Case Study: World's Largest Retailer's Supermarket Chain Achieves $10M Annual Savings with Zvolv

An Intelligent solution to optimize resources for a leading supermarket chain, driving significant cost savings and other datadriven insights

Zvolv worked with World’s Largest Retailer, a leading supermarket chain with more than 750 outlets, to address the complexity of managing frontline workforce planning across a large, variable retail network. The customer needed a better way to optimize staffing, employee rostering, and daily task tracking, since manual scheduling was time-consuming, prone to conflicts, and often led to over- or understaffing.

Using Zvolv IPA, Zvolv implemented three linked applications: an ML-based optimizer for resource forecasting, an automated rostering system, and a task/time tracking module with mobile attendance and feedback features. The solution reduced variable resources by 15% per store on average, delivering over $10M in annual operational savings, while also cutting store manager time by 30 minutes per day and improving consistency, visibility, and task quality across stores.