Reflexis is introducing several new solutions to simplify, streamline, and optimize retail workforce management and store execution. Many of these solutions leverage Artificial Intelligence (AI) and Machine Learning, empowering retailers to drive improvements at every level of their organizations.
Annual- and period-level budget planning can be an iterative and time-consuming process for retailers. Reflexis AI Budget Planner provides retailers with a flexible and robust solution to create budgets for specific stores, departments, or resource groups. It also can aggregate and analyze relevant data, model layered “What If” scenarios, and use built-in configurable workflows to review and approve labor budgets.
This solution empowers store managers to identify gaps, trends, and opportunities in their staffing. Reflexis AI Staff Planner applies Machine Learning models to run staffing simulations based on given parameters, including efficiency targets, hiring freezes, and associate skills and utilization. AI Staff Planner then makes AI-influenced scheduling and staffing recommendations to maximize staffing efficiency for retailers.
(Release Date: Q2-2020)
By applying Machine Learning models to store data from point of sale systems, traffic counters, and workforce management and HR systems, Reflexis AI Performance Manager identifies patterns and exceptions in associate, manager, and team performance. Retailers can recognize and reward high performers in real-time, implement targeted best practice trainings, and respond proactively to dips or spikes in store productivity.
Retailers no longer have the luxury of long planning and testing cycles. Reflexis AI Decisions simplifies the pilot-testing process, by applying AI and Machine Learning models to pilot data sets. With AI Decisions, retailers can accelerate the process of building best-practice pilots, tracking performance in real-time, interpreting results, and scaling test initiatives.