Case Study: Polaris achieves faster, more accurate forecasting with OneStream Software's Sensible ML

Polaris - Customer Case Study

Polaris Inc., a global leader in powersports, faced a rapidly changing business environment after COVID-19 and supply‑chain disruptions flipped its supply/demand model. Finance relied on a highly manual, driver‑based revenue forecasting process spread across multiple Oracle Hyperion applications, creating data movement, maintenance and speed challenges that limited agility and accuracy.

Polaris moved to OneStream and piloted OneStream’s Sensible ML on a 12‑month shipped‑units forecast using historic weekly data for 181 products plus commodity and event variables. Sensible ML generated thousands of models, produced the most accurate forecasts, and cut forecast cycles from days to hours while providing transparent driver insights. The solution is now being productionized within Polaris’ unified planning platform to expand horizon and feature inputs for further accuracy and efficiency.

Polaris

Melanie Hermann

Director, Finance Process & Systems