Our client is a leading multinational telecommunications conglomerate headquartered in Singapore.
The client was looking to leverage historical data to accelerate the process of submitting first cut quotations to large enterprise customers which took 15-27 days. The objective was to develop a price recommendation engine to generate costs faster and eliminate manual dependencies using ML/AI models in combination with the then-existing rules engine to pre-estimate the cost elements like Monthly Recurring Cost (MRC) and One-time Cost (OTC)
Reduced Turn Around Time (TAT) for developing the first stage pricing from 15 days to 2 days
Developed models for 7 countries to predict OTC (one-time cost) and MRC (monthly recurring cost) for multiple products with ~70% in range accuracy
Developed dashboards to monitor the performance of the model predictions and refresh the models if performance degrades over time