Amid Rising Economic Uncertainty, Legion Launches 60-Day Free Trial of Demand Forecasting Solution
On November 10, 2022, Legion Technologies announced a free 60-day pilot of its demand forecasting solution, covering up to 50 stores and 10 demand drivers, aimed at helping businesses optimize labor budgets during uncertain economic times. The solution is based on Legion's 2022 Seasonal Hourly Worker Report, where 87% of managers reported unchanged or increased pressure heading into the upcoming holiday season.
Palo Alto, California — Legion Technologies, an innovator in workforce management (WFM), announced on November 10, 2022, that it is offering a free 60-day pilot for itsdemand forecastingsolution, designed to help organizations maximize labor efficiency and accurately forecast demand at 15-minute intervals across all stores and customer touchpoints. The free pilot covers up to 50 stores and up to 10 demand drivers (such as product sales, transaction volume, and store traffic) and works seamlessly with existing workforce management solutions.
In times of economic uncertainty, optimizing labor budgets is critical. According to Legion's recently released2022 Seasonal Hourly Worker Report, 87% of managers said they feel the same or more pressure heading into the holiday season compared to last year. Economic uncertainty and reduced consumer spending/decreased foot traffic ranked among the top three reasons. One-third of managers said the most effective support employers can provide is equipping them with automated demand forecasting tools.
"Traditional WFM solutions and manual spreadsheet-based demand forecasting methods cannot handle the complexity and volatility of today's environment. They fail to incorporate weather and local event factors that significantly impact demand. In the current economic climate, accurate demand forecasting is essential for optimizing labor costs," said Sanish Mondkar, CEO and founder of Legion Technologies. "To accurately forecast demand, businesses must automatically integrate store-specific operational data along with weather and local event information. Based on our benchmark data, a 1% improvement in forecast accuracy can lead to a 0.5% reduction in labor costs, a 4% increase in sales conversion, and a 5% improvement in customer satisfaction."
To help businesses improve agility, accuracy, and labor efficiency, Legion's demand forecasting engine offers the following features:
- Provides granular, store-level forecasts:The solution accurately forecasts demand every 15 minutes across all customer touchpoints and stores, enabling intelligent automation.
- Integrates hundreds of thousands of data points:Data includes operational data and external data (such as weather and local events) that influence demand.
- Self-learning with continuous improvement:Legion Demand Forecasting continuously optimizes as new data becomes available, instantly generating updated forecasts and labor guidance while allowing human intervention.
- Seamless integration with leading WFM solutions:No need to replace existing systems or change management processes; the module can also be used standalone.
For more information about the free 60-day pilot of Legion Demand Forecasting, clickhere。
About Legion Technologies
Legion Technologies provides an industry-leading workforce management platform that helps businesses simultaneously maximize labor efficiency and increase employee engagement. The Legion WFM platform is intelligent, automated, and employee-centric, and has been proven to deliver a 13x return on investment by optimizing scheduling, reducing turnover, and improving productivity and operational efficiency. Legion delivers cutting-edge technology in an easy-to-use platform and mobile app that employees love. The company is backed by Norwest Venture Partners, Stripes, First Round Capital, XYZ Ventures, Webb Investment Network, Workday Ventures, and NTT DOCOMO Ventures, and has been named one of Inc.'s fastest-growing private companies in America. For more information, visit https://legion.co or follow its LinkedIn page.
