Few days back, I read an article about the courier company UPS, who introduced a right turn policy for their trucks and saved millions of USD annually, from 2000s onward. The logic is very simple, After analysing driving routes and realising that the left turns resulted in wasting fuel waiting in traffic, UPS rearranged their routes so that drivers turned right 90% of the time. Due to the proper planning of right turns, the total distance travelled has also decreased drastically. Nowadays, the system became more efficient by the use of vehicle tracking devices.
When we introduced Thinture fleet management system in one of the major breweries in Africa, they were trying hard to improve their fleet efficiency. The major hurdle was about the turnaround time for each delivery. Almost 80 loaded trucks leave their facility by 6 in the morning and are supposed to take 3 more rounds of delivery every day. Daily, The transport manager makes a route map according to the sales plan, and assign each vehicle in a way that every truck comes back on a particular interval for the next pickup.
There were two major constraints. The reloading time and actual delivery time at shops. The load, majorly crates carrying beverages, is normally packed, marked and kept for each vehicle. Every morning, the biggest truck which goes the maximum distance will start first. When the trucks come back after the first delivery, there is a waiting period. The transport manager has to arrange the particular load for the truck which has arrived, and then prepare transport documents. They were losing so much of time in this process. We sat with the transport team and collected some data. With Thinture vehicle tracking system installed, we have created an algorithm to find out the ETA of each vehicle as per the route assigned to it. The system will automatically update the ETA in case of delay in deliveries due to traffic or any other reasons. Once the truck finishes certain deliveries, the delivery manager will be alerted for arranging the next load for that particular truck. The system will alert the driver to reach a particular loading area at a given time slot. This has created a smooth delivery system for the company. The efficiency has improved a lot. But there was one more problem.
The drivers at the delivery locations, mainly small shops, were wasting too much time. For them, increasing efficiency means more workload. We made a solution by creating Geo-fences at all delivery locations, approximately, 15000 points, and attached it to an alert system. The alert system will generate negative points to the drivers, if they violate time-limit attached to each fence. If a driver is not getting a certain score at the end of the month, he is not eligible to get the bonus.
Initially, Drivers were completely against the point system. But after a few months, we got feedback from the company that, drivers are the first ones to inform them, if anything goes bad with the system. They are getting a better take-home salary and clarity on deliveries. The system is a huge success. Now, The trucks are running at the maximum efficiency, and Transport manager is happy to say that they have added one more daily delivery trip for almost 50% of the their trucks.
As a company, we are happy to hear that our solutions help our customers solve their existing issues and create additional profit. As users and providers, we need to seriously think about adding value to our existing systems with the help of real-time data, we collect through today's information channels. I would be really grateful for your comments on this article.
Good day !