At Honor, we’ve used machine learning since 2016 to drive predictable schedules and consistent hours for each Care Pro who wants them. The impact: ✅ Higher retention ✅ Better care ✅ Happier families Predictable schedules = better lives. And better lives = better care.
Most hourly workers would take a 20% pay cut for one thing: A predictable schedule. Studies from Princeton and Harvard show that workers value stable scheduling so much that they’re willing to trade a fifth of their pay to avoid last-minute shift changes. This is the scheduling crisis no one’s talking about. Nearly 1 in 5 U.S. workers face unstable hours—especially in retail, food service, and healthcare. This is a big deal in Honor's neck of the woods—home care. One of the earliest problems we identified that needs to be fixed is how to create stable schedules. And the massive fragmentation of our industry, and many other hourly work industries, is a big part of the problem. It hits part-time workers, women, and people of color the hardest. The cost? • Income swings up to 33% week to week • Mental health strain (1 in 3 workers) • Kids missing 6 more days of supervision a year It’s bad for workers and bad for business. When Gap Inc. tried predictable scheduling: → Productivity rose 5.1% → Absenteeism dropped → Retention improved The myth: workers just want higher pay. The reality: they want stable pay—which comes from stable hours. Stable pay brings higher TAKE-HOME pay. You see, that's the thing. It's about take-home pay, not hourly rate. And it's about knowing that it'll be there next week, too, and that you'll still be able to afford that lunch or toy for your daughter. So how do you scale that? AI. At Honor, we’ve used machine learning since 2016 to drive predictable schedules and consistent hours for each Care Pro that wants them. The impact: ✅ Higher retention ✅ Better care ✅ Happier families This isn’t just a tech fix. It’s a lifestyle fix. It's a better job. Predictable schedules = better lives. And better lives = better care. I'm curious—have you seen this in your industry, too? How did you address this critical challenge?