With a fleet of over tens of thousands of trailers and containers that performs approximately million annual deliveries, our client is one of the Fortune 500 transportation and logistics company. To stay ahead of competitors, they partnered with Infosys to predict accurate market price, using AI and ML solution, that helps them arrive at the best carrier cost and shipper price resulting in optimal margin.
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Infosys delivered a novel dynamic pricing approach by predicting market price that gives maximum margin using cognition and hyper-automation. The dynamic pricing is powered by advanced ensemble-based machine learning approach with multiple models implemented across lanes considering relevant features. The power of Artificial Intelligence is leveraged to reduce the manual effort and time consumed to determine the market price. The solution is hosted in cloud environment and the entire pipeline is automated starting from extracting data from legacy system, data quality, transformation and loading, feature engineering, modeling, and integrating with the consuming systems.
Infosys solution predicted carrier cost with an accuracy greater than 90%, which led to the following estimated benefits:
$19M annual savings with 12% increase in prediction accuracy
Bid-win rate has been increased from 1% to 3%
Increased Gross Margin per Employee per Day (GMED) from $200 to $900 using cognition and hyper-automation