Demand and Asset Relocation Planning at a Shipping Company has been saved
Demand and Asset Relocation Planning at a Shipping Company
Real Time Dynamic Optimization through Predictive Modelling
Reducing idle time and increasing fulfilment is an important focus area in the logistics industry. To realize this is not always as straightforward, but with our methodologies we have shown that we can improve operations to improve volume and price.
A global shipping company was struggling with margin leakage due to excessive discounting, lost deals due to delay in sending quotations and missed margin opportunities due to sub-optimal demand forecasting and asset relocation planning.
The client was losing margins due to multiple operational challenges ranging from inability to forecast demand accurately, high idle vessel time and low fulfilment rates. On the commercial side, the inability of sales to provide quotes in a timely manner (due to lack of information) was causing poor performance compares to peers on the spot market.
A multi-faceted Pricing transformation program, with initiatives on data, analytics, forecasting, optimization, tooling, technology and change enablement, was designed to facilitate a complete commercial transformation.
The pricing program was structured into multiple workstreams (Data & Infrastructure, Forecasting & Optimization, Tooling & technology & Change Enablement) all working in unison to deliver minimum viable products on regular interval for the organization to pilot and launch. The data team was responsible for breaking data silos and creating a data lake. This data was then used by the Optimization team to build algorithms that could predict costs, prices, demand and make recommendations on how to relocate the vessels and routes to take. All the data, insights, recommendations were visualized for sales in a pricing tool (a Configure Price Quote solution built in a low-code solution) to enable them to improve margins and conversion on both the spot and contract business by capture willingness to pay.
At the onset of covid 19, when the platform was in its midst, event modelling was applied on demand models to simulate impact of changes in demand and create alternative business planning scenarios
This transformation journey has enabled us to ‘Sell the Right Service to the Right Customer in the Right Place at the Right Time at the Right Price’.
Our client was able to impact their operations by using our capabilities as they reduced idle tank time and increased demand fulfilment. Also, they improved their quote win probability by being able to offer a quotation to customers within 5 minutes instead of 5 days.
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