Case Study: Wells Lamont Reduces Forecasting Time by 33% with Intuendi

Improving Forecast Accuracy to Strengthen Decision Confidence

Wells Lamont, the glove company founded in 1907, needed a better way to manage demand forecasting as its business grew. Its planning team was spending about 15 hours each week on manual forecasting, with limited visibility into emerging demand patterns and difficulty turning forecasts into actionable decisions. To address this, the company turned to Intuendi’s AI-powered demand forecasting software.

With Intuendi, Wells Lamont automated and streamlined its forecasting process using predictive analytics and real-time demand signals. The result was a 33% reduction in forecasting time, from 15 hours to 10 hours per week, along with improved SKU-level insight and greater confidence in projections. This freed the planning team to spend more time on strategic planning and faster, data-driven decision-making.

Wells Lamont