Sanish Mondkar realized something wasn’t right when his data points didn’t line up. He was looking at workforce engagement data and noticed that more and more people were looking for flexible hourly jobs at the same time that many employers were seeking hourly workers. What was the disconnect? The data paradox became Sanish’s obsession for the next six months as he delved deeper into the puzzle.
“I was noticing retail employers putting out their ‘Hiring’ signs everywhere and wondered, what’s going on?” Sanish said. “These employers are struggling to hire and retain, while employees are often leaving or have to take multiple jobs because they aren’t getting the flexibility in schedule that they need.”
Sanish ultimately decided that workforce engagement in these environments was fundamentally broken—and fixing it became the mission of his new entrepreneurial journey: Legion, which upgrades hourly workforce engagement for employers and employees alike. The Legion platform automates end-to-end workforce operations–labor forecasting, scheduling and matching the best employees to the right shifts.
Legion was a perfect match for Sanish as well. He has a passion for building platforms that harness network effects and he saw a way to use such a platform to make life easier for the 78 million hourly workers who now comprise 56 percent of the U.S. workforce and the companies that hire them.
Sanish has worked as an executive at SAP and Ariba, where he built the largest B2B network in the world–one that today facilitates transactions amounting to $1 trillion a year. Legion is his first startup. We sat down with Sanish to hear more about his entrepreneurial journey and the lessons he’s learned as he has built Legion, which is now live across all locations of Philz Coffee, one of the Bay Area’s favorite coffee places.
Tell us how you discovered this hourly workforce pain point and how it inspired you to start Legion?
I realized that one of the largest problems from an expense management standpoint, especially in retail, is related to labor: finding and retaining workers. It was shocking to me how big the problem was and how little technology has helped to improve it. There is a lot of discussion about the “future of work” lately, particularly in the tech media, but not much attention is given to the future of hourly work. I was fortunate to meet investors who were paying close attention to this space and were aligned with my thesis. Meeting Jacob and partnering with Philz Coffee early on helped immensely in building early product-market fit. During the series A round, it was great to work with Sean Jacobsohn and Parker Barrile at Norwest, who immediately got our model due to their deep HR and LinkedIn backgrounds.
What are some big challenges facing employers in the hourly workforce market?
For starters, there are the age-old challenges of high employee turnover and the high cost of replacing those people. Then there are new problems impacting industries like retail and hospitality that hire hourly workers in large numbers. These problems include difficulty engaging and retaining the millennial workforce, who are seeking gig-like flexibility, modern technology and compelling work options. These problems are important to address because they have a big impact on employee satisfaction and productivity.
Legion focuses on engagement of the hourly workforce to help our customers accurately forecast labor demand and optimally match workers to work.
Was there an “a-ha moment” when you realized this was going to be your first venture?
It wasn’t a single moment but a growing realization based on conversations, research and data that gave me the conviction to step away from the corporate executive management path and start Legion. I met many hourly employees and heard their stories of needing multiple jobs to support themselves and balance work and life. Yet I also saw data that appeared to contradict that data, such as the high attrition rate in the hourly workforce, which often exceeds 70 to 80 percent.
How have enterprise software products changed over the past few years–and how is this transformation changing the future?
Enterprise software products have gone through a massive transformation in the past 10 years as they’ve moved to the cloud. The revolution of the next decade will be enterprise applications that are smart enough to make truly autonomous business decisions. Legion’s platform is a great example of these applications, which have a “brain” powered by deep machine learning and AI capabilities.
How is Legion applying machine learning and AI to build better workforce engagement?
Legion uses machine learning to accurately predict how much work needs to be done, by what roles and skills, etc. These forecasts are fully automated, they take into account external factors that impact customer traffic and they’re tailored to the unique attributes of every retail location, service or sales category. What’s more, Legion uses AI to automatically match these forecasts to the best workers based on a wide variety of factors like employee preferences, skills, productivity, labor compliance policies, etc. Then these rules can be easily customized to the unique policies and best practices of every customer. Legion’s AI engine continuously learns and improves the matching, resulting in improved optimization and better engagement.
Also published on Medium.