Enmovil – Supply Chain Decisioning Platform

Enmovil’s predictive algorithms analyse routes to make optimised recommendations and reduce logistics cost


The manufacturer had to ensure that the overall cost of finished goods (FG) remained unchanged, if not lower.
A significant component of the FG cost is the logistics expense in shipping the goods to destination.
The manufacturer had a two-fold problem to address within a very short span.

1. Get comprehensive visibility regarding the movement of FGs from source to destination with thorough insights about the source of losses.
2. Identify areas of improvement that can assist in reducing logistics expense.


The manufacturer onboarded Enmovil’s Road logistics module to meet the goal of optimizing its road logistics operations.

Some of the features of the deployed module are:

  • Seamless end-to-end visibility of operations for the complete fleet without imposing any tracking constraints on the transporters.
  • Identifying inefficiencies : Analytics accompanied with strong reporting and escalation mechanisms enable the stakeholders (manufacturer, dealer & transporter) to be fully aligned on the movement of goods and ensure no loss in communication.
  • Machine Learning algorithms to identify optimal routes : Enmovil’s super-integrated platform with its 360 degree integration with toll, weather and other databases evaluates every route taken by transporters and isolates the most optimal route from source to destination. It also provides quantifiable insights into the savings should optimal routes be taken.


The manufacturer started seeing results quite soon after deployment of platform. The application was able to deliver benefits much beyond the original expectations.

Optimized route recommendation algorithms reduced logistics costs by over 10%. With an integrated application, the manufacturer was able to accurately identify various sources of inefficiencies. This increased the fleet utilization by more than 15%.

Enmovil’s enhanced visibility and proprietary predictive algorithms also enabled the manufacturer and dealer get a precise ETA prediction of material resulting in wellcoordinated operations and a great experience

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