We’re now living in a world where ‘Amazon effect’ is a thing, and customers’ expectation on delivery is higher than ever before. We expect both fast and free deliveries, but never fully appreciate when our orders arrive on time.
According to The Last Mile Delivery Challenge by Cagemini Research Institute, 55% of consumers will switch to a competing retailer/brand if it offers a faster delivery service.
Therefore, route optimization has become a norm rather than an exception for delivery companies who wish to make deliveries on time and keep their customers from jumping ship.
Time to walk the walk
All of us at ElasticRoute are consumers ourselves and we have undoubtedly take fast deliveries for granted. We’ve constantly overlooked the fact that every time our online orders are delivered on time, we have a route planner somewhere to thank.
We figured it was time to put ourselves in the shoes of these behind the scenes heroes who tirelessly plan the routes so our orders could be delivered on time.
Let the games begin
We started the activity by dividing the team into pairs. To have a level playing field, each pair contained one ElasticRoute ‘expert’ who had been involved in the testing stage and was more familiar with the system.
Anyone on Charles’ team immediately got tagged favourites because of his role as ElasticRoute’s Lead Support. If there’s one person who knew the frequently asked questions about the solution, it was Charles.
After settling down, teams were given instructions for the first task.
All of them received a file containing 100 random addresses in Singapore. The teams had:
- 2 drivers for workload distribution
- 5 minutes service time for each location
- Permission to make use of Google Maps
- 60 minutes to complete the tasks
There was a collective sense of relief at the mention of Google Maps. Getting to use a familiar app made the task at hand seem much more doable now, and immediately gave everybody a confidence boost… or so they thought.
With the available resources, the team were instructed to plan out the most optimized routes if they were to deliver to each of the 100 location between 9am to 6pm that day.
An hour to complete the task seemed like a very reasonable amount of time and in the first 10-15 minutes, the teams were laser-focused. All the screens had Google Maps on and everyone was busy keying in the information at hand.
Like a well-rehearsed play, there was a stark drop to the frantic sounds of fingers hitting the keyboards at the 20 minute mark. Focused faces slowly but surely made way to concerned ones, expressions which ultimately turned from puzzled to flat out lost.
Sixty minutes quickly became sixteen, and before they knew it, there were only 5 minutes left.
As everyone submitted their end results, the teams broke into discussion and started talking about all the unexpected obstacles they faced.
Not one team managed to complete the task, but Terence and Aline were the pair who achieved the best results. They managed to utilize both their drivers and deliver to all the locations, but completed their deliveries almost 2 hours past the deadline of 6pm.
If a couple of hours overtime was the best result, I wouldn’t want to be a delivery driver with these guys as route planners.
With a new found appreciation for route planning, I demonstrated how ElasticRoute was able to complete the exact same task with the same restrictions in less than a minute.
Eyes widen, jaws dropped.
Every one of us were busy fixing, promoting and working on ElasticRoute, we were so caught up with our jobs we never had time to fully appreciate what the solution could do, and what a big difference it could make in the real world.
As the teams got excited after seeing what ElasticRoute was capable of, it was time for Task 2.
This time around, each pair received 300 random local addresses. They also had:
- 6 drivers for workload distribution
- To include 15% buffer time for 3 drivers
Drivers for this task compared to Task 1 also had to return to their respective depots after completing their deliveries. But more importantly, the teams were able to use ElasticRoute for Task 2.
In a matter of minutes, everyone was scrambling not only to key in the information provided, but some were already adding the final touches to their end results.
For the second consecutive task, Terence & Aline came in first again, completing Task 2 in less than 5 minutes. These guys are getting a hang of route planning alright.
Finally, we’ve been in the shoes of actual route planners and experienced first-hand the obstacles they faced on a daily basis.
Appreciating route planning, and I mean really appreciating the task itself would help all of us understand who we’re creating ElasticRoute for.