There’s a lot of talk about employees wanting much more flexible work schedules, and a lot of that is thanks to the emergence of companies like Lyft and Uber that allow people to work on their own schedules. But that ability still doesn’t exist for the rest of the world, especially when it comes to hourly jobs with rigid schedules.
But that doesn’t mean that employees don’t want those kinds of schedules — or that they vary a lot — and that’s the reason why Sanish Mondkar started Legion. The startup uses large amounts of data, all the way down to the weather near a store, to try to predict how busy it will be and how to intelligently staff that store and prepare for the foot traffic. It also works to sort out the best possible schedule for each employee, whether they want to work a regular shift at the same hours or vary from week to week and trade shifts a lot. The company is rolling out with Philz, one of Silicon Valley’s favorite coffee projects, to try to prove out such a concept.
“You can recognize the fact that there are some employees on your roster that are looking for predictable, 40 hours a week, with full benefits,” Mondkar said. “Others, today especially, are on the opposite side of the spectrum and want gig-like jobs, owning their schedule. Legion lets you provide that full spectrum of options. Employees choose where they want to be on that spectrum. It leads to better retention, an empowered culture, that to me is very important going forward for any business that employs a large hourly workforce.”
To continue to roll this out, Legion has raised a $10.5 million series A led by Norwest Venture Partners, with Norwest’s Sean Jacobsohn joining the board. Earlier investors First Round Capital, XYZ Ventures, and Webb Investment Network also participated in the financing round, which has helped flush the enterprise startup with the kinds of capital it needs to expand beyond just a business like Philz and into the larger hourly retail field.
Legion’s goal at the end of the day is to try to accurately predict traffic and labor forecasts, helping each employee find the slot that fits them best for the schedule and lifestyle they want. By starting there, Mondkar wants to try to help employees feel better about their jobs and their lives — which, in the end, helps them be happier at their jobs and deliver a better experience to customers. While there may have been some stabs at intelligent scheduling, it’s largely been on the managers to spend the nearly dozen hours to ensure that everyone gets what they want.
“The solution you would design today, versus three or even five years ago, would be very different because the kinds of enablers that are uniquely available today,” Mondkar said. “Machine learning and AI is at a point that’s at least accessible in a form that can be applied to solve these problems. Both need a lot of data, and data now — especially in retail thanks to the adoption of cloud point of sale devices and traffic counters — is available that just wasn’t available three or five years ago that would drive these algorithms.”
For starters, the company has begun deploying in Philz as a proof-of-concept to show that it ends up having a positive impact on the workforce. Philz CEO Jacob Jaber wasn’t able to articulate exactly why it took up until recently for a product like Legion to exist, but said it was an issue for the company — and any retail company — that was dying for some kind help. The other part of the equation, he said, was that it had to be constructed with all sides in mind: the business, the manager, and the employee.
“You need to think more holistically and you have to have empathy for multiple parties,” Jaber said. “I’d say there hasn’t been a lot of progress in the workforce as a whole and I think they’ve been left behind to some extent and working class. I think [businesses] are now getting to scratch the surface in thinking about them more and how we can make sure as a company and as people we’re respecting them and giving them a very good environment to work and grow in. Scheduling is a really big part of that.”
There will, of course, be challenges for Legion. Over time, employee priorities may change and the service will have to keep up with that. It makes sense for Legion to plug into other HR dashboards like Zenefits for now, but they may see the opportunity to go after the problem with a robust set of data on employees. There are also a lot of startups trying to create a simple employee scheduling application, such as When I Work, that may see an opportunity in the low-hanging fruit that large public data sets and more accessible machine learning tools have to offer. Mondkar’s hope is that starting with Philz as a launching point and eventually gunning for a schedule that fits everyone’s needs automatically will be the one that wins in the end.
“This is basically a very large problem that impacts a lot of lives and a lot of people,” Mondkar said. “The core of that problem, scheduling and matching people optimally and in a consistent manner, is a very fundamental step toward solving that problem. Today, as I was saying before, approaching that problem in a whole new way makes a lot of sense.”