Dynamic Integrated Pricing for Supply Chain Optimization

Pricing Solution that cuts across the entire organisational value chain to integrate multiple systems, processes, data and predictive/forecast models to achieve real-time dynamic pricing

Challenge

A global logistics and transportation services company wanted to:

  • Optimize Margin Leakage due to Excessive Discounting,
  • Reduce Lost Deals due to Delay in Computing & Sending Quotations
  • Missed Margin Opportunities due to Sub-Optimal Demand Forecasting and Asset Relocation Planning

Approach

MRD put in place a Pricing Roadmap for ‘Dynamic Integrated Pricing ’ which meant that every time a customer asks them for a quote to ship a container on a particular trade lane – they get a price that has the highest probability of winning the deal since it is market adjusted, capturing the customer willingness to pay while also maximising revenues. The computation of this ‘perfect price’ is done by a Dynamic Price algorithm that looks at a whole range of different variables and computes a price intended to strike an optimum. The data and variables that go into price determination are historical transactional data, vendor costs, market demand and supply, customer negotiation and purchase history, customer price sensitivity, macroeconomic indicators. These dimensions are then computed by the price orchestrator – a large optimisation model – that tries to give the best price for a deal depending on the objective chosen.

Deliverables 

The key deliverables of the Real-time Dynamic Optimization Project are:

  • A Price Orchestrator (a large optimization model) that provides sales with price recommendation
  • Underlying predictive and forecast models used to optimize and automate sub-functions and processes in the organization

Results

  • Quotation time reduced from 5 days to 5 mins
  • Improved quote win probability by 17%
  • Demand fulfillment up by 13%
  • Idle tank time reduced