Netstock Integrated Business Planning launches new machine learning functionality
Netstock Integrated Business Planning (IBP) – formerly Demand Works – now offers customers the ability to predict the effects of promotions and other events on demand.
This exciting new Machine Learning based functionality helps customers to quickly understand the financial and operational impact of anticipated events on their business, ensuring agility and preparedness while minimizing costs.
What is the new Netstock IBP ML Casual Event Forecasting feature?
- Causal – It’s the first causal event forecasting capability to be added to the IBP solution
- Machine Learning – Utilizes “Random Forest Regression” and it is “trained” with previous events in similar items, regions, customers, etc.
- Easy – Unlike most machine learning functionality, you don’t need help from a team of data scientists.
- Useful – It will produce better forecasts, particularly for higher volume products
- Visible – You can see the estimated effects of previous events as well as the expected effects of future ones
A cool fact to highlight, since the ML in Netstock IBP is based upon training in a multi-attribute model, it will produce usable estimates of event effects for items or customers that have never been promoted.
Here’s how the new ML Casual Event Forecasting works:
- Create “event types” and associate them with items, customers, regions, etc.
- The ML technology “trains” on the historical events, learning event effects based on an ongoing comparison of the actual and expected values when the events occurred.
- The feature will then automatically estimate the effects of future events on demand.
Events such as consumer or trade promotions are associated with items, customers, and periods of time. Then, once trained with historic events, the system will accurately estimate effects for future events.
