Process analytics revealed that the client’s real order management process matched its documented process only 5% of the time. Standardised KPIs and process mining tools gave management the visibility to fix the deviations that mattered.
A new transportation lane cost prediction model and a stochastic optimiser replaced an unsuitable linear model for assigning orders to plants, cutting prediction error from 30% to 9% and saving millions in transport and operations cost.
Process analytics and predictive modelling optimised warehouse stock across production-to-order and production-to-inventory scenarios, cutting required warehouse space by 20% and improving loading efficiency.
Niagara Bottling unified siloed supply chain data with real-time feeds and actionable reporting, cutting decision time from days to minutes, improving truck loading time by 30% and saving over $7 million a year.
An electric vehicle technology company cut its warehouse space needs by about 20% through predictive safety-stock optimisation, a data-driven layout and overstock minimisation, with no new warehouse built or leased.
