This is an exciting example from NXP of how machine learning (ML) can enhance and support the work of product managers and Line of Business decision-makers. NXP was interested in predicting the product lifecycle (Introduction, Growth, Maturity, and Decline) of newly introduced products. This enables to further allocate R&D funding to the products generating the highest amounts of sales or products with the highest potential to maximize the ROI for R&D activity. Additionally, NXP can predict long-term sales on a micro level, which gives them a bottom-up look at how their revenue changes over time.
On the ML side, the blog discusses novel method developed to predict the product lifecycle while taking into consideration a cold start. It introduces a point cloud-based method and also discusses the introduction of additional features, including product description as a bag of words to tackle the cold start problem for predicting the product lifecycle curve.
“… [the] Amazon Machine Learning Solutions Lab … delivered a sales forecast model, which complements our current way of manual forecasting, and helped us model the product lifecycle with novel machine learning approaches using Amazon Forecast and Amazon #SageMaker.” Bart Zeeman.
