Case Study – Logistics Digitalization

November 6, 2018 admin

Our customer, a logistics company specialized on retail market, was not reaching the annual objectives nor results desired. The company had a low delivery compliance rate, resulting in a negative impact on its image with the clients and ultimately impacting its profitability.

We run the initial analysis using our methodology of the Digitalization Factor, which led us to the optimal areas to focus on. We decided to work on the communication between the delivery fleet and the retailers, keeping in mind the final goal of achieving delivery time reduction.

OUR APPROACH AND TOOLS USED

We started by studying data from tracking devices already installed in the delivery fleet. We noted that each
delivery was taking longer than expected due to long idle times at each stop, the reason remained unknown.
Performing a root cause analysis we detected that customers were not readily available at the time of delivery.
The company used to inform its customers when the products would be delivered. Nevertheless, the variability
of the delivery time was very high and the exact time was difficult to predict accurately, reason why they could
only announce a delivery schedule with a wide 4 hours window.
Customers, not knowing precisely at what time they would receive the order, were not 100% ready to receive it
as soon as the truck arrived. This reaction time was the cause deliveries took longer than expected.
We define and implement an early alert system that, based on GPS technology, automatically update the exact
delivery time. The clients started to receive automatic communications, announcing the arrival of their order
and allowing them to be prepared in time for the delivery.

 

RESULTS

Improvements on customers’ appraisals. They are now notified with higher accuracy when the driver is nearby
and order are about to be delivered.
Without the need to announce extremely narrow delivery times, that still depends on different external factors
and is more complex to solve, customers are now ready to receive the order as soon as they arrive.
Average waiting time per delivery was reduced by 70%.

 

 

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