If you’ve never worked an hourly job, it’s hard to grasp how broken hiring and scheduling really are

If you’ve never worked an hourly job, it’s hard to grasp how broken hiring and scheduling really are. A few numbers that should stop us in our tracks:

-In restaurants, ~40% of hourly hires leave within 72 hours. Three days.

-In many hourly roles, turnover runs ~130–150% annually.

-Every time someone leaves, it costs businesses $5,800+ in replacement and training expenses.

-Some stores lose $5,000+ per week simply because they’re understaffed at the wrong times.

-Zooming out, the U.S. has ~80M hourly workers and ~146B hourly work hours each year.

This isn’t “people don’t want to work.” It’s bad fit - on both sides. Workers take jobs that don’t match real life (hours, pay expectations, childcare, second jobs, commute). Managers hire in a rush because they’re short-staffed. Schedules get chaotic. The cycle repeats.

This is exactly what we’re building to solve at Ando.

We use AI to forecast demand for a given location, then turn that into schedules that fit real people. Not just availability on a form, but the preferences and constraints that actually determine whether someone stays - school pickup, a second job, or how many hours they need to make the week work.

When predictive demand and intelligent schedules are paired with better fit from day one, fewer people quit in the first few days, managers spend less time in panic mode, and workers get the hours they need.