Dynamic Pricing and Capacity Allocation

Energy & Infrastructure / Australasia / Network Optimisation

$2 BI

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$4.3 MI

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73%

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Goal

A railway operator was having issues with last-minute cancellations that led to numerous trains being under-utilized.

The goal was to minimize unused capacity in trains (spoilage) and allocate freed capacity dynamically to the right customer type to maximize revenues.

Approach

• Ingested more than 150 tables directly from the ERP system and worked closely with SMEs to understand and link them.

• Implemented a change data capture logic to preserve historical data previously being overwritten or lost.

• Created an algorithm using historical data to compute the right amount of overbooking to maximize service usage while minimizing the impact on customer satisfaction.

• A second algorithm allocated freed capacity to the right type of customers in a way that maximized profitability while protecting long-term agreements with key customers.

Interventions

• Algorithm-driven recommendations for overbooking, pricing, and booking type allocation, used by commercial teams on specific routes.

• Robust data pipeline for processing, cleaning, and testing approximately 150 raw tables from the ERP system, enabling other use cases.

• Change data capture system implemented to preserve historical data.