Live from NRF Retail Converge: Automate Decision Making to Ensure Happy Customers and Employees Using AI-Powered Workforce Management
June 30, 2021
by Casey Castellanos
Retailers and employees are under pressure. Back in May, Starbucks made headline news as workers described understaffing, low pay for more work, and increasingly aggressive behavior by customers over COVID rules. Coming out of last week’s NRF Retail Converge event, we learned that many retailers are still struggling with these same challenges.
Stressed Out Employees and Unhappy Customers
Employees complained that the labor hours they were getting weren’t enough for the sheer volume of orders they had to produce. And managers were asking too much of them when they didn’t have enough people to do it all.
For Starbucks and many other retailers, things changed dramatically during the pandemic. The popular coffee vendor saw a huge increase in channel complexity – offering mobile orders, drive-thru, delivery, and in-person options. And the mix shifted. According to the article, mobile orders grew from 10-20% in 2020.
And COVID-19 added pressure. Nerves were raw for employees and customers, attrition continued to be high, and call-outs due to sick or quarantined employees added to the pressure.
Outdated Data Models and Manual Processes
The data models that organizations used to forecast demand and ensure appropriate staffing just couldn’t keep up with the complexity. One Starbucks shift supervisor said that the complexity wasn’t being adequately translated into labor hours.
Many large businesses still use manual operations to forecast demand and create labor plans, and they just can’t keep pace with the complexity retailers face today. Manual processes require significant effort from operations and finance teams, and the results aren’t very good. Often teams use spreadsheets or simple forecast models that rely on assumptions. They apply one general forecast even though a location’s characteristics may be very different.
One location might be in a crowded plaza, while another may be near a beach town. But, the locations look the same when using a general model. And, each channel may have very different demand patterns that are hard to discern manually. Many retailers still rely on YoY models. And those don’t work because everything changed with COVID-19. Simply throwing 2020 data out doesn’t work either because demand patterns have changed forever for many retailers.
AI-Powered Legion WFM
AI-powered WFM automates decision making and operations, which can lead to happier customers and employees. Using AI-based demand forecasting ensures proper staffing at every location, which decreases wait times. And AI-based scheduling can automatically create fully-compliant schedules that match employee preferences with business needs resulting in lower costs, happier employees, and lower attrition. Happier employees provide better service, which leads to happier customers. AI automated decision making frees up managers to focus on training their teams and interacting with customers.
To learn more about how Legion WFM can help your company, watch our session from NRF Retail Converge “Automate Decision Making and Ensure Happy Customers And Employees with AI-Powered WFM.”