In sectors like food service and retail, where front-line employees work hourly and customer traffic is highly variable, the conflict between businesses’ need for flexible staffing and employees’ desire for predictable hours and incomes has led to increased labor activism and efforts to regulate variable scheduling. Even though most employees with variable schedules don’t have a problem with them, they can be a hardship for low-income employees struggling to make ends meet, or parents trying to schedule around the needs of their children. The controversy has led to some major retailers dropping the practice of “on-call” scheduling.
Fortunately, a growing number of technological solutions are coming to market to help organizations set and communicate schedules in ways that are more predictable and less disruptive to their employees. The latest of these is a startup called Legion, which recently raised $10.5 million in funding for its platform. Founder Sanish Mondkar tells TechCrunch’s Matthew Lynley that he hopes to use big data to crack the challenge of intelligent scheduling once and for all:
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. …
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.