Data analysis and modeling to optimize logistics

Client
Exxon Mobil
Deliverables

- Optimized Data Analysis
- Modelled Data Driven Strategy


Challenge

Heavy traffic congestion, inefficient road systems, customer and driver behavior, weather conditions: everything seems to impact the duration and costs of the last mile.

Background

New technologies have quickened the delivery of goods, but failed in speeding up the last mile from local distribution centers to retailers or customers’ homes. Meanwhile, these technologies have led customers to expect increased performance on speed, flexibility, transparency and reliability.

Altruistic last mile delivery data optimization for Exxon Mobil

Solution

Data scientists and statisticians modelled and optimised new last-mile supply chain strategies. The community, collaborating with our partners, used GPS data-collecting tools — something as simple as the driver’s smartphones — to better track the progress of delivery vehicles and inform route planning by identifying patterns in delivery times. We integrated driver-specific data with external sources such as road network reports, weather updates and congestion recognition tools.

As a result, supply chain managers have a clear picture of what happens in the time between goods leaving a delivery truck and arriving at a customer’s doorstep. They can better design delivery training programs, decide the most efficient routes, and even choose the right vehicle to minimise environmental damage from logistics — no need for a truck when a bicyclist will do.

The developed model analysed large volumes of data through which the project team identified critical revisions to improve the network’s performance and cost-effectiveness.

Implementing these measures reduced the company’s transhipment centres by 30% and its vehicle fleet by 15%. Overall, the new models project to reduce the cost of last-mile operations by 6% per year while improving the network performance.

The UN reports that by 2050, 70% of the global population will migrate to cities. Logistics challenges and the data gathered around them are only going to compound as this future unfolds.

Creating a fully optimised model at scale required extensive input from data scientists and analysts. An impossible ask for most companies today. Through Altruistic, enterprise businesses can access necessary talent and harness the power of open innovation. Building the future starts with community.

Results

6%
cost of last-mile operations reduction per year
-30%
company’s transhipment centres
-15%
vehicle fleet

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