Save on the manufacturing cost and control expedited expenses by determining the surged price pattern through predictive data analysis.
Read how GSPANN helped a California, US-based semiconductor manufacturer in determining the factors that impacted the surge in price by the suppliers.
What can you learn from this paper?
- Optimize cost: By predicting the expedited fees, the client was able to estimate the cost as per the schedule, enabling them to cut-off the expedited expenses.
- Improved data governance: We put the existing data in a trained model to identify and analyze the factors that may cause a price surge.
- Easy-to-use web application: The web application was hosted on a centralized Azure Cloud platform to display the predictive data, which is comparatively easy to use.
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