The Covid-19 crisis is having a violent impact on energy and raw material markets. But the traditional concept of price volatility doesn't capture the many aspects of that instability, and is actually misleading in some cases. Chief Procurement Officers need finer insights to optimize buying decisions in the post Covid-19 world.
For continuous intelligence applications, the relationship between prediction and prescription is richer than described in the classic framework of analytics capabilities:
It’s always fun to watch business consultants and IT companies search for the next buzzword - throwing candidates to the wall, hoping that one of them will stick and help them own the next big thing. (IBM is particularly adept at the game, rotating buzzwords every two years.)
Data scientists are waking up to the fact that combining multiple, relatively simple predictive models is often more efficient, when tackling a time series forecasting challenge, than using the latest super-duper neural network.
Datapred's machine learning software for direct material procurement helps companies save 3-5% off their commodity, energy and raw material costs year over year, through a unique combination of price predictions and constraint optimization.
