Where does AI meet life at the lakehouse or on the boat? One story of where they meet is Polaris – a “powersports” equipment manufacturer- which means they make boats, ATVs, and snowmobiles. They were using AI to help forecast retail sales, but doing so did not consider some operational and supply constraints (cost and availability of steel or aluminum for example) and other financial drivers. And this need was based in finance: the office of the CFO – and they didn’t have their own AI team. So they turned to OneStream. Already using OneStream for their budgeting and forecasting, they tried OneStream’s Sensible Machine Learning (Sensible ML) solution.
Upping the Game from Driver-Based Planning
Driver-based forecasting was in place at Polaris, but didn’t (and couldn’t) consider a host of constantly changing operational factors (the price of steel, availability of chips, production constraints, etc). But AI can handle all those other aspects of production – and when you look closer and are better at all these variables – you get more accurate forecasts. And that is exactly what happened at Polaris: 14% more accurate to be specific. That, by the way, means lower inventory, better-working capital and better planning conversations.
AI Alive in Finance
One fun aspect of this boat story is that it happened all in the domain of finance. The finance team at Polaris sets parameters, tweaks models and sees results and plans at a level and cadence that works for them, unencumbered by time or cost constraints from IT. Specifically, that means they are able forecasting down below simple product level forecast to named models, campaigns and more.
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