Shifting to automated scheduling
By Glynn Davis
With the costs of employing people continuing to rise the need to accurately deploy labour across retail businesses is becoming increasingly critical to their financial success and ultimate success.
The Retail Bulletin recently met up with Sanish Mondkar, founder & CEO of Legion Technologies, at Retail’s Big Show, organised by the National Retail Federation (NRF), to hear how his solution is using AI to automate the process of WFM (Workforce Management) to the benefit of both businesses and employees.
One key area of focus is scheduling, which he highlights as a problem that absolutely needed solving because retail has very high staff turnover levels and Mondkar says people move not because of wages but because they want a better work experience.
Never Miss a Retail Update!“Can they own their own schedule, or do they have to negotiate with their manager, and are they paid quickly. Managers can’t do this day in, day out, so we’ve automated it and solved the problem for retailers,” he explains.
The reality, according to Mondkar, is that it’s a tricky problem to optimise labour through automation. For scheduling associates’ working hours requires managing many inputs including budgeting the demand through the day, adhering to compliance regulations, giving enough visibility to staff of their hours, and ensuring every employee has a say on how they work. This has to be combined with an understanding of the roles of each individual, their productivity capabilities, and their individual work preferences.
“It’s a very hard problem and it needs to be automated. It’s a big maths problem and we use AI to solve it. AI is important because it enables you to automate the decision-making. It’s all based on data,” he says.
The solution takes internal unstructured data and combines it with third-party data that includes the likes of weather reports and school holiday dates. Basically anything that could impact the work environment.
Mondkar suggests many AI businesses don’t have a data strategy or a pipeline whereas in contrast at Legion it trains 300,000 AI models each week that enable it to currently forecast 1.6 billion data points a week. Through this 1.5 million shifts per week are automatically determined for various retailers and brand owners.
“In the pilot phases the feedback has been phenomenal. Transformational for businesses. Nike is rolling it out in waves to its business around the world,” he says, adding that initially implementation is for store-based employees but distribution centres and call centres will also ultimately benefit from the solution.
It is the hourly workforce that is most impacted by the empowerment it provides and often in retail these are a younger grouping. They have particularly welcomed the self-service style approach provided by Legion, with its interface being an app.
The interfaces that have been developed are also benefiting managers through their ability to use the conversational layer – in the form of a Gen AI assistant – to change the schedules of employees through a simple conversation. This is especially useful as most users are deskless and reliant on operating/managing through their devices when on the move.
