Ando

Every restaurant manager knows the feeling. It’s 11:45am. The lunch rush is about to hit. Two people called out sick. One employee is late. Someone else texted saying they can’t make their shift. The dining room fills up anyway. None of this is surprising. The lunch rush arrives around the same time every day. Weekends are always busier. Seasonal spikes show up like clockwork. Demand, it turns out, is incredibly predictable. Staffing isn’t. At Ando, one thing we keep noticing when we look closely at hourly work is how stable the demand side of the business actually is. Most restaurants can tell you with surprising accuracy what Tuesday lunch or Saturday dinner will look like. And this is not just a restaurant problem. The same pattern shows up anywhere supply and demand fall out of sync - retail floors, logistics networks, and even healthcare systems. But the staffing side of the equation is chaotic. Managers are hiring while they’re already understaffed. Schedules get built quickly, often in spreadsheets or text threads. Workers are juggling school, childcare, second jobs, and transportation. The result is a constant mismatch between when customers show up and when the right team is actually on the floor. You see it everywhere: -Shifts that can’t get covered -Last-minute schedule changes -Burned-out managers -Workers who can’t rely on their hours -Lost revenue because the store simply isn’t staffed when demand arrives It’s one of those problems everyone in the business feels every day, but somehow almost nobody talks about. What makes it stranger is that other industries solved this problem a long time ago. Logistics companies don’t guess how many trucks they’ll need tomorrow. Airlines don’t send planes into the air without knowing exactly where they’ll land. Entire systems exist to match predictable demand with the right resources at the right moment. That shift didn’t happen by chance. It came from better data, better systems, and now increasingly, AI that can predict demand and allocate resources in real time. But in hourly work, we still mostly rely on guesswork. Managers do their best. The tools just weren’t built for the reality people live in. At Ando, we’re trying to change that. The goal is simple: help stores staff the day they’re actually going to have, and help workers get schedules that actually fit their lives. #WorkforceAI #FutureOfWork #AI #Labor #HourlyWork

At Ando, we keep coming back to the same thing: hourly hiring still runs on guesswork because it runs without real labor intelligence. If you’re reading this from a more traditional professional role, it’s easy to assume work is stable. You have one employer, a predictable calendar, and if something changes, it’s usually a meeting, not your paycheck. Hourly work is different. In many roles, hours change week to week, shifts get edited late, and a worker’s “availability” is constrained by childcare, transportation, school, and often a second job. A small schedule change can force someone to choose between two shifts to which they are already committed. And yet most hiring still relies on static resumes, generic job posts, and timing luck. Finding a candidate with the right skills and the right availability to see a help-wanted ad at exactly the moment an employer needs them is almost impossible. That kind of serendipity is not something on which businesses can rely upon. What we need is a persistent, verified view of the workforce: who people are, how they actually perform, what schedules work for them, and when demand really exists. In restaurants, ~40% of hourly hires don’t make it past 72 hours. Turnover in many frontline roles runs ~130–150% annually. And when many workers juggle more than one job, even a small schedule change can create a chain reaction. At Ando, we’re trying to replace “timing luck” with labor intelligence so the right people can find the right roles, and schedules don’t break the moment real life shows up.

Hiring today is kind of like speed-dating in the dark. When a manager needs coverage for a shift, they usually only see the small slice of people who happen to apply at that exact moment. Meanwhile, a lot of great workers are out there, they just are not job hunting on the same day a shift opens up. That’s a systemic flaw, and even sophisticated recruiting platforms haven’t solved it. They optimize for who’s raising their hand right now, not who’s actually the best match overall. It’s like apartment hunting by only looking at listings posted today. And for workers, it’s a guessing game too. A job post rarely tells you what you really need to know: - Is the schedule consistent? - Will your availability actually work with what the job requires? - If you show up and do great work, does that lead to more hours and more trust? Someone once told me, “We’re not short on good people. We’re short on a way to find them at the right time.” That line has stuck with me. It captures the real issue. That gap creates the same loop over and over: rushed hires, mismatches, churn, and managers right back to scrambling. The costs add up fast. Replacing an employee costs 0.5 to 2 times their annual salary. For skilled hourly roles, replacement can run 75 to 100 percent of annual salary once hiring, training, and lost productivity are included. Total impact is often 90 to 200 percent. Turnover costs U.S. businesses more than $1T annually, plus an additional $1.8T in lost productivity. At $60K per year, replacement typically costs $30K to $45K, with total losses of roughly $54K to $120K. This is not a people problem. It is a systems problem. Hiring runs without labor intelligence, especially across the hourly workforce. There is no shared, verified view of identity, reliability, performance, availability, and real demand across the market. So we keep guessing. That is why we are building Ando. Not another job board. Not another scheduling tool. A labor intelligence layer that helps dependable workers and great operators find each other at the right time, with real data behind the match. #WorkforceAI #FutureOfWork #HourlyWorkforce #WorkforceTech #LaborIntelligence #AI #Hiring #FrontlineWorkers

Most people on LinkedIn have one job – one employer, one role, one calendar to juggle. But that’s not true for everyone in the hourly sector. More than 5% of employed Americans are working more than one job. Roughly one in twenty. And that stat has been climbing again since the pandemic. Looking specifically at hourly work, the picture gets even starker. In a 2025 survey of hourly-paid workers, 34% said they rely on more than one job to get by. Not because they’re chasing a hustle-driven ideal, but because one paycheck doesn’t reliably cover the basics, hours can shift week to week, and gaps show up where benefits or steady schedules used to be. The hardest part isn’t just the extra hours. It’s the logistics of trying to make two schedules (or three or four) fit into one life. A last-minute change isn’t just annoying; it can throw everything off – childcare, rides, the other shift already committed to. It makes stability feel out of reach. At Ando, we’re building around that reality. Most scheduling tools still assume people have one job and unlimited flexibility, and then everyone is surprised when it falls apart. We’re building for a different reality. We’re making a work schedule something people can actually plan around. Fewer last-minute surprises for workers, fewer staffing scrambles for managers, and a calmer day to day for everyone. But it’s more proactive than that. It’s a work schedule built around people’s personal responsibilities and needs in advance. Ando is bigger than scheduling software. Hourly work is changing fast. More people are stitching together hours across employers, and time is becoming the thing everyone is trying to manage. The companies that win will treat workers’ time with the same seriousness they treat costs and operations. #WorkforceAI #FutureOfWork #HourlyWork #FrontlineWork #AIForGood

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.

I started Ando because hourly work is the backbone of so many businesses, but the way we schedule and staff people has barely changed in decades. Managers are still piecing together shifts with spreadsheets and texts, and workers are left with hours that change week to week. That is not good for anyone. Advances in AI now make it possible to understand demand patterns with high accuracy and support scheduling decisions that used to require guesswork. LLM driven, agentic systems can support both workers and businesses with clearer decisions and more stability. We are building Ando to help teams match staffing to real demand and to give hourly workers schedules for which they can depend. It means fewer last minute scrambles for businesses and more steady hours for people. I am excited to share that we have formed an advisory group to help us on this journey. These leaders have built great companies, scaled important technology, and helped shape the future of work. I am grateful for their time and guidance. Grateful to partner with:  Niren Chaudhary  Jim Messina  Loni Mahanta  Andy Mutz  Adam Sah Full release below. https://lnkd.in/gTdMTqjS www.ando.work #AI #FutureOfWork #HourlyWorkforce #AIAgents #Leadership #WorkforceTech #Restaurants #Retail #AndoWork

Fireroad Ventures is pleased to announce our investment in Methodic. to bring order to chaos for W-2 shift-workers and their employers. Read more about what Paul Wellons, Frenchie Audette, Adam Sah and team are building in our full announcement at: https://lnkd.in/g8wS93wT