurance payments for several medical groups, looking for claims that were underpaid. They were using an aging reporting tool. Every new client meant weeks of manual setup, and analysts spent their days waiting on slow reports they could not change.
Outcome: Totals match the old system within about 1%, so the firm could switch over with confidence. The heaviest reports load about 4 times faster. Adding a new client is now a settings change, not a custom project.
Read the full case →Professional services (engineering)
A national engineering firm needed current financial and project numbers across all of its offices. The nightly data refresh was slow, and some important information, like performance targets and employee details, lived in spreadsheets that nobody owned.
Outcome: The nightly update stays quick. Edits are saved in seconds and show up in reports within minutes, so finance and operations work from the same numbers.
Read the full case →K-12 online education
An online education provider had about 80 reports, each pulling and calculating its own numbers from the same handful of systems. The same figure came out differently in different reports, and nobody could tell which one was right.
Outcome: Each number now has one definition. Leadership tracks 14 key measures from one trusted scorecard, and there is a clear, repeatable path for moving the remaining reports.
Read the full case →Healthcare payments
To recover money from underpaid claims, you first need to know what each claim should have paid. But the insurers' price lists were incomplete and inconsistent, so that number was often a guess.
Outcome: More than 95% accurate: on average, predictions land within about 4.5% of what was actually paid. For the hardest insurer to predict, accuracy rose from about 14% to nearly 90%.
Read the full case →Healthcare staffing
Nurse managers in nursing homes and hospitals build 4 to 6 week schedules by hand. They juggle how many patients there are and how sick they are, required staffing levels, certifications, rest rules and fairness, and the same people end up covering the weekends, nights and holidays nobody wants.
Outcome: The scheduling engine is finished and checked by about 1,190 automated tests, and the app around it is being built. When a schedule cannot be fully covered, managers see the reason with the arithmetic behind it, for example how many shifts need a credential that only one available person holds.
Read the full case →K-12 education
Teachers rebuild seating charts by hand around IEP and 504 accommodations, hearing and vision needs, students who must be kept apart, and a mix of abilities at each table. One change can undo an hour of shuffling.
Outcome: In daily classroom use, backed by more than 595 automated tests. When a teacher's rules conflict, the app says which ones and why instead of quietly breaking one.
Read the full case →Small business finance
An owner-led business ran on QuickBooks Online and spreadsheets. Month-end numbers took days and were out of date when they arrived.
Outcome: Current financials on demand, without manual exports.
Read the full case →Post-acute care
Life plan communities and skilled nursing facilities needed to track quality measures, staffing and census without waiting for monthly reports.
Outcome: Where DashPoint started. Our founder spent 18 years in healthcare IT before DashPoint, and that background still shapes how we approach healthcare data.
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